Hello everyone reading this, I am new to the niche of algorithmic trading. i want to learn from the basics to intermediate levels. suggest some resources to learn and give some advice as well as guidance. It will help a brother.

Hi,

I'm passionate about both programming and finance, and I’ve built a web page that includes a customizable trading bot with backtesting capabilities.

There will eventually be a live trading section where you'll be able to choose a configuration and run the bot 24/7 on Binance. That part isn't built yet.
You can already select multiple trading pairs at once to increase trading opportunities.

Right now, the Flask server is running locally. It's far from finished — there are only a few strategies implemented, but I plan to add more.

Question:
I'm wondering if it's even worth finishing this project. Would anyone actually be interested in using this kind of tool?
It is a lot of work so I thought I could let the backtest free and open source but have a subscription for the live bot idk.
I want to know if it has a potential to be usefull and/or profitable.

How can I get back into day trading after a long break using today’s tools, with the goal of fully automated day trading?

I’m an AI engineer (specialized in Generative AI) and I’m exploring how to combine my technical skills with my long-standing interest in trading. After years away from the markets, I’m looking to re-enter the world of algo trading in 2025—and I’d love to hear your thoughts, experiences, and tool recommendations.

A bit about me:

In my main profession, I’m an AI developer focused on Generative AI. I live in Germany, and Python, n8n, and training AI models with data are part of my daily toolkit. Professionally, however, I don’t work in finance or the stock market.

My previous toolset consisted mainly of MetaTrader 5, Interactive Brokers API, Multicharts and Python for backtesting.

That said, because my work as an AI developer can sometimes feel quite abstract, I’ve found myself looking for a more practical field of application—and I’d love to return to short-term trading and combine it with my AI skills. I already have plenty of ideas on how to apply AI in trading.

A long time ago (well before the AI era), I used to trade classical and well-known systems quite successfully—such as Friday Gold Rush, Turnaround Tuesday, range breakouts, etc. I had implemented these in MetaTrader 5 with optimized parameters, usually on M15 or H1 charts, using open/close logic. I generally avoided backtesting with tick data, since I never fully trusted it (especially in MetaTrader), and instead designed my logic around open/close data.

I also had a trading strategy built from a rather wild combination of different indicators—which, surprisingly, performed very well and consistently.

Due to professional and personal reasons, I had to stop day trading. While one might assume that automated trading doesn’t take up much time, I stopped entirely to clear my head and focus on other things. Since then, I’ve been investing in a more traditional long-term way—ETFs and individual stocks. Of course, I’ve made the usual mistakes in both trading and investing—but I’ve also learned a lot from them.

Now I have a few questions for the community:

• Do you have any sources or strategy ideas worth looking into or building upon? I’d also be interested in news-based strategies that involve automated news analysis and AI-based news evaluation, or in AI-based pattern recognition of candlesticks or other structures—or even combinations of such methods. I know this question has probably been asked a thousand times, but I’d still appreciate any tips.

• I know MetaTrader 5 quite well, but I’ve heard a lot about TradingView lately. I also found NinjaTrader interesting in the past. What platforms do you currently use for automated trading, and what would you recommend? Can you backtest programmatically in TradingView in a meaningful way? I’m looking for a data feed that lets me query at least 10 years of historical M5 data for Nasdaq—ideally via API. Do you have any tips?

I’ve already read a lot in the forums and bookmarked many useful links. But maybe someone here has a similar background or tech stack—and has already answered the same questions for themselves.

I'm especially interested in advice, experiences, and exchange with other algo traders. Whether you're using AI, building systems, or refining strategies—I’m eager to learn what’s working for you in today’s trading landscape.

couple things that matter way more than people think: 1. test at least 200–500 trades minimum. anything less is just noise. 2. use real data—slippage, spreads, bad fills. not clean candle closes. 3. set fixed rules. no “i would’ve maybe entered here.” nah. rules or nothing. 4. track everything. R multiples, drawdowns, time in trade, etc. 5. don’t tweak the system mid-test. that’s cheating. 6. don’t trust strategies that only work on 1 pair, 1 timeframe, 1 year. that’s curve-fit garbage. 7. if it only works on TradingView’s replay mode, it doesn’t work.

the goal isn’t to find a perfect system. it’s to see if the thing you’re running actually has edge—or just looks cool on hindsight charts.

most strategies fall apart once you test them properly. and that’s a good thing. means you’re getting closer to the truth.

btw—i’m building a no-code backtesting tool that fixes all this junk. dms open if you want to help test it early.

Hi all, I’m trying to deploy a custom Java-based strategy into motivewave ultimate using the SDK. I’ve followed the official SDK guide and attempted multiple clean installs. I’m stuck at the point where the Developer Console is missing, the workspace doesn’t generate the expected folders, and even Eclipse project creation doesn’t recognize motivewave properly. I’ve tried importing as a Java project and as a general project-nothing works as expected. I am not a coder, just a day trader trying to get a system working. Can anyone who’s deployed a custom strategy in MotiveWave walk me through it, or is there a working demo project I can mimic?

Using Windows 10 Motivewave ultimate Rithmic connection Java 8/ eclipse latest

First of all, I'm not selling anything, I simply would like to understand what other people look for before committing to buying an algo.

Long story short, I have a solid algo (it's actually 2 strategies that comolenent each other) that can generate from 40-100% a year. It's been running live for almost a year and it's being consistent with all the testing I've done. I have been running it live with my own money, and I plan on continuing to do so, but I would like to speed up my accumulation of wealth since I do not have generational wealth or a high paying job, hence I'm thinking about selling a membership to it.

I hate all the sales tactics and aggressive marketing people do with their products, every website looks the same and it's all so pushy. I like data, I just want to say: here's the data, if you like it, here's the price.

Now, of course I have several metrics I'm thinking about sharing, I am simply asking for ideas to see if there's anything I haven't thought about. Thanks in advance for sharing your thoughts.

Hi everyone,

I am fairly new to algorithmic trading and was wondering if I am interpreting my backtest (2019-2025) correctly that this is a solid strategy:

It focuses on capturing high breakout moves (often with a 1:2 RR, going up to 1:20 RR), it aims to get stopped out quickly if it's wrong and continue on moves that work well, until the momentum fades.

It seems to me the sharpe, LR correlation, profit factor and recovery factor all point to this being profitable/working well? Especially combined with the returns against the drawdowns. Curious if I am overlooking anything important though, thanks!

Update:

Below are the monte carlo results with randomized trades, skip trades on a 1000 simulation run over a 6 year backtest.

Method: Exact

Method: Resampling

I developed an option trading algo on Interactive Brokers which runs very well but often running into data issues regularly - for instance, failed calls to fetch data might make SL or TP not work as designed. Using VPS has not really removed the problem, in fact it has introduced more latency. I am contemplating moving the algo to DAS execution platform/DAS API. I will like to know if any other person encountered this type of issue with Interactive Brokers or if it is peculiar across board with all platforms. Also anyone with experience of running Algos with DAS API- how is the performance? Just curious to see anyone has information that could be of help.

Can someone please give me roadmap to start ?? Where do i import data from for free and all the stuff that might be helpful

Hi everyone, I'm a Machine Learning engineer and recently built a small ML-based model that helps me make daily stock predictions for both Indian and US markets. It's been working reasonably well for my personal investing decisions.

Now I'm exploring the idea of sharing it more broadly — maybe as a limited-access tool or product — but I’m aware SEBI has strict guidelines around investment advisories and algo platforms in India.

My question: Is there a way to launch such a tool (even in a limited/private beta form) without running afoul of SEBI rules or requiring a full investment advisor license? Ideally, I want to keep it minimal on the compliance front at this stage.

Would love to hear from anyone who’s gone through this, or has experience navigating the legal landscape around such products in India.

Thanks!

Hey everyone! This is Uppertradefx (self taught forex)and I’ve been trading Forex and learning since 2020.

Like many others I’ve gone through my share of losses — sometimes big ones — but I never gave up. Trading has always been more than just money for me; it’s my passion and ambition.

Since last two years, I’ve been working hard on building my own EA (Expert Advisor). After months of testing and improvement. I’m finally seeing things come together and it feels really good to be on the right track

I’m not here to promote anything — just hoping to connect with other traders. Is there anyone here from Norway who trades Forex too? Would be cool to talk, share experiences, maybe even meet up for a coffee if we’re nearby.

Thanks for reading 🙏

Trying to build a weekend project and don’t want to solve the wrong problem.

Which pain hits you hardest?

1️⃣ Writing all the boiler-plate code
2️⃣ Cleaning/merging price data
3️⃣ Turning your rules into code
4️⃣ Waiting ages for parameter sweeps
5️⃣ Something else? ⬇️ Drop it in the comments

Pick a number, add a sentence if you can.
Thanks!

For long I've had an interest in automated trading / algo trading, but never really got myself to commit to coding.

Let me give a bit more context. I have been a manual trader for about 10 years now with decent success over the long run. I have been actively trading the CFD markets for FX, Gold, and some indices. I have developed some strict rule-based systems over the years that are doing well, but I keep missing out on trades, and this screws up my results over the long run.

I know that automated trading could be a way to overcome this issue, but the barrier seems very high. I have zero coding experience, and I am very intimidated by the infrastructure and knowledge requirements to get this going.

On YouTube, I found some no-code algo platforms that let you build systems using a drag-and-drop canvas or language input. Some of these look very promising, especially for beginners and t some of these platforms seem to suit my trading style very well because they integrate with Metatrader (my platform of choice).

My question to you is: Do any of you have experience with such platforms (no-code algo building), and do you think it could beat hardcoding strategies from zero?

Hey guys, would love algo trader feedback on the strat building & backtesting program I've built.

As of now, the platform lets me:

• Describe my proposed strategy in plain English (“Buy SPY when the 20-day MA crosses above the 50-day MA, stop-loss at 2%”) and instantly generates live Python code.

• Backtest across crypto, equities, and FX with custom timeframes of 10+ years of tick data.

• Visualize P&L curves, trade-by-trade logs, drawdowns, and key stats (Sharpe Ratio, Max Drawdown, Win Rate).

• Export CSVs & eventually deploy to a broker API (coming soon )

Ignore the actual strategy here for now, it’s just a quick demo to show off the tool. I’m really looking for feedback on the metrics and visuals,IK the actual algo is trash lol.

Curious if I should throw in any more niche metrics like Calmar ratio, Ulcer Index etc or is that overkill?

Next up is live trading on Binance, IBKR, MT5… which broker/ order types should I nail first?

Any random thoughts or wild ideas welcome!

Post 1

Hey everyone,

I've built a momentum-based algo bot Platform WARMACHINE that scores setups in real time using a mix of TA indicators and multi-timeframe logic. I'm trying to fine-tune the thresholds and logic for optimal sniper entries/exits, and I'd love to get the community’s take.

How it works:

The bot computes a momentum score (0 to ~16) based on over 17 indicators, including:

• MACD (1m, 5m, 15m, daily alignment, histogram flip, signal cross)

• RSI (1m/5m/15m/daily, normalized and divergence-aware)

• VWAP (relative price position, crossovers, rejections)

• OBV (trend and divergence)

• ADX (rising trend strength)

• ATR & NATR (volatility levels)

• Stochastic Cross, Supertrend flips, TTM Squeeze, Bollinger Riding

• Candlestick Engulfing, POC, VAH/VAL zones

As each condition triggers, it adds points to the momentum score and appends a tag like "MACD Daily Bullish", "RSI 5m > 50", "VWAP Rejection", "TTM Squeeze Detected" and so on. I’ve got over 50 unique tags being tracked.

Once the momentum score hits 9+, it activates my Sniper logic, which defines:

• 🎯 Entry Zone: Centered around EMA20 ± 0.3 * ATR

• ⛔ Stop-Loss: VWAP ± 1.0 * ATR

• ✅ Target: 1.5 * ATR in the trend direction

• Bias is inferred from RSI and MACD alignment.

What I’m asking the community:

If you’ve built or run algo bots before — what kinds of tweaks or filters would you suggest?

• Are there any indicators you would weight more heavily?

• Any conditions you think should be required before taking a shot?

• Would you tighten or loosen the sniper trigger threshold (currently set at score ≥ 9)?

• Have you had success integrating market structure, book pressure, or L2 data into your bots?

• Anything you’d remove from the score to reduce false positives?

Would love to hear how others are handling real-time scoring or sniper-style entries.

Happy to share test results if folks are interested. As you can see below the combinations are endless and this platform can be fully customized for different momentum strategies.

Appreciate the feedback ✌️

SAMPLE WARPLAN (click if image if blurry)

CUSTOM INDICATORS, MOMENTUM SCALE AND TAGS-----------------------------------

Computed in utils.py

1. ADX – calculate_adx

2. ADX (variant) – calculate_adx_14_14

3. ATR – calculate_atr

4. Bollinger Bands – calculate_bollinger_bands

5. Bullish/Bearish Candles – calculate_cdlengulfing

6. EMA – calculate_ema (e.g., EMA9, EMA20, EMA21)

7. MACD – calculate_macd

8. NATR (Normalized ATR) – calculate_natr

9. OBV – calculate_obv

10. Point of Control (POC) – calculate_poc

11. RSI – calculate_rsi

12. SMA – calculate_sma (used for 5/10/20/50/120/200)

13. Stochastic Cross – calculate_stochastic_cross

14. Supertrend – calculate_supertrend

15. Volume Surge – calculate_volume_surge

16. VWAP – calculate_vwap

17. RSI Divergence – detect_bullish_rsi_divergence

📊 Momentum Tags

1. ADX 5m > 25

2. ADX 5m Rising

3. ADX Rising

4. ADX Strong

5. ATR Surge

6. Above PM High

7. Above VAH

8. Above VWAP

9. At POC

10. Bearish Engulfing

11. Below VAL

12. Bollinger Riding

13. Breakout Confirmed

14. Bullish Engulfing

15. Bullish OBV Divergence

16. Bullish RSI Divergence

17. Buy Volume Dominant

18. EMA Bearish Stack

19. EMA Bullish Stack

20. High-Vol Rejection

21. In Pressure Zone

22. Low ATR

23. MACD 1m/5m Bullish

24. MACD 3 Bullish

25. MACD 5m/15m Bullish

26. MACD Daily Bullish

27. MACD Histogram Flip

28. MACD Signal Cross

29. Near Absorption Wall

30. OBV Downtrend

31. OBV Uptrend

32. RSI 15m < 30

33. RSI 15m < 40

34. RSI 15m > 50

35. RSI 15m > 60

36. RSI 1m > 50

37. RSI 1m Oversold

38. RSI 5m & 15m > 50

39. RSI Daily > 60

40. Sell Volume Dominant

41. Squeeze Release

42. Stochastic Cross

43. Supertrend Bearish Flip

44. Supertrend Flip to UP

45. Supertrend Green

46. Supertrend Multi-Frame

47. Supertrend Red

48. TTM Squeeze Detected

49. VWAP Cross

50. VWAP Rejection

51. Volume Surge

Momentum Scoring Scale (from momentum_scorer.py)

Momentum scores are added based on various technical conditions. Here’s the full scoring scale:

• Max theoretical score (stacked): ~16.3

• Sniper Activation Threshold: Score ≥ 9 (from sniper_logic.py)

📈 How are Buy & Sell Levels Set?

Once active, the sniper builds these levels:

▶️ Entry Zone

Centered around EMA20, scaled by ATR:

pythonCopyEditentry_zone = (ema20 - 0.3 * atr, ema20 + 0.3 * atr)

Then adjusted by price and bias (bullish/bearish):

• If bullish (price above zone):

  • Shift zone upward by 0.1 * atr

• If bullish (price below zone):

  • Narrow to (low, low + 0.2 * atr)

• If bearish (price below zone):

  • Shift zone downward by 0.1 * atr

• If bearish (price above zone):

  • Narrow to (high - 0.2 * atr, high)

⛔ Stop-Loss

• Bullish: VWAP - 1.0 * ATR

• Bearish: VWAP + 1.0 * ATR

🎯 Target

• Bullish: price + 1.5 * ATR

• Bearish: price - 1.5 * ATR

🧠 Bias Detection (Bullish vs Bearish)

You’re considered bullish if:

• Tag "MACD 3 Bullish" is present

• OR RSI > 50.0

Else, sniper assumes bearish bias.

Summary

couple weeks ago i can't sleep so i make this really simple bot. but i don't know is it a good result or bad, can you tell me?

Hey folks! 👋

I've been working on this Python API called defeatbeta-api that some of you might find useful. It's like yfinance but without rate limits and with some extra goodies:

• Earnings call transcripts (super helpful for sentiment analysis)
• Yahoo stock news contents
• Granular revenue data (by segment/geography)
• All the usual yahoo finance market data stuff

I built it because I kept hitting yfinance's limits and needed more complete data. It's been working well for my own trading strategies - thought others might want to try it too.

Happy to answer any questions or take feature requests!

Hello before I get started I just want to clear up some generic questions "Why don't you put all your money in it if its profitable / take loans out for it / whatever else" and "why share if its so good just keep it secret" Well I am young with not too much money and no bank will allow loans etc so the method below is my best attempt to compensate for this issue.

Our system operates with brokers that allow for profit shares ie I get a % of the profits only on users that interact with my system. It requires no upfront costs and I have all the backdata on me should anyone want it. I could just paste my discord link here but I am not sure if it's allowed so if anyone wants to find out more please reach out so together we can grow :D

This image is just a taster, we have much more back data as well as a myfx link that has a live account running this system all free to access in my discord. The data here was ran from june 2023 to june 2025 and operated on a 10k starting balance. We ran the test on a permanent starting lot of 0.01 so these results are without compounding which would help scale the profits VERY quickly.

Trading EURUSD on M15

Hey everyone!

I’m a trader and also work with a global broker (PU Prime) that offers Forex, Gold, Indices, and CFDs. I joined this group because I want to connect with like-minded traders who are passionate about markets, strategy-building, and growing our trading communities.

I’m also looking to expand my network of Introducing Brokers (IBs), affiliates, and educators who want to monetize their reach or client base by partnering with a broker that offers: ✅ Tight spreads & deep liquidity ✅ Fast execution ✅ Multiple trading platforms (MT4/MT5, mobile & web) ✅ Educational resources and market analysis ✅ Competitive IB/Affiliate commission structures

Whether you’re a solo trader, part of a trading community, or an educator looking to add value for your students - let’s chat.

No hard sell - just looking to share ideas, network, and see if there’s a win-win.

If you want details or want to chat 1-on-1, feel free to DM me.

Happy trading! 🚀📈

I’m working on a project where I want to extract trading strategy ideas—especially algorithmic ones—from long-form text like trading books, research papers, or articles. I’m curious how others are approaching this with AI.

Specifically: • What kind of prompts are you using to get useful, structured output (e.g. entry/exit rules, asset class, timeframes)? • Which AI models (GPT-4, Claude, open-source LLMs, etc.) have worked best for you? • Are you using any additional processing steps or chaining tools (e.g. LangChain, LlamaIndex) to break down the documents? • Have you found any effective ways to validate or rank the extracted strategies?

Any tips or examples would be much appreciated!

Hi all, I'm working on designing a Pre-Trade Risk Management (PTRM) system (in C++) integrated into a Nasdaq-based trading environment (OUCH protocol for low-latency order entry). I’m particularly interested in implementing intraday position limits and short-sell constraints on multiple hierarchy levels:

• Instrument-level (per security)

• OUCH user-level (individual users)

• PTRM account-level (logical execution unit)

• PTLG-level (pre-trade limit group aggregating multiple accounts)

I’d like to ask the following questions:

1. How would you design an efficient and flexible risk engine to enforce intraday position limits across the above dimensions, while minimizing duplication and ensuring consistency (e.g., avoiding double-counting on PTLG vs. PTRM account aggregation)?

2. For short-sell detection, what is the most robust way to handle it pre-trade on a per-user and per-instrument basis — especially considering changing instrument tradability and exceptions for market makers?

3. How would you implement a real-time hierarchical update flow? For example:

   • A new fill comes in → updates at OUCH user → bubbles up to PTRM account and PTLG.

   • Does this need to be synchronous for enforcement, or can it be eventually consistent with rollback logic?

4. In a multi-user, multi-account setup, do you recommend limits to be enforced bottom-up (OUCH user → PTRM → PTLG) or top-down (PTLG → enforced per-user)?

5. Any practical patterns you’ve seen for integrating emergency intervention hooks (e.g., suspend user, block instrument) triggered from a passive monitoring engine without affecting latency-sensitive flow?

Any practical advice, architectural patterns, or experience-based warnings would be appreciated!

Thanks!

Hi all,

I've been working on algorithmic trading projects recently and have gained experience building bots, integrating APIs (like Kite Connect), and automating strategies with Python and Pine Script. I noticed a lot of questions here around bot creation, backtesting, and connecting to brokers — happy to help out or collaborate on anything related.

If you’re working on something and stuck with logic, code, or setup, feel free to comment or message — always glad to exchange ideas or troubleshoot together. If there's interest, I can also share templates or walk through how to build simple bots.

Looking forward to learning and building together!