MesoSim – DSL for Options Trading

Hacker News

Hello, I quit my engineering job in 2021 to fully focus on trading. After a year of limited success with stocks (algos floating around break-even) I started studying Options. It turned out that selling options (risk premia harvesting) is a sound approach for income generation. Back in the day there were no suitable automated backtesters to effectively study these trades, so I built one: I infused JSON with Lua to create a Job Definition which models how Options Traders build, adjust and hedge their positions. Fast forward to today, many retail traders and small hedge funds are using MesoSim on a daily basis. They executed over 120k backtests with strategies frequently reaching (and exceeding) Sharpe Ratio of 3. You can also try it after a free signup I'm doing my best to provide educational material via blog posts on public income trades, such as: - The weekend effect: https://blog.deltaray.io/the-weekend-effect - Volatility Hedged Theta Engine: https://blog.deltaray.io/volatility-hedged-theta-engine - NetZero Trade: https://blog.deltaray.io/netzero-trade - and more under our strategy library: https://github.com/deltaray-io/strategy-library As of today the live part is running as a private beta and targeting to fix the annoyances around these complex instruments. Tech details: The solution is created using C# with Blazor as I prefer not to touch JS or TS. When I started I knew very little about C#, and nothing about blazor and dotnet (I'm a linux person). I have no regret choosing these technologies. During the process I also fell in love with Lua, a language I'll definitely use in the future. Please check it out and let me know what you think. Thanks for your kind feedback!

Visit product View on Hacker NewsNov 24, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: trading, education · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos

17%17% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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