Automatic Forex

Automatic Forex System Trading – Does it Really Make Any Difference at All?

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Automatic Forex System Trading – Does it Really Make Any Difference at All?

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Forex Robot – Building Your Own Automatic Trading System for Triple Digit Gains!

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Forex Robot – Building Your Own Automatic Trading System for Triple Digit Gains!

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Forex Miracle Review – Automatic Forex Trading Systems

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Forex Miracle Review – Automatic Forex Trading Systems

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Forex Robot – Building Your Own Automatic Trading System for Triple Digit Gains!

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Forex Robot – Building Your Own Automatic Trading System for Triple Digit Gains!

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Forex Miracle Review – Automatic Forex Trading Systems

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Automatic Forex Trading Systems

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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.
submitted by getmrmarket to Forex [link] [comments]

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.
submitted by getmrmarket to Forex [link] [comments]

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https://preview.redd.it/e63kae9rz9j51.png?width=3116&format=png&auto=webp&s=eeb8869dbccb0fca7c64d3c91f83cebcdb446e84
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perior over different cryptocurrencies?
LATESTBITCOINETHEREUMALTCOINSTECHNOLOGYADOPTIONBLOCKCHAINEVENTSCONTACT
PRESS RELEASEWhy is Bitcoin superior over different cryptocurrencies?Akshay KSPublished a pair of weeks agoon August 12, 2020By Akshay KS
Source: Pixabay
During this technical world, bitcoin is the foremost used digital currency all over the world. However the main question then arises within the minds of the many folks is why bitcoin is considered the foremost superior over other cryptocurrenc Bitcoin Freedom
Bitcoin is that the one method of creating transactions daily as alternative currencies. But it's its options and uniqueness that make it superior. Bitcoin and different currencies are based mostly on the cryptographic algorithms or mathematics that are encrypted, with that the user becomes the owner of the currency. Bitcoin currencies are easily accessible at Bitcoin ATM and online exchange
The main feature of the bitcoin, which makes it superior is that it is the safest option for digital transactions. These will be used for on-line searching and transfer of money too.
There are many alternative blessings to using bitcoin. A number of them are mentioned below
Decentralized and digital
Bitcoin offers the freedom of exchanging the price without representatives that proves helpful in controlling the lower fees and high funds. Bitcoin is that the faster method of transaction than others. It is secure as it is free from theft and frauds and is constant. The main advantage is that bitcoin has its homeowners whereas the bank controls the money.
Makes online looking
Normally, bitcoin will be used for on-line shopping too. Bitcoin is the opposite face of e-wallet, that is created by blockchain technology that is used to store money and will easily pay everywhere digitally. For this reason, it also makes your searching easy by which you'll be able to look from your home solely

Bitcoin is accepted globally at each corner of the planet, which makes it less volatile than local currencies or cash. This feature makes it superior because it enables us to form transactions on-line and across the boundaries
Bitcoin unable the means of tracking cash

https://preview.redd.it/4vpws3gtz9j51.jpg?width=1280&format=pjpg&auto=webp&s=179af0fcc33f85322d48b6be65fce2e4442c6cd6
Bitcoin is created by blockchain technology. Blockchain is the sole technology which will either make it or break it. There are many computers which are used to keep up a permanent record of each bitcoin transactions with the help of cryptographic technique. In this approach, it becomes a lot of valuable together with the tracking of the payment. At the same time, there's no method of tracking the cash

While not any transformation method, it will be used over the entire world. It provides the simplest platform for the investment as it is free from the restrictions of governments or banks. It provides an open market and combines the simplest of gold and money.

Bitcoin provides the power to access the balance of the users with a password which is named a personal key. It additionally permits the exchange of values through the web without any middle person. Thus, bitcoin becomes safer, stuffed with privacy, and open to everyone
Unlike cash, it is not possible to form the duplicate quite bitcoin that makes it more efficient. It's protected with the technology of blockchain. Even if anyone tries to form a replica of bitcoin to use it, then the system will automatically reject it as the system recognize it as unknown

Bitcoin Freedom failed to allow two persons to transact on the one price. Once the bitcoin is transferred, its possession is also transferred. So this is the simple approach of maintaining records for any tax functions. It conjointly makes it a easy and healthier metho

Bitcoin is the foremost reliable manner of online transactions. Many questions arise in folks’s minds that are solved on websites like bitcoin revolution. One in all them was the above-mentioned question. Bitcoin provides many facilities, and it comes with more and a lot of blessings which makes it distinctive and special over different cryptocurrencies. It can be preferred as the simplest digital platform for transac


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eToro: impressions, doubts and (ignored) lessons from copy trading

(no promotional content, no affiliate links)
Hi,
exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account:
https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing
In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot.
What I did after that?
Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading.
Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
My observations and thoughts are as follows:
  1. Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
  2. I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now?
I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are.
rubymza (Heloise Greeff)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market.
Wish me good luck!
Michael

P.S.
You might find those copy-trading related readings interesting:

Disclosures:
submitted by investing-scientist2 to StockMarket [link] [comments]

H1 Backtest of ParallaxFX's BBStoch system

Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are.
TL;DR at the bottom for those not interested in the details.
This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.

Background

For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX!
I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose.
This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem.
I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.

System Details

I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:

And now for the fun. Results!

As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker.
EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.

A Note on Spread

As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits.
Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way).
However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades.
You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term.
Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.

Time of Day

Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either.
On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate.
That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.

Moving stops up to breakeven

This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers.
Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability.
One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)?
Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right?
Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert.
I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall.
The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.

2-Candle vs Confirmation Candle Stops

Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it.
Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL.
Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.

Correlated Trades

As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular.
Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system.
This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here).
Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses.
Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels).
Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant.
One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak.
EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much.
I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system.
This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions.
There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated.
I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful.
Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.

What I will trade

Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.)
I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:

Demo Trading Results

Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc).
A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade.
I'm heading out of town next week, then after that it'll be time to take this sucker live!

Live Trading Results

I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
submitted by ForexBorex to Forex [link] [comments]

Copy trading with eToro: impressions, doubts and (ignored) lessons

(no promotional content, no affiliate links)
Hi,
exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account:
https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing
In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot.
What I did after that?
Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading.
Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
My observations and thoughts are as follows:
  1. Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
  2. I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now?
I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are.
rubymza (Heloise Greeff)

OlivierDanvel (Olivier Jean Andre Danvel)

rayvahey (Raymond Noel Vahey)
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market.
Wish me good luck!
Michael

P.S.
You might find those copy-trading related readings interesting:

Disclosures:
submitted by investing-scientist2 to InvestmentClub [link] [comments]

What do regulators say about BitQT ?

What do regulators say about BitQT ?

We discovered that it is so convenient to create a deposit. There are different on-line payment platforms to settle on from, for our initial live trading session, we have a tendency to created a deposit by doing an instantaneous bank transfer from our account into the BitQT account. The transaction was completed in seconds.
Live trading with BitQT

https://preview.redd.it/zrxveikvhim51.png?width=975&format=png&auto=webp&s=524850e4ff5890df2a7c25e4213090444bf46255
This is often the best part; we have a tendency to started our live trading session early within the morning and ended it when six hours. During the live trading session, we have a tendency to hardly required to try to to something except activating the live trading robot with a click. After the live trading session started, we had nothing else to try and do, the trading robot took complete control, and it automatically selected and completed the best deals out there.BitQT success
What we have a tendency to suppose concerning BitQ
Here are the most points we noted while testing the essential options of BitQT
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Realize a mentor online; you'll be able to get helpful data about the crypto market by following a mentor and crypto trading skilled on social media
BitQT has been created for everybody; it's user-friendly and profitable. We encourage our audience to join us, begin making money from the crypto market each day.
© 20twenty Straightforward To Browse • Powered by GeneratePress

BitQT BQ could be a laptop program that trades bitcoin CFDs automatically. The program claims to rely on advanced AI technologies to conduct trading research execution with a supposed win rate of up to 99p.c. BitQT BQ appears widespread with passive on-line investors, providing it is easy to use for all and doesn’t require a lot of your time to operate
It's conjointly said to require solely a tiny minimum capital deposit ($250) and reportedly generates up to $1k in daily profits from such a little account. However is BitQT BQ legit and if so, does it earn its users the said profits
As usual, we tend to have conducted a thorough investigation to determine if this bot is legit. We have a tendency to will gift our findings in this review and offer tips to assist you get started with it
https://preview.redd.it/4my2soawhim51.png?width=1046&format=png&auto=webp&s=515978aeca1497910fb83c4168326888697ef07a
BitQT BQ App reviewWhat is BitQT App?How will BitQT App work?Getting started with BitQT BQ
STEP ONE: Register a free accountSTEP 2: Verify ID with the underlying brokerSTEP 3: Deposit at least 250 USD as trading capitalSTEP FOUR: Trade with a demo accountSTEP FIVE: Live tradingIs BitQT BQ legit? The verdict!FAQsWhat is BitQT BQ App?Is BitQT App a Ponzi scheme?How much ought to I invest with BitQT BQ?How do I withdraw the supposed profits from BitQT BQ app?

Our criteria for determining the legitimacy of BitQT BQ took under consideration multiple factors, together with transparency, reputation, safety, simple use, and client service. The findings are summarized below.

BitQT BQ creates a transparent trading ecosystem through the coveted blockchain technology. This technology makes it possible for users to watch their accounts in real-time and raises disputes through smart contracts.
The robot has an glorious reputation with a rating of on ForexPeaceArmy when nearly 6k reviews.
We can make sure that a minimum of 95% of BitQTBQ reviewers report a positive experience with this robot.
BitQT BQ additionally scores exceptionally well in customer service. Users are pleased with how fast customer care responds and the way knowledgeable they are.
We tend to have additionally conducted background checks on Bitcoin BitQT partner brokers, and they seem well regulated and reputable.
BitQT BQ ensures users data privacy by applying 128-bit key encryption on all its platforms. It additionally appears to go with information privacy measures among them the EU General Knowledge Protection Regulation (GDPR)
As mentioned above, BitQT BQ may be a robot for all. Scan our Bitcoin Robot review for the fundamentals of auto trading.
What is BitQT App?
cribes itself as a highly specialised and powerful pc algorithm that automatically conducts the trading functions of an skilled BTC CFDs trader.
https://www.cryptoerapro.com/bitqt/

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submitted by Anteater_Same to u/Anteater_Same [link] [comments]

200 achievements of Modi Govt

  1. Fragile five to Fastest growing economy - India
  2. 11th largest to the 5th largest economy - India
  3. Share of world GDP from 2.43% in 2014 to 3.08% in 2018
  4. Average GDP 7.3% against 6.7% in previous regime
  5. Forex reserves from 300 bn USD in 2014 to 420 bn USD in 2018
  6. Doubling of FDI inflow from 36 bn USD in 2014 to 66 billion USD in 2018
  7. Inflation less than 2.3 % (Nov 18) against 10.1% in 2014
  8. Growth of sensex from 24,121.74 in 2014 to 36,395.03 on 12 Feb 19 (50.88%)
  9. Fiscal deficit under control
  10. Per capita income increased by 45% from Rs 86,647 in 2014 to Rs 1,25,397
  11. IT exemption from 2 lakh in 2014 to 5 lakh (effectively 9.85 lakh with home loan)
  12. Restaurant bills tax reduced from 18% in 2014 to 5%
  13. Transaction charges through card down from 1% to 0%, domestic money transfer fee down from Rs 5 in 2014 to zero
  14. Financial inclusion (32 crore bank accounts with 260 billion worth deposits). Almost 100% coverage from earlier 50%
  15. DBT (savings of 83000 crores @ 15000 crore annually), No of govt schemes DBT applied to increased from 34 in 2014 to 433, 2.7 lakh fake mid-day meal students, 3.3 crore fake LPG connections, 87 lakh fake MNREGA job cards, 3 crore fake ration cards eliminated
  16. Zero IT for businesses with turnover upto 60 lakhs
  17. GST exemplifying cooperative federalism, rates of 83 items down from pre-GST rates, out of 1211 items only 35 items in above 18% slab, 39% reduction of cost of basic household items. Average 1 lk crore monthly revenue through GST collection. Exempted for business upto 40 lk
  18. Insolvency and Bankruptcy Code, constitution of NCLT, 3 lakh crores of NPAs recovered, 66 cases resolved, 260 cases liquidated, resolution of stressed assets, 2100 companies pay back 83000 crore to banks settling their pending loan repayments
  19. 75 billion $ or Yen to Rupee exchange agreement with Japan
  20. 1 lakh shell companies deregistered, FCRA licenses of 4800 NGOs cancelled
  21. Fugitive Economic Offenders Bill, properties of economic fugitives seized and auctioned
  22. 1.9 lakh km of rural roads. Rural road connectivity at 91% from 55%
  23. 36 new airports, from 65 in 7 decades to 106, all states now in air connectivity map
  24. Effective international diplomacy following 59 visits to nations, 38 single, 10 double, 3 triple and 2 quadruple visits by PM.(Seen during Airstrikes,No Country opposed India)
  25. Benami Act for action against Money Laundering
  26. Rural sanitation coverage 95 % up from 39% (8.8 crore toilets)
  27. Solar energy capacity increased 8 fold from 2.63 GW to 22 GW, 19. 8.5 GW of biogas grid installed.
  28. Ganga waterway transportation, usage by shipping giant Maersk, cost of transportation reduced from 10/ton (road) / Rs 6/ton (rail) to Re 1/ton
  29. More than 2.4 crore households lit up, rural electricity coverage to households up from 70 to 95%, only 19836 homes remain (in Chhatisgarh) out of 2,48,09,235
  30. Electricity accessibility rank jump from 99 in 2014 to 26 in 2019
  31. 7 crore new gas connections to 3.5 crore households u/69000 conections per day, coverage 90% from 55%, 82% return for refill, 42% beneficiaries Dalits
  32. 14.4 crore mudra loans worth Rs 7 lakh crore disbursed
  33. 18000 remote villages connected with electricity
  34. 2.92 lakh km of optical fibre laid, 0.02% to 50% gram Panchayat connectivity
  35. Swachh bharat mission has saved, according to WHO, 3 lakh lives and will save 1.5 lakh lives per year.
  36. IT filers increase from 3.79 crore to 6.08 crore, enterprises registered for indirect tax up from 64 lk to 118 lakh
  37. Entry of India in global regimes Missile Technology Control regime (MTCR), WA (Wassenaar Arrangement) and Australia Group
  38. 17 crore soil health cards
  39. 1.5 crore houses built, 91.37 crore in rural areas and 13.5 lakh in urban areas against 25 lakh houses built between 2010-2014. House for all target year is 2022.
  40. 1,78,346 houses built in NE over existing 2875 houses built till 2014
  41. Home loan interest rate down from 10.3 % in 2014 to 8.4% in 2018, annual savings of Rs 47,160 for 30 lakhs over 30 years, no GST on affordable housing, 5% on remaining
  42. Trading agreement in rupee with Iran and UAE
  43. Common service centres up from 84k to 3 Lakh
  44. OROP implemented after 43 years, 35000 crores disbursed to 8 crore veterans
  45. India's vaccination programme Indradhanush amongst 12 best practices of world
  46. 5035 Jan Aushadhi and - 1054 medicines under price control (60-90% discounts).
  47. More than 150 Amrit stores, reduction of cost of cromium cobalt Knee implant from 1.58-2.5 lakh to 54,720 and high flex implant from Rs181728 to 56490 (69%), 85% reduction in cardiac stent price to Rs 28000
  48. 87% reduction in 400 cancer drugs
  49. Rate of Interest on higher education loans dropped from 14.75 in 2013 to 10.88% in 2019, savings of 1.18 lakh on 10 lakh loan over tenure of 60 months, Rs 2000 savings on EMI
  50. Data revolution: Cost of 1 GB $0.26 in India against $12.37 in US, $6.66 in UK and $75.2 in Zimbabwe. Unlimited mobile+ 45 Gb data = Rs 150 against Rs 1000 in 2013; annual savings of 10,200
  51. Katra rail line work completed after 16 years
  52. Dhola Sadiya bridge work completed after 16 years
  53. Sardar Sarovar Dam work completed after 15 years
  54. Aadhaar act
  55. Pakyong airport completed after 10 years
  56. Chennai Nashri Tunnel after 10 years
  57. Assam NRC after 40 years
  58. National War Memorial after 50 years
  59. NE cpas after 60 years
  60. Kollam bypass after 43 years
  61. Indo-Bangladesh enclaves after 42 years
  62. Bansagar canal project after 40 years
  63. Bogibeel bridge after 23 years
  64. Western peri expressway after 15 years
  65. Kota Chambal bridge after 11 years
  66. Maibang-Lumding Stretch completed
  67. Delhi Meerut Expressway completed
  68. Ganga Expressway project (world's longest) underway
  69. Metros in Ahmedabad, Nagpur, Jaipur, Lucknow, Washermenpet
  70. All umanned level crossings eliminated
  71. Ayushman Bharat: annual 5 lakh health care to every family, 15.05 lakh hospital admissions for secondary/ tertiary treatment, 2.4 crore e-cards generated as on 10 Mar 19 in 170 days. Target 50 crore people.
  72. 59minutes loan portal: 92,000 loan applications of MSME amounting to 30,000 crores approved, 6000 crores sanctioned till Nov 18
  73. 87% of farming house (owning land of 2 hctrs) or 12 cr ppl to get kisaan sammaan nidhi of Rs 6000 pr year. Rs 5215 cr transferred directly to 2.6 crore farmers in 37 days (for households with holding less than 0.01 hectares incm per month so far was Rs 8136 agnst exp of 6594
  74. 1.5 million electric rickshaws
  75. Procurement of 36 Rafale on Government to Government Basis avoiding middlemen
  76. 05 billion$ S 400 Triumf air defence missile system deal with Russia
  77. 145 M777 howitzer deal
  78. 22 Apache AH 64E multi-role combat helos
  79. 200 KA-226T helicopters
  80. 56 EADS CASA C-295 transport aircraft
  81. 15 CH 47 Chinook tactical transport helicopters
  82. 2.3 lakh Bullet proof jackets
  83. 1.6 lakh Bullet-proof helmets
  84. 777 mn USD Barak 8 LRSAM contract
  85. 5 bn USD S-400 air defence systems
  86. 10 Heron TP armed drones
  87. 4 additional P8I MR aircraft
  88. 40 units of Laser sensor border fence installed
  89. 72,400 Sig Sauer Assault rifles
  90. 100 self-propelled K9 Vajra howitzers
  91. 700000 AK-103 Kalashnikov assault rifles indigenous facility
  92. Surgical strikes in Myanmar, across LoC and in Pakistan. Only Country to bomb a Nuclear Powered Country
  93. 240 million visitors at Kumbh Mela 2019, cost 4236 crores @ Rs 177 per tourist, revenue 1.2 Lakh crores
  94. 833 teraflop supercomputer Param Shivay by IIT BHU at Rs 32.5 crores
  95. Divisional status to Ladakh
  96. 470 bed ESIC hospital in Ennore
  97. 100 bed ESIC hospital in Tiruppur
  98. Namami Gange - Ganga is 30% cleaner, 83 out of 97 ganga towns and 4456 villages achieved ODF status, 08 out of 16 drains emptying 16 crore l sewage into Ganga tapped. Target date Mar 2020
  99. 5,45,122 ODF villages, 598 ODF districts, 27 ODF states/ villages
  100. RERA implementation
  101. Udaan scheme - flight cost down from Rs 5000/1000 km in 2013 to 3400/1000 km in 2018, 34 airports operationalised, small towns connected, all states on aerial
  102. Preventive conservation of 39275570 folios, curative conservation of 3656863 filios, digitisation of 2.83 lakh manuscripts consisting of 2.93 crore pages
  103. India is now world's largest 2-wheeler manufacturer, 2nd largest smartphone manufacturer (94% of mobiles sold now made in India), 4th largest automaker, 2nd largest steel producer
  104. 5100 m Mandvi Bridge in Goa in 3.5 years
  105. Ease of doing Business ranking jump from 134 in 2014 to 77 in 2019
  106. Therubali - Singapur Bridge No 588
  107. Restoration of Asurgarh Fort, Kalahandi
  108. GeM portal with 731431 product categories, 180,862 registered sellers and 32114 govt buyers
  109. 10% EWS reservation
  110. 40% of ongoing 700 NH projects completed, adding 40,039 km between 2014-18 against 91,287 km between 1947-2014
  111. Highway construction rate jumped from 12 km/day in 2014 to 27 km/day in 2019
  112. 101 terrorists and 11 offenders extradited
  113. 90,000 ex-partite Indians evacuated
  114. Chabahar port, Sittwe port and Duqm port
  115. Military installation in Seychelles
  116. International logistics agreements with US, France and Singapore
  117. Work underway on 25 MLD ZLD Common Effluent Treatment Plant at Gujarat Eco Textile Park and will save 25 million litres of water per day
  118. Beautification of 65 railway stations, all stations fitted with LED lights, wi-fi, multi-brand food centres, kiosks, executive lounges, lifts (445 from 97 in 2014), escalators (603 from 199 in 2014), travellators and ramps
  119. Record number of foot over bridges built
  120. 871 new train services
  121. 180 new rail lines
  122. Dedicated railway freight corridor - 2 sections completed
  123. 100% electrification of railways underway, first solar powered railway station (Guwahati). First solar powered train (world's second), savings of Rs 40 Lakhs and 90,000 ltrs diesel per year
  124. Make in India semi-high-speed trains - Tejas, Gatiman and Vande Bharat
  125. Humsafar and Antodaya trains, Deen Dayalu and Anubhuti coaches, UDAY double decker, glass dome Vistadome coaches
  126. Project Swarn and Project Utkrisht to upgrade Rajdhani/Shatabdi and Mail/Express respectively
  127. Largest coach production in world at ICF, Chennai
  128. No more human extreta on railway tracks. Installation of 1.37 lakh out of 2.5 lakh completed in Jun 18.
  129. 400 wi-fi railway stations (Aug 18)
  130. 80% reduction in rail accidents
  131. 10 high speed rail corridors underway, target date 2025-26
  132. Export of world class customised coaches from MCF, Rae Bareli
  133. LIC and Air India register profit
  134. 2300 km rail tracks constructed, speed jumped from 4.1 km/day in 2014 to 6.53 km/day in 2018
  135. Neem coating of urea
  136. Gokul mission - record 160 million ton milk production
  137. Online availability of CBSE and NCERT books
  138. 10 crore LED bulbs distributed, 5000 crore savings
  139. Investment in urban infrastructure jumped from 157703 crores to 795500 crores
  140. Statue of Unity to commemorate Iron Man of India
  141. Rs 2509 crore sales in Khadi
  142. 482.36 million digital transactions worth Rs 74,978 crores in Oct 2018 against 0.3 million transactions worth Rs 90 crores in Nov 2016
  143. 30% increase in ATMs, 208% increase of PoS machines from 10.81 lakh in May 14 to 33.32 lakh in Aug 18, 111% increase in credit cards from 1.94 crore in May 14 to 4.10 crore in Aug 18, 144% increase in debit cards from 40.17 crore to 98.02 crore
  144. Ease of Doing Business Index 142 (2014) to 100 (2018)
  145. Ease of getting electricity index 99 (2014) to 26 (2018)
  146. UN's e-govt index 118 (2014) to 97(2018)
  147. Globalisation index 112 to 107 (2018)
  148. Innovation index 76 to 60 (2018)
  149. Competitiveness index 71 to 39
  150. Logistics performance index 54 to 35
  151. Global peace index 141 to 137
  152. DBR ranking 100 to 77
  153. India ranks 3rd in global start up ecosystem
  154. 06 crore jobs in MSME sector based on CII data
  155. 448 million formal jobs based on EPFO, NPS and PPF data
  156. 10 crore jobs in entrepreneurship via mudra and other schemes
  157. 80% increase in tax payers, 51.3 % increase in gross tax revenue
  158. Black Money report card - Voluntary income declaration scheme (Rs 65250 crore), IT search and survey operations (35,460 crore), Pradhan Mantri Garib Kalyan Yojana(5000 crore), Benami transactions Act (4300 crore), Black Money and Imposition of Tax Act (4100 crore)
160 Rs 6000 financial assiatence for pregnant women
161/1 . Sagarmala: port capacity increase from 8 to 14.7 lakh ton, cargo up from 89 to 116 MMT 8 new national waterways including ganga waterway NW-1 and Brahmaputra waterway NW-2.
161/2. domestic cruise service between Mumbai and Goa, ro-ro services on Ghoga-Dahej reducing travel distance from 294 to 31 km
161/3. New international cruise terminals at Chennai and Goa, railway line between Haridaspur and Paradip underway, LNG import terminal at Kamarajar port, Oil berth ai Jawahar Dweep,Coal berth at Mangalore port
161/4 . deep draft Iron ore berth at Paradip berth, JNPT SEZ, Kandla and Paradip smart industrial port city, largest dry dock and international ship repair facility at CSL, modernisation of 17 fishing harbours
  1. 800 km Delhi-Mumbai Expressway underway
  2. Replacement of bio-toilets with upgraded vacuum bio toilets in trains underway. Order for 500 placed on experimental basis.
  3. No terror strikes in hinterland
  4. 103 new KVs
  5. 62 new Navodaya Vidyalayas
  6. 6 new IITs against 16 in previous 57 years
  7. 6 new IIMs against 13 in previous 57 years
  8. 7 IIITs against 7 in previous 57 years
  9. 02 new IISER
  10. 12 new AIIMS against 7 in previous 57 years.
  11. 141 new universities against 30 in previous 57 years
  12. 01 new NIT
  13. Life Insurances @ Rs 12 annual and @ Rs 12 monthly premiums
  14. Atal Pension Yojana
  15. Pension to 42 crore people of unorganised sector
  16. Ambedkar memorial
  17. BHIM application for digital payments
  18. Khelo India Initiative for tracking of athletes' development, Rs 5 lk per annum scholarship for 1000 budding athletes per year for eight years each; monthly Rs 50000 out-of -pocket exptr, 2000 PETs, salary cap of coaches doubled from Rs 1-2 lk per month, target 15 yrs
  19. Special Task Force for Olympics
  20. RERA Act
  21. Bullet train maiden project
182/1. Rs 6.92 lakh crore Bharatmala project, 44 economic corridors with 9000 km road, 2000 km port connectivity, 9000km roads to connect district HQs with NH,
182/2. 2000 km road with Nepal, Bhutan, Bangladesh and Myanmar, opening up of 185 choke points, road development to char dham, 12 greenfield expressways spanning 1900 km
  1. 36 murtis retrieved and brought back to India in 2014-2019 under India Pride Project against 02 between 2000-2013, 02 in 90s, 03 in 80s, 01 in 70s and nil in 50s and 60s
  2. Unemployment rate 3.8% against 13.8 % in 2013
  3. India is a less-cash society now
  4. Develpment of Trincomalee and Columbo port while checkmating China's Hambantota by taking operations of near by (15 km away) Mattala Rajapaksha International Airport
  5. Plugging the 'double taxation avoidance' black money loophole through a new tax agreement with Mauritius
  6. Deal with Switzerland for automatic tax data sharing from 01 Jan 2019
189/1 Varanasi - Varanasi ring road phase 1 completed, phase 2 underway, inland waterways terminal, Babatpur airport highway, 140 MLD Dinaput STP, facelift to railway station, big cow shelter for stray cattle, BPO centre, piped gas project, Varanasi-Balia rail project,
189/2. Vande Bharat Express, Kashi Vishwanath temple - Ganga Ghat corridor project, renovation of all bathings ghats, LED illuminations of ghats and major roads, underground electricity cabling,
189/3. new sewage plants, 02 cancer treatment facilities, 65th to 29th rank in swachhata sarvekshan (2016), 90% ODF district.
  1. Creation of 100 Smart cities, 100 crore per year per city for 05 years, 500 acres for retrofitting, 50 acres for redevelopment, 250 acres for green field projects, 10% of energy from renewable resources, 80% of green building construction, special purpose vehicles.
191/1 Development of 500 AMRUT cities underway, urbanization project of rejuvenation and transformation which includes beach front development, prevention of beach erosion, improvement of water supply, replacement of pipelines,
191/2. New sewerage connections, greenery and open spaces, digital and smart facilities, e-governance, LED streetlights, public transport, storm water drainage projects in a phased manner, Target date 2022
  1. Increase in Child Sex Ratio (CSR) in 104 BBBP (Beti Bachao Beti Padhao) districts, anti-natal care registration in 119 districts and institutional deliveries in 146 out of total 640 districts as in Mar 18. CSR of Haryana increased from 871 to 914.
  2. International Yoga Day
  3. Aspirational Districts Programme: 115 'backward' districts placed under 'prabharis' and for competitive development on the basis of 49 performance indicators, target year 2022.
195/1. Make in India: 16.4 lakh crore investment committments, 1.5 lakh crore investment inquiries, 60 bn USD FDI, 26 sectors covered, 23 positions jump in World Bank's Doing Business Report (DBR), 32 places in WEF's Global Competitiveness Index (GCI),
195/2 19 places in Logistics Performance Index, 42 places in Ease of Doing Business index, schemes include Bharatmala, Sagarmala, dedicate freight corridors, industrial corridors, UDAN-RCS, Bharat Broadband Network, Digital India.
  1. 251 Passport Seva Kendras (PSKs) and Post Office Passport Seva kendras (POPSKs) against 77 till 2014, target of one PSK every 50 km across India.
  2. Unanimous election of Justice Dalveer Bhandari to ICJ forcing UK to pull out own nominee Christopher Greenwood, demonstrating India's clout in international arena.
  3. India Post Payments Bank: India's biggest banking outreach with 1.55 lakh post offices (2.5 times banking network) linked to IPPB system
  4. Philip Kotler award, Seoul Peace prize, Champion of the Earth Award, Grand Collar of the State of Palestine, Amir Abdulla Khan Award, King Abdulaziz Sash award, Amir Amanullah Khan award.
  5. 1900 gifts and memorabilia received by Modi auctioned and 11.7 crores added to Namami Gange fund, 1.4 c of Seoul Peace award also to Nammami Gange.
New Adds
  1. Removal of article 370 and thereby also 35a after several decades.
  2. Giving citizenship to persecuted minorities in Pakistan, Bangladesh and Afghanistan through passing of CAA.
  3. Trust for creation of Ram Mandir underway.
  4. Abolishment of Haj subsidy.
  5. Abolishment and criminalization of instant triple talak.
  6. Deal with Bodo community.
  7. Getting Maulana Masood Azhar listed as an UN designated terrorist.

Source - https://www.reddit.com/IndiaRWResources/comments/bgkus6/200_achievements_of_modi_govt/

List more achievements in the comment section and lets make the list bigger, a big thank you to our fallen kar sevak u/Alive_Firefighter
submitted by justchillar to Chodi [link] [comments]

Reality check for newbie roadmap with algo trading

Hey guys,
I'm planning to start trading on forex in the next few months. Right now I'm doing babypips :) I've got some ideas/long term plans on how I want my trading journey to look like and I'd really appreciate reality check if it's plausible to achieve.
First some background. I'm a software dev and I'm doing really ok for myself, I've been able to put aside some money that if lost or spent it won't affect anything, retirement, personal savings, vacations, travel and all other budgets are all separate from it.
Roadmap:
  1. Finish babypips
  2. Open demo account and trade for around 6-12 months to get a hang of it - the goal is to create a trading strategy
  3. Open a live account and try to not blow it for the next 12 months - the goal is to break even, tweak and adjust the strategy
  4. Be profitable after 24 months on the market - the goal is to achieve 1%-6% monthly returns
  5. Create algo system as a helper - this is the final chapter, reflect my strategy the best I can in automatic system. What'd be left is to tweak and configure it on a weekly basis into the future.
This is my dream scenario, long term plan and direction to follow. I'm making no assumptions on anything, I know it might take 3 or 4 times longer or not work at all. Right now I don't know what I don't know and wanted to clash my imaginations with reality how this journey might look like before I start committing countless hours to this. I want to give myself enough time to be successful with this plan, even if it'll take a decade or more.
Some explanation on the algo. I'm not looking for silver bullet that'll crack the market and make me rich. I'm wishing to build a system that will be an extension (like another limb) to my body and mind to anything that can be automated in trading, something that constantly has to be improved and adjusted with the changing market. I just want it to reflect a strategy that I'd already apply manually.
The end goal (many years into the future) is to acquire enough account size to be able to quit my day job and live comfortably from mostly automated trading.

What are your thoughts on this roadmap? Is this a reasonable plan to follow? Is it possible to achieve something like a constant 2%-5% monthly returns with algo trading and putting max 8 hours in a week for maintenance and tweaking?
submitted by PancakeFrenzy to Forex [link] [comments]

on the fakeness of the internet

funny to see that subject pop up again. it was what drove me insane enough to find this sub in the first place.
at any rate, the problem is not the bots. I thought it was, but those are just part of the parasitic ecosystem.
but to get that, first we need to take a few steps back on web history, ad serving, UX, tracking technology and media advertising.
too lazy to gather links, but you know, do your googlin'.
I assume that most of you are fairly web literate here, but I'll try to go down into the bare bones as much as possible for those who aren't.
so let's start with a basic question - what is a web visitor anyway?
from the standpoint of a normal person, that would be a person browsing a given website or piece of content. from the standpoint of technology however all you know is that some device has downloaded content from your server using the http protocol. thanks to the wonderful technology of web browsers, you can plant browser cookies on a visitor - stuff that's used to remember if they logged in, what their preferences are, stuff that your service can read from the device. it also serves usually very basic telemetry like last visit time, session time, and so on.
this, over time has evolved in what we call browser fingerprinting, a convoluted bunch of technology that allows websites and web services to uniquely identify you.
it still doesn't know if you're a human or not, but from the standpoint of the web technology, you're a visitor.
now back in ye old days of the web, when the first banner ads were springing up, these were important questions. most consumers were still to be reached on traditional media channels, and ad spend would have to be justified somehow on the risky ventures of online business. so beyond traditional polls that would infer the value of visitors, websites would start tracking number of visitors, time on page and so on. these were used to milk the advertising cow so to speak, and it gave in to some funny developments like the creation of the popup ad - if I recon correctly on geocities, where they would just but the ads everywhere until some big auto company noticed that they're appearing on porn sites. so - put the ad in the popup, and you can claim it's not in the context of porn!
around this point in time the online ad business is still pretty low tech. you actually have to call a physical human being, they send you ppts and pdfs, you send back image files and excel sheets, you wire money, the ads run, and so on. this is called direct sales, and it's tracked again by counting a bunch of visitors, and telling you how much impressions and clicks your marvelous creatives and ad budget generated.
now enter google - or more precisely, a technology firm called doubleclick that was to be acquired by google. they developed a tool for automatic ad serving, later to be called programmatic advertising, that keeps the pesky sales dude out of the loop and achieves reasonable amounts of scale for a more hefty price - after all, if the sales are automated, you get a bidding war for attention between different advertisers, and you're paying for clicks.
so you can see how this was a strategic move for google - they already had the most valuable data available in this situation. they were seeing in real time what people were searching for, and using the programmatic ad serving system, you could effectively bid not just for general attention - but for attention with an intent to buy.
...and the way that google got this data is because they indexed the web, using bots. at least GoogleBot would identify itself as a site visitor, but in the meantime they developed a service for websites to comprehensively track their own visitors and where they were coming from and what they were doing on your website. incidentally, you could also put on google's ads on your webpage to earn quite a bit of money, as content relevant ads would be shown through the doubleclick system.
this kicked off two things:
one, the ability to classify your website visitors into different clusters and segments allowed businesses to start tailoring the appearance of the website or service to fit that specific audience segment, starting off the great fracture - segmentation of the web (in the sense that two people viewing the same website at the same time were not seeing the same thing)
two, it created a very strong financial incentive for people to trick google into thinking they were having actual human visitors that would click on ads, when in fact they were bots. in an even funnier twist, some of them were from browser hijackers, commonly known as malware at the time, which google cross-financed. look up download valley and crossrider.
at the cross section of the above two, you had one interesting twist: websites that would appear differently to the security bots or the compliance officers of Google as they would to fake visitors or malware jacked human beings. the former would get a benign looking website, while the latter would get bombarded with auto clicking ads.
this kicked off the billion dollar arms race called online advertising fraud.
I'm not here to shed a tear for big money corps bleeding money. the real fallout lay somewhere else, but for that you have to understand that you never really saw the real internet, you only saw your corner and the one that was personalized for you.
but if you ever had the pleasure of watching daytime TVs or off channels and witnessing the ads, you could kind of infer what kind of audience must be watching these shows generally. from quite clear rip offs to magic number lotteries and television fortune telling, these sorts of programming was aimed at the most gullible, bought for pennies, where the smallest audience portion had to be converted into a money making operation.
...and with audience segmentation and data gathering, that was now possible at unprecedented scale, automatically. so big was the scale in fact, that it gave birth to an entire new beast of an industry called affiliate marketing, where instead of a regular payroll, you'd get a cut of the sale should you figure out an angle on where to push whatever fucking bullshit the vendors were offering to whoever the fuck would be dumb enough to click on an ad and buy. (the funniest story I recall was someone pulling five figures a month because he figured out that if you buy ads on anime-hentai pages and sell PUA shit courses and e-books you'd make a killing)
at any rate, affiliate marketing brought with it the killer landing page, the thing that's supposed to hammer the nail in the coffin once you get through the banner ad. the earliest form of deceptiveness in memory comes from various pirate sites, that had fake download buttons as banner ads and virus alerts as the landing pages. but then at some point, some schmuck realized that for certain type of products, like diet pills or forex trading or whatever, the best lander is in fact a fake news page that comes packed with comments and all. that would convert like crazy, because it had the appearance of social proof.
until at least the lawsuits came raining down, and these sorts of landing pages and campaigns for being banned left right and centre on all platforms. which just launched a new arms race as the campaigns would be disguised for the bots doing the checkups, and aged facebook profiles would start selling for like 5K USD - these people were making 30-40k a day, they could afford to spend that much to continue running the shop.
speaking of facebook - it came just about the right time for the shit to brew max total. first they were unprecedented in the amount of data they were getting off of their users, and they came just in time to catch the full swing of what we call the 'responsive web' - that no user at the same time would see the same thing on their page, it was all allocated through an intricate web of recommendations, running real time, based on previously gathered and forecast behavioral data.
it also ran on one simple premise: take over the starting page position from google for most people, then they do not have to justify, ever, any ad spend that takes place on their platform, as long as it performs. furthermore, it was completely lacking any revenue share sort of scheme (save for the short period of facebook gaming, see Zynga), thus there was no incentive for the amount of bot traffic that the previous internet era had bred. instead, it came with an entirely different one - bots that would offer social proof in the way of shares and likes, but would not directly risk the business model, thus giving no incentive for facebook to fight them. (note that google didn't do much jack shit either besides indiscriminately penalizing websites it deemed suspicious when they reached critical payout thresholds)
the rest of the story you kind of sort of know. how the obama campaign was brilliant in using the new social media to inspire hope and blah blah blah, kicking the door open for big money politics who could hire the best snake oil salesmen in the market, who had the data and as you can see from the above, had the ethical standards of a shoe. at around 2014-2015 the press (the mainstream media) started to raise question about the duopoly, the buzzword of filter bubbles started appearing, not entirely unrelated to the fact that facebook by this time cannibalized their traffic with a fucking embedded share / like button and started charging money for them to reach their own audience. after 2016 the cries of fake news were everywhere, because there was no online space left which everyone was viewing the same way, and you had no way to verify what the person next to you was looking at.
since then, we've all become grandpa yelling at the television set, with nobody around us seeing what we're seeing on the screen, so we're being accused as bots and looking for bots under the carpet.
but it's been a long way coming, and the bots are honestly the least of our worries. trust me, I went bankrupt over that one. truth or fake doesn't even begin to describe the magnitude of the problem: more like we entered the phase where every word, event or picture is defined by who ever the fuck wins the auction over it, as the marketers of human attention grind the gears of the money mill without even understanding how fast they're digging towards hell.
don't believe me? look around the marketing and advertising related subs these days. the priests are eating the indulgences, and we're only now entering the period of deep fakes, good algo generated audio and good enough NLP. and in the meantime, the shadowrunners running up between two corp headquarter-highrises are skinning your belief systems.
so the best you can do is really, not litter the remnants of cyberspace which are not being mined, astroturfed or being pulled apart by the algos. no human connections on a nuclear trash heap mate.
submitted by gergo_v to sorceryofthespectacle [link] [comments]

WikiFX: the murky business and the murkier methods

WikiFX: the murky business and the murkier methods
https://preview.redd.it/1rf74ljv34l51.png?width=960&format=png&auto=webp&s=566235871ce22dd3078f0532dfb672bff6eb0707
The irony of financial markets is that this business that officially has got as much regulation as arms trafficking, has also got the same problem –- numerous illegal entities that evolve around the niche.
Scam brokers, funds recovery services that rob the robbed traders, HYIPs, “learn how to make millions overnight” trading courses and a number of other schemes all tend to exploit the weak point of human nature – the belief that there is the magic device with the “MORE MONEY” button out there, that someone can sell you.

A thief shouting “Thief!”

Considering the above there is a high demand in society for truthful and unbiased information about the market players. WikiFX claims to be the provider of such honest information about brokers but in fact, makes money by blackmailing brokers and promoting any company that offers to pay enough in their rankings.
WikiFX is a classic illustration of a thief shouting “Get the thief!” louder than anybody else in the crowd. The strategy works unfortunately and traders tend to trust WikiFx broker’s ratings without questioning what these ratings are based on and who sponsors this global brokers’ database.

Paving the road with some good intentions

Even the most horrible crimes against humanity were done under the cover of best intentions. Starting with the first crusades and ending with the holocaust. There are always some sound arguments, protected people and reliable methods.
Ask any trader whether each forex broker must be regulated by a third party? The answer will be “yes” with a near 100% probability and this answer is totally correct. Know-your-customer procedures and some unbiased third-party control are essential for maintaining the overall transparency of any business in a sphere of finance. This is the argument that WikiFX starts with when promoting its service and there is absolutely no point to argue. Starting with an indisputable truth is a good strategy to win the debate.
“The long-term presence on the market adds credibility”, – says WikiFX, and hears “yes” again.
“Don’t you agree that the longer the company is in the business, the better?”. “Sure”, – the trader agrees one more time.
The mission is completed. This is when the broker ranker can add any other criteria to their appraisal methods. Traders will tend to trust the service because they’ve agreed upon the most important criteria. The rest are minor details.
But what if the rest of the appraisal methods are not just minor issues? What if these details can be the means to manipulate the facts as much as they want to?

Can WikiFX appraisal criteria be trusted?

If we take a look at any broker’s WikiFX rating, we can see that the criteria of appraisal are the following:
  • The year of registration
  • Regulations
  • Market Making license
  • Software license
For example, this is what the top-rated broker’s summary looks like at WikiFX:
WikiFX Forex com example
https://preview.redd.it/t4ugtbt344l51.png?width=625&format=png&auto=webp&s=95fddf8434faf8938d1a3f18bbd5f1da2ceb47e4
Looks good. Really. Regardless of the attitude to this particular brokerage, the work seems to be done fine. All the regulators are listed below, the information on the used software, licensing, and years of operation is included.
But what if we take some other random brokerage with one of the lowest rankings at WikiFX?
NinjaTraderBrokerage WIkiFX Ranking
https://preview.redd.it/pgyqp0u644l51.png?width=631&format=png&auto=webp&s=eb268faac83608a494c31a39eb1621f7132e3520
This is where the truth reveals itself. Once again, regardless of the attitude to this particular brokerage this is really easy to find out what they do, what licenses they’ve got and what kind of software they use.
Suspicious clone? Seriously? If WikiFX staff cared enough to do any investigation prior to stamping that “Suspicious” mark on the brokerage, they would have seen that both domains, nijatrader com and ninjatraderbrokerage com belong to the same entity.
NinyaTrader whois data
https://preview.redd.it/2097lkw944l51.png?width=563&format=png&auto=webp&s=079cc4248b825a3cd941c6b691a67bb9769f4f7f
If they cared enough to collect information on the brokerage from at least one reliable source, like Investopedia or any other similarly known database, they would also have found out that the company not only provides the brokerage service, but also is known for its trading platform with advanced technical analysis tools. But the only trading software that WikiFX considers reliable seems to be MT4/MT5. They simply ignore the fact that trading does not evolve around MetaTrader products, no matter how good and popular they are. WikiFX lowers the score of any brokerage with custom-developed software. We can clearly see this with the above example.
Other criteria that WikiFX is proud to use for the broker’s appraisal are regulations. Using the same example let’s see how well they do the appraisal in this field. As you can see above, WikiFX used the “Suspicious Regulatory License” stamp for NinjaTrader Brokerage.
And here is what The National Futures Association, that NinjaTrader is registered with as a futures broker has on its record:
NFA regulation of NTB proof that WikiFX did not consider to be trustworthy

https://preview.redd.it/di8fwkdd44l51.png?width=629&format=png&auto=webp&s=2de618d5df26bd8fcca99c51a6030f4bdfa7f776
We can’t expect every trader to know that any futures broker that wants to operate on the US market must be a member of NFA. This is the requirement of the Commodity Futures Trading Commission regarding the futures broker’s operations. But this is totally unacceptable for a broker ranking website, which WikiFX claims to be, to mark NFA-registered futures brokerage as non-reliable.
By the way, did you notice on the above screenshot that NTB has obtained the NFA license in 2004? Yet, this does not prevent WikiFX from claiming that the brokerage has only been providing its services for 1-2 years only, instead of the factual 16 years of operations.
We can long discuss the reasons that lie behind such selectivity of WikiFX but this random example clearly shows that any brokerage that provides access to non-forex derivatives trading or dares to suggest custom-developed software to its traders is in danger of receiving a negative review at WikiFX regardless of the factual reliability and regulations.

What lies beneath WikiFX selectivity?

WikiFX claims to have a team of professionals that are all involved in objective appraisal of broker’s services, licenses and used software. The methods used by these professionals remain unrevealed and as we see from the above comparison two similarly reliable brokerages can get any score from 1.0 and up to 10.0 at WikiFX, no matter what regulations they’ve got, for how long they’ve been in the business and what kind of software they use.
This is difficult to say what lies behind such selectivity with 100% confidence. The first thing that comes to mind is that WikiFX might be affiliated with some brokers. The hypothesis gets even more realistic if we try to understand who sponsors WikiFX.
There are no transparent built-in ads neither on the web-version of the website nor in its applications. There are no paid subscriptions for access to the database. This means that users sponsor the service with neither their attention to ads nor directly. Being the non-charity and non-governmental organization WikiFX can’t be sponsored with donations or a government. The only option that we have left is that brokers sponsor this ranking system directly, which automatically makes the whole system non-reliable and highly biased.
The only transparent method that we know WikiFX uses to collect money is sponsorship fees they collect from their offline events participants. Let’s have a look at the exhibitors of the recent WikiFX Expo in Thailand.
WikiFX Expo Exhibitors

  • TLC is a non-regulated investment platform that was founded in 2019
  • Samtrade FX is not regulated by any of the agencies that WikiFX itself lists as reliable
  • Forex4you is not regulated by any of the agencies that WikiFX itself lists as reliable
  • B2 Broker is a non-regulated broker
  • XDL FX is a non-regulated broker
  • VAT FX is a non-regulated broker
    Six out of sixteen WikiFX recent expo exhibitors do not have proper legal status according to the “standards” of WikiFX itself. This fact does not prevent them from promoting the services of these companies at their offline events. This conspicuous fact tells a lot about the attitude of WikiFX to common traders looking for reliable partners. Reputation is nothing but a sale item for this brokers’ ranking system.

Murky & Murkier

So far we’ve only discussed the facts that anyone can check himself using free tools and sources.
It was not that difficult to discover that WikiFX uses non-transparent standards for brokers’ appraisal. It ignores the specifics of some brokerages lowering their scores due to non-standard derivatives they offer to trade or custom trading software. It also promotes non-regulated and non-licensed brokerages, which is 100% against the declared WikiFX values and mission.
The rumors are that this company was also noticed blackmailing brokers with the purpose of making them pay for better reviews at WikiFX. There are also some signs that indicate suspicious promotion of WikiFX platform through social media and Quora. Some of the WikiFX positive reviews also look highly suspicious. All of the above is a matter of further investigation.
Nevertheless, thousands of users keep relying on the information provided by this scam ranking system. It may even look like all these users are satisfied. WikiFX has got 4.5 starts at Google Play, which sounds good enough. However, positive WikiFX reviews use similar semantics and are also highly suspicious. Despite the high average grade, Google Play finds the following messages to be most relevant and brings them to the top of WikiFX reviews:
Google Play most relevant WikiFX reviews

https://preview.redd.it/kftutvcl44l51.png?width=532&format=png&auto=webp&s=1ccb74ee156388285a2fab711dd604945c04377c

You’ve got the facts now and it’s time to make your own conclusions.

submitted by WorriedXVanilla to u/WorriedXVanilla [link] [comments]

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