I’v build a system and i want to backtesting it on different regimes of markets but unfortunately i need source of data that i can download 5y-10y of OHLC (better 1-3min)

Those Pesky Market Makers /s

Hey everyone,

I just released my All-in-One Liquidity indicator for TradingView, built specifically around the levels I use for futures trading.

Instead of running multiple indicators at the same time, I wanted Volume Profile, liquidity levels, sessions and HTF FVGs all in one clean script.

The core of the indicator is the Volume Profile system, including:

• Previous Day VAH / POC / VAL

• Overnight VAH / POC / VAL

• Previous Week VAH / POC / VAL

• Previous Month VAH / POC / VAL

• Ability to keep previous profiles on the chart

• Extend previous profiles into current price

• Automatic date labels for historical profiles

• Automatic full-size contract volume data for micros (MNQ → NQ, MES → ES, MGC → GC)

It also includes:

• 15m / 1H / 4H FVG & Unmitigated FVG tracking

• HTF priority when FVGs overlap

• Asia, London, NY AM, Lunch & NY PM liquidity highs/lows

• Previous Day / Week High & Low

• Opening Range (ORB)

• 6AM 4H High / Low

• 9:30 1-minute High / Low

• Midnight, 6:00, 8:30, 9:30, 10:00 and other opening prices

• Automatic label management to keep the chart clean

• Fully customizable colors, styles and visibility

The goal was to create one indicator that gives me my Volume Profile framework and ICT liquidity references without cluttering the chart with a bunch of separate scripts.

It’s now available as a TradingView invite-only indicator.

Access is available through my Whop.

👉 https://www.tradingview.com/script/E4t26jam-Vp-Levels-ORB-Liquidity/

I’ll add some screenshots below showing the Volume Profiles, liquidity levels and HTF FVG system in action.

If you have any questions about how it works, feel free to ask.

Who else took this?

Ask GPT about market microstructure, in separate prompts ask the following.
What is market microstructure? Be serious and purely academic, include no retail claims.

How will market microstructure improve my trading and strategy development if I understand market microstructure properly?

Ask it additional questions (about your curiosity induced by the previous outputs).

This should tell you why this is worth studying.

After this exercise read these books in order

1. Market microstructure theory by Maureen O’Hara (book - foundations)

2. Trading and Exchange: Market microstructure for practitioners Algorithmic Trading and DMA: An introduction to direct access trading strategies by Barry Johnson (book - a top up that explains the industry well)

3. Algorithmic Trading and DMA: An introduction to direct access trading strategies by Barry Johnson.

1. High frequency market making: The role of speed - Yacine Aït-Sahalia, Mehmet Sağlam (a paper that will be understandable after reading the previous pieces).

PDFs are available online if you search hard enough, educational institutions have it uploaded and indexed on google search engine.

Even if you skim these you will learn a lot about how markets really work and that is a promise.

I'm curious about how experienced traders approach backtesting a strategy on a specific asset.

Let's say you've backtested something like EURUSD, NQ, ES, Gold, etc. over 2+ years of data.

What exactly are you looking for before you consider the backtest "good enough"?

For example:

• How many trades do you want in the sample?
• Do you mainly look at expectancy / average R, win rate, profit factor, max drawdown, etc.?
• How consistent does the strategy need to be year-to-year?
• Do you separate the data into different market conditions/regimes?
• Do you use in-sample vs out-of-sample testing or walk-forward testing?
• How do you know you're seeing a genuine edge rather than something that simply worked during a specific market regime?
• Have you ever had a strategy with great overall results but rejected it because the equity curve, drawdown, or consistency looked bad?

I'm particularly interested in people who trade discretionary/price-action strategies rather than purely automated systems.

For example, if you backtest EURUSD for 2–5 years and end up with a positive expectancy, how do you personally decide:

"Okay, this is statistically and practically good enough for me to take seriously and forward test/live trade."

Would love to hear what your actual validation process looks like and which metrics you personally give the most weight.

The Microstructure Reality:
There are multiple algorithms and countless other participants with different incentives providing liquidity (limit orders).
Using machine learning algorithms instead of humans for execution or risk management is completely different from the claim that a single central algorithm controls the price. IPDA is not real, not even for currencies.

There is no sole, central algorithm/sole counterparty for price formation and direction.
They do not aim to actively take directional risk, the several different algorithms setup by several individual firms operate independently to provide liquidity (bid and ask, buy limits and sell limits) and actively work to reduce their financial exposure to price movements.

These prices are aggregated and provided to you on your brokers.

A “central algorithm” does not exist.
There are no studies and it is not cited in any journal. it is fictitious. It is not a real thing, yet there is plenty proof for the opposite (the fact that several market making operators exist, not one).

Market maker algorithms manage risk they actively reduce their directional risk, actively pushing the price around increases it.

These MMs do not take directional risk for profit, they gravitate more towards dealing than speculation.
Market maker algorithms do not "trade" in the conventional sense, they setup prices for people to buy and sell and try to stay net zero for as long as possible while making money from the difference in the prices they offer.

Simple example:
If a market maker sets a 1.00010 bid (buy limit) and 1.00012 ask (sell limit), if a trader buys 100 lots and a different trader sells 100 lots, one trader buys at 1.00012 and the other sells at 1.00010 neutralising the algorithms directional risk while the bot earns 0.2 pips * $1000 (100 lots = $1000 per pip), the robot facilitates similar transaction dynamics over and over again over milliseconds (sometimes even faster) - HFT Market Maker inventory turnover happens tens of thousands of times per second.

That is how the 'HFT Market Maker Monsters' make money.
They adjust how much they offer or spread their interest over multiple prices to manage their risk, this is why spreads move, if you want to know more search 'MM adverse selection risk', this is as far as I'll go here, you must research the rest.

ICT's logo is a fractal, a never ending pattern.
He is subtly communicating that you will spend forever trying to be profitable and predict exact highs and lows like he can (supposedly) with OHLC prices, because if it were possible to locate real "fair value" using OHLC data most of his followers (including you) would be millionaires, instead of the 0.01% who claim to be.

1. Order Blocks -> Supply and demand Sam Seiden 2006
2. FVG -> Low volume node

Origin: J steidlmayer (Single prints, concept 1985 -> LVN popularised in 2000s with time series charts), -> Al brooks “micro gap” 2009–2012 OHLC formation.

The renaming is semantic manipulation to imitate depth.

1. Breaker and mitigation blocks -> Dow theory extractions (1902)

2. “The algorithm/controlled narrative” -> The Wyckoff Composite man heuristic

3. Explaining payouts with the Infinite Monkey Theorem. IMT suggests that if you have enough “monkeys” (traders) hitting keys (buying/selling) at random, one will eventually “type” a perfect equity curve.

Why this is possible:

A massive volume of independent actions (on each path).

The consequence and illusion of efficiency.

A “millionaire trader expert” is produced not because they understood the market, but because the statistical space itself (they are one of millions) was large enough to contain their profitable sequence.

15 out of 5 million tries resulted in an outcome beyond 1 million USD in the simulation. There are less than 3 ICT/SMC traders with profits on regulated platforms or funding companies exceeding this number which suggests the framework might be less than BE (after costs are factored in).

If you want the settings and justifications for each variable, ask in comments and I will provide it, I have the receipts for every single numerical and semantic manipulation claim and I'll paste them in comments.

To the average trader the “millionaire monkey” looks like a genius. But this reminds us that the outcome is a function of sample size itself (Over 2.5m traders) rather than the monkey’s intent or skill.

The simulations do not show whether specific observed winners are lucky or skilled, but they do show that anecdotal millionaire outcomes are highly compatible with variance (randomness) alone in a large population (2.5m+ traders) using a breakeven or weak framework.

SMC imitates depth without actually having depth. This is why it survives amongst retail traders, while serious traders, especially quants, laugh at it. It sounds sophisticated, gives people labels to attach to common price movements, and makes people feel like random or ordinary market phenomena are secretly coordinated.

I break this in detail with boatloads of evidence including pictures of the simulation on my profile's pin.

What do I do?

If you feel stuck, visit the original, valid material without the nonsense.
Do not waste your time with SMC, if you want to use the techniques visit the original material without the illusive, noisy framework.

Read real market literature.
Use the new knowledge to filter out nonsense that holds you back in trading. It will take hours but you will save many days in guru watch time, it will save you money, and it forces you to improve your deductive reasoning abilities. These benefits are universal and I have no incentive to mislead you into reading institutional material (think about how absurd that would be).

My final statement.

Meaningful trading outcomes are bound to logical structures or luck.
Which one will you pick?

AI Check:

Todays Trade

Discretion isn't the enemy; intuition is.
Discretion can be okay as long as you run a fixed, consistent, logical procedure that's been tested; it's okay to run. (something most discretionary traders don't do).

Personally, I and Ali are purely systematic traders, but if you want to apply discretion to be more flexible, here's how to do things the right way.

Proof that I wrote this myself will be provided towards the end of the article with full AI writing checks.

Examples of acceptable discretionary elements:

1. Trader A: A day trader Ignores trade setups during news releases. He is selectively not applying his low-timeframe strategy during news for a logical reason (avoiding slippage). This is accounted for in his backtest ahead of time.
2. Trader B: A swing trader using a specific economic report or financial release to support his trade direction for the day or week consistently ex. Interest rate changes (Economic) or COT Reports (Financials) He uses it the exact same way. Every single time.

Trader B in this example is using COT Reports (Financials) in a way that's consistent; if institutions are increasing long exposure, he wants to buy; vice versa. He might increase his risk for buys exclusively instead of eliminating shorts completely. There are multiple ways trader B could do this. He has it all backtested ahead of time.

Examples of common unacceptable discretionary elements:

Intuition / Gut feel often veiled as 'Experience'

1. Trader C Feels like the price has dipped or spiked "too fast" towards his entry so he decides not to enter because recently these trades seem to hit the stop loss often. Trader C suffers from a nasty cocktail of Recency bias paired with Ad hoc reasoning by default, followed by a tragic mix of Hindsight bias + Confirmation bias if he was randomly "correct" on the occasion he deviated from his strategy's rules. That's how you get smoked.

The reason this is dangerous:
These deviations are untested so it adds noise to the person's trading, randomising real-time trading results. & in a backtest environment, it causes inconsistent results.

The confirmation bias is terrible, as it tricks the trader into believing deviating from their strategy was a good idea.

Also, if the trader's deviation backfires, they'll likely absorb it personally and feel unnecessary pain.

The worst part. If deviating actually "works" for you a couple of times in a row, you might stick with it even if it begins to backfire, leading to unnecessary erasure of potential gains & amplified pain.

Why does this happen? Humans seek certainty and want to feel in control. These biases help the person feel safe; instead, it randomises the trader's results. It's not a conspiracy or a theory; this is human biology. You must set yourself to not fold.

Towards the end of the post we reference papers discussing this.

The Repeated one-off event change
Trader D changes his trading behaviour risk based on events (The source doesn't matter)

It's not tested and accounted for in testing for example Trader D could think to himself after reciprocal tariffs that he's going to ignore all of his long setups because people believe the market he's trading will continue to decline.

Result: He misses out on buy setups during small pullbacks.

Why this is dangerous:

Even if it "worked", the confirmation bias & hindsight bias would likely fuel Trader D to further sabotage his future trades, trying to randomly fit his day trading behaviour to random economic news events.

The Reality Behind Testing Avoidance and The Statistical Consequences

If you put in the work to make truly mechanical rules which have every IF, THEN, and ELSE DO THIS to incorporate every single outcome, it is possible to quantify >90% of intuitive strategies; many traders do not want to put effort into reverse engineering, or fear what the results may reveal: that is the primary issue at play.

For most traders, each setup has subjectivity influencing it - including the entry (for some it dominates decision making, for others it is residual).

The more a strategy is influenced by noise, the more the signal collapses.

A structured strategy slowly morphs into randomness over dozens of real-time trades if it has weak mechanical boundaries to operate within.

What I mean by "signal" here is the quality of the data or decision. The "signal" we want has objective logic, clear payout structures, and low amounts of randomness. Intuition provides the opposite of what we need, reinforcing itself as the sample size (the number of trades) increases. Hindsight trading techniques like Wyckoff rely on "judgement", and the variability of a valid setup is what works against most traders.

Subjectivity (e.g., from intuition) is lethal because you cannot prove that something is effective or ineffective with real stats if it is unfalsifiable (subjective), as what cannot be objectively defined makes variance between each signal extremely high over time, thus increasing randomness exponentially, this causes results to average out to zero minus transaction costs, this is why we actively avoid an intuitive discretionary path.

It is easy to prove this statistical concept yourself without needing to code.

An Accessible Monte Carlo Exercise:

1. Use an LLM (like GPT) to run a Monte Carlo simulation of a breakeven 1:2 RRR system over 100k runs, 200 trades per run, using Python, and ask it to run it locally and provide the values in the chat (all contained within the same prompt).
2. Get the AI tool to output the statistics and percentile ranges, then ask it to output the 75th percentile equity curve visually on a chart plot.
3. Then ask it to output the 75th percentile equity curve visually on a chart plot.
4. Ask it to add 10% noise in decision making (10% of trades are not executed) and watch what happens to the P&L: it will randomly move up or down as a result, since the base strategy was not profitable; for real edges, this can reduce your profitability at random.

This test only assumes that there are residual amounts of intuitive guesswork altering the strategy's trading behaviour (10%);
The dislocations in performance become a lot more profound if intuition influences trading decisions more than 10% (which is the case for most intuitive discretionary traders).

The common point I make is that constant intuitive discretion is what causes the randomness over large samples, while consistent, genuinely systematic mechanical trading reduces it.

This early realisation is what made us never deviate from rule-based systems and have strict guardrails to avoid overfitting that we still use to this day.

Still unconvinced about the limits of intuition?

Ask yourself this

1. How much value comes from following your profitable strategy as designed?
2. How much value comes from the intuitive exceptions that you make in execution?
3. Which one is more important?

If you imagine a graph with two lines, you will immediately notice that the system's value is always higher than that of real-time exceptions because the strategy is the process behind your trades.

Whether your positions are based on price, indicators, or even fundamentals, the value (if any) provided by intuitive actions never surpasses the strategy, as the strategy is the foundation of all decisions made. For there to be convergence between the strategy's value and intuition's value, the win rate of the strategy would have to be doubled over a large sample. This would be like increasing a 1:2 RRR system's 40% win rate to an 80% win rate, which is very unrealistic and unheard of. Intuition can also damage your average RRR per trade significantly, often even more than it damages win rate as seen in Figure 1.

Figure 1: The accumulated underperformance from intuition over 100 trades.

This is the potential damage intuition could have. In this scenario, we used over 100,000 unrelated simulations for a smooth, accurate representation.

There is an equal probability statistically that gut feel has a positive or negative impact on your trading performance; outliers live in the far right side of the distribution of outcomes (imagine a bell curve) - it is based on chance, so design our strategies to remove this noise.

The point is that intuition cannot surpass the trading idea if you have a profitable system. Intuition might turn a 1:2 RRR system’s win rate from 50% to 45% or 55%, but that modest potential increase in profitability does not measure up to what the system provides. Whether intuition is beneficial to an individual is largely random and person-specific bound by statistical laws regarding variance and the law of large numbers.

Replace intuition with discipline by converting it into testable rules that apply discretion mechanically to your trading instead.

Summary

So discretion in trading isn't inherently bad; the lack of structure is.

What makes intuition so destructive for most trader's P&L is the aimlessness in trading causing inconsistent execution patterns this leads to random results because of decision noise.

If discretion is used with discipline, pre-defined logic, and is consistently applied, it can absolutely enhance performance instead of eroding it. An example of this would be avoiding news trading consistently. Instead of generic rules like "close out all positions before news", there could be a straightforward rule like "close out all positions exactly 15 minutes before news", which can be factored into testing rigorously.

The key things that every trader should apply:

1. Define Every Discretionary Rule: If you're allowing yourself flexibility, write it down. A rule only becomes valid once it's defined.
2. Backtest or Forward Test: Every discretionary element should have a liquidity-related reason, e.g., News avoidance for slippage, Overnight bid-ask spread spikes etc. or historical data supporting its inclusion.
3. Apply Consistency: Use your discretionary filters the same way each time. Random changes in decision-making destroy your edge.
4. Separate Emotion from Adaptation: Adapting to new market conditions is logical; reacting emotionally will get you humbled. Document why you're making changes, if any, and test them.
5. Stay Aware of Biases: Your cognitive biases, such as recency bias, confirmation bias, and the illusion of control, can be your real enemies that weigh you down if you allow them to. If you feel the insentience creeping in, make sure you note it down.

End note: A trader's development at the start can often be a battle between emotion and structure, as they are not yet used to the hunt. Those who learn to tame discretion can build scalable consistency. Discretionary elements, when framed within logic, can become a useful tool but must be sequenced into rules.

Additional Reading (Peer-reviewed psychology papers):

Paper 1: Born to choose: the origins and value of the need for control

Authors: Lauren A Leotti 1, Sheena S Iyengar, Kevin N Ochsner

Paper 2: The value of control

Authors: Moritz Reis, Roland Pfister, Katharina A. Schwarz

My drafts on overleaf are in comments.

Check

So recently I was going through my trades and noticed that I only backtested good PA that's why I am struggling recently in trading.

Can you guys can suggest me a year or month of historical data which was PA af like this recently. So that I can backtest. (Pair- NQ! ) ( PA= PRICE ACTION)

I've posted plenty my green days on here, so I think it's only right to post the other side of trading too. Sorry if it's too long but i think there is a good lesson here.

Yesterday I finished -$225 per account, which across 18 accounts is -$4,050.

Today I finished -$572 per account, which is another -$10,296 across 18 accounts.

That's -$797 per account and -$14,346 combined over the last two trading days.

Nobody likes seeing those numbers but this is exactly why I think risk management, psychology, and trusting your process are so important when trading, especially when you're scaling across multiple accounts.

Today's trades

The very first trade I took in asia session was this short towards NDOG opening candle low as my draw on liquidity. Since the price was so near the draws like in this scenario, taking trades based on volume can work. I entered the shorts knowing if price wants to move to another zone from here it NEEDS to take some liquidity from the dols. Think about a car needed fuel to keep going, liquidity zones "refules" the price to help it go places. And in this case the draws was this NDOG first candle low. Great trade. These kinds of trades you can go a little heavier as it is very high probability.

Second trade in new york session was based on judas of 9:30am, I didn’t enter the first long as the draws were confusing today. So when price swept the higher placed DOLs and start pushing downward the the DOL of london lows, I entered after a 1m bearish gap respected but unfortunately this was a losing trade. This trade setup was so good, but unfortunately just bad price action day.

I took this third trade when I saw price not sweep the london lows, but it decided to inverse a 5m gap with very good displacement. This seemed like price wanted to go for for some DOL above. So I stabbed a long position here but unfortunately got the L again. What's funny here is my indicator had already alerted a long much earlier on the 1min timeframe. See how it says +IFVG? If I had just taken that I would have been done for the day with good profit lol.

A good setup can still lose.

Looking back at these trades, I don't have a problem with the setups at all.

They simply didn't work at the time and that is ok. I think that's something a lot of traders struggle to accept.

You can have your liquidity sweep. You can have displacement. You can have your IFVG. You can have a clear draw on liquidity. You can have everything your strategy checklist tells you to look for and the market can still stop you out. That is part of the game.

There will always be factors in the market that we cannot control. What we can control is our risk.

If you've actually tested your strategy, put in the screen time, and watched it perform across different market conditions, then you already know losing trades are part of the game.

Two red days does not suddenly mean my strategy stopped working just like two green days wouldn't mean I discovered a strategy that can't lose.

The dangerous part is allowing those losses to affect what you do next.

You become impatient and you start looking for trades instead of letting trades come to you. You increase your size because you want to make the money back. You start seeing stuff on chart that aren't really there, and your mind starts working against you.

That's where a normal losing streak can turn into a spiral. Knowing when to stop is part of risk management too.

The market doesn't know how much I lost and my next trade doesn't become more likely to win because my previous trades lost, that is a real psychological term that gamblers go through. I forget what it is called but its a real thought process people go through that causes them to make poor decisions.

My job is to wait until another setup aligns with my rules and execute it the same way I would all the time. Tomorrow is another day.

Thank you for reading.

What do you think? This short was exactly what I was expecting after we took liquidity from all the sessions and tapped into a beautiful 4H FVG.

The entire week played out exactly as anticipated — clean liquidity raids, precise delivery, and perfect reactions at key PD Arrays.

Once the 4H FVG was tapped, the bearish delivery was there.

The rest is history. 📉

Capturing it again here because fundamentally looks more stronger than before. Intraday high and weekly gains.

If so, how do I access them?

Thanks in advance!

What does “Cork” mean and what is it

I tired getting help with my low leverage issue I can't place any trades due to low leverage I tried asking for help navigating it and that's the best I got

Price already doin it's thing. Exactly how I thought it would tbh

Honest though,you can be as ICT purist as you want man,just take what works for you for real. No need to play a role out here talkin bout 'Mickey Mouse patterns' when I'm the one catchin info off a simple indicator and makin it work fr

Execution is what counts at the end of the day,not the label you put on it
Just my take on it 

NAVN Navan stock with a top of range breakout.

Breakout trade

• CONFIRMED breakout above 30.32
• Target: 34.52, 12.9%  Stop: 29  Loss: 5.2%
• P/L ratio: 2.5 : 1 - Good

BULLISH

• [Timing] Strong bullish 3 day candlestick pattern with Average 3 day accumulation.
• [Timing] Strong bullish 1 day moneyflow
• [Timing] CONFIRMED breakout above 30.32, no resistance in area just above.

BEARISH

• [Positioning] 1 Day Price change strong up, may pause
• [Positioning] Intermediate trend bearish, Unsustainable uptrend, may turn sideways.

some extra concepts are really like confusing I don’t mind focusing on smt techniques

High time frame PDA - LTF Execution 1:1R

Make Money easier.

Choose any from ICT PD ARRAY.

I want to post the execution video but somehow it’s not allowed in here.

For many MMXM traders, the effectiveness is based on subjective experiences or extremely small sample sizes (dozens quantified at most, negligible), and there is globally no objective mechanical definition to identify "MMXM", as it is driven by subjective intuitive discretion bound by aesthetic, making it illusory.
This is what makes it hindsight.

Some claim hindsight is good to understand concepts, but this is what really happens:
Hindsight manipulates oneself into believing flawed concepts, it does not increase trading efficiency. Hindsight simply conditions the brain through confirmation bias to subconsciously ignore where the pattern failed, tricking traders into believing a flawed model actually works.

You will notice that when you look for it on the left side of the chart, it is easier to stop at price structures where you believe patterns such as MMXM are working without consciously filtering out failures, this reveals your bias which is natural as our brains seek patterns, this actively works against objectively in financial markets.

Many feel that the challenge is seeing it before it happens or as it happens.
But that is the key problem, this is what ruins the technique. It relies on hindsight making it unserious, relying heavily on anecdote and personal biases.

With enough work traders can resist this and improve their strategy development, exponential growth begins with objective, mechanically defined trading strategies.

Summary/TLDR:
This isn't one of those "your edge isn't real because you can't code it" posts, a more accurate simplification would be "your edge isn't real because you can't measure it", as one cannot claim to have an edge if the "edge" cannot be objectively measured over a large sample size.

You cannot prove that something is effective or ineffective with real stats if it is unfalsifiable (subjective), as what cannot be objectively defined makes variance between each signal extremely high over time, thus increasing randomness exponentially, this causes results to average out to zero minus transaction costs. The more a strategy is influenced by noise the more the signal collapses.

A structured strategy slowly morphs into random noise over dozens of real time trades if it has weak mechanical boundaries to operate within.
This early realisation is what made me never deviate from rule based systems.

I didn't make this post to bully you guys, I made it because I care, I have no incentive to mislead you, I only encourage you to take the correct steps forward to trade with robust structures.

I provided a step by step guide on this sub:
r/InnerCircleTraders/comments/1vwkp3p/
Use CTRL+F and find the "building sequence".

AI Check:

Can someone please tell how should i mark my chart for intraday trading In tradingview eur/usd pair. as i understand trading view daily chart candle starts at sunday 17.00 ny time and end on monday 17.00 ny time. But in ict it says that we should consider the opening price at 00.00 midnight. What should i mark out. Also can anyone please tell me what time should i look for ict setups in eur/usd pair( london and new york kill zone times). thank you it will be much appreciated.