How to Calculate Risk Reward Ratio in Forex - Forex Education

Former investment bank FX trader: some thoughts

Former investment bank FX trader: some thoughts
Hi guys,
I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert.
I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning.
When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions.
The first topic is Risk Management and we'll cover it in three parts
Part I
  • Why it matters
  • Position sizing
  • Kelly
  • Using stops sensibly
  • Picking a clear level

Why it matters

The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.”
You have to keep it before you grow it.
Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around.
The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices.
Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.

Capital and position sizing

The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose.
Position sizing is what ensures that a losing streak does not take you out of the market.
A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples.
So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000.
We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be?
We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator".

https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14
So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital.
You should be using this calculator (or something similar) on every single trade so that you know your risk.
Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later.
The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work.
As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you.
Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints.
For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly:

https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b
To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you.
Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown.
It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance.
Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k.
Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money.
Do not let this happen to you. Use position sizing discipline to protect yourself.

Kelly Criterion

If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number?
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet.
Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin.
Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips.
Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds.
Applying the formula to forex trading looks like this:
Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio
If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically.
If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss.
So that’s 0.3 - (1 - 0.3) / 3 = 6.6%.
Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit!
With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not.
Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account.
Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see.
This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders.
Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
  • How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
  • What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.

How to use stop losses sensibly

Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them.
A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter.
The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’.
This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK.
Why are stop losses so important? Well, there is no other way to manage risk with certainty.
You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter.
Learning to take a loss and move on rationally is a key lesson for new traders.
A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not.
Bruce Kovner, founder of the hedge fund Caxton Associates
There is an old saying amongst bank traders which is “losers average losers”.
It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong.
Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.

Picking a clear level

Where you leave your stop loss is key.
Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible.

If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop
You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200.
The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up.
Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD.

https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802
If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend.
So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level.
There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section.
There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high.

https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81
Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument.
Here are some guidelines that can help:
  1. Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
  2. Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
  3. Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out.
For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.

Coming up in part II

EDIT: part II here
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Risk:reward ratios
Risk-adjusted returns

Coming up in part III

Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
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Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
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Which are your Top 5 favourite coins out of the Top 100? An analysis.

I am putting together my investment portfolio for 2018 and made a complete summary of the current Top 100. Interestingly, I noticed that all coins can be categorized into 12 markets. Which markets do you think will play the biggest role in the coming year?
Here is a complete overview of all coins in an excel sheet including name, market, TPS, risk profile, time since launch (negative numbers mean that they are launching that many months in the future) and market cap. You can also sort by all of these fields of course. Coins written in bold are the strongest contenders within their market either due to having the best technology or having a small market cap and still excellent technology and potential. https://docs.google.com/spreadsheets/d/1s8PHcNvvjuy848q18py_CGcu8elRGQAUIf86EYh4QZo/edit#gid=0
The 12 markets are
  1. Currency 13 coins
  2. Platform 25 coins
  3. Ecosystem 9 coins
  4. Privacy 10 coins
  5. Currency Exchange Tool 8 coins
  6. Gaming & Gambling 5 coins
  7. Misc 15 coins
  8. Social Network 4 coins
  9. Fee Token 3 coins
  10. Decentralized Data Storage 4 coins
  11. Cloud Computing 3 coins
  12. Stable Coin 2 coins
Before we look at the individual markets, we need to take a look of the overall market and its biggest issue scalability first:
Cryptocurrencies aim to be a decentralized currency that can be used worldwide. Its goal is to replace dollar, Euro, Yen, all FIAT currencies worldwide. The coin that will achieve that will be worth several trillion dollars.
Bitcoin can only process 7 transactions per second (TPS). In order to replace all FIAT, it would need to perform at at least VISA levels, which usually processes around 3,000 TPS, up to 25,000 TPS during peak times and a maximum of 64,000 TPS. That means that this cryptocurrency would need to be able to perform at least several thousand TPS. However, a ground breaking technology should not look at current technology to set a goal for its use, i.e. estimating the number of emails sent in 1990 based on the number of faxes sent wasn’t a good estimate.
For that reason, 10,000 TPS is the absolute baseline for a cryptocurrency that wants to replace FIAT. This brings me to IOTA, which wants to connect all 80 billion IoT devices that are expected to exist by 2025, which constantly communicate with each other, creating 80 billion or more transactions per second. This is the benchmark that cryptocurrencies should be aiming for. Currently, 8 billion devices are connected to the Internet.
With its Lightning network recently launched, Bitcoin is realistically looking at 50,000 possible soon. Other notable cryptocurrencies besides IOTA and Bitcoin are Nano with 7,000 TPS already tested, Dash with several billion TPS possible with Masternodes, Neo, LISK and RHOC with 100,000 TPS by 2020, Ripple with 50,000 TPS, Ethereum with 10,000 with Sharding.
However, it needs to be said that scalability usually goes at the cost of decentralization and security. So, it needs to be seen, which of these technologies can prove itself resilient and performant.
Without further ado, here are the coins of the first market

Market 1 - Currency:

  1. Bitcoin: 1st generation blockchain with currently bad scalability currently, though the implementation of the Lightning Network looks promising and could alleviate most scalability concerns, scalability and high energy use.
  2. Ripple: Centralized currency that might become very successful due to tight involvement with banks and cross-border payments for financial institutions; banks and companies like Western Union and Moneygram (who they are currently working with) as customers customers. However, it seems they are aiming for more decentralization now.https://ripple.com/dev-blog/decentralization-strategy-update/. Has high TPS due to Proof of Correctness algorithm.
  3. Bitcoin Cash: Bitcoin fork with the difference of having an 8 times bigger block size, making it 8 times more scalable than Bitcoin currently. Further block size increases are planned. Only significant difference is bigger block size while big blocks lead to further problems that don't seem to do well beyond a few thousand TPS. Opponents to a block size argue that increasing the block size limit is unimaginative, offers only temporary relief, and damages decentralization by increasing costs of participation. In order to preserve decentralization, system requirements to participate should be kept low. To understand this, consider an extreme example: very big blocks (1GB+) would require data center level resources to validate the blockchain. This would preclude all but the wealthiest individuals from participating.Community seems more open than Bitcoin's though.
  4. Litecoin : Little brother of Bitcoin. Bitcoin fork with different mining algorithm but not much else.Copies everything that Bitcoin does pretty much. Lack of real innovation.
  5. Dash: Dash (Digital Cash) is a fork of Bitcoin and focuses on user ease. It has very fast transactions within seconds, low fees and uses Proof of Service from Masternodes for consensus. They are currently building a system called Evolution which will allow users to send money using usernames and merchants will find it easy to integrate Dash using the API. You could say Dash is trying to be a PayPal of cryptocurrencies. Currently, cryptocurrencies must choose between decentralization, speed, scalability and can pick only 2. With Masternodes, Dash picked speed and scalability at some cost of decentralization, since with Masternodes the voting power is shifted towards Masternodes, which are run by Dash users who own the most Dash.
  6. IOTA: 3rd generation blockchain called Tangle, which has a high scalability, no fees and instant transactions. IOTA aims to be the connective layer between all 80 billion IOT devices that are expected to be connected to the Internet in 2025, possibly creating 80 billion transactions per second or 800 billion TPS, who knows. However, it needs to be seen if the Tangle can keep up with this scalability and iron out its security issues that have not yet been completely resolved.
  7. Nano: 3rd generation blockchain called Block Lattice with high scalability, no fees and instant transactions. Unlike IOTA, Nano only wants to be a payment processor and nothing else, for now at least. With Nano, every user has their own blockchain and has to perform a small amount of computing for each transaction, which makes Nano perform at 300 TPS with no problems and 7,000 TPS have also been tested successfully. Very promising 3rd gen technology and strong focus on only being the fastest currency without trying to be everything.
  8. Decred: As mining operations have grown, Bitcoin’s decision-making process has become more centralized, with the largest mining companies holding large amounts of power over the Bitcoin improvement process. Decred focuses heavily on decentralization with their PoW Pos hybrid governance system to become what Bitcoin was set out to be. They will soon implement the Lightning Network to scale up. While there do not seem to be more differences to Bitcoin besides the novel hybrid consensus algorithm, which Ethereum, Aeternity and Bitcoin Atom are also implementing, the welcoming and positive Decred community and professoinal team add another level of potential to the coin.
  9. Aeternity: We’ve seen recently, that it’s difficult to scale the execution of smart contracts on the blockchain. Crypto Kitties is a great example. Something as simple as creating and trading unique assets on Ethereum bogged the network down when transaction volume soared. Ethereum and Zilliqa address this problem with Sharding. Aeternity focuses on increasing the scalability of smart contracts and dapps by moving smart contracts off-chain. Instead of running on the blockchain, smart contracts on Aeternity run in private state channels between the parties involved in the contracts. State channels are lines of communication between parties in a smart contract. They don’t touch the blockchain unless they need to for adjudication or transfer of value. Because they’re off-chain, state channel contracts can operate much more efficiently. They don’t need to pay the network for every time they compute and can also operate with greater privacy. An important aspect of smart contract and dapp development is access to outside data sources. This could mean checking the weather in London, score of a football game, or price of gold. Oracles provide access to data hosted outside the blockchain. In many blockchain projects, oracles represent a security risk and potential point of failure, since they tend to be singular, centralized data streams. Aeternity proposes decentralizing oracles with their oracle machine. Doing so would make outside data immutable and unchangeable once it reaches Aeternity’s blockchain. Of course, the data source could still be hacked, so Aeternity implements a prediction market where users can bet on the accuracy and honesty of incoming data from various oracles.It also uses prediction markets for various voting and verification purposes within the platform. Aeternity’s network runs on on a hybrid of proof of work and proof of stake. Founded by a long-time crypto-enthusiast and early colleague of Vitalik Buterin, Yanislav Malahov. Promising concept though not product yet
  10. Bitcoin Atom: Atomic Swaps and hybrid consenus. This looks like the only Bitcoin clone that actually is looking to innovate next to Bitcoin Cash.
  11. Dogecoin: Litecoin fork, fantastic community, though lagging behind a bit in technology.
  12. Bitcoin Gold: A bit better security than bitcoin through ASIC resistant algorithm, but that's it. Not that interesting.
  13. Digibyte: Digibyte's PoS blockchain is spread over a 100,000+ servers, phones, computers, and nodes across the globe, aiming for the ultimate level of decentralization. DigiByte rebalances the load between the five mining algorithms by adjusting the difficulty of each so one algorithm doesn’t become dominant. The algorithm's asymmetric difficulty has gained notoriety and been deployed in many other blockchains.DigiByte’s adoption over the past four years has been slow. It’s still a relatively obscure currency compared its competitors. The DigiByte website offers a lot of great marketing copy and buzzwords. However, there’s not much technical information about what they have planned for the future. You could say Digibyte is like Bitcoin, but with shorter blocktimes and a multi-algorithm. However, that's not really a difference big enough to truly set themselves apart from Bitcoin, since these technologies could be implemented by any blockchain without much difficulty. Their decentralization is probably their strongest asset, however, this also change quickly if the currency takes off and big miners decide to go into Digibyte.
  14. Bitcoin Diamond Asic resistant Bitcoin and Copycat

Market 2 - Platform

Most of the cryptos here have smart contracts and allow dapps (Decentralized apps) to be build on their platform and to use their token as an exchange of value between dapp services.
  1. Ethereum: 2nd generation blockchain that allows the use of smart contracts. Bad scalability currently, though this concern could be alleviated by the soon to be implemented Lightning Network aka Plasma and its Sharding concept.
  2. EOS: Promising technology that wants to be able do everything, from smart contracts like Ethereum, scalability similar to Nano with 1000 tx/second + near instant transactions and zero fees, to also wanting to be a platform for dapps. However, EOS doesn't have a product yet and everything is just promises still. Highly overvalued right now. However, there are lots of red flags, have dumped $500 million Ether over the last 2 months and possibly bought back EOS to increase the size of their ICO, which has been going on for over a year and has raised several billion dollars. All in all, their market cap is way too high for that and not even having a product.
  3. Cardano: Similar to Ethereum/EOS, however, only promises made with no delivery yet, highly overrated right now. Interesting concept though. Market cap way too high for not even having a product. Somewhat promising technology.
  4. VeChain: Singapore-based project that’s building a business enterprise platform and inventory tracking system. Examples are verifying genuine luxury goods and food supply chains. Has one of the strongest communities in the crypto world. Most hyped token of all, with merit though.
  5. Neo: Neo is a platform, similar to Eth, but more extensive, allowing dapps and smart contracts, but with a different smart contract gas system, consensus mechanism (PoS vs. dBfT), governance model, fixed vs unfixed supply, expensive contracts vs nearly free contracts, different ideologies for real world adoption. There are currently only 9 nodes, each of which are being run by a company/entity hand selected by the NEO council (most of which are located in china) and are under contract. This means that although the locations of the nodes may differ, ultimately the neo council can bring them down due to their legal contracts. In fact this has been done in the past when the neo council was moving 50 million neo that had been locked up. Also dbft (or neo's implmentation of it) has failed underload causing network outages during major icos. The first step in decentralization is that the NEO Counsel will select trusted nodes (Universities, business partners, etc.) and slowly become less centralized that way. The final step in decentralization will be allowing NEO holders to vote for new nodes, similar to a DPoS system (ARK/EOS/LISK). NEO has a regulation/government friendly ideology. Finally they are trying to work undewith the Chinese government in regards to regulations. If for some reason they wanted it shut down, they could just shut it down.
  6. Stellar: PoS system, similar goals as Ripple, but more of a platform than only a currency. 80% of Stellar are owned by Stellar.org still, making the currency centralized.
  7. Ethereum classic: Original Ethereum that decided not to fork after a hack. The Ethereum that we know is its fork. Uninteresing, because it has a lot of less resources than Ethereum now and a lot less community support.
  8. Ziliqa: Zilliqa is building a new way of sharding. 2400 tpx already tested, 10,000 tps soon possible by being linearly scalable with the number of nodes. That means, the more nodes, the faster the network gets. They are looking at implementing privacy as well.
  9. QTUM: Enables Smart contracts on the Bitcoin blockchain. Useful.
  10. Icon: Korean ethereum. Decentralized application platform that's building communities in partnership with banks, insurance providers, hospitals, and universities. Focused on ID verification and payments. No big differentiators to the other 20 Ethereums, except that is has a product. That is a plus. Maybe cheap alternative to Ethereum.
  11. LISK: Lisk's difference to other BaaS is that side chains are independent to the main chain and have to have their own nodes. Similar to neo whole allows dapps to deploy their blockchain to. However, Lisk is currently somewhat centralized with a small group of members owning more than 50% of the delegated positions. Lisk plans to change the consensus algorithm for that reason in the near future.
  12. Rchain: Similar to Ethereum with smart contract, though much more scalable at an expected 40,000 TPS and possible 100,000 TPS. Not launched yet. No product launched yet, though promising technology. Not overvalued, probably at the right price right now.
  13. ARDR: Similar to Lisk. Ardor is a public blockchain platform that will allow people to utilize the blockchain technology of Nxt through the use of child chains. A child chain, which is a ‘light’ blockchain that can be customized to a certain extent, is designed to allow easy self-deploy for your own blockchain. Nxt claims that users will "not need to worry" about security, as that part is now handled by the main chain (Ardor). This is the chief innovation of Ardor. Ardor was evolved from NXT by the same company. NEM started as a NXT clone.
  14. Ontology: Similar to Neo. Interesting coin
  15. Bytom: Bytom is an interactive protocol of multiple byte assets. Heterogeneous byte-assets (indigenous digital currency, digital assets) that operate in different forms on the Bytom Blockchain and atomic assets (warrants, securities, dividends, bonds, intelligence information, forecasting information and other information that exist in the physical world) can be registered, exchanged, gambled and engaged in other more complicated and contract-based interoperations via Bytom.
  16. Nxt: Similar to Lisk
  17. Stratis: Different to LISK, Stratis will allow businesses and organizations to create their own blockchain according to their own needs, but secured on the parent Stratis chain. Stratis’s simple interface will allow organizations to quickly and easily deploy and/or test blockchain functionality of the Ethereum, BitShares, BitCoin, Lisk and Stratis environements.
  18. Status: Status provides access to all of Ethereum’s decentralized applications (dapps) through an app on your smartphone. It opens the door to mass adoption of Ethereum dapps by targeting the fastest growing computer segment in the world – smartphone users.16. Ark: Fork of Lisk that focuses on a smaller feature set. Ark wallets can only vote for one delegate at a time which forces delegates to compete against each other and makes cartel formations incredibly hard, if not impossible.
  19. Neblio: Similar to Neo, but 30x smaller market cap.
  20. NEM: Is similar to Neo No marketing team, very high market cap for little clarilty what they do.
  21. Bancor: Bancor is a Decentralized Liquidity Network that allows you to hold any Ethereum token and convert it to any other token in the network, with no counter party, at an automatically calculated price, using a simple web wallet.
  22. Dragonchain: The Purpose of DragonChain is to help companies quickly and easily incorporate blockchain into their business applications. Many companies might be interested in making this transition because of the benefits associated with serving clients over a blockchain – increased efficiency and security for transactions, a reduction of costs from eliminating potential fraud and scams, etc.
  23. Skycoin: Transactions with zero fees that take apparently two seconds, unlimited transaction rate, no need for miners and block rewards, low power usage, all of the usual cryptocurrency technical vulnerabilities fixed, a consensus mechanism superior to anything that exists, resistant to all conceivable threats (government censorship, community infighting, cybenucleaconventional warfare, etc). Skycoin has their own consensus algorithm known as Obelisk written and published academically by an early developer of Ethereum. Obelisk is a non-energy intensive consensus algorithm based on a concept called ‘web of trust dynamics’ which is completely different to PoW, PoS, and their derivatives. Skywire, the flagship application of Skycoin, has the ambitious goal of decentralizing the internet at the hardware level and is about to begin the testnet in April. However, this is just one of the many facets of the Skycoin ecosystem. Skywire will not only provide decentralized bandwidth but also storage and computation, completing the holy trinity of commodities essential for the new internet. Skycion a smear campaign launched against it, though they seem legit and reliable. Thus, they are probably undervalued.

Market 3 - Ecosystem

The 3rd market with 11 coins is comprised of ecosystem coins, which aim to strengthen the ease of use within the crypto space through decentralized exchanges, open standards for apps and more
  1. Nebulas: Similar to how Google indexes webpages Nebulas will index blockchain projects, smart contracts & data using the Nebulas rank algorithm that sifts & sorts the data. Developers rewarded NAS to develop & deploy on NAS chain. Nebulas calls this developer incentive protocol – basically rewards are issued based on how often dapp/contract etc. is used, the more the better the rewards and Proof of devotion. Works like DPoS except the best, most economically incentivised developers (Bookkeeppers) get the forging spots. Ensuring brains stay with the project (Cross between PoI & PoS). 2,400 TPS+, DAG used to solve the inter-transaction dependencies in the PEE (Parallel Execution Environment) feature, first crypto Wallet that supports the Lightening Network.
  2. Waves: Decentralized exchange and crowdfunding platform. Let’s companies and projects to issue and manage their own digital coin tokens to raise money.
  3. Salt: Leveraging blockchain assets to secure cash loands. Plans to offer cash loans in traditional currencies, backed by your cryptocurrency assets. Allows lenders worldwide to skip credit checks for easier access to affordable loans.
  4. CHAINLINK: ChainLink is a decentralized oracle service, the first of its kind. Oracles are defined as an ‘agent’ that finds and verifies real-world occurrences and submits this information to a blockchain to be used in smart contracts.With ChainLink, smart contract users can use the network’s oracles to retrieve data from off-chain application program interfaces (APIs), data pools, and other resources and integrate them into the blockchain and smart contracts. Basically, ChainLink takes information that is external to blockchain applications and puts it on-chain. The difference to Aeternity is that Chainlink deploys the smart contracts on the Ethereum blockchain while Aeternity has its own chain.
  5. WTC: Combines blockchain with IoT to create a management system for supply chains Interesting
  6. Ethos unifyies all cryptos. Ethos is building a multi-cryptocurrency phone wallet. The team is also building an investment diversification tool and a social network
  7. Aion: Aion is the token that pays for services on the Aeternity platform.
  8. USDT: is no cryptocurrency really, but a replacement for dollar for trading After months of asking for proof of dollar backing, still no response from Tether.

Market 4 - Privacy

The 4th market are privacy coins. As you might know, Bitcoin is not anonymous. If the IRS or any other party asks an exchange who is the identity behind a specific Bitcoin address, they know who you are and can track back almost all of the Bitcoin transactions you have ever made and all your account balances. Privacy coins aim to prevent exactly that through address fungability, which changes addresses constantly, IP obfuscation and more. There are 2 types of privacy coins, one with completely privacy and one with optional privacy. Optional Privacy coins like Dash and Nav have the advantage of more user friendliness over completely privacy coins such as Monero and Enigma.
  1. Monero: Currently most popular privacy coin, though with a very high market cap. Since their privacy is all on chain, all prior transactions would be deanonymized if their protocol is ever cracked. This requires a quantum computing attack though. PIVX is better in that regard.
  2. Zcash: A decentralized and open-source cryptocurrency that hide the sender, recipient, and value of transactions. Offers users the option to make transactions public later for auditing. Decent privacy coin, though no default privacy
  3. Verge: Calls itself privacy coin without providing private transactions, multiple problems over the last weeks has a toxic community, and way too much hype for what they have.
  4. Bytecoin: First privacy-focused cryptocurrency with anonymous transactions. Bytecoin’s code was later adapted to create Monero, the more well-known anonymous cryptocurrency. Has several scam accusations, 80% pre-mine, bad devs, bad tech
  5. Bitcoin Private: A merge fork of Bitcoin and Zclassic with Zclassic being a fork of Zcash with the difference of a lack of a founders fee required to mine a valid block. This promotes a fair distribution, preventing centralized coin ownership and control. Bitcoin private offers the optional ability to keep the sender, receiver, and amount private in a given transaction. However, this is already offered by several good privacy coins (Monero, PIVX) and Bitcoin private doesn't offer much more beyond this.
  6. Komodo: The Komodo blockchain platform uses Komodo’s open-source cryptocurrency for doing transparent, anonymous, private, and fungible transactions. They are then made ultra-secure using Bitcoin’s blockchain via a Delayed Proof of Work (dPoW) protocol and decentralized crowdfunding (ICO) platform to remove middlemen from project funding. Offers services for startups to create and manage their own Blockchains.
  7. PIVX: As a fork of Dash, PIVX uses an advanced implementation of the Zerocoin protocol to provide it’s privacy. This is a form of zeroknowledge proofs, which allow users to spend ‘Zerocoins’ that have no link back to them. Unlike Zcash u have denominations in PIVX, so they can’t track users by their payment amount being equal to the amount of ‘minted’ coins, because everyone uses the same denominations. PIVX is also implementing Bulletproofs, just like Monero, and this will take care of arguably the biggest weakness of zeroknowledge protocols: the trusted setup.
  8. Zcoin: PoW cryptocurrency. Private financial transactions, enabled by the Zerocoin Protocol. Zcoin is the first full implementation of the Zerocoin Protocol, which allows users to have complete privacy via Zero-Knowledge cryptographic proofs.
  9. Enigma: Monero is to Bitcoin what enigma is to Ethereum. Enigma is for making the data used in smart contracts private. More of a platform for dapps than a currency like Monero. Very promising.
  10. Navcoin: Like bitcoin but with added privacy and pos and 1,170 tps, but only because of very short 30 second block times. Though, privacy is optional, but aims to be more user friendly than Monero. However, doesn't really decide if it wants to be a privacy coin or not. Same as Zcash.Strong technology, non-shady team.
  11. Tenx: Raised 80 million, offers cryptocurrency-linked credit cards that let you spend virtual money in real life. Developing a series of payment platforms to make spending cryptocurrency easier. However, the question is if full privacy coins will be hindered in growth through government regulations and optional privacy coins will become more successful through ease of use and no regulatory hindrance.

Market 5 - Currency Exchange Tool

Due to the sheer number of different cryptocurrencies, exchanging one currency for the other it still cumbersome. Further, merchants don’t want to deal with overcluttered options of accepting cryptocurrencies. This is where exchange tool like Req come in, which allow easy and simple exchange of currencies.
  1. Cryptonex: Fiat and currency exchange between various blockchain services, similar to REQ.
  2. QASH: Qash is used to fuel its liquid platform which will be an exchange that will distribute their liquidity pool. Its product, the Worldbook is a multi-exchange order book that matches crypto to crypto, and crypto to fiat and the reverse across all currencies. E.g., someone is selling Bitcoin is USD on exchange1 not owned by Quoine and someone is buying Bitcoin in EURO on exchange 2 not owned by Quoine. If the forex conversions and crypto conversions match then the trade will go through and the Worldbook will match it, it'll make the sale and the purchase on either exchange and each user will get what they wanted, which means exchanges with lower liquidity if they join the Worldbook will be able to fill orders and take trade fees they otherwise would miss out on.They turned it on to test it a few months ago for an hour or so and their exchange was the top exchange in the world by 4x volume for the day because all Worldbook trades ran through it. Binance wants BNB to be used on their one exchange. Qash wants their QASH token embedded in all of their partners. More info here https://www.reddit.com/CryptoCurrency/comments/8a8lnwhich_are_your_top_5_favourite_coins_out_of_the/dwyjcbb/?context=3
  3. Kyber: network Exchange between cryptocurrencies, similar to REQ. Features automatic coin conversions for payments. Also offers payment tools for developers and a cryptocurrency wallet.
  4. Achain: Building a boundless blockchain world like Req .
  5. Req: Exchange between cryptocurrencies.
  6. Bitshares: Exchange between cryptocurrencies. Noteworthy are the 1.5 second average block times and throughput potential of 100,000 transactions per second with currently 2,400 TPS having been proven. However, bitshares had several Scam accusations in the past.
  7. Loopring: A protocol that will enable higher liquidity between exchanges and personal wallets.
  8. ZRX: Open standard for dapps. Open, permissionless protocol allowing for ERC20 tokens to be traded on the Ethereum blockchain. In 0x protocol, orders are transported off-chain, massively reducing gas costs and eliminating blockchain bloat. Relayers help broadcast orders and collect a fee each time they facilitate a trade. Anyone can build a relayer.

Market 6 - Gaming

With an industry size of $108B worldwide, Gaming is one of the largest markets in the world. For sure, cryptocurrencies will want to have a share of that pie.
  1. Storm: Mobile game currency on a platform with 9 million players.
  2. Fun: A platform for casino operators to host trustless, provably-fair gambling through the use of smart contracts, as well as creating their own implementation of state channels for scalability.
  3. Electroneum: Mobile game currency They have lots of technical problems, such as several 51% attacks
  4. Wax: Marketplace to trade in-game items

Market 7 - Misc

There are various markets being tapped right now. They are all summed up under misc.
  1. OMG: Omise is designed to enable financial services for people without bank accounts. It works worldwide and with both traditional money and cryptocurrencies.
  2. Power ledger: Australian blockchain-based cryptocurrency and energy trading platform that allows for decentralized selling and buying of renewable energy. Unique market and rather untapped market in the crypto space.
  3. Populous: A platform that connects business owners and invoice buyers without middlemen. Invoice sellers get cash flow to fund their business and invoice buyers earn interest. Similar to OMG, small market.
  4. Monacoin: The first Japanese cryptocurrency. Focused on micro-transactions and based on a popular internet meme of a type-written cat. This makes it similar to Dogecoin. Very niche, tiny market.
  5. Revain: Legitimizing reviews via the blockchain. Interesting concept, though market not as big.
  6. Augur: Platform to forecast and make wagers on the outcome of real-world events (AKA decentralized predictions). Uses predictions for a “wisdom of the crowd” search engine. Not launched yet.
  7. Substratum: Revolutionzing hosting industry via per request billing as a decentralized internet hosting system. Uses a global network of private computers to create the free and open internet of the future. Participants earn cryptocurrency. Interesting concept.
  8. Veritaseum: Is supposed to be a peer to peer gateway, though it looks like very much like a scam.
  9. TRON: Tronix is looking to capitalize on ownership of internet data to content creators. However, they plagiarized their white paper, which is a no go. They apologized, so it needs to be seen how they will conduct themselves in the future. Extremely high market cap for not having a product, nor proof of concept.
  10. Syscoin: A cryptocurrency with a decentralized marketplace that lets people buy and sell products directly without third parties. Trying to remove middlemen like eBay and Amazon.
  11. Hshare: Most likely scam because of no code changes, most likely pump and dump scheme, dead community.
  12. BAT: An Ethereum-based token that can be exchanged between content creators, users, and advertisers. Decentralized ad-network that pays based on engagement and attention.
  13. Dent: Decentralizeed exchange of mobile data, enabling mobile data to be marketed, purchased or distributed, so that users can quickly buy or sell data from any user to another one.
  14. Ncash: End to end encrypted Identification system for retailers to better serve their customers .
  15. Factom Secure record-keeping system that allows companies to store their data directly on the Blockchain. The goal is to make records more transparent and trustworthy .

Market 8 - Social network

Web 2.0 is still going strong and Web 3.0 is not going to ignore it. There are several gaming tokens already out there and a few with decent traction already, such as Steem, which is Reddit with voting through money is a very interesting one.
  1. Mithril: As users create content via social media, they will be rewarded for their contribution, the better the contribution, the more they will earn
  2. Steem: Like Reddit, but voting with money. Already launched product and Alexa rank 1,000 Thumbs up.
  3. Rdd: Reddcoin makes the process of sending and receiving money fun and rewarding for everyone. Reddcoin is dedicated to one thing – tipping on social networks as a way to bring cryptocurrency awareness and experience to the general public.
  4. Kin: Token for the platform Kik. Kik has a massive user base of 400 million people. Replacing paying with FIAT with paying with KIN might get this token to mass adoption very quickly.

Market 9 - Fee token

Popular exchanges realized that they can make a few billion dollars more by launching their own token. Owning these tokens gives you a reduction of trading fees. Very handy and BNB (Binance Coin) has been one of the most resilient tokens, which have withstood most market drops over the last weeks and was among the very few coins that could show growth.
  1. BNB: Fee token for Binance
  2. Gas: Not a Fee token for an exchange, but it is a dividend paid out on Neo and a currency that can be used to purchase services for dapps.
  3. Kucoin: Fee token for Kucoin

Market 10 - Decentralized Data Storage

Currently, data storage happens with large companies or data centers that are prone to failure or losing data. Decentralized data storage makes loss of data almost impossible by distributing your files to numerous clients that hold tiny pieces of your data. Remember Torrents? Torrents use a peer-to-peer network. It is similar to that. Many users maintain copies of the same file, when someone wants a copy of that file, they send a request to the peer-to-peer network., users who have the file, known as seeds, send fragments of the file to the requester., he requester receives many fragments from many different seeds, and the torrent software recompiles these fragments to form the original file.
  1. Gbyte: Byteball data is stored and ordered using directed acyclic graph (DAG) rather than blockchain. This allows all users to secure each other's data by referencing earlier data units created by other users, and also removes scalability limits common for blockchains, such as blocksize issue.
  2. Siacoin: Siacoin is decentralized storage platform. Distributes encrypted files to thousands of private users who get paid for renting out their disk space. Anybody with siacoins can rent storage from hosts on Sia. This is accomplish via "smart" storage contracts stored on the Sia blockchain. The smart contract provides a payment to the host only after the host has kept the file for a given amount of time. If the host loses the file, the host does not get paid.
  3. Maidsafecoin: MaidSafe stands for Massive Array of Internet Disks, Secure Access for Everyone.Instead of working with data centers and servers that are common today and are vulnerable to data theft and monitoring, SAFE’s network uses advanced P2P technology to bring together the spare computing capacity of all SAFE users and create a global network. You can think of SAFE as a crowd-sourced internet. All data and applications reside in this network. It’s an autonomous network that automatically sets prices and distributes data and rents out hard drive disk space with a Blockchain-based storage solutions.When you upload a file to the network, such as a photo, it will be broken into pieces, hashed, and encrypted. The data is then randomly distributed across the network. Redundant copies of the data are created as well so that if someone storing your file turns off their computer, you will still have access to your data. And don’t worry, even with pieces of your data on other people’s computers, they won’t be able to read them. You can earn MadeSafeCoins by participating in storing data pieces from the network on your computer and thus earning a Proof of Resource.
  4. Storj: Storj aims to become a cloud storage platform that can’t be censored or monitored, or have downtime. Your files are encrypted, shredded into little pieces called 'shards', and stored in a decentralized network of computers around the globe. No one but you has a complete copy of your file, not even in an encrypted form.

Market 11 - Cloud computing

Obviously, renting computing power, one of the biggest emerging markets as of recent years, e.g. AWS and Digital Ocean, is also a service, which can be bought and managed via the blockchain.
  1. Golem: Allows easy use of Supercomputer in exchange for tokens. People worldwide can rent out their computers to the network and get paid for that service with Golem tokens.
  2. Elf: Allows easy use of Cloud computing in exchange for tokens.

Market 12 - Stablecoin

Last but not least, there are 2 stablecoins that have established themselves within the market. A stable coin is a coin that wants to be independent of the volatility of the crypto markets. This has worked out pretty well for Maker and DGD, accomplished through a carefully diversified currency fund and backing each token by 1g or real gold respectively. DO NOT CONFUSE DGD AND MAKER with their STABLE COINS DGX and DAI. DGD and MAKER are volatile, because they are the companies of DGX and DAI. DGX and DAI are the stable coins.
  1. DGD: Platform of the Stablecoin DGX. Every DGX coin is backed by 1g of gold and make use proof of asset consensus.
  2. Maker: Platform of the Stablecoin DAI that doesn't vary much in price through widespread and smart diversification of assets.
EDIT: Added a risk factor from 0 to 10. The baseline is 2 for any crypto. Significant scandals, mishaps, shady practices, questionable technology, increase the risk factor. Not having a product yet automatically means a risk factor of 6. Strong adoption and thus strong scrutiny or positive community lower the risk factor.
EDIT2: Added a subjective potential factor from 0 to 10, where its overall potential and a small or big market cap is factored in. Bitcoin with lots of potential only gets a 9, because of its massive market cap, because if Bitcoin goes 10x, smaller coins go 100x, PIVX gets a 10 for being as good as Monero while carrying a 10x smaller market cap, which would make PIVX go 100x if Monero goes 10x.
submitted by galan77 to CryptoCurrency [link] [comments]

Interessante Einladung von Bob Prechter's ElliottwaveInternational

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Regards,
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submitted by siggi2018 to Debitismus_Forum [link] [comments]

b

If you guys could post other things that you've found useful too, that'd be great.
submitted by confluencefx to u/confluencefx [link] [comments]

Top 5 Options Trading Facts You Should Know

Top 5 Options Trading Facts You Should Know
Top 5 Options Trading Facts You Should Know

Options trading has become so popular in the past few years, pulling in a lot of newbies with the hopes of earning money. Yes, with options trading you can earn money but behind the stage, there's a lot of hard work and efforts you have to put. The first step should be knowing what you are getting into. Here are 5 facts about options trading that could help you gain a basic understanding.

1. OPTIONS TRADING GRANTS YOU THE RIGHT TO BUY OR SELL INSTRUMENTS:-

Options trading can be practiced on different instruments like commodities, forex, futures & more by choosing the best options trading platform. When trading options, you get the right to buy or sell an underlying instrument. You just have to be sure about the instrument you are going to invest in, which requires a bit of research and a lot of analyzing skills.

2. IT IS EITHER A CALL OR A PUT:-

With options trading, things are always kept simple to the ground. The entire currencies options trading process relies on only two options. It is either a Call or a Put. When you feel that the price of the underlying asset is about to rise, you go for the call option. When the markets go the opposite way, you opt for the put option. It's just that you have to be able enough to predict the markets before you decide for yourself.

3.THE EXPIRY TIME PERIOD:-

Every option you buy comes with an expiration time, after which you lose your right to exercise the particular option. You can neither buy nor sell the option once it expires which is why you have to take calculated decisions and decide time frames when you buy an option.

4. OPTIONS TRADING IS HIGHLY EFFECTIVE & LIQUID:-

Options Trading is considered as one of the most liquid forms of trading, making it highly efficient & reliable. There are a lot of people around the world trading options, buying & selling instruments. So, liquidity will never be a problem to be worried about.

5. OPTIONS ARE HIGHLY REWARDING:-

When it comes to options trading, you should know that the rewards are high & obviously, there are risks involved with it. But the best thing is, you can choose the level of risk and carry out your trades accordingly, making options trading suitable for every options trader irrespective of how much he can afford. The bottom line being, options trading carries minimum risk with it and at the same time generates substantial profits provided you are top-notch with the basics.If you have read this far, then you are someone who is considering options trading seriously. It's a good thing because we can help you trade options and develop your options trading career. Feel free to contact us at [email protected]
submitted by DualOptions to u/DualOptions [link] [comments]

reminder

Here's a collection of random tools you might find useful in your trading. If you guys could post other things that you've found useful too, that'd be awesome.
submitted by confluencefx to u/confluencefx [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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Getting Started

Hey guys! I found a super cool list of everything a new forex trader would need to get started! Originally made by to nate1357. Link to original thread http://redd.it/328cjr
Free Resources
Education:
www.babypips.com/school
www.informedtrades.com/f7
www.forex4noobs.com/forex-education
www.en.tradimo.com/learn/forex-trading
www.youtube.com/useTheTradeitsimple
www.traderscalm.com
www.orderflowtrading.com/LearnOrderFlow.aspx
www.profitube.com
Calendars:
www.forexfactory.com/calendar.php
www.dailyfx.com/calendar
www.fxstreet.com/economic-calendar
www.forexlive.com/EconomicCalendar
www.myfxbook.com/forex-economic-calendar
www.investing.com/economic-calendar
Free News Websites:
www.forexlive.com - Daily live news, analysis and resources
www.financemagnates.com - FX industry news and updates
www.fxstreet.com - Daily news, analysis and resources
www.forextell.com
www.forexcup.com/news
www.bloomberg.com/markets
Forums:
www.reddit.com/forex
www.forums.babypips.com/
www.forexfactory.com/forum.php
www.elitetrader.com/et/index.php
www.forex-tsd.com/
www.fxgears.com/forum/index.php
www.trade2win.com/boards
Margin / pip / position size calculators
www.myfxbook.com/forex-calculators
Brokerages:
There are many factors to consider when choosing a brokerage. Regulations typically force US traders to only trade at US brokerages, while international traders have more choice. After considering location you need to consider how much capital you will start trading with as many have minimum deposit levels. Once you’ve narrowed that down you can compared spreads and execution. ECN brokers execute your orders straight through to their liquidity providers, while market maker brokers may pair up your trades with other clients. Market maker brokers typically will partially hedge your positions on the interbank market. Many consider this to be a conflict of interest and prefer to trade at an ECN broker who would have an active motive to see you succeed. Lastly, brokers run inherently risky business models so it is important to consider the risk of bankruptcy.
www.forexpeacearmy.com - Aggregates broker reviews. Be warned though that people only seem to make bad reviews.
www.myfxbook.com/forex-broker-spreads - Live comparison of executable spreads
United States & International-
-Interactive Brokers
International Only-
-LMAX (whitelabel DarwinEx)
*DMA broker based in the UK. Note that as a DMA broker LMAX eliminates the ability for LPs to last-look transactions. This may result in reduced liquidity during volatile times as liquidity providers would be likely not to risk posting liquidity to LMAX's pool. *Tight spreads *Minimum deposit $10,000 *Fairly well diversified
-Dukascopy
*ECN based in Switzerland, but available elsewhere depending on local regulations.
*Tight spreads *Minimum deposit $100 *Fairly well diversified
-IC Markets *ECN based in Australia *Fair spreads on standard account, tight spreads on professional accounts. *Minimum deposit $200 *Fairly well diversified
-Pepperstone
*ECN broker based in Australia. *Fair spreads on standard account, tight spreads on professional accounts. *Minimum deposit $200 *Not well diversified
Software / Apps:
Desktop/mobile
Terminology/Acronyms:
www.forexlive.com/ForexJargon - Common terms and acronyms
FAQ:
I need to exchange money, how do I do it?
This isn’t what this sub is for. Your best bet is using your bank or an online exchange service. Be prepared to pay a hefty fee.
I have money in one currency and need to exchange it into another sometime in the future, should I wait?
Don’t ask us this. We speculate intraday in FX and shouldn’t be relied on to tell you what’s best for you. Exchange the money when you need it.
I have an FX account, should I start trading demo or live?
This is highly debatable. You should definitely demo trade until you have mastered how to use the trading platform on desktop and mobile. After that it’s up to you. Many think that the psychology of trading live vs demo trading is massively different. So it may pay to learn to trade live. Just be warned that most FX traders lose almost their entire first account so start with a low affordable balance.
What’s money management?
Money management is a form of risk management and is arguably the most important aspect of your trading when it comes to long term survival. You should always enter trades with a stop loss - the distance of the stop allows you to calculate how large of a percent of your account balance will be lost if your trade stops out. You can run a monte carlo simulation to figure out the risk of having a number of trades go against you in a row to drain your account. The general rule is that you should only risk losing 1-4% of your account per trade entered.
More on this here: www.investopedia.com/articles/forex/06/fxmoneymgmt.asp[35]
www.swing-trade-stocks.com/money-management.html[36]
What about automated trading?
Retail FX traders have been known to program “Expert Advisors” (EAs) to automate trading. It’s generally advisable to stay away from that until you’re very experienced. Never buy an EA from a developer because the vast majority of them are scams.
What indicators are best?
That’s up to you to test and find out. Many in this forum dislike oscillating indicators since they fail to capture the essence of what moves price. With experience you will discover what works best for you. In my experience indicators that are most popular with professional traders are those that provide trading “levels” such as pivot points, fibonacci, moving averages, trendlines, etc.
What timeframe should I trade?
Price action can vary in different timeframes. In longer term timeframes the price action and fundamentals are much more clear. Unfortunately it would take a very long time to figure out whether or not what you’re doing is successful on longer timeframes. In shorter timeframes you can often tell very quickly if what you’re doing is profitable. Unfortunately there’s a lot more “noise” on these levels which can prove deceptive for those trying to learn. Therefore the best bet is to use a multi-timeframe analysis, working from top-down to come up with trades.
Should I trade using fundamental analysis (FA) of technical analysis (TA)?
This is a long standing argument in these forums and elsewhere. I’ll settle it here - you should have an understanding of both. Yes there are traders who blindly ignore one of the other but a truly well rounded trader should understand and implement both into the analysis. The market is driven in the longer term through FA. But TA is necessary to give traders a place to enter and exit trades from a psychological risk/reward standpoint.
I’ve heard trading Binary Options is an easy way to make money?
The general advice is to stay away from binaries. The structure of binary options is so that when you lose the broker wins. This incentive has created a very scammy industry where there are few legitimate binary options brokers. In addition in order to be profitable in binaries you have to win 55-65% of the time. That’s a much higher premium over spot FX.
Am I actually exchanging currencies?
Yes and no. Your broker handles spot FX is currency pairs. Although they make an exchange at the settlement date they treat your position in your account as a virtual currency pair. Think of it like a contract where you can only buy or sell it as a pair. In this sense you are always long one currency while short another. You are merely speculating that one currency will appreciate or depreciate vs another.
Why didn't my order fill?
Even if price appears to cross over a line on your chart it does not guarantee a fill. Different charting platforms chart different prices - some chart the bid price, some the ask price and some the midpoint price. To fill a limit order price needs to cross your limit's price plus the spread at the time that it is crossing. If it does not equal or exceed the spread then it will not fill. Be wary that in general spreads are not fixed. So what may fill at one time may not at another.
submitted by ClassicalAnt6 to TeamOceanSky [link] [comments]

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submitted by tranlinhphuong1 to SetForgetPattern [link] [comments]

Stock Trading: Reward/Risk Spreadsheet Calculator - YouTube CALCULATING RISK - FOREX TRADING - How to Calculate Lot ... How to Calculate Risk & Reward in Day Trading MetaTrader Forex Risk Reward Ratio Indcator ver. 4.00 ... How to Trade Forex Risk Reward Trade Calculator

When you are starting to get into Forex there are some a couple areas you need to pay big attention to one is risk management and the other is risk to reward ratio which also falls under risk management. If you are making trades and winning 9 out of 10 this isn’t as much of a problem. You can profit greatly and only win 6 out of 10 trades however with good risk to reward ratio. You can utilize a basic calculator to find the successful risk to compensate the proportion of your trades, or you can utilize a few tools to streamline the procedure, including a Microsoft Excel sheet or an online Forex risk reward calculator. However, past that there is a lot simpler approach to do the RVR computation on the off chance that you are using charting programming like forex lot ... Risk/Reward Ratio – indicator for MetaTrader 4 is a Metatrader 4 (MT4) indicator and the essence of the forex indicator is to transform the accumulated history data. Risk/Reward Ratio – indicator for MetaTrader 4 provides for an opportunity to detect various peculiarities and patterns in price dynamics which are invisible to the naked eye. Based on this information, traders can assume ... Free Forex Trading Signals; Risk Reward Indicator MT4 and MT5 (Free) Risk reward is a straightforward concept that will have a large effect on your trading strategy. Whilst it may be simple and easy to understand, the way in which you use risk reward in your trading and the strategy you choose to deploy it with is extremely important. If you are a trader that aims for large reward trades, then ... The risk/reward ratio is used by many forex traders to assess the expected return and the risk of a trade. For example, if a trader buys EUR/USD at 1.3500 and places his stop-loss order at 1.3450 and his take profit at 1.3650, he's risking 50 pips for a potential profit of 150 pips. The risk/reward ratio is therefore 150/50 = 3. Below is the risk-reward calculator: The risk-reward ratio or risk-return ratio in trading represents the expected return and risk of a given trade or trades based on entry position and close position. A good risk-reward ratio tends to be less than 1, that is, the return (reward) is greater than the risk. Risk and Reward Forex Calculator. The risk and reward calculator will help you to calculate the position's best targets and their respective reward-to-risk ratios based on the Fibonacci retracements from the local peak and bottom. It's a powerful tool to determine the potential risks before entering any positions. Bullish or Bearish? The price needs to be inside the wave for you to use this ... I'll udpate this calculator to cover the fees soon. Calculate Your Risk Reward Ratio If you like my content, subscribe to my blog, share this post to Social Media Networks, and follow my Facebook and Twitter Page. How to use the risk-reward ratio to be profitable. Risk reward ratio traders need to use together with the Winning ratio and Kelly ratio to create better position size and improve trading performance. If you use a 1:5 risk-reward ratio and your winning ratio is 3% it is bad, even you have a great risk-reward ratio.

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Stock Trading: Reward/Risk Spreadsheet Calculator - YouTube

Quick explanation of my risk/reward spreadsheet. Click this link to download for free: https://drive.google.com/open?id=0BzJh5rMoj57MMjdINVNXaUdaSXc To get a free stock through Webull, zero commissions options/stock trades, plus more https://act.webull.com/k/NYiqwnSruaHE/main Join the Beginner Trading Dis... How to Trade Forex enjoyably and safely managing risk and setting targets for positive trade outcomes. Risk Reward Ratio is one of the basic elements of money management, but many people don't know how to use it properly. Not talking about risk reward ratio tool ... Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.

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