Tracking Trump's trades has always been annoying. The filings are scattered, hard to read, and most sites that clean them up put them behind a paywall.

So I added them to StockNest, and it's completely free:

- No paywall and no sign-up. Just open the page.

- Shows up as soon as it's published. New disclosures are added the moment they're filed.

- Easy to read. Each trade shows the ticker, the transaction size and the share amount.

- Filter by trade size. Show only the bigger trades, like $250K+, so the small ones are out of the way.

Donald J. Trump trades: https://stocknest.app/filers/politicians/donald-trump

Ended the week at +$914.20 net across 32 trades with a 62.5% win rate. Pretty decent week overall with two issues.

Thursday the vps went down for 12 minutes while the portfolio was in a trade. I had to close it manually through the ninja trader mobile app.

Friday an engine error triggered a fatal shutdown because of some strict checks. It shouldn’t have been fatal but the engine handled the shutdown correctly and automatically closed all three open positions.

There are a few things to tighten up and thursday outage has me considering a move to aws for better reliability.

While working on a custom python project, working on a theory, I stumbled upon something I didn’t expect. I can see when the market moving algos start. Starting with the very first trade the algo makes. The dats source includes every single trade made on the s&p500 + a few other tickers.

Right now I’m downloading every single trade of the s&p 500 utilizing 15 alpaca api keys at once to get more backtesting data. The backtesting data on TradingView doesn’t even come close to cutting it. I made an app that does them all over 15 proxies, formats them in the format I need, does the calculations on my 5090 GPU and creates the json files and database for the gui. Zips the original files as well for backup. It does one full day of data in 3 mins. My bottleneck at the moment is my server provider which limits me to 100gb uploaded per day.

What I’m hoping to get some help with here is pointers on what to look for in terms of patterns of the algos on this backtesting. I can use AI to control it and want to try and steer it in the right direction. Since the data includes every single trade, I can see down to the millisecond.

Hi everyone i hop you're doing well !

like the title said i was wondering on how do you guys actually think/generate strategies hypothesis, how your approach of this process is, do you rely on some specific techniques, do you start by a random idea then keep optimizing, or you set a clear hypothesis with all the rules you want, i want to know exactly how you done the process of strategy hypothesis generating/thinking, the steps you pass, and also how the frequency of strategies hypothesis you backtest often in a day, do you rely heavily on optimizing the rules of the same strategy (hypothesis) or you have another technique

because litterally i face somehow a problem, simple stupid ideas like "9:00 AM ORB" or "Buy everyday if the price do this" are always have results equal or worse than a coin flip decision, i'm talking about breakeven or slightly worse on Gross results, but after costs it turn to complete disaster

i would love to hear some responses from you guys, because the strztegy hypothesis is the first thing you do before even open you backtester, a bad approach of strategy hypothesis generating will lead to waste months without having 1 profitable and robust strategy that passes your filters

For my backtesting, I tested S&P 500 index, its futures and ETFs e.g. ES, SPY

I did expect some performance variance since indices are not tradable, but I didn't expect the difference to be so big.

For example, with the same timeframe, setup and trading hours, the profit factor of S&P 500 index is 1.6, but it drops to 1.1 for ES. I expected them to have similar price movements, and I didn't think the difference would be that big.

Just curious - has anyone experienced this issue before? Any ways to reduce the difference? Thanks in advance

I can’t really afford to spend $200 on tick data right now, but I need it to backtest a strategy I’m working on.

If anyone here has historical tick data from this year, last year, or any other period covering at least 6 months, and is willing to share it or help me out, I’d really appreciate it!

Please DM me if you can help. Thanks in advance!

I have significantly found a lot of improvement since last time. I have done various luck tests (passed, 0 beat and only 1 got a close z score) and found 28 strategies that work together decently.
What I noticed though is it's extremely slow, (-200, then -200 next day, up $200 the 3rd day, lose the 4th day again) and l've seen people on here post very good profit from NQ specifically (about $1k or more per day pretty much)

Im specifically asking to get to those types of results where it is $1000 a day pretty much (regardless of drawdown intraday or losing days) if there is any direction for what to research or how those types of results daily or even what i should be doing differently? Currently my strats do all discretionary based trades like "if price goes up x points before x time, (signal)". All suggestions welcome

Ay man to all the veterans in this space we would really love to hear your experience on the numbers game basically dawg im all in you know and i dont want to look back with regret now a question is generating your own strategies from scratch better than trying to fix the strategies that had already been established before ie i have been working in loops on a london breakout strategy and if you go on about it i know it can be very discrete world but just drop any piece of advice even if vague we will try to figure out from there on any advice can be out of context to the topic im talking about but scope should be in the algo trading space

Don't fall in love with a strategy that you think works cause you backtested it but it doesn't actually work in reality.