Live 14-day $SPY OHLC view + daily vote distribution for the MRE v0.6 engine.
Since upgrading the Arsenal chart output to show a deeper understanding of the signal, I thought it might be useful to have the same approach for the MRE engine.
On the “2YR History” tab inside of the members area you will now see some additional information regarding the current state of the MRE along with last two weeks of price action (for $SPY).
The bottom panel shows how the votes are evolving overtime and more importantly, “(locked 13d)” will become significant once we get to a point where there might be a material regime shift.
The engine uses a symmetric 7-day hysteresis to confirm any regime change (including same-side flips like Reflation → Goldilocks). The practical impact only shows up on risk-on ↔ risk-off transitions, but the state machine is regime-aware, not side-aware.
This avoids (most) false signals and chop. It sits on the Pareto frontier and is the Sharpe-maximizing point, I’ve tested asymmetric configurations and none of them improve on it without giving up upside.
What this means in practice: If we were to get a massive shift in bearish votes as of tomorrow mornings output, it would take 7 consecutive days of the same bearish regime (Inflation or Deflation) holding to confirm the flip.
This is important to understand and it’s a critical path to how the system operates.
Here is where to find the updated chart:
You can also download a snapshot of the latest PNG by using this button:
I’ve been working on a side project to kill boredom. Most of you already know the hardships I went through when porting my original MRE version out of TradingView (PineScript) and into Python.
Well I’m trying to simplify that for other folks that might want to do the same thing, along with some clever bells and whistles.
This is available for free, it’s a Github repo that will let you currently:
Import a TradingView trade log (from a strategy backtest) and confirm the actual numbers along with any warnings about the strategy. It includes proper max-drawdown figures, intraday max-dd, sharpe, sortino, calmar, etc.
Import a simple PineScript strategy and convert it to Python for independent analysis, improvement & forward-testing.
The next version will use an LLM to aid in the conversion process once I’m done scaffolding out the numerous PineScript available functions.
You can follow along here: https://github.com/durdenbtc/survival-alpha
If you have a Github account, I’d hugely appreciate a star!
— Durden out.
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Disclaimer: This content is for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any asset. Trading equities and futures involves substantial risk of loss, including the potential for loss exceeding your initial investment.
Past performance, whether backtested or live, does not guarantee future results. Backtested performance has inherent limitations: it is designed with the benefit of hindsight, does not reflect actual trading, and does not account for all factors that may affect real-world execution.
The author is not a licensed financial advisor. Always do your own research and consult a qualified financial professional before making investment decisions. You are solely responsible for your own trading decisions.
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