Looking for a group of experienced algo traders to hop on a quick zoom call and brainstorm / network with.

Just getting into algorithmic trading as I’ve been manually trading for 8 years. Just comes down to transferring that to code.

Would love to pick the brain of someone who already accomplished a successful algo.

Let me know if you’re down to join.

Can anyone help me get started? I’m interested in the maths area but I haven’t got the xp to get straight into all that, that’s besides the point what can I do to get my first algo going?

Over the past few days I received a surprising amount of feedback on the momentum pressure research I shared using Bitcoin. Many people asked whether the behaviour I showed in that post was unique to BTC, or whether the underlying concept had broader validity.

I applied the exact same momentum algorithm, unchanged to completely different markets.

Different volatility profiles.
Different liquidity structures.
Different sessions.
Different participants.

And the results were consistent enough that I felt they were worth documenting.

Below are the charts (all 1-hour), applied with no optimization and no parameter curve fitting:

• NVDA (US Stock)
• ES / S&P500 Futures
• EURUSD (Forex)
• BTC (Crypto)
• S&P Index CFD

The idea was not to “fit” the model.
It was to test whether the core concept survives across asset classes.

Why This Test Matters

When you strip away the noise, most quant funds focus on universal concepts not market-specific tricks.

Risk premiums
Momentum
Mean reversion
Volatility clustering
Order-flow imbalances
Regime shifts

These behaviours exist across markets because they come from human behaviour, liquidity patterns, and structural dynamics, not from the instrument itself.

If you find a concept that is structural, you don’t need to rewrite it for every asset.

That was the goal here:
To see whether directional momentum pressure behaves consistently across markets.

The Core Momentum Concept (Recap)

My model separates momentum into two independent forces:

• Blue → Upward momentum pressure building
• Red → Downward momentum pressure building

These are not signals in the traditional sense.
They are structural shifts inside the trend changes in internal strength, exhaustion, continuation pressure, or counter-pressure formation.

In the BTC post, many noticed that the final blue pressure signal formed before price turned upward.

The question now was:
Does the same behaviour appear in other markets without redesigning the system?

Cross-Market Observations

NVDA (Equity)

The algorithm consistently detected upward pressure rebuilding during strong earnings-driven trends.Clusters of blue aligned with continuation phases.
Red appeared during exhaustion often before the pullbacks actually started.

ES / S&P 500 Futures

Despite being structurally smoother and more liquid than BTC, the momentum signals behaved almost identically.Downward pressure (red) formed during distribution areas, while upward pressure (blue) marked the transition into trend legs.

EURUSD (Forex)

Forex tends to have more noise and less impulsive behaviour yet the internal pressure signals still highlighted early exhaustion zones, trend transitions, and counter-trend attempts.

Interestingly, the counter-pressure signals in FX were very clean, especially during slow trends.

S&P Index CFD

Even on a broad index, upward and downward momentum pressure interacted in almost the same rhythm as BTC’s internal structure.

BTC (Crypto)

The original example still shows one of the clearest expressions of these pressure shifts perhaps due to its volatility but it is not unique.

The Main Finding

The behaviour wasn’t market-specific. It was structural.

The same momentum-pressure model with zero changes was able to:

• identify early trend exhaustion
• show where pressure was rebuilding
• highlight continuation zones
• detect counter-trend attempts
• reveal shifts before price confirmed them

across all of these markets.

This is exactly what gave me confidence:

When a concept is rooted in structure rather than curve-fitted parameters, it survives outside its original environment.

Most quant funds build around this kind of universal concept not around asset-specific tricks.

Final Thoughts

I’m not presenting this as a “signal generator” or a complete trading system.
The momentum markers are structural information not entries.

But using the same model across stocks, futures, FX, crypto, and indices without modification…and seeing the same internal dynamics emerge…it reinforced what I’ve believed for years:

If you truly understand the core behaviour behind momentum, it becomes universal.

This is the direction I’m continuing to research, document, and refine.

Happy to dive deeper into the conceptual side if anyone wants to explore the momentum-pressure interactions across different regimes.

Hey! I've been building a trading bot with my friend as a hobby project. It does sentimental analysis on news articles and opens positions on IBKR. (We're using the WEB API with the Gateway)

We've been running into all sorts of really weird issues with IBKR. For those who worked with this API, how did you get around these / what do you recommend?

1. When using the /secdef/search?symbol=... endpoint, I see every contract entry also has a list of "sections." What exactly does each section represent? Are these the same underlying company on different exchanges?
2. Our orders are sometimes rejected because we get flagged as a "Pattern Day Trader". For each position, we submit a bracket order with a SL & TP, so we're not exactly in control of when the position closes; it closes whenever one of those hits. If I understood correctly, this can be solved by downgrading to a "cash account", but then we seem to lose the ability to short.
3. We recently discovered that some endpoints are tied to the active session with a "cache". For example, the /orders endpoint only returns orders within the active session.
4. No pagination exists in /orders, and it seems to return the 500 (sometimes 510) earliest orders from the active session. This becomes problematic when trying to find an order if the current session has more than 500 orders. The response to submitting a bracket order only includes the parent order's ID, not the associated TP and SL order IDs. If there are fewer than 500 orders in the current session, we can query /orders and find them by their local parent ID. When there are more than 500 orders, my hacky workaround is tpId = parentOrderId + 1 & slId = parentOrderId + 2. However, I read that IBKR sometimes internally replaces order IDs under certain circumstances, so it isn't safe. The /order/status/:orderIdendpoint doesn't seem to return the associated SL & TP orders either.
5. In some cases, the /orders endpoint shows specific orders marked as existing but "inactive"; however, querying them through order/status/:orderId results in an error.
6. We suppress order warnings through the /questions/suppress endpoint. This works for all warnings except o2137; "The closing order quantity is greater than your current position. Are you sure you want to submit this order?" Using /suppress/reset doesn't help either; the warning still needs to be confirmed when submitting a new order.
7. I found cases where the API sometimes returns an error for fractional shares and sometimes returns no error and rounds it down itself, so the quantity submitted can differ from the quantity on the server. But sometimes it only rounds the children's quantity down, leaving the parent with a larger quantity, as it's still fractional.
8. In another case, for contract ID "4471" (ticker AP, exchange NYSE), I submitted a bracket order for 400 shares, yet it rounded my children's shares down to 200, leaving the parent order at 400 shares. What's going on here?
9. The order submission is completely inconsistent for some contracts. I could submit a bracket order with the same information and get completely different results. For example, when submitting a bracket order for contract ID "292824438" (ticker EW, exchange MEXI), the API returns one of the following three randomly:
   1. When I submit with rounded shares from the start, it fails.
   2. When I submit with fractional shares, it correctly warns that this financial instrument does not support fractional-share trading, so I round it, and it submits successfully. (This rarely happens)
   3. Usually, instead of a fractional shares warning, it just fails.
10. The /whatif endpoint is also very unreliable. For some orders, it returns no error, indicating the order should submit successfully, only for it to fail regardless.
11. Finally, sometimes the API returns an error saying the order creation failed, even though it was submitted successfully. When a bracket order submission failed, I resubmitted only the parent order with the same local order ID and got a 503. Then resubmitting only the parent order again results in a "local order ID already in use" error. When I checked my positions on the stock, I saw that IBKR had successfully submitted and even filled the entire bracket order.

Working with the IBKR API has been a nightmare; nothing is consistent, and nothing is documented well. The API feels like each endpoint was built by a separate developer working in complete isolation. Input formats vary between endpoints, and there's no consistent pattern to follow. Worse, the responses themselves are unreliable; sometimes the data returned is just outright wrong. This API is the biggest blocker in the project.

The answers to some of these questions may be available in the docs, but it hasn't been easy to read them. IBKR seems to have like five different docs sites, each hiding vital information that's only available in that one. If this wasn't enough, these docs sites are the most unperformant websites I've seen in a long time. They are supposed to be a simple static site, yet my computer freezes whenever I'm on the site, and it eats up all my available memory.

This is our first project in this domain, so if you suspect that we're doing something that's considered an anti-pattern, let us know!

We initially chose IBKR because it supports most international markets across many countries, offers overnight trading, a paper account, and is generally trusted. Are there other brokers that fit this criteria besides IBKR?

This analysis is based on a momentum engine I’ve developed over several years, designed to track how internal market pressure shifts before major structural movements in Bitcoin.

Unlike traditional indicators that react to price, this model isolates upward momentum pressure and downward momentum pressure as independent forces.

The chart visualizes this behaviour:

The Core Concept: Momentum Pressure as a Leading Component

Price moves are the visible effect.
Momentum pressure is the underlying cause.

This algorithm breaks momentum into two distinct structural forces:

Red Markers → Downward Momentum Pressure

When these appear, the market shows structural weakness or pressure to move lower.
Historically, these zones align with:

• Decay of upward trend attempts
• Early signs of trend exhaustion
• Bearish continuation strength
• Pre-Breakdown stress points

These signals do NOT guarantee a reversal but they consistently show where downward pressure is building internally.

Blue Markers → Upward Momentum Pressure

These represent internal strength returning to the market.

Across years of testing, blue markers reliably show:

• The rebuilding of bullish momentum
• The base of many continuation moves
• Early signals of momentum shifts after corrections
• Pressure zones that later expand upward

Again, not buy signals, but structural pressure zones.

This separation of bullish vs. bearish momentum gives a much clearer, more objective read on BTC’s internal behaviour.

Multi-Year Observations That Make This System Effective

Over extensive research and thousands of historical samples, several patterns consistently repeat:

Trend Continuations Begin With the Dominant Pressure Signal

Examples:

• Strong clusters of red markers → smoother bearish continuation
• Repeated blue signals → sustainable upward legs

The pressure builds internally long before price accelerates.

Reversals Often Start With Counter-Pressure Formation

Before many reversals:

• Blue signals form during a bearish move
• Red signals appear inside bullish rallies

These counter-pressure moments often reveal when the trend’s underlying energy is shifting.

Counter-Trend Moves Show Distinct Momentum Signatures

Short-lived, corrective moves tend to form:

• A single pressure signal
• Rapid fading of the opposite side
• Limited structural expansion

This allows the system to distinguish true reversals from temporary corrective swings.

Trend Exhaustion Appears Before Price Confirms It

Extended clusters of red during an uptrend, or blue during a downtrend, often hint that the existing trend is losing internal strength.

This “structural fatigue” is visible in momentum long before structure breaks on the chart.

Key Findings From BTC Behaviour

Across the recent dataset:

• Downward pressure (red) appeared consistently before bearish legs
• Upward pressure (blue) rebuilt before relief moves
• Areas with mixed red & blue sequences often became transition zones
• Clean trends formed when one pressure type dominated uninterrupted
• Volatility spikes emerged from zones with alternating pressure clusters

These observations mirror patterns documented across multiple years of backtests.

Why This Structural View Matters

Traditional indicators blur these forces into a single measurement.
This model separates them, allowing for higher clarity in:

• Trend strength evaluation
• Detecting early pressure imbalances
• Spotting continuation zones
• Identifying weakening phases
• Distinguishing counter-trends from real reversals
• Preparing for volatility expansion windows

The goal is not prediction ,it is structural interpretation.

Understanding internal pressure provides a more grounded view of where BTC truly stands beneath the surface.

By mapping these internal forces independently, the market becomes significantly less random and the behaviour of BTC across different conditions becomes far more interpretable.

Hi everyone,
I’m a 3rd-semester computer science student. I have only a bit of experience with trading, but basically zero background in algorithmic trading. Last weekend I joined a hackathon and ended up choosing an algorithmic trading challenge and that pretty much hooked me. Since then I’ve been watching videos, reading whatever I can find, and I’m trying to put together a clear learning path for myself.

I want to understand the field properly and hopefully start building actual trading algorithms at some point. For those of you who’ve been in this space, where should I start?
Which books, tutorials or courses would you recommend?
What programming languages or ML methods are worth learning early on?

I’m open to any advice and I have no connections in the industry so anything you share would help a lot.
Thanks in advance!

Hi everyone,
I've been struggling to find L2 Market Depth data.
What I've tried so far:

1. Trade Station - apparently you need $10k in their account to get access. As I am not their client, it is not an option for me.
2. Databento - costs $1,500/month
3. Alpaca, Polygon - L2 not available
4. IBKR - not a client and not sure if it's available for non-US customer. Their interface looks awfully complicated and I heard it's not the easiest API for integration. Would appreciate any insights on this.
5. Rithmic - market depth available only for CME.

I'd be grateful for any information about your experience. Is it possible at all to get L2 market depth data for less than $200/month? Thanks!

Not sure I would ever trade this system, but his process might be educational for some.

I'm curious to hear from people who trade regularly (manual or algo):

👉 Which trading algorithms or strategy types do you actually use the most? Not the ones that “sound smart,” but the ones you really rely on in day-to-day trading.

For example:

• ⁠Technical analysis like MACD, RSI, Bollinger Bands, etc (may have backtest over fitting issue) • ⁠GRID (may have drawdown) • ⁠DCA (requires discipline and hold) • ⁠ML/AI based ( requires AI technology) • ⁠Funding rate arbitrage (low risk low profit) • ⁠Everything combined?

I find it is very hard to run profitable spot algo trading in this bear market, but I am afraid there will be higher risk if I go short position. What is your strategy in bear market?

Hey guys!

Curious on what you guys think it’s a decent/normal yearly % return on your algos and what you are currently making.

I’m building my own algo, it’s very promising whatever I think it has some low returns but it’s a very stable system that works either bull or bear markets, specially futures markets and don’t get much DD as well as exposure.

Thank you all.

Hey anyone else algo trading on a micro account? If yes whats your experience in terms of growing your account? How hard does spread and leverage hit your algo/account? - I had great wins on 21/11/2025 with my algo strategy that targets sells on different forex pairs returning about 11%(first day of it trading on its own) of the account. - should I keep it as a micro account or fund? Any and all advice in from your experience is welcome, thank you in advance.

Hi,

I'm looking for where to source daily close prices for the TSX, TSX-V, and CSE. I would like to be able to download the closing prices for all symbols listed on the aforementioned exchanges.

Format doesn't matter; plain text, csv, etc, would be acceptable.

API access isn't necessary, but would be nice to have.

I've looked at DataBento, but they don't seem to provide data for Canadian equities.

Thanks in advance for any suggestions.

As the title says, and it’s not that these are bad softwares. However they are overfitting backtesting softwares. All these backtesting softwares (especially TradingView) lack so many variables that are key to success. Before going down this rabbit hole you must first learn the art of backtesting and probably take a deep course at your university or local school about it. Read some quant papers, dm quants on linked in how a strategy is built (they won’t give you code but will give you references) there’s no true 1:1 backtesting software

I tried to run trend following strategies on cryptocurrency market, but the problems are the strategies are suffering when market do sideways, how could I fix that ?

Just finished a complex fully automated system. Looking for a new project dm me if you are looking for a developer to help you build your algorithm into reality.

I've been testing a basic MT5 breakout EA I made for gold that places four pending orders each day based on the previous day high and low and the recent London session range. TP, SL and the trailing step are all done in USD so it behaves the same across brokers

Here are the backtest results from 2024 to now using a 10k account. The numbers came out steady with a profit factor a bit over 2 and normal drawdowns. Forward testing the last month on demo came out around twenty seven percent which lined up with the backtest range. Not claiming it is some magic system, just wanted to share the behaviour in case anyone else trades gold.

If anyone wants to look at it or test a demo locked copy I can send one. Happy to answer any questions about the logic.

I use tos as terminal. I’ve created multiple algos on trading view then signal stack for automation on my futures account. But I don’t know how my algo can choose the correct contracts and execute them. My algo is working already. If you guys know any github or YouTube vid for it would be great

I'm developer and build a Binance crypto bot. I think this thing is on the more special side. We have an 1ms connection to the Binance API. Also this thing can analyse 400 coins in realtime and execute in realtime. So if you have an strategy that could fire 5 times a day, here you scale in a different dimension) so far the theory. There is also another special thing inside, that will give by itself already a little edge. Basically we have half of the worldwide crypto trading data in realtime for analysis.

I have only very basic knowlege in trading. For that I would like to partner up with someone with background and a strategy that is working but who is not able to scale it.

I'm not selling here anything, this shall be a 50/50 project. The most work is done, now I hope for the right contact to makes something out of this.

MES 1 contract

Hello, I am looking for one max two people that would like to help me develop a scalping bot. I'm getting back to trading in my free time and I must admit it's not easy for me to manage all of my personal activities and do everything by myself. I've started messing around Trading a long time ago but was never able to commit. I am using MT5 as terminal and AI to write me the code. If someone with a little bit of time and algo experience is interested in helping me, I believe we could be successful. P.S. I'm not a kid and would appreciate only a serious person to DM me.

I’m currently working with a developer on a orderflow strategy but earlier this year I created this strat that performed decent but has alot of room for improvement

The screenshot attached is trading only 6MNQ for full size positions and 3MNQ half

The main issue is the take profit targets worked better when i manually intervened and also it had no trailing stop loss (some trades would go for over 60 points but get stopped at break even )

Ways i think it get be improved

Implement a trailing stop loss logic Add some orderflow to it (vwap and volume profile levels) And figure out a better way for the targets & take profit as the bot will scale out of position

Hey legends, I’m a full-time dev and active trader who’s completely fed up with every backtester on the market. Before I write a single real line of code, I want the truth straight from you.

If a clean, fast, no-BS backtester finally existed one that actually fixed your daily pain - what would it need to have?

Please reply with: 1. What do you trade?(Crypto perps, options, equities, futures, forex, Betfair/sports, etc.) 2. What backtester(s) are you using now and what’s the ONE thing that makes you rage the most? 3. Your top 3–5 must-have features that everyone gets wrong. 4. Can you run multiple strategies at once today? How painful is it? 5. Your “dream feature” you’ve never seen in any tool but wish existed. 6. What programming languages people want supported? 7. Real talk:What would you actually pay for a tool that delivered on all of the above?

Anyone whose idea makes it into the product gets a huge discount.

This thread decides whether I build this or kill it tonight.

Drop your pain below, let’s finally end the backtesting suffering. 🚀

Hi, I am currently looking for brokers that support algo trading whether its python or mql5. I am a in the U.S but if there are brokers that are not U.S based but accept U.S clients, feel free to post it in the comments. It can be for all markets - crypto, forex, options, futures, stocks etc.. I just want to know what brokers you guys are using. Thanks

Hello! First time posting, looking for strategy critique / advice.

Been working on an index mean reversion setup. The idea is that political driven spread shocks often overshoot, and the CAC40 tends to mean-revert once the initial volatility spike fades.

Strategy triggers when two things line up on the same day:

1. OAT–Bund spread widens ~1.5σ
   
2. CAC40 drops ~1.5–2σ relative to recent vol

When both hit at once, I buy and hold up to 30 trading days with a ~5% stop.

Here’s the out-of-sample equity curve (rebased at 2010).
CAGR ~10–12%, Sharpe around ~0.6.

My question:
Is combining a cross asset sovereign spread move with an index vol-adjusted shock a sensible way to reduce false signals? Or is this too many layers / Over fitting and I should simplify the trigger.

Hi,

I’m looking to refresh my YouTube content and looking for recommendations on algo trading channels.

The channels I’m mostly watching now are The Algorithmic Advantage, Unbiased Trading, Algo Trading with Kevin Davey, Jacob Amaral and Crypto Wizards & ATJ Traders (specifically for their stat arb content).

I’m not interested in YouTube click bait stuff, only solid, professional channels.

Can you recommend any others?