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 weekly report presents diagnostics for the ten highest-ranked anonymous factors in a Chinese quantitative research competition. It describes average style exposures estimated with daily multivariate regressions and average industry-level Rank ICs, the…
This document lays out an ordered process for adding a strategy to a live trading system or replacing an existing one. It covers preparing instrument data, confirming a working backtest, configuring strategy and control files, implementing custom backtest,…
This literature digest covers two topics. The first evaluates asset-pricing factor models using the maximum squared Sharpe ratio. It describes comparisons among nested models, from CAPM through three-, five-, and six-factor specifications, and non-nested…
This Chinese-language research summary describes a top-down framework for institutional fund allocation that connects macro asset views with strategy and product selection. It argues that asset allocation recommendations need to flow through to specific…
This strategy maintains an equal-weight portfolio of Bitcoin and Ethereum using daily checks and monthly rebalancing. At each rebalance, it estimates target quantities from current portfolio value, divides value evenly between the two assets, and submits buy…
The document reviews research on whether crowded mutual fund ownership predicts subsequent stock returns. It defines stock-level crowding as active mutual fund ownership divided by average share turnover, using lagged holdings and turnover data. Stocks are…
This configuration describes a Chinese equity forecasting experiment using Qlib’s Alpha158 features and an LSTM model. It selects 20 features, applies robust feature normalization and missing-value filling, and ranks labels cross-sectionally. The prediction…
This research report presents Qualified Domestic Institutional Investor funds as an accessible route for mainland Chinese investors to gain overseas exposure. It argues that international assets can diversify portfolios because their returns may be less…
This overview introduces artificial intelligence as the design of systems that make decisions or predictions, including methods such as machine learning and probabilistic reasoning. It explains why these methods can help with complex tasks involving many…
This talk connects volatile Chinese markets with plentiful liquidity, scarce investment assets, and changing market structure. It contrasts China’s active market cycles with the speaker’s account of increasingly competitive US markets, and argues that…
This research summary adapts the Merrill investment clock to Chinese A-shares by grouping sectors according to their economic-cycle behavior and proposed roles across recovery, overheating, stagflation, and recession. It describes two index families:…
This recap presents four trading scripts developed by participants in an educational program. The examples include a portfolio that rebalances equally across assets, spot–perpetual arbitrage that opens positions when the price spread exceeds a threshold and…
This introduction defines an algorithm as a set of explicit, consistently followed rules for trade entry, exit, sizing, and risk management. It contrasts discretionary, rule-based, and hybrid trading, then describes two potential advantages: control over…
This report describes three Chinese active-equity portfolios designed to outperform active stock funds. The fund-enhancement strategy selects funds by performance tiers, reconstructs their holdings, and optimizes a portfolio while limiting deviations in…
This report tracks three Chinese active-equity strategies against an active-fund benchmark and describes how each portfolio is constructed. The fund-enhancement approach selects funds using performance tiers, builds a holdings-based universe, then optimizes…
This report explores whether stocks held together by investment funds form a useful relationship network. It offers two explanations: shared holdings may reflect common traits recognized by fund managers, and co-owned stocks may respond similarly because…
This performance note describes Haitong’s broad-market multi-factor portfolio, which scores Chinese stocks using factors related to company size and trading behavior. It selects the 100 highest-scoring stocks for an equal-weight portfolio, with holdings…
This tutorial explains how to prepare data and use Alphalens to evaluate cross-sectional alpha factors. It distinguishes factor research, which tests whether relative signal values predict later returns, from trading strategy evaluation, which also needs to…
This report summary outlines a regime-based approach to multi-asset allocation. It uses historical averages or filtering methods to estimate whether macroeconomic indicators are rising or falling, then compares asset-class returns across those trend…
The article uses simulations to argue that a strategy with a modest standalone Sharpe ratio may still add value when its returns have low correlation with an existing portfolio. It models twenty daily signals with an annualized Sharpe ratio of 0.6, varies…
This bot outlines a disclosure-driven copy-trading process based on a member of Congress’s reported stock and call-option holdings. A research agent reads annual and transaction reports, reconstructs current holdings, and ignores filings dated after the…
The document summarizes research on how macroeconomic conditions relate to cyclically adjusted price earnings ratios and stock returns. CAPE smooths earnings using a long inflation adjusted history, which can make it informative about long horizon returns…
This LumiBot example uses a team of agents to build a basket from leveraged long and inverse ETFs, with SHV as a cash-like fallback. Separate agents assess growth, inflation and rates, and debt and liquidity. A fourth challenges their conclusions, and a…
This example describes an automated multi-agent strategy that selects among leveraged long and inverse ETFs, with a short-term Treasury fund as a cash-like fallback. Specialist agents assess growth, inflation and rates, and debt and liquidity using…