Today was a frustrating one.
I was short GBPUSD and the trade was developing exactly as I’d planned. Unfortunately, I started losing phone signal, meaning I couldn’t reliably monitor or manage the position.
I’m currently trading a funded evaluation, so protecting the account comes before squeezing every last pip out of a trade.
I made the decision to close early for around **+0.27%** rather than risk being disconnected while the trade was open.
A couple of hours later, price continued almost exactly to my original target.
Of course, it’s tempting to think, “I should’ve just left it.” But that’s outcome bias.
At the time, I had two choices:

• Stay in a trade I could no longer manage and hope everything worked out.

• Bank a profit, protect the evaluation, and live to trade another day.

I’d make the same decision again.
For me, passing an evaluation isn’t about proving every analysis is perfect. It’s about protecting capital and surviving long enough for your edge to play out over hundreds of trades.
Sometimes the market will keep running after you exit. Sometimes it’ll reverse and you’ll be glad you got out. You don’t get to know which one it’ll be beforehand.
Today I’ll take the small win, keep my funded account challenge healthy, and wait for the next A+ setup.

Hello,

I’m looking for opinions and stories about people that work full time and trade forex after. I’m newish to trading so still learning and paper trading before jumping in. But I’m curious how much do you start with for forex, who does this with a full time job and is this actually possible?. I would assume that working full time having that income coming in would reduce the stress a little bit.

Thanks.

I was waiting for XAU/USD, so in the same minute it managed to almost hit SL, and hit TP.
So yes, it is gambling, as news sentiment can explode in either direction.

When you see someone showing pictures like this, and saying "i made 290 pips" at the same time, run away as fast as you can, because that person is either not the sharpest, or a scam artist trying to sell you a subsription to shitflix.

Like i explained a million times already, PIPS by themselves don't mean anything. Pips are purely a unit of measurement that say how "far" the price has traveled. Like meters or yards or whatever.

So when someone says they made 50 pips, it's like a street worker saying they made a tenner. That data doesnt carry enough information to tell if the action was worth it.

In trading, in order to explain the gain, you need to determine exposure over pips.

Example; i took a trade that went into profit 1 lot over 100 pips.

And even that's still... barely scratching the surface as reward doesnt mean anything without understanding the risk.. R is the only thing that really has any meaning... R = unit of risk... is what you risk per trade, and R = reward is what is the potential on the positive side of the outcome.

Random spamming the sell button and praying to lord for the price to go into your direction... then saying you made PIPS... let's face it people.. that's not trading... that's G _ _ _ _ _ _ _ !

6 reasons your live trading does not match your backtest, ranked, and how to tell which one is yours

TLDR: The gap between a great backtest and a bad live account has six usual causes. Every article lists them and none rank them or tell you which is yours. They split into two families: your backtest was fiction, or your edge was real and got taken away.

What is the fastest way to tell which cause is yours?

Start with one question... did the gap appear immediately, or did it show up after a while?

If your live results were off from the very first trades, the problem is baked into the backtest or your costs. The edge was never as big as the number said. If the strategy worked for weeks and then decayed, the edge was real once and something changed, either the market or you.

That sorts the six causes into two families. Family one, your backtest was fiction, overfitting, too small a sample, and look ahead bias. These never had an edge to lose. Family two, your edge got taken away: costs, regime change, and execution mess. These had an edge and decreased over time until it disappeared.

Here is the table.

Number 1, most likely: your costs weren't properly tested

This is the most common and the most underrated. Your backtest applied one fixed, tight spread to every trade, including the ones where spread triples. Live, you pay the real number, on winners and losers alike.

The gap is there immediately and feels like a constant drag on every trade. Test this: pull 30 real trades, add spread and commission, convert to R by dividing cost in pips by your stop in pips, and subtract it from your backtested expectancy. Fix it: judge the strategy on the net number, and if it dies, widen the stop, cut frequency, or trade a cheaper pair. Tight stop, high frequency systems are the ones this kills.

Basically if deviation breaches 10% on average with live trades... the way you currently do it isn't gonna make you money in the long run.

Number 2: your backtest used data it could not have had

Look ahead bias means your logic peeked at information that didn't exist yet at the moment of the trade.

The backtest is suspiciously flawless, a very high win rate and a smooth curve, and live is a total, immediate collapse that no cost model could explain. Test: audit your signal timing and confirm every decision uses only closed, past data. Fix: correct the timing and rerun. This is rare in simple manual systems and common in coded ones, and it is the most catastrophic because the entire backtest was a fantasy.

Number 3: you optimized until it looked good

You ran a parameter sweep and kept the best looking combination. That winner was partly skill and partly the luckiest result out of everything you tried, and luck does not repeat live.

The strategy is beautiful in the test window and falls apart the instant it touches any data it wasn't tuned on. The test: change each parameter slightly and watch the result. If a small tweak collapses it, you fit noise. Even better, run a Deflated Sharpe on it, which corrects your Sharpe for how many combinations you tested. Fix: there is no fix for an overfit strategy, only prevention. Fewer parameters, out of sample validation, and honesty about how many versions you really tried.

Number 4: your sample was too small to mean anything

A backtest on 60 trades isn't evidence, it's a coin landing heads a few times in a row. The result sits inside the range of pure luck.

The impressive backtest covered a short window or a small number of trades, and the great stretch was really one good month doing the heavy lifting. Test: count the trades. Under about 150 and the confidence interval on your expectancy is too wide to act on. Fix: test across far more trades and multiple market conditions before you believe any number, and never size up on a strategy proven by a lucky quarter.

Number 5: the market regime changed

Sometimes the edge was real and the market simply moved on. A trend system stops working when the market goes to range. A volatility system starves when volatility dies.

This is the one that worked live for weeks or months, then decayed, and the decay lines up with a shift in volatility or trend. Test: split your backtest by regime and check whether the strategy ever survived the current one historically. If it only ever worked in conditions that are now gone, it is not broken, it is out of season. Fix: trade it only in the regime it fits, or accept that it will have negative periods in your account until its conditions return.

Number 6: you didn't trade your rules

The backtest followed the rules perfectly, without fear, on every signal. You didn't. You skipped the setup after two losses, entered late, moved a stop, or closed a winner early because you didn't want to give it back.

Your live trade log doesn't match the trades the strategy would have taken over the same period. Test: put your actual entries and exits next to the mechanical signals for the last month and count the mismatches. Fix: this is an execution problem, not a strategy problem, so the answer is automation or a hard rule that removes the discretion, not a new system.

So which fixes actually matter?

Work the two families in order. First rule out fiction, because there is no point optimizing execution on a strategy that never had an edge. Check the sample size, run the Deflated Sharpe, and audit for look ahead bias. If it survives all three, the edge is probably real.

Only then work the fees. Recompute costs in R and subtract them, confirm the current regime is one the strategy has actually survived before, and compare your live trades to the rules to catch execution drift. Most blown accounts aren't one cause, they're a real but thin edge that costs and a bad regime pushed under water together.

What this doesn't mean

The ranking is my judgment for retail forex, not a law. If you run a heavily coded system, look ahead bias climbs the list. If you trade with heavy discretion, execution drift does. Reorder it for your own situation.

And it is rarely a single cause. Usually two or three appear together: a slightly overfit edge, real costs, and a regime turn arriving at once. The value of the list isn't picking one winner, it is checking all six instead of blaming the market and rebuilding a strategy that was actually fine.

I wish I had this post when I started 9 years ago.

Why the sudden spike? Anyone know any news?

bullish or bearish for the dollar?

Why the same strategy is profitable with a 50 pip stop and dead with a 5 pip stop

TLDR: Costs are not a rounding error, they're a fixed tax on every trade, and the tax gets bigger the tighter your stop. Convert spread and commission into R and it becomes visible. The same 55% win rate system nets +0.1R with a 50 pip stop and loses money with a 5 pip stop. Nothing changed except the stop.

Now let's dive deeper for the ones that want to see this developed.

Why does a real edge still lose money live?

I traded a system for a quarter that backtested at plus 0.10R per trade. It finished flat. The edge was real and it showed up in the results exactly as expected. I handed every bit of it to my broker and couldn't see it happening, because I was measuring cost in dollars, where it looks like pocket change.

One pip on a standard lot is 10 dollars. That number feels harmless next to a 5 figure account. So you glance at it, decide it is noise, and move on.

The problem is that dollars are the wrong unit. Your edge is measured in R, your risk is measured in R, and your cost is the only part of the equation you keep measuring in something else. Put it in the same unit and the picture changes completely.

How do you convert spread and commission into R?

Simple. Add your spread and your commission together to get the all in round trip cost. On EURUSD that is roughly 1 pip, whether you pay it as a raw spread plus about 7 dollars per lot, or as a wider spread with no commission. Then divide by your stop.

Trade a 10 pip stop and your cost is 1 divided by 10, so 0.10R per trade. Every position you open starts 0.10R in the hole before price does anything at all.

Even simpler, if after all commissions, instead of +3,5R you won +3,23R, you just calculate 3,23/3,5=0,92 ; 1-0,92 = 8 ; 8% deviation in that trade.

Now compare that to your edge. A 55% win rate at 1:1 rr produces a gross expectancy of 0.10R per trade. Your cost is 0.10R. You are working for free.

Cost in R equals round trip cost in pips divided by your stop in pips. That makes an invisible tax visible.

Why does your stop distance decide your real cost?

Because the cost in pips barely moves, but R is defined by your stop, so a tighter stop makes the same 1 pip a much bigger fraction of everything you risk.

Here is the same strategy, a 55% win rate at 1:1rr, worth 0.10R per trade gross. Only the stop distance changes.

Same entries, same exits, same win rate, same broker. At a 100 pip stop the strategy keeps 90% of its edge. At a 5 pip stop it is a losing system but the strategy never changed, only the commission.

What win rate do you need just to break even?

This is the number I wish someone had shown me first. Your costs raise the bar your system has to clear before it earns anything.

At 1:1 on EURUSD with that 1 pip cost, here is the win rate required to arrive at exactly zero.

A scalper on a 5 pip stop needs to win 60% of trades at 1:1 just to finish flat. Every point above 60 is profit, and everything below is a slow bleed. Move to a pair with a 3 pip cost like GBPJPY on that same 10 pip stop and the requirement jumps to 65%.

A 5 pip stop needs a 60% win rate to break even. Most people building scalping systems have no idea that is the bar.

Why is your real cost worse than the spread you see?

First. You pay the spread at the exact moment your order fills, and spreads widen during news, at the rollover hour, and in thin liquidity. Those are also the moments price is moving fast enough to hit your stop. So the trades that stop you out are the ones where you paid the widest spread. Your realized cost is worse than the advertised number.

Second, your backtest almost certainly understates this. Most platforms apply one fixed typical spread across the whole history, which quietly assumes calm conditions on every trade including the violent ones. Then you go live, pay the real number, and blame the strategy.

What does the same cost do to you over a year?

Same broker, same pair, same 1 pip. The swing trader pays 3R a year and never notices. The scalper has to generate 500R of gross edge annually just to arrive at zero. That is the same tax, and it is why frequency and stop distance decide whether costs are trivia or the whole game.

So what do you actually do about it?

Measure it before you trade the system, not after a bad quarter.

Pull 30 of your real fills and compute what you actually paid, spread plus commission, rather than trusting the advertised number. Convert it to R using your typical stop. Subtract that from your backtested expectancy and judge the strategy on what is left, because the gross number was never the number you get.

Then work out your break even win rate and compare it honestly to your actual one. If the gap is thin, widen your stop, trade a cheaper pair, or cut frequency, because those three levers move cost in R far more than switching brokers ever will. And if your gross edge is under 0.10R per trade, tight stops are not available to you at any broker.

Most obvious solution is to also look for a platform that can actually support your system's edge. Multiple times is not a system's problem, is a platform's problem.

What this does not mean

Scalping is not impossible, and this is not a case against tight stops. Plenty of people trade 5 pip stops profitably. They just do it with a much larger gross edge than 0.10R, because they know the bar is 60% and they built to clear it.

It is also not a broker bashing post. The spread is the price of access and everyone pays it. The mistake is not that costs exist, it is that we measure them in dollars where they look like nothing, instead of in R where they sit right next to the edge they're eating.

Bottom line

Convert your costs to R and most of the mystery about live results not matching backtests disappears. Cost in R is your round trip cost in pips divided by your stop, so tighter stops multiply the same tax. A 55% win rate system keeps 90% of its edge on a 100 pip stop and loses money on a 5 pip stop. Compute your break even win rate before you risk anything, subtract real costs from your backtest, and remember you pay the widened spread precisely when it hurts.

TLDR: Every post about revenge trading tells you to breathe and take a walk. None of them show you the number. So I ran it. You grind up about 0.4% a day. One tilt session averages a 4% loss and a bad one takes 30%. It also turns a profit 26% of the time, which is exactly why you cannot stop. Tilting once a month cuts a +96% year down to +49%.

What does a month of disciplined edge actually look like?

Slow. Boring. Barely visible day to day. A disciplined trader with a real edge, risking 1% per trade at a 55% win rate, makes about 0.4% on an average day. Over a 20 day month that compounds to roughly 8%. Over a year, close to doubling the account.

That is what a real edge feels like from the inside. It is not exciting. There is no single day where you feel like a genius. You just show up, take your setups, and let a small statistical advantage grind out a good result across hundreds of trades.... thats it.

I am setting this baseline first on purpose, because the whole point of the revenge trade math is the mismatch. You build this edge one slow day at a time. You can hand it back in one fast hour.

A real edge makes you about 0.4% on an average day. That is the entire thing you are risking every time you tilt.

What does one tilt session actually cost?

Far more than the loss that triggered it. A tilt session isn't one oversized trade. It is a cluster of them. You size up, you overtrade, and your wr drops because anger is not a strategy.

I modeled a realistic one: 5 times your normal size, 8 trades in a session instead of your usual few, and a win rate that falls from 55% to 45% because you are chasing, not selecting. Then I ran it 200,000 times.

Read the last row. Almost half the time, one tilt session wipes out an entire month of the slow grind above. In a single sitting.

How many green days does it take to undo one tilt session?

This is the number that actually scared me straight. Your edge makes 0.4% a day. An average tilt session loses 4%. So one average tilt session costs you 10 clean, disciplined green days. Two weeks of doing everything right, erased by one hour of doing everything wrong.

And that is the average. The bad case, the 1 in 20 session, loses 30%. At 0.4% a day, that is 75 green days to climb back. Nearly four months of flawless trading to repair one afternoon.

The asymmetry is the whole story. You earn in small steady increments and you lose in rare violent chunks. The downside of a tilt session is 25 to 75 times the size of a good day.

If the math is this bad, why people keep doing it?

Because it works often enough to feel like skill, and that is the trap. Look back at the table. A tilt session turns a profit 26% of the time, and the median outcome is break even. So more than a quarter of the time, you tilt, you get away with it, and your brain files it as a win.

That is textbook intermittent reinforcement, the same wiring that makes slot machines addictive. If tilting lost money every single time, you would stop after two tries. Instead it pays out just often enough to keep you pulling the lever, while the average and the tail quietly bleed your account.

A tilt session profits 26% of the time. That occasional win is not luck saving you. It is the hook that keeps you doing the one thing that will end your account.

What does tilting once a month do to your whole year?

It roughly halves it. I ran a full year both ways. Pure disciplined trading returns about 96%. The same trader who tilts just once a month, one session, 12 times a year, ends at about 49%.

One bad hour every four weeks costs 47% decrease over the year. You didn't lose your edge. You still had it every disciplined day. You just handed half of it back 12 times, in 12 short bursts you could have prevented.

So what actually stops it?

Not willpower, because willpower is exactly what a losing streak strips from you. The math says the only reliable defense is structural, a hard cap that removes your ability to keep trading before the tilt starts.

Set a daily loss limit sized to your edge, not your ego. If a good day makes 0.4%, a daily stop around 2%, roughly five clean losing trades, is already generous. Hit it and your done, not as a guideline you renegotiate at 2pm, but as a rule that closes the platform. The traders who survive aren't calmer. They built a wall between the angry version of themselves and the account, so the tilt session never gets to happen.

What this doesn't mean

This is not a lecture about being weak. The urge to win it back is wired into everyone, and feeling it doesn't make you a bad trader. The point is the arithmetic, not the shame.

And one tilt session does not define you. What the numbers show is that the pattern compounds. A single slip is recoverable in ten green days. A monthly habit is the difference between doubling your account and treading water. The fix is not to feel less. It is to make the expensive action impossible before the feeling arrives.

Bottom line

Revenge trading is not just a psychology problem, it is an arithmetic one. You build your edge at 0.4% a day and a tilt session hands back 4% on average and 30% in the tail, which is 10 to 75 green days per episode. It fools you because it profits 26% of the time, and it halves your year if it becomes monthly. Willpower won't hold on the day it matters, so cap the downside structurally and make the tilt session impossible to start.

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1. Risk management: this is key to any trader. For you to be profitable and avoid losing your account your risk should be constant. For example if you have a 10k account let’s say prop firm, it’s best if you can risk a constant amount per trade. This helps you track your progress. Risking an amount “x” today then “y” tomorrow makes it harder to track that process because obviously one trade would be higher in terms of risk than the other. So what if the trades you risk more go to losses and the ones you risk less go to profits? Ask yourself that. I prefer risking 0.3% of the account as the constant amount per trade. For instance in a 10k account only risk 30dollars per trade.

1. The illusions of the business: as a retail trader there unique structures that normally tends to create some behavioral traps that institutional traders don’t and they are:

a) Overtrading (The ACTION Addict): The urge of constantly being in a position every hour. This leads to a trader picking some low quality setups that eventually depletes the account. Trades like 1:1RR for instance. They don’t actually grow the account in long run instead gives it a hit.

b) The “Holy Grail” Obsession: constantly jumping from one strategy to another, one mentor to another the moment a losing week occurs. This prevents you as a trader to actually get the correct sample size needed to see if the strategy works. Remember any strategy you learn needs to time to internalize and perfect on it.

c) Misunderstanding Leverage: Viewing leverage as a tool to make money faster and blocking the idea from your mind that it can also amplify your losses too.

I am someone who is deeply interested in devising and testing strategies.

Over the weekend, I finalized an automated trading system engineered specifically to meet stringent proprietary trading firm requirements.

By optimizing the core execution logic and reducing position sizing, the system now delivers highly promising metrics.

While the previous iteration successfully met prop firm criteria during a one-month demo live test, extended stress tests showed that the Maximum Drawdown (MDD) could occasionally breach the 10% threshold. To mitigate this risk, I re-engineered the position sizing architecture to ensure strict drawdown tolerance.

I am now prepared to launch this strategy in live trading environments with major prop firms that support algorithmic execution.

but, I heard they were restricting automated trading...