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.
5,922 documents
This research summary argues that factor signals weaken over time, so holding a monthly portfolio unchanged can leave later-period capital exposed to less informative signals. It proposes measuring a factor’s decay speed through the half-life of its…
This forum post outlines the basic workflow of a multi-factor analysis backtest: sort stocks into groups by factor value, buy according to a rebalancing schedule, calculate each group’s returns, and report performance measures. It also notes that…
This article summarizes research on the relationship between U.S. industry portfolio returns and the VIX, an options-derived measure of expected stock-market volatility. It describes analysis of 49 industry portfolios, comparing return characteristics and…
This research summary reviews a study of how U.S. industry returns respond to market uncertainty measured by the VIX and its change. Using 49 industry portfolios over a historical sample, the study compares return distributions and return spreads across VIX…
Gerber statistics offer a threshold-based way to estimate dependence between asset returns. Each return is classified by whether it rises or falls beyond an asset-specific threshold; paired observations count as concordant when both move substantially in the…
This strategy rebalances a portfolio when asset weights move far enough from their targets. It calculates each holding's drift, then sells assets above target and buys those below target. Users specify target assets and weights, choose a drift threshold, and…
This reference explains several ways to measure dependence among asset returns and distance between correlation structures. Distance correlation can detect nonlinear dependence and is zero exactly when variables are independent, unlike Pearson correlation,…
This study examines value, momentum, carry, and defensive factor returns across six asset classes using data spanning roughly a century. It compares each factor’s discovery period with earlier and later periods, using the long history and cross-asset…
The document reviews a holdings-based framework for attributing Spanish domestic equity mutual fund performance to four sources: momentum-related trading, security selection, active market timing, and passive timing effects caused by changing security betas.…
This A-share strategy ranks eligible stocks using year-over-year net-profit growth and total market capitalization. It subtracts each stock’s size rank from its growth rank, favoring companies with stronger earnings growth and relatively smaller market…
This report summary reviews Schroders as an asset manager and describes its investment approach, asset mix, and historical fund performance. It says the firm focuses on asset management, with equities prominent in its portfolios, and reports that many funds…
This forum post documents a user’s difficulty placing repeated buy orders in a BigQuant backtest. The strategy loops over target stocks and submits equal-weight target-percentage orders; some buys return error -108, while later orders in the same loop can…
The document explains how Brinson attribution uses portfolio holdings to separate active return into allocation and security-selection effects. The framework can be applied across industries for equity funds or across broad asset classes for mixed-asset…
This event announcement describes a strategy framework that uses macroeconomic timing to adjust a multi-asset portfolio as markets and economic conditions change. The stated approach is to monitor macro indicators for turning points in the economic cycle,…
This report summary presents a strategic allocation framework that shifts the budgeting unit from asset classes to macroeconomic drivers, aiming to reduce exposure to changing correlations among assets. Principal component analysis is used to derive five…
This code implements a portfolio stage that recalculates instrument positions across dates. For each date, it builds an optimization objective from target contract positions, a covariance estimate, contract values, transaction costs, previous positions,…
This report tracks three China-focused active equity quant portfolios against an active mutual fund benchmark: an enhancement portfolio built from selected fund holdings, a portfolio that filters earnings-surprise stocks, and an enhancement portfolio based…
This study summary describes a low-risk portfolio approach for South Korean equities. It forecasts KOSPI 200 constituent volatility with Gaussian process regression, support vector regression, an artificial neural network, and GARCH, then ranks stocks into…
This brief summary introduces Markowitz modern portfolio theory as a framework for choosing asset weights by balancing expected return and risk. It describes mean and variance as ways to represent asset return characteristics and investor preferences, then…
This competition update reports diagnostics for the highest-ranked factors and tracks a CSI 1000 index enhancement portfolio. Factor descriptions are anonymized: the report gives average style exposures estimated through daily multivariate regressions and…
This research note proposes a two-stage way to use public mutual-fund holdings. First, it selects funds by Sharpe ratio and rebalances the fund basket quarterly. Next, within those funds’ ten largest holdings, it selects stocks with the highest relative…
This discussion post argues that a quantitative trading operation may need to work across high, medium, and low frequencies. It characterizes high-frequency trading as a field with relatively clear technical aims, including reducing latency and improving…
The document presents a monthly long-short residual-momentum strategy for U.S. equities. It describes ranking stocks by risk-adjusted residual returns over the prior 12 months, skipping the latest month, and buying the strongest decile while shorting the…
This BigQuant backtest handler describes a daily portfolio process driven by a date-filtered prediction ranking. It allocates roughly one holding-period fraction of portfolio value to daily purchases during an initial staging phase; afterward, it can use up…