Stocks/Futures
Forex/cfd
So don't buy it, when "mentors" and advice givers say they can't show their verified stats. If they can't show them, they don't have them.
Stocks/Futures
Forex/cfd
So don't buy it, when "mentors" and advice givers say they can't show their verified stats. If they can't show them, they don't have them.
Stocks/Futures
Forex/cfd
So don't buy it, when "mentors" and advice givers say they can't show their verified stats. If they can't show them, they don't have them.
Yes, they can.
Here are some live verified profitable accounts that are 9-13 years old:
https://www.darwinex.com/account/D.22041
https://www.darwinex.com/account/ERQ.4
https://www.darwinex.com/account/D.51735
https://www.darwinex.com/account/D.48146
https://www.darwinex.com/account/D.129008
https://www.darwinex.com/account/D.29190
https://www.darwinex.com/account/D.32176
Don't only look at their all time maximum drawdown. Check the last 2 years, last year, etc.
***
And here are some more on Myfxbook: 6-8 years old (reputable regulated brokers):
https://www.myfxbook.com/members/FERRARI2009/ic-markets/3534905
https://www.myfxbook.com/members/adsa/bigpicture/2322122
https://www.myfxbook.com/members/iminwarn/555/6426348
https://www.myfxbook.com/members/eafiltergrid/eafg-190304/10188767
If the main problems traders faced were psychology and discipline, we would see almost 100% profitability among algo traders. We don’t. Therefore, basic common sense already refutes this claim.
The real problem is edge – a combination of factors that provides positive expectancy across a statistically significant sample. 99.9% of traders on this sub don’t have it. That is the only reason they are not profitable. Their strategies are random, like a coin flip.
“Psychology” fans want to make them disciplined at flipping coins. But they still don’t become disciplined, because even when they try to be disciplined, they still lose, so they feel no incentive to keep being disciplined. They improvise, try changing things, and don’t understand why it keeps failing.
It keeps failing because there is NO EDGE – there is nothing that provides positive expectancy across a statistically significant sample.
They don’t have edge, because they never even tried to look for it. They don’t even know how it is done, because throughout their entire journey they have been wasting time following stupid rules instilled by the trading “education” industry, which lies to them with things like: “backtests don’t work,” “your problem is psychology,” “risk-to-reward must be at least 1:2,” “you must cut losses fast,” "improve your chart analysis", "that's because you should stay on paper account for long enough" etc. How convenient for them, isn’t it? Their goal is not your success. Their goal is more YouTube views and more course sales. Their goal is fewer successful traders.
And we arrive at the sad reality that 99% of traders don’t even know how to backtest correctly. They think a backtest is one single test over the longest period possible. No! Absolutely not! After such a backtest, no matter how good it looks, they still keep losing.
No one told them about the minimum condition for profitability in trading: rolling walk-forward analysis (in the past!) across a statistically significant sample. Let alone all the other tests they should perform as part of a well-structured research process that they must develop themselves. If a trader has tested their strategy inside and out, they trust it. They stay calm and don’t feel the need to interfere or break their own rules every hour. Suddenly, there are no discipline problems and no psychological rush, because their trading actually works. On the other hand, if a trader enters the market with no statistical assurance, they constantly doubt themselves and stay stressed, because they simply don't trust that it all can work.
* * *
Disclaimer: I am a profitable trader with a publicly accessible live track record, verified by a company regulated by the Financial Conduct Authority (UK). You can disagree with me, but you cannot deny that I am speaking from personal experience and backing it with real trading results. Can the attackers of this post demonstrate the same?
I don't teach! I believe that only you can teach yourself, if you want it badly enough. If you want to know more about me and my trading style, simply read my posts.
Hey everyone,
I am a systematic algorithmic trader. I have only one "psychology" rule: don't ever interfere with your automated strategy that has been proven with statistical significance.
But
What if the circumstances are unique? I currently have several positions, some in profit and some in loss. I know that if the war with Iran restarts (high risk), these positions will probably move against me due to risk aversion.
On the other hand, my strategy is always stress-tested, including during wars.
Yet, I look at these positions and I feel tempted to close them.
Would you interfere and close those positions?
a strategy capacity of $190M, and managing an external investment of €100k that has a high chance of growing to several million (paid 20% of profits).
The question to you all:
Should such a trader seek a job in the quant industry?
Hi everyone,
Two years ago I made my first million and I I honestly thought sky is the limit, so I decided I would stop trading and invest most of my capital into safer assets for my future. I traveled for a while, met people, and tried to enjoy life. But after some time I realized that when you remove the goal and struggle from your life, you start being bored. The people I met already had their own life, families, and goals, and I wasn't part of their plans.
That’s when I decided to start teaching people how to trade. Not for money. Just because I wanted to help talented people avoid the mistakes I made. I started posting here on Reddit, answering questions, coaching a few students privately (never more than 3 at the same time), and eventually recording several introduction courses. Over time I realized that teaching gave me more satisfaction than making money itself.
A lot of people ask me what strategy I use, so I’ll briefly explain the core philosophy behind it. My approach is based on multi-timeframe market structure analysis combined with liquidity sweeps, institutional order-flow concepts, volatility compression, and momentum confirmation. I mainly focus on identifying engineered liquidity zones where retail traders are statistically trapped before expansion phases. The process starts with weekly and daily directional bias. Then I refine entries on lower timeframes using: market structure shifts, fair value gaps, displacement candles, volume imbalance, Fibonacci premium/discount zones, ATR-based volatility filters, session timing, psychological price levels, and confirmation through price delivery algorithms.
Risk management is everything.
I never risk more than 0.5%–1% per trade, and discipline matters more than strategy. Most traders fail not because their strategy is bad, but because they lack emotional control and consistency. People always search for a “holy grail,” but the real edge comes from patience, journaling, discipline, and understanding market psychology. Here’s an expanded “discipline guru” section you can insert before the disclaimer to make the satire even stronger:
The biggest misconception in trading is that people lose because of strategy. They don’t. In my opinion, almost every strategy can work if the trader behind it has enough discipline.
Discipline is the real edge.
Most traders already know what they are supposed to do: cut losses, let winners run, avoid revenge trading, stay patient, respect risk, follow the plan, avoid emotional decisions. But knowing something intellectually and actually executing it consistently are two completely different things. The market is designed to attack human psychology. Fear makes people close winning trades too early. Greed makes them overleverage.Ego makes them average into losers. Boredom makes them force trades that were never there.Hope makes them hold bad positions. Impatience makes them abandon profitable systems before the edge statistically plays out. Most people are not losing against the market. They are losing against themselves. That is why I always tell my students that trading is not really about predicting price. Trading is about predicting your own behavior under stress. When I first started trading, I had to completely rebuild my mindset and daily habits. I removed distractions. I stopped checking social media during trading sessions. I created strict routines. I journaled every trade. I tracked emotional states before and after execution. I reviewed losing weeks in detail. I learned to sit still and do nothing for hours if conditions were not aligned. A professional trader must become emotionally neutral. You cannot become euphoric after winning. You cannot become depressed after losing. You cannot increase risk because you “feel confident.” You cannot break rules because “this setup looks different.” The market punishes emotional inconsistency very quickly. One thing I learned is that discipline is not something you use only in trading. It becomes part of your personality. The same discipline that allows someone to: wake up early, exercise consistently, eat correctly, avoid distractions,control impulses, and stay focused for years, is usually the same discipline that allows them to become profitable traders. People constantly ask me: “What indicator changed your trading?” Honestly? Probably none. The biggest change happened when I stopped trying to get rich quickly and started behaving like a risk manager instead of a gambler. This post is fiction. I wonder how many readers trusted the c**p above and immediately wanted mentorship, courses, or strategy details without even seeing a verified profitable live track record that proved that c**p I told in the beginning. That's exactly how "mentors" and influencers make you waste your time or your money. Once you truly understand that survival is more important than profit, your entire perspective changes. A disciplined trader understands that: there will always be another setup, missing a trade means nothing, protecting capital is the first priority, and consistency matters more than excitement. The market rewards boring behavior. Most beginners want adrenaline. Professionals want stability. And ironically, the moment you stop chasing money emotionally is usually the moment your performance improves the most.
Anyway, that’s my story. Just wanted to share it with all of you.
Hi everyone,
Two years ago I made my first million and I I honestly thought sky is the limit, so I decided I would stop trading and invest most of my capital into safer assets for my future. I traveled for a while, met people, and tried to enjoy life. But after some time I realized that when you remove the goal and struggle from your life, you start being bored. The people I met already had their own life, families, and goals, and I wasn't part of their plans.
That’s when I decided to start teaching people how to trade. Not for money. Just because I wanted to help talented people avoid the mistakes I made. I started posting here on Reddit, answering questions, coaching a few students privately (never more than 3 at the same time), and eventually recording several introduction courses. Over time I realized that teaching gave me more satisfaction than making money itself.
A lot of people ask me what strategy I use, so I’ll briefly explain the core philosophy behind it. My approach is based on multi-timeframe market structure analysis combined with liquidity sweeps, institutional order-flow concepts, volatility compression, and momentum confirmation. I mainly focus on identifying engineered liquidity zones where retail traders are statistically trapped before expansion phases. The process starts with weekly and daily directional bias. Then I refine entries on lower timeframes using: market structure shifts, fair value gaps, displacement candles, volume imbalance, Fibonacci premium/discount zones, ATR-based volatility filters, session timing, psychological price levels, and confirmation through price delivery algorithms.
Risk management is everything.
I never risk more than 0.5%–1% per trade, and discipline matters more than strategy. Most traders fail not because their strategy is bad, but because they lack emotional control and consistency. People always search for a “holy grail,” but the real edge comes from patience, journaling, discipline, and understanding market psychology. Here’s an expanded “discipline guru” section you can insert before the disclaimer to make the satire even stronger:
The biggest misconception in trading is that people lose because of strategy. They don’t. In my opinion, almost every strategy can work if the trader behind it has enough discipline.
Discipline is the real edge.
Most traders already know what they are supposed to do: cut losses, let winners run, avoid revenge trading, stay patient, respect risk, follow the plan, avoid emotional decisions. But knowing something intellectually and actually executing it consistently are two completely different things. The market is designed to attack human psychology. Fear makes people close winning trades too early. Greed makes them overleverage.Ego makes them average into losers. Boredom makes them force trades that were never there.Hope makes them hold bad positions. Impatience makes them abandon profitable systems before the edge statistically plays out. Most people are not losing against the market. They are losing against themselves. That is why I always tell my students that trading is not really about predicting price. Trading is about predicting your own behavior under stress. When I first started trading, I had to completely rebuild my mindset and daily habits. I removed distractions. I stopped checking social media during trading sessions. I created strict routines. I journaled every trade. I tracked emotional states before and after execution. I reviewed losing weeks in detail. I learned to sit still and do nothing for hours if conditions were not aligned. A professional trader must become emotionally neutral. You cannot become euphoric after winning. You cannot become depressed after losing. You cannot increase risk because you “feel confident.” You cannot break rules because “this setup looks different.” The market punishes emotional inconsistency very quickly. One thing I learned is that discipline is not something you use only in trading. It becomes part of your personality. The same discipline that allows someone to: wake up early, exercise consistently, eat correctly, avoid distractions,control impulses, and stay focused for years, is usually the same discipline that allows them to become profitable traders. People constantly ask me: “What indicator changed your trading?” Honestly? Probably none. The biggest change happened when I stopped trying to get rich quickly and started behaving like a risk manager instead of a gambler. This post is fiction. I wonder how many readers trusted the c**p above and immediately wanted mentorship, courses, or strategy details without even seeing a verified profitable live track record that proved that c**p I told in the beginning. That's exactly how "mentors" and influencers make you waste your time or your money. Once you truly understand that survival is more important than profit, your entire perspective changes. A disciplined trader understands that: there will always be another setup, missing a trade means nothing, protecting capital is the first priority, and consistency matters more than excitement. The market rewards boring behavior. Most beginners want adrenaline. Professionals want stability. And ironically, the moment you stop chasing money emotionally is usually the moment your performance improves the most.
Anyway, that’s my story. Just wanted to share it with all of you.
Please don't fall for this. Any price data for almost any asset can be obtained for free through different platforms. MT5 and Yahoo finance are just several examples. A few clicks, and the data is yours in different file formats.
Hey everyone,
I keep seeing people presenting one single long backtest as proof that their quant strategy works. That is basically not a test at all, because you use one period to develop (fit) a strategy and then expect it to work on another period. That's called a curve fit. Curve fits don't work on another curve, unless you want to be a gambler.
To evaluate whether a strategy actually has an edge, you should perform a walk-forward analysis (WFA). The idea is that the strategy has to repeatedly survive unseen market periods after recalibration. That is much harder than simply fitting one long historical sample.
If at least about 10 independent forward out-of-sample cycles remain profitable/stable, then you probably start seeing evidence of real statistical significance, rather than pure historical fitting.
Simple example of a rolling WFA:
You are currently at month 25.
Cycle 1:
Cycle 2:
And so on.
Hey everyone,
I keep seeing people presenting one single long backtest as proof that their strategy works. That is basically not a test at all, because you use one period to develop (fit) a strategy and then expect it to work on another period. That's called a curve fit. Curve fits don't work on another curve, unless you want to be a gambler.
To evaluate whether a strategy actually has an edge, you should perform a walk-forward analysis (WFA). The idea is that the strategy has to repeatedly survive unseen market periods after recalibration. That is much harder than simply fitting one long historical sample.
If at least about 10 independent forward out-of-sample cycles remain profitable/stable, then you probably start seeing evidence of real statistical significance, rather than pure historical fitting.
Simple example of a rolling WFA:
You are currently at month 25.
Cycle 1:
Cycle 2:
And so on.
Much success!
Hey everyone,
I keep seeing people presenting one single long backtest as proof that their strategy works. That is basically not a test at all, because you use one period to develop (fit) a strategy and then expect it to work on another period. That's called a curve fit. Curve fits don't work on another curve, unless you want to be a gambler.
To evaluate whether a strategy actually has an edge, you should perform a walk-forward analysis (WFA). The idea is that the strategy has to repeatedly survive unseen market periods after recalibration. That is much harder than simply fitting one long historical sample.
If at least about 10 independent forward out-of-sample cycles remain profitable/stable, then you probably start seeing evidence of real statistical significance, rather than pure historical fitting.
Simple example of a rolling WFA:
You are currently at month 25.
Cycle 1:
Cycle 2:
And so on.
Much success!
Hey everyone,
I keep seeing people presenting one single long backtest as proof that their strategy works. That is basically not a test at all, because you use one period to develop (fit) a strategy and then expect it to work on another period. That's called a curve fit. Curve fits don't work on another curve, unless you want to be a gambler.
To evaluate whether a strategy actually has an edge, you should perform a walk-forward analysis (WFA). The idea is that the strategy has to repeatedly survive unseen market periods after recalibration. That is much harder than simply fitting one long historical sample.
If at least about 10 independent forward out-of-sample cycles remain profitable/stable, then you probably start seeing evidence of real statistical significance, rather than pure historical fitting.
Simple example of a rolling WFA:
You are currently at month 25.
Cycle 1:
Cycle 2:
And so on.
Much success!
Hey everyone,
I made a list of some of the most important metrics used to evaluate the quality of trading and investing strategies. I tried to make the explanations as simple and short as possible. Let me know if I missed some popular metrics or if anything is unclear.
Sharpe Ratio - Measures how much return a strategy makes compared to how volatile the ride is. A higher Sharpe means the strategy makes better returns for the amount of overall risk and instability it takes.
Sortino Ratio - Similar to Sharpe, but only cares about downside volatility (losses). Better for strategies that naturally move around a lot but where downside risk matters most. More useful for trading systems and active strategies.
Alpha (CAPM - Capital Asset Pricing Model) - Measures how much return a strategy generates beyond what would be expected from its exposure to the market. In simple terms: it tries to measure the “real edge” or skill of the strategy, not just gains from the market going up. Alpha is usually expressed in %. Very important for both active trading and investing.
For institutional investing:
For trading:
Beta - Measures how strongly a strategy or asset moves together with the overall market.
Example: If the stock market goes up 10%
t-Statistic (t-Stat) - Measures how likely it is that the results are real and not just luck.
p-Value - Measures the probability that a strategy’s results happened purely by luck rather than from a real edge.
Example:
Recovery Factor -Measures how well a strategy recovers after losses or drawdowns.
Calmar Ratio - Measures annual return compared to the maximum drawdown.
Profit Factor - Total profits divided by total losses.
Expectancy - The average amount you expect to make (or lose) per trade over the long run. This is the mathematical “edge” of the system, but it can be misleading and should be combined with statistical significance metrics like:
Win Rate - Percentage of trades that win. Important, but misleading by itself. A strategy can win 90% of trades and still lose money if the losses are huge.
CAGR (Compound Annual Growth Rate) - The “true” average yearly growth rate after compounding.
Volatility - Measures how wildly returns move up and down.
Value at Risk (VaR) - Estimates the worst loss a strategy is expected to suffer over a certain time period under normal market conditions.
Example:
Time Under Water (TUW) - Measures how long a strategy stays below its previous all-time high.
MAR Ratio - Similar to Recovery factor, but with CAGR, instead of total net return: CAGR / Max drawdown. Very popular for hedge fund evaluation.
Correlation - Measures how similarly two assets or strategies move.
P.S. If you want to measure some of these metrics for your strategy, let me know. I made a nice instrument for that.
Hey everyone,
I made a list of some of the most important metrics used to evaluate the quality of trading and investing strategies. I tried to make the explanations as simple and short as possible. Let me know if I missed some popular metrics or if anything is unclear.
Sharpe Ratio - Measures how much return a strategy makes compared to how volatile the ride is. A higher Sharpe means the strategy makes better returns for the amount of overall risk and instability it takes.
Sortino Ratio - Similar to Sharpe, but only cares about downside volatility (losses). Better for strategies that naturally move around a lot but where downside risk matters most. More useful for trading systems and active strategies.
Alpha (CAPM - Capital Asset Pricing Model) - Measures how much return a strategy generates beyond what would be expected from its exposure to the market. In simple terms: it tries to measure the “real edge” or skill of the strategy, not just gains from the market going up. Alpha is usually expressed in %. Very important for both active trading and investing.
For institutional investing:
For trading:
Beta - Measures how strongly a strategy or asset moves together with the overall market.
Example: If the stock market goes up 10%
t-Statistic (t-Stat) - Measures how likely it is that the results are real and not just luck.
p-Value - Measures the probability that a strategy’s results happened purely by luck rather than from a real edge.
Example:
Recovery Factor -Measures how well a strategy recovers after losses or drawdowns.
Calmar Ratio - Measures annual return compared to the maximum drawdown.
Profit Factor - Total profits divided by total losses.
Expectancy - The average amount you expect to make (or lose) per trade over the long run. This is the mathematical “edge” of the system, but it can be misleading and should be combined with statistical significance metrics like:
Win Rate - Percentage of trades that win. Important, but misleading by itself. A strategy can win 90% of trades and still lose money if the losses are huge.
CAGR (Compound Annual Growth Rate) - The “true” average yearly growth rate after compounding.
Volatility - Measures how wildly returns move up and down.
Value at Risk (VaR) - Estimates the worst loss a strategy is expected to suffer over a certain time period under normal market conditions.
Example:
Time Under Water (TUW) - Measures how long a strategy stays below its previous all-time high.
MAR Ratio - Similar to Recovery factor, but with CAGR, instead of total net return: CAGR / Max drawdown. Very popular for hedge fund evaluation.
Correlation - Measures how similarly two assets or strategies move.
P.S. If you want to measure some of these metrics for your strategy, let me know. I made a nice instrument for that.
What does the majority do that makes them unprofitable?
Please don’t just say “psychology” or “risk management.” I can’t believe that 99% of traders have a problem with psychology, and I can’t believe that 99% of traders can’t calculate basic position sizing to avoid getting margin-stopped.
I have my own answer to this question, but I’m interested to see how other people think about it.
Hey everyone,
I think the key to profitability is building a strategy with a real edge, validated through statistically significant walk-forward analysis.
I found my edge after backtesting hundreds of strategies and variations. Through that process, I came up with new ideas that helped me create a set of custom-made indicators, which I combined in different ways, optimized, and eventually turned into an edge that led to this result:
https://www.darwinex.com/account/D.384809
Risk management: position sizing based on the maximum drawdown observed in the backtests.
Disclaimer: I’m speaking only about my own logic and experience as a currency trader. Other workflows for finding an edge may exist. I personally hven’t seen verified profitable accounts using those workflows.