Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
9 documents
The document explains an exponentially weighted moving average crossover (EWMAC) forecast. It subtracts a slower exponential moving average of price from a faster one, then divides that difference by daily price volatility. A positive or negative result…
This code describes a volatility-sensitive adjustment to trading forecasts. It calculates daily percentage volatility, compares it with a rolling ten-year average, and converts the normalized volatility observations into quantile ranks. A multiplier…
This configuration module sets parameters for a fast mean-reversion futures strategy and derives operating bounds for its estimated price range, R. It estimates that range from hourly high-low data: zero ranges are discarded, a rolling average is taken, and…
This introduction shows how to build a futures trading rule and assemble it into a larger systematic trading process. Its example EWMAC forecast subtracts a slow exponential moving average from a fast one, then normalizes the difference by a robust estimate…
The code describes a portfolio-wide risk overlay that scales all positions by a shared multiplier between zero and one. It computes separate multipliers from normal risk, volatility-shock risk, aggregate absolute risk, and leverage, then applies the lowest…
This configuration describes a futures trading system that estimates forecasts from several exponentially weighted moving average crossover rules and a carry rule. The EWMAC rules pair faster and slower lookback periods, while the carry forecast uses…
This configuration describes a multi-asset systematic trading framework that combines rules for breakouts, relative and absolute momentum, moving-average trends, carry, acceleration, and skew-related factors. The rules use multiple horizons and include…
This position-sizing stage converts a combined trading forecast into a subsystem position. It scales the forecast by an average position size derived from the account’s daily cash volatility target and the instrument’s volatility, then normalizes by the…
This document describes a raw-data stage in a futures trading system that prepares reusable price and carry calculations for later forecasting. It retrieves daily, natural-frequency, and hourly prices; computes absolute daily and hourly price changes; and…