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Some python education (when backtesting goes wrong)

Hi everyone, I recently made a post about insider performance highly outperforming real performance by crazy amounts. While this is still true, I want to highlight a bug that made this way higher than it should’ve been. Hopefully this also helps those of you that are interested in programming and backtesting your own things. Basically, to do this backtesting I was pulling the tickers from my database, sorting and filtering, then getting the long term

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Weekly recap for the alerts at insidertradingalerts.ai (5% gain this week)

Hi everyone, Posting my weekly recap here as the backtest of the insider trade following available on my website. This assumes buying at open and selling at close the day after the stock is alerted. As usual, note that this may not reflect real returns due to spreads, delays, and possible issues in my backtest code that I am not aware of. that being said, here was this weeks performance: TLDR: 5% return this week.

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REZI – Long Term Alert (How insiders have returned 1700%, and climbing)

Hi everyone, Today I want to highlight a stock I’ve posted on here about once before, REZI. 3 months ago, I posted about how insiders beat the return of the stock already: https://www.reddit.com/r/InsiderTradingAlerts/comments/1l1885w/rezi_how_insiders_didnt_lose_on_trading_their_own/ When I posted it, the stock was at 22 dollars. It is trading at 33 as of today, a 50% rise. How did I know to look at this stock? Easy – I compared insider returns when buying to the return of

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CARVANA – Unusual insider trading (why following insider trades is so important)

So in the development of some of this long term algorithmic stock identification stuff I had just posted about, one of the top “scoring” stocks was CVNA. Once thought to be dead, the company’s stock has postede an incredible turn around. And who would’ve known? The CEOs and Directors! So I plotted the buys and sells from my database against the stock price, and it’s incredible. To put some numbers to this: The stock appreciated

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