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.
22 documents
This analysis asks whether futures with more negative return skew earn higher returns, both across assets and when skew changes over time. It estimates skew from percentage returns after filtering extreme volatility-normalized observations, then uses…
This guide walks through a hand-built method for allocating a long-only portfolio across assets or trading strategies. It groups assets hierarchically, assigns volatility-based weights within groups, and can optionally adjust for estimated Sharpe ratios and…
The post develops a framework for thinking about the compensation investors should require for taking on risk, focusing on standard deviation and skew. It evaluates investments by geometric growth or final wealth at selected points in the return…
The post compares a stateless trend-following approach with trade management that changes as a position develops. It describes a test system using a moving average signal, volatility-scaled positions, and stop losses. Dynamic volatility control resizes…
The document describes how to add a risk overlay to a systematic futures strategy and where to place it in a process that uses dynamic position optimization. The overlay scales unrounded target positions by a multiplier, while separate controls address…
The document compares four moving-average crossover approaches on a diversified futures portfolio: fixed-size systems with stop or signal exits, a binary system that adjusts exposure for volatility, and a continuous forecast system that also targets…
The document considers whether volatility targeting improves a trend-following strategy. Its motivating example is a long position that gains as price rises but is reduced because the position’s risk has increased. The author notes that trend following often…
The document discusses several systematic trading ideas. It frames short volatility as harvesting the gap between option-implied and expected realized volatility, using short volatility futures with a constant negative forecast and volatility-based position…
The document compares Average True Range (ATR) with standard deviation as measures related to market movement. Standard deviation is based on close-to-close returns and centers observations around their average, then squares deviations before averaging and…
The document explains positive skew as a return pattern with frequent small losses and less frequent large gains, then examines whether trend-following strategies display that pattern. It relates trend following to a lookback straddle: both can benefit from…
The document describes a systematic overlay for reducing a trading system’s positions when estimated portfolio risk rises above chosen limits. It starts by comparing realised portfolio volatility with expected risk and argues that expected risk can vary…
The document outlines a test of whether trend-following strategies perform better in less liquid futures markets, or whether any apparent advantage comes from diversification. It frames three possible sources of CTA outperformance: stronger pre-cost returns,…
The document models daily-reset two-times long and short leveraged ETF returns by multiplying each day’s underlying return and compounding the resulting daily values. It includes annual management, spread, and commission costs, then uses Gaussian daily…
The document frames stop losses as one part of a broader risk process. It describes a trailing stop that moves upward as a position reaches new highs, with the aim of limiting the amount of accumulated profit that can be given back. The examples are…
The article tests whether trading rules should adapt as volatility changes, using historical volatility divided by its rolling ten-year average to classify market conditions. It compares momentum and carry rule performance across volatility groups, then…
The post investigates why strong risk-adjusted trading forecasts can have weaker subsequent outcomes than a linear relationship would imply. Since forecasts divide expected return by recent volatility, a strong signal can reflect unusually low volatility as…
The post compares two ways to estimate volatility: standard deviation of percentage returns and standard deviation of absolute price changes. For futures, it recommends forming percentage changes with back-adjusted price differences in the numerator and the…
This article tests whether recent volatility levels relate to next-month risk-adjusted returns across futures markets. It builds a relative-volatility measure by dividing estimated volatility by a long-run exponential average, then compares next-month…
The document examines whether improving volatility forecasts is worth the effort when volatility estimates are used to scale trading positions inversely. It contrasts basic estimates based on recent realized volatility with more involved approaches,…
The document presents risk management as a repeatable cycle: identify important risks, choose measurements, define thresholds and responses, monitor conditions, and reverse interventions when conditions normalize. It distinguishes market, counterparty,…
The post asks whether the VIX level predicts stock prices or volatility. It reports that average stock returns appear similar across the compared VIX conditions, while the return distribution is wider when spot VIX is high. It also notes more negative…
The document examines whether return distributions can help explain or forecast asset performance. It distinguishes comparisons across assets from time series tests asking whether an asset’s current skew or kurtosis predicts its later returns. The reported…