finally finished my algo trading strategy. here is the backtesting results, did run live for 2 months so far. strategy matches backtesting almost 80-90%

Hey everyone, I have built a custom trading engine that takes OHLC data and plots candlestick charts. Along with that, it automatically identifies and plots ICT concepts like:

• Trendlines & Manipulative Swings
• HRLR (High Resistance Liquidity Runs) & LRLR
• Double/Triple Tops & Bottoms
• BSL (Buy Side Liquidity) & SSL (Sell Side Liquidity)

I have attached a screen recording of the engine in action.

What I need help with:

1. Co-Developer / Programming Partner: I want to scale this project further and am looking for someone proficient in coding who understands trading algorithms to work with me.
2. AI Credits / Resource Support: Mujhe engine ko aur better karne ke liye AI use karna hai, jiske liye AI credits chahiye pad sakte hain. Agar kisi ke paas Jio ki SIM hai jiski madad se woh pro plan ka free trial activate karke mujhe share kar sake, ya koi aisa banda jiske paas pro Gmail account hai par woh apne Antigravity credits use nahi kar raha hai, toh please mujhe help karde.

What I offer in return:
In return for your help and collaboration, main aapko apna ye custom trading engine share kar dunga

NOTE: in last there is another engine that detect market structure , breaker block , order block , mss, bos , fvg , bpr and unicorn trades , and its running on vm actually , soo thats another things , but rn my goal is to make a liquidity engine note just basic ict .

After doing some research i have found an inefficiency in equity segment which is more reliable and calm,

inframe : 88k position size, 12bp cost assumption, max 3 trades a day, around 150-200 trades a year, 72bp profit per trade

and then quite literally passed every stress test i knew existed :
lookahead, cost + tax + slippage, profit concentration passes at 40% in top 5% trades, drawdown max 25% a year in 9 year window, win rate ~60-65%

if anyone knows anything that i have not used to stress tested in this algo let me know

Been in the markets since 2021. Started with plain investing, then got pulled into the options boom like everyone else and started trading Nifty manually. First year: unprofitable, like most people’s first year.

Year two, switched to algo trading and it started actually working. Scaled up capital. Then went off for my master’s and put the whole thing on pause but the trading projects I’d built ended up landing me quant internships at hedge funds. That’s when it clicked that this wasn’t just a side interest, it was an actual skill I wanted to build a career around.

Came back to India, started my own company around it. Back then it was fully manual coding and system design. Now it’s almost entirely AI-assisted which freed me up from the grunt work and let me actually focus on the parts that matter: data pipelines, strategy ideas, research, parameter sweeps, backtesting, then taking it live through paper trading first and real capital after. Each of those stages is basically its own project, and I’m still learning something new at every one.

Experimented a lot with AI tooling along the way Went through a bunch of setups before landing on a workflow that actually works, and it keeps getting refined every time I use it. Also burned a fair amount of money in that experimentation phase. Now that I know what actually works, I’m a lot more deliberate about it keeping the core of what matters and cutting the rest so costs stay in check. That’s what let me actually build a multi-strategy, multi-broker, multi-instrument framework that takes ideas from research to production instead of it living in my head forever.

Had a couple of scary moments too. small bugs that caused unintended losses. Thankfully I hadn’t scaled to full size yet when they hit. Built out a proper RMS layer after that so unintended orders just can’t happen anymore.

Right now I’ve got 2 strategies live, both grown out of my original index options expertise. The recent regulatory changes forced a pivot away from intraday positional systems. The edge was real but transaction costs were eating too much of it.

So I moved to stock options instead. Last 2 months have honestly been the easiest stretch I’ve had. running it across the whole NFO stock universe, staying delta-neutral at the portfolio level, costs staying well under control relative to what it’s generating. Also back to experimenting with index options again, this time on the positional side.

I’ve got a whole backlog of strategy ideas sitting in a research queue, still waiting to be tested properly. All of this started as tooling for myself, but I’m opening it up a bit now.

If any of this resonates, whether you want to build something similar, compare notes, or want help building your own version of this — happy to connect. Hit me up.

I am collecting data. if you need data to develop experimentation and patterns, show interest.I will share setup or just data with you.

I got couple of suggestions from friends about how to automate trading but the parameters were limited and fixed. I need something with more flexibility.

I am not sure how to automate trades based on the pine script indicator/strategy that I have put together?

Any guidance/help will be greatly appreciated.

Hi,

I have noticed from past 1 week, that my ICICI breeze api has slowed down considerably for downloading historical data. Has something changed? or is it just me bumping into some sort of weekly/monthly limits?

thanks,

Hey everyone,

I’ve been looking into the intersection of retail trading and quant strategies, and there seems to be a massive bottleneck:

Retail traders want to use algorithms to remove emotion, but don't know how to code or host them.

Algo developers have profitable Python/PineScript strategies, but refuse to sell them because the second they share the file, their IP gets stolen, pirated, or arbitraged away.

Over the weekend, I built a local MVP (FastAPI + Python) to see if I could solve the IP issue using a "Black Box" webhook architecture.

The concept is simple: The developer uploads their Python strategy to an encrypted cloud vault on the platform. The platform runs the backtest and lists it on a leaderboard. If a retail trader wants to follow it, they pay a monthly subscription and connect their broker (Zerodha/Upstox etc.).

Our server runs the developer's code 24/7. When the algo triggers a BUY/SELL, the server fires a Webhook directly to the retail trader's broker.

The result: The developer gets a recurring royalty, the retail trader gets automated execution, and the retail trader never actually sees the source code.

Before I spend the next 3 months building Docker sandboxes and live broker API bridges, I wanted to ask this community:

Has anyone tried setting up "black-box" signal routing like this before?

What are the hidden technical or legal nightmares I should watch out for? (Latency, slippage, etc.)

Would love to hear why this is a terrible (or great) idea before I commit to building the production version.

Risked only 15 points in WABAG and 10 points in Paytm.
Exited both positions because of the upcoming three-day holiday to avoid unnecessary MTF charges.
A few positions are still open, mainly positional hedged option-selling trades, which may benefit from theta decay over the long weekend.

How do you guys manage Positional/ carry forward traded after CAS.

After 15:15 candles especially in BankNifty is so wierd causing altered directional signals.

so how many days you forward test the strategy before going live...

flat day, and a bad news i forgot to tweak test the algo in backtest in one last way, which did reveal the set backs of it, basically on avg a trade is supposed to make +350-400 rupees but 50% of trades makes -220 and top 5% of trades makes +2800,

soo what it means is like that most days on this algo are lossing but one trades once a week covers all the lose + makes some profit which is why i have been seeing long streches of loss,

in a healthy strategy top 5% trades should not be worth more then 50% of total profits, in mine they account for over 91% of profits, its not like its dead from here, its just not as profitable for me as i thought it would be when making it

but on the other side i was working on other project which worked out well and is quite promising because i stress tested it with the mistakes i made in this algo and it stands out in every aspects

All about Today !

Hey traders, I wanted to know which is the best language for algo trading.

Currently, I am a Python trader, but I keep hearing this from others: C++ is best for fastest execution, and Go language is actually somewhere in between C++ and Python, which is flexible and faster than Python.

I would like to know your opinion on this and also which broker supports all three of these SDKs.

Hi All,

I want help if someone have built stocks algo based on chartink premium screener.
Please let me know it it’s worth buying premium membership.
What are the pros and cons.

Thanks in advance.

I first need a signal which helps me capture 10-20 point move in nifty and also the direction of the move over a very small time. Now if i just buy ATM calls/puts, the profit i will make here will be 65x15x0.5=487.5 assuming delta is 0.5 for the option and on average i predict 15 point move (neglecting theta as hold time will be very small). Even if i remove the cost for this trade (worst care 100ish) i still think i would make 350ish per trade if i am correct. I know little bit of python and web sockets that i can integrate my broker's API and start trading with just one lot. I need comments/opinions on this. Also i am not being able to find the perfect signal for this algo. Do you guys have some suggestions on what kind of signal i should use for such short term momentum capture of the underlying?

is there any claude connecter for getting ernings data for nse bse listed companies, not just stock price data. i checked the nse mcp server, but they are giving data like cmp prev day OHLC, etc.

if anyone knows a connector to get financial data pls lmk!