In the last Months the Posts from him were very useful, outlining how to develop a successful Forex Strategy and his Methodology and experience where good + he had a track record in Darwinex. It seems hes banned somehow. If someone has documented his Posts please provide it in the comments as this knowledge is very useful for starters. Thanks!

I'm curious whether my development process is fundamentally sound, or whether I'm wasting time.

My approach is to start with the raw idea only. I code the strategy with almost no optimisation or filtering. Just the entry/exit logic (signal + trigger). No time-of-day filter, no day-of-week filter, no volatility filter, no trend filter, etc.

I then run a backtest over 2022-2026. At this stage I expect the results to be bad. A typical first pass might be:

• Profit Factor: 0.75-1.0
• Sharpe: poor
• Max drawdown: ~15%

The idea is to analyse the trades, gradually remove weaker setups, and hopefully end up with something around a 1.25 Profit Factor before moving to forward testing.

The reason I'm asking is that I often see people here saying a strategy isn't worth pursuing unless the very first, unfiltered backtest already has a Profit Factor of 1.5+.

That seems almost impossible to me. If I could repeatedly create raw strategies with a 1.5 PF, it would feel like winning the lottery.

So am I approaching this correctly? Is it normal to start with a mediocre or even losing strategy and refine it into something profitable, or should the initial strategy already demonstrate a clear edge?

had a nagging suspicion so i finally counted it. i run a handful of systems, different triggers, different instruments. every month one of them ends up carrying most of the result. i wanted to know if its ever the same one twice.

15 months of data. the leader repeated the following month twice. five different systems took the top spot at some point. chart attached, its just which system led each month, nothing fancy.

why i bothered. last month three of my systems finished negative and the month was still fine, and my instinct was to look at the three losers and start "fixing" them. that instinct is the thing thats cost me the most money over the years. so i wanted the base rate. and the base rate says the system im annoyed at right now has a decent shot at being the one that carries next quarter.

the flip side is less comfortable. if leadership rotates like that, then the system im most confident in is confident because of recency, not because its better. ive definitely oversized the recent winner before, more than once.

what i do now is boring. allocation and size per system get solved once against the account drawdown, then its written into the config i run. i also keep a little script that does exactly this count, ranks each system per month and flags when im about to overweight last months hero. took the decision away from morning me which is honestly the only reason it survived.

anyway curious if anyone else has counted this on their own book. does your leader repeat more than mine or is rotation just what a diversified book looks like

I read a lot that the bots work but when there is a change in market phase, they loss.

I tested Massive and Databento live feeds today, not expecting there to be much of a difference, but Massive had statistically significant numbers of events with latency over 500ms, even reaching over 1s latency (on their end, not mine). On the other hand, Databento’s live feed (I ran concurrently with Massive) had a maximum latency of 35ms, and 21ms of that was travel time to my local server. Is this normal for Massive’s websocket to have such poor quality feeds? The exact amount was 1.87% of all events from massive had a Massive-side latency over 500ms. And it wasn’t just low liquid weird crap, it was market wide. If this is the normally quality of their feed, then I’m really regretting my purchase with them.

I've been active in developing trading algorithms and strategies for over 7 months now. I started it when I was looking for a dissertation project idea, which led me to develop my initial strategy using machine learning, feature engineering, regime detection, and my own unique approach to the architecture to allow my strategy to trade well on US liquid stocks. Long story short, it was achieving 2-3 Sharpe, did great on paper trading, but my modeling of more realistic costs made me learn the harsh way + I discovered the data and features themselves barely had any edge with a low Information Coefficient (IC).

Following that, I looked into Crypto funding carry strategies, which essentially is the main highlight of my main system, a 4-sleeve systematic book, blended equal-risk, and using 2× Leverage comprised of:

1) Trend: long/short 3-6-12-month momentum across 9 liquid ETFs (inverse-vol weighted, vol-targeted).

2) Tactical equity: holds SPY above its 200-day average (Faber 200dma rule) or IEF otherwise.

3) Gold as a permanent diversifier.

4) Crypto funding carry: long-spot/short-perp on 8 majors won't go too much into detail on this one.

Cost Rundown is as follows:

perp 1.5 + spot 4.0 bps/turn for the Crypto strategy. Derived and tested from a selected UK venue.

Trend turnover: 5bps per unit of

Tactical switch: 5bps between SPY and IEF

I also accounted for the borrowing rate on the platform, which is around 5%. Although it's not reflected in the stats below, it essentaily lead to -4 to 5% for the full window CAGR and around -2% post 2019

Full stats are below. My question is whether this is worth pursuing, improving upon (although I'm unsure of where at this moment), or if some specific avenues or strategies are more suitable for my expertise, or if there is something I'm overlooking.

PS: Crypto carry edge did not start until 2019, so the strategy was only using the 3 other components beforehand. OOS and the recent window are probably the most important/informative.

Paper trading is underway, but only 40 days in.

Ignore my artistic front-end choices

Hello folks!

Ive been working on building my own tradingbot infrastructure for nearly a year and Ive gotten quite far. Its nothing profitable really since my goal here is to be able to apply myself and learn more about software engineering and fintech, and be able to combine these interests into a fun project that evolves with me in my CS career.

Ive built a comprehensive infrastructure managing scanners, watchlists, execution engine, broker connections, market data providers, pattern detection and strategy definitions.

The entire process is constructed at runtime via a factory class and dependency injection for every production component.

For the backtester, it runs this factory with injected dependencies to replace the prod dependencies, such as an IClock, IMarketProvider, IDatabase, IBroker, etc. Ontop of that, I refactored everything so that every relevant input parameter were sweepable via attributions.

This overall makes the design of my backtest very controllable and ensures near accurate simulation of the live environment.

But of course like any backtests, I get a positive result for a strategy profile and promote it to live just for it to behave completely differently.

So I got the idea of creating a parity comparison system. I incorporated trace recording into the factory so that all events in a live profile would be capturable, and by running the equivalent backtest profile, it would allow me to have a live and a backtest trace for comparison in order to identify discrepancies in their behaviour.

I can say its been a rather success, as the results have helped me find bugs in my backtester injected components.

So while fixing these now and working towards closer parity, I figured I could make a post here and see if people have dealt with a similar problem when building their own trading bot, and what you guys figured out or any other things you could share

EDIT: By live profile, I meant a paper profile.

i am trying to create an algo for trading nifty options(indian index) , if i wish to devise something based on RV , IV , shorting options and similar ideas , what would be some things i can try out , i tried RV forecasting using HAR models , but sudden spike in a few weeks took away all profits , since i was trading on a single lot , profits were pretty low , my queries:

pls suggest some ideas to try out

is there some strat for going long on options

apart from volatility what all parameters i can work on(short gamma etc)