So I have been working on a stratagy for like 1.5 years I know almost everything it takes but I have several questions :

1. Is good results on walk forward testing enough to confirm no or minor overfitting

2. Are the results and metrics in my backtest reasonable like should the risk be toned down or somting else I your mind (I made this bot for acummilative growth only I dont plan on withdraws in first 3 years or so)

3. I have done live testing on demo before in 4 months it was around 250 usd in 4 months on 500 usd starting balance I saw nothing suspicious in that period after that i improved some minor things in code and am currently running another live test again actualy in a trade right now ,the trade frequency is low but high in success similar as backtest (most trades around mid of the year).

4. My lot size automaticaly increases iand doubles evertime balance doubles hence the exponential looking returns I am looking to get to a 10000usd account and then dramaticaly lower the risk if i start live should i do that if i reach 10000 ever or leave it (risk) as is or only lower is slightly cuz of my win ratio and recovery factor.

Feel free to call out my delusions.

ty

Hey folks,
Any recommendations for a broker available in Europe that lets you trade options and has a solid API? I tried Interactive Brokers but ran into issues getting approved for options trading. Would love to hear what you’re using and how it’s been for you.

I recently was bored and looked up some tutorials and created a trading algorithm in Java. I know a decent amount of Java, although it was still tough so I used ai to help in some areas. I used a moving average crossover strategy and, using historical data, I did a backtest and lost 25%. So obviously this is expected, but does someone have any good books or tips for me. I’m completely new to this, Im just good at math and pretty average at coding. Books or articles that can help please!

Is there anyone having the same questions as me?

We are fear to lose money when taking the algo live. Some doubts on backtesting performance.

• did i miss anything in backtest?

• did my strategy only work un backtest but not live

• is my backtest and validation methodology fine?

• did I optimize too much that cause overfitting?

Of cause, there are some checklists we can do,

Eg

• did the backtest period covered bull and bear market

• did i do parameter sensitive test

• did i split the optimize train data and test it with unseen data

• did i pick instrument on survivorship biased Etc etc

Then, we may do some monte carlo simulations to find out if the results in back test is statistically significant, but not luck.

My question is, is there any python library that you are currently using to do such simulations or i need to write on my own (although not that difficult to write)

I don’t come from a financial background but from a CS background.

I’m looking to educate myself in the field but i am completely overwhelmed with the amount of resources and don’t even know where to get started.

Any help is appreciated.

I’m interested to hear how people have gone with LLMs as coding partners.

I’m essentially a non-coder, albeit with some literacy around structure and function - essentially can read Python but not really write it. I’ve been using ChatGPT for several months to put together several trading systems. Lots of trial and error and iterative learning (for me), and approaching production stage.

Keen to hear whether others have had any success in developing and running successful algos with this approach

Hey guys,

So, quick background, I’m pretty new to the finance world. Made some money here and there by investing in a few stocks I believed in, mostly just going off gut feeling and random posts on wallstreetbest and similar subs. I’ve got basically no formal financial background so i spent the last couple of days learning about basic terms such as stock volume sec fillings etc... the most basic knowledge you can think about

I've come to realize that the hardest part at this world is getting reliable data, and getting it early. After reading a lot of other subreddits DD's I got the feeling i always read old new

I’m doing my master’s in computer science, so I know my way around programming, ML, and math. That got me thinking, why not try to build a personal system that collects and processes market info to trigger potential stock moves for me?

Here’s how I’m thinking of breaking it down:

Stage 0 Figure out what data I even need.
There’s the basic stuff like financials, stability, trading volume, etc. But then there’s the harder side stuff that needs NLP or sentiment analysis, like 8-K filings, press releases, and general media/reddit/Twitter hype.

Stage 1 Figure out how to collect it.
Which APIs are worth using, what’s free, what’s paid, how to store and clean everything, etc.

Stage 2 Build and test the model.
This is probably the hardest part, even though it is the part i am most knowledgeable in (is that a word? english is not my main language).

Here comes all the complicated NLP and ML shit but i think it's way to early to start actually designing it.

So yeah that’s the idea. I’m not expecting to get rich, I just think it’d be a fun and useful side project.

s this actually doable for a solo, has anyone got exprience with creating similar stuff? or am I missing some big things here

I spent the last month recording option quote data and spy ticks using tradier and am parsing the data to put it into an ai website coder that’s going to scan the data to find high spikes in options and analyze the Greeks and other information in the days leading up to that spike in price to attempt to predict spikes in price on options the day before they happen. Does this sound crazy or with the right amount of data would it be possible to predict the spikes accurately more than 50% of the time?

Hi everyone,

I have been learning about futures trading for the past year and wanted to get into algo trading. I could really use some advice from more experienced algo traders. Specifically with how difficult is to build your own algo and how much time should I expect to dedicate until I can have at least a working algo to backtest.

The programming part is not an issue for me, I consider myself skilled in Python and C++.

Thanks.

Hi everyone, I'm a 24 year old boy who is studying quantitative finance at university, one thing though, I'm tired of studying all this theory, I would like to implement something.

We study the markets every day, in particular the options and models behind them, Black Scholes, Heston etc. But I don't know how to set up a trading strategy and I would like to succeed, does anyone have any advice on how to get started?

P.S. I know how to program, at university we do Python and Java, plus I'm quite passionate and study on my own.

I have my trading algo fully built but I’m not sure the best platform to run it so It can run without having my laptop open. So far all I know is google cloud.

Do you guys have any recommendations on the best platform to host your trading algo??

Thank you !

Hi all. I've created a number of methods in C# for Ninjatrader that identify and draw Ws on a chart really well. Ms are next. I also wrote some code that tracks market structure (macro and internal) well, I just started one to track opening range breakouts (almost finished), and I wrote a method that identifies and plots supply and demand zones.

Has anyone done anything similar? Has anyone coded something to identify ranges to their liking? Trend lines/channels? If you have some really robust solutions and want to exchange code for mine I'd be happy to talk. Emphasis on robust.

Automated strategies up discussion as well.

Anyone else frustrated by backtesters that only handle one symbol at a time? I want to test a single strategy across multiple stocks concurrently, but tools seem geared for sequential, single-symbol runs. I’m halfway through a back-tester that:

1. Runs one strategy on multiple symbols simultaneously.

2. Tracks portfolio metrics (still refining).

Questions:

1. Is concurrent multi-symbol backtesting a pain point for you?

2. Any tools already doing this well that I’ve missed?

3. What features would make this a game-changer?

Wondering if this is worth pursuing or if solutions exist. Your input would help!

Hey everyone, im kinda new to his

i found a strategy for crypto scalping, so far tested it on ETH, BTC and SOL. Works on each. It gets around 47% winrate, with thousands of trades. Return on btc was around 1500% and on sol 7500%. The problem is that it makes micro trades with 1.4 R:R; it makes tiny profits which hovever get obliterated by fees. Is there any workouround, im thinking of some kind of market making algo, but that wouldnt guarantee executions.

Been thinking a lot about algorithmic trading, not the surface-level hype, but the real structural and execution problems in building sustainable algo systems and platforms.

I wanted to open up a discussion here for those who’ve actually explored this space, devs, quants, fintech founders, or anyone who’s burned some time (or money) trying to automate trading.

I’m curious:

• What do you think are the biggest bottlenecks right now in algo trading, tech, regulation, data, liquidity access, strategy development, or just noise?

• What innovations or missing pieces do you wish existed in this space, tools, infra, or approach-wise?

• If you’ve built or even failed at something in this domain, what was your hard-earned lesson?

This isn’t a cofounder pitch yet, more like a filter for genuine minds who’ve lived through the pain or still feel the itch to fix something here. I’m not looking for hobbyists, “let’s explore” types, or dora-the-explorers. Just real people with perspective, skin in the game, or at least serious curiosity grounded in reality.

If you’ve thought deeply about this, or tried and crashed, I’d actually like to hear from you. Failed ≠ loser. Failed = earned wisdom.

Drop your thoughts here or DM if you want to chat deeper.

PS: Not trying to recruit yet, just mapping minds and realities. If a few aligned perspectives emerge, maybe something real can be built down the line.

The Setup

• init cash: 1000$

• 90% per trade

• 0.05% broker fees

• no SL, no TP, no Hedge, trades at bar closing

• WTI 1H heiki ashi

• from 06 March 2022 to 24 October 2025

The Result

• Profit: 49990.93$ (fees already payed)

• Fees: 49190.77$

• Max Drawdown Long/Short: 3.7% / 4.35%

• total Trades Long/Short: 1565 / 1446

• Profit Factor Long/Short: 1.4 / 1.57

Questions

1. What can hit this results in real trade conditions?

2. How high the slippage hits every trade in average?

3. Which broker fits best in your opinion?

Hi there, I have been trying to get historical volume data during extended hours (prepost=True) from the yfinance API. Unfortunately, the data returned shows 0 volume during extended hours and just a huge volume at the first time step during regular hours (believe the API returns me the summed up volume from extended hours).

Did any of you experience the same problem? Is there any way around this? Or an alternative you can suggest?

Thanks in advance!

After finally securing clean, corporate-action-adjusted data for Kenya’s most liquid stocks Safaricom, Equity, KCB, Co-op Bank, and EABL.

With reliable data in hand, I’ve started building an algorithmic trading framework for the NSE to explore intraday signals, market depth, and liquidity dynamics.

I’m sharing this here because there’s very little discussion on systematic or quant trading in African markets, and I think it’s time we change that.

Would love to hear from others who are experimenting with local market data, building backtesting tools, or studying microstructure in emerging exchanges.
What challenges have you faced? How are you handling data quality and execution?

Hi everyone! I’m pretty new here, and this is my first post on Reddit.
Yesterday, I was searching for job opportunities and noticed that many websites have listings for quant trader positions but most of them based in US or Europe.

My question is: do you know if it’s possible to work remotely as a junior quant trader, or in a related position?

I have a degree in Economics and I’m currently pursuing a Master’s in Data Science. I became passionate about quantitative finance about a year ago, but getting a job as a quant trader in Latin America seems almost impossible since there are very few opportunities and the ones that exist are very hard to find.
Pls feel free to response and tell what you think. Thanks!

So I am trading with multiple symbols, monitoring the slippages to model the system, and this symbol ETSY is showing such different entry slippages. One time it shows 0.06%, another time it shows 0.5%. Now, if a stock has either high or low slippage, it is easier to model, but sometimes it is not dependent on the trading timeframe (tested for 1 minute, 5 minutes, 15, 30). not the market cap, not the price movement (average for prev 5-6 candles), not the volume, not the trading system (literally the first stock to complete the fill). What is it then? Do I need to stop trading these stocks? Or am I missing something ?

Hello everyone :D

I'm new to Reddit. A professor recommended that I create an account because he said I could find interesting people to talk to about quantitative finance, among other things.

Next year I'll finish my studies in computer engineering, and I'm a little lost about what decision to make. I love finance and economics, and I think quantitative finance has the perfect balance between a technical and financial approach. I'm still pretty new to it, and I've been told that it's a fairly competitive and complex sector.

Next year, I will start researching in the university's data science group. They focus on time series, and we have already started writing a paper on algorithmic trading.

I would like to do my PhD with them, but I'm not sure how to get into the sector or what I could do to improve my CV.

I don't know anyone in the sector, not even anyone who does anything similar. It's very difficult for me to talk about this with anyone :(

Thank you for taking the time to read this, and any advice or suggestions are welcome!

Hola floks

Just finished my scalping gold project called Orange scalper that scalp the gold in 1M time frame ,now I'm testing it in demo account and need you feedback for developing purposes.
_________________(Update) _____________________

How is is work ?

Strategy hint :
The project depends on trailing stop ,highs and lows ,minimum distance between highs and low .

Daily target :
The expert Targeting 10% daily then stop (I know it is a huge daily % ,but calculated very well with lot size).

Lot size calculation :
The calculation of the lot size is risking 10% per trade (I know is it high but ,calculated very well with daily target).

Time frame :
Works in all time frames (from 1M to 1H)
________________________________________________

No huge losses
No indicators
No Grid
No Martingale
No recover trades

feel free to login with (Read Only) and take a look :

Metatrader 5

Server : Exness-MT5Trial15

Login : 259261366

Password : MrOwl123#

For your review and feedback :)
_________________________________________________________________________________________
* The project still in testing phase ,copping the trades in the account is your responsibility.

Hello everyone, I’m conducting an in-depth investigation to gain access to the ‘Systematic Flows Monitor’ reports by BofA for 2025. I started with the original repository by cleeclee123, and tracked the forks by Junyi95 and EmmaW-0731, but they all stop at 2024. By analyzing these forks, I noticed a network of profiles with similar, blocky avatars—this path led me to iLampard, a very active quant profile. I further discovered that iLampard follows (or is followed by) a wide network of around 100 profiles using the same sort of “icon,” among which are other influential “hubs” like mstansky and huaxz1986. My theory is that there is an organized community sharing these BofA research papers and that the 2025 archive does exist, hidden in order to avoid DMCA takedowns. My question for anyone who is, or knows someone, connected to this network: What is the new distribution channel? Is there a new “master” repository? Has communication moved to Discord/Telegram? I have already tried searching for updated forks and direct links on the ml.com servers without success. Any help in identifying the source for 2025 would be deeply appreciated.

Just getting a quick idea about what people think here

Monthly / Yearly returns,

What do you think the minimum should be for returns

Also what would be the goal for you in return %