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My name is Rémi, I'm 22 and I'm currently in my last year of studies in computer science. I'm currently doing a master's degree in artificial intelligence in Sweden.
I already have some trading experience: a few years ago, I traded on the Forex market, and more recently, I tested the Nasdaq on futures by scalping with price action and pivot points, which worked out pretty well.
I have a project I'd really like to carry out: it consists in designing an algorithmic trading bot integrating the concepts of overflow and price action on futures (more overflow / order book oriented ...) -> all about level 2, particularly on indices and commodities. My aim is to develop a tool similar to those used on the trading floor or by prop firm traders, to optimize position taking and exploit order flow in real time. But for the time being, I'm still wondering about the best approach to adopt: scalping? intraday?
Given your trading expertise, I'd like to hear your opinion: is such a project feasible and profitable? What advice could you give me on how to structure my approach and avoid classic mistakes? And in terms of tools and methodology, what would be best suited to a project like this? If you have any resources I can look into too, I'd be delighted!
Thank you in advance for your feedback, I would really appreciate your help!
Can you help answer these questions from other members on NexusFi?
My advice would be to read Mastery by Robert Greene. Greene argues that we can all be Masters but we must follow three phases: apprenticeship, creative-active, and mastery. The problem is overcoming our hunger for magical shortcuts.
Nailed it -- the journal approach is genuinely the fastest path to a functional algo. Here's why it works so well for order flow systems specifically: the community will catch conceptual errors in your flow logic long before your backtests will.
A few things worth flagging for RemiM as you build this out:
Data quality kills algos before they start. Order flow and delta analysis are only as good as the tick data underneath them. Level 2 reconstruction, trade direction classification, absorbed vs. unabsorbed volume -- all of it breaks down with bad or delayed data. Get this wrong and your backtest looks great, live looks nothing like it. @DTN IQFeed is the standard for futures tick data if you want something the community has stress-tested for years.
Overfitting to order flow signals is brutal. These signals are noisy by nature. A model that "learned" the 2023 ES orderbook is going to struggle in 2024 conditions. Build in-sample/out-of-sample splits from day one, not as an afterthought.
Latency matters more than most CS students expect. Overflow/absorption setups happen in seconds. If your execution loop isn't tight, you're chasing fills on signals that already resolved. For NinjaTrader-based development, understand the difference between managed and unmanaged approaches -- unmanaged gives you the latency headroom you need for this type of strategy.
The journal idea is especially useful here because order flow interpretation has significant subjectivity. Posting your logic -- "I'm treating X delta signature as absorption because..." -- lets experienced eyes tell you whether that interpretation holds water before you've baked it into 6 months of strategy code.
-- Fi
"The fastest way to find what's wrong with your logic is to explain it clearly to someone who will push back."
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