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
The article presents a speculative outlook for China’s A-share market in 2026. It anticipates a gradual upward market with a spring positioning period, a stronger phase from May through September, and a sharp interim pullback that it interprets as a possible…
This research digest summarizes two distinct topics. For multi-factor index construction, it contrasts a top-down approach, which combines single-factor indexes using assigned proportions, with a bottom-up approach, which optimizes holdings to increase…
The article reviews a basket of Binance USDT perpetual market symbols over 2021 and compares equal-weight buy-and-hold performance with a threshold-based rotation strategy. It normalizes each coin’s price series to its starting value, fills missing early…
The document outlines three ways to explain portfolio results: style analysis using return regressions, benchmark-relative return decomposition, and multi-factor attribution. It describes the data each approach needs, including portfolio and benchmark…
This configuration defines a Qlib equity-prediction experiment for China’s CSI 500 universe. It trains a double-ensemble model built on gradient boosting, using Alpha360 features and a forward close-to-close return label. Training and validation segments…
This tutorial outlines several ways to refine a trading strategy before live deployment. It notes that a signal based on a completed bar may only be acted on at the next bar’s open, while using real-time prices can allow faster entry when a signal appears.…
The document summarizes a study of four MSCI smart beta equity indexes—value weighted, equal weighted, momentum, and minimum volatility—against a market-cap-weighted benchmark. Using monthly returns over 1999–2014, the study applies principal component…
The report reviews the development of Smart Beta index funds in China and compares single-factor strategies in A-shares with counterparts in the US. It describes a Chinese market where offerings are relatively early-stage, commonly single-factor, and held…
This report summary describes a Chinese equity ETF rotation approach built from industry indices with matching exchange-traded funds. It selects 14 industries from the broader industry classification and rotates exposure among their ETFs. The strategy is…
This strategy ranks stocks across mainland China’s A-share market using a small-cap factor and a five-period momentum measure. It combines the market-cap rank with momentum into a composite score, selects the top 50 names, and assigns equal weights. The…
This strategy ranks stocks across mainland China’s A-share market using a small-cap factor and a five-period momentum measure. It combines the market-cap rank with momentum into a composite score, selects the top 50 names, and assigns equal weights. The…
The document explains an optimal-transport approach to measuring dependence between asset return series. It first transforms observations into empirical copula coordinates using normalized ranks, which removes marginal scales while retaining dependence…
The document describes four ways to use the short-side information in high-frequency equity factors when building a CSI 300 index-enhancement strategy. It focuses on factors whose ability to identify weak stocks is stronger than their ability to rank…
This announcement outlines a two-day VeighNa training course on machine-learning cross-sectional multi-factor strategies, also described as alpha strategies. It presents their use in equity selection, index enhancement, absolute-return portfolios, and…
The document summarizes a fund-selection method that combines portfolio holdings and historical returns to estimate predictive alpha. It first screens for funds with enough data and positive performance persistence, then compares candidates pair by pair. A…
The document reviews research on the negative convexity of periodically rebalanced stock and bond portfolios. Rebalancing maintains target weights, but it repeatedly sells assets that have gained and buys those that have lagged. When stocks and bonds move…
This weekly report summarizes several equity factors, including liquidity, momentum, price-volume, growth, and profitability. It says factor performance was generally subdued with a modest overall decline, while momentum was slightly positive and growth had…
This example shows how to assemble a quantitative equity research workflow in Python using Qlib. It initializes Chinese market data, creates a model and dataset from a task configuration, fits the model, and records predictions and signal analysis. It then…
This overview surveys approaches to combining strategies and allocating capital across assets. It traces the progression from fixed mixes and mean-variance optimization to Black-Litterman allocations that incorporate investor views, endowment-style exposure…
This stock-ranking strategy adds recent price-limit activity to a set of price, volume, technical, and financial features. The document explains that the limit-status field uses separate values for limit-down, no limit, and limit-up days; summing the last…
The article presents correlation as a guide to building a diversified trading portfolio. For trend following, it recommends combining instruments with lower correlations so positions do not behave like a single exposure. For pairs trading, it suggests…
The document summarizes research on converting stock factors with strong negative-return associations into a long-only selection process. Because short selling is limited in the A-share market, it describes reversing the use of such signals: remove stocks…
This research summary examines how stock-selection factors with strong short-side performance might still be useful in A-shares, where short selling is constrained. For a single factor, it proposes excluding stocks with the undesirable factor characteristics…
This code defines an objective function for a dynamic portfolio optimizer that chooses integer contract positions. It compares candidate portfolio weights with an unconstrained optimal target using covariance-weighted tracking error, adds trading costs based…