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 note proposes a simple screen for Chinese stocks associated with the metaverse theme. It selects companies with a circulating share count no greater than 5.5 billion and a share price around 18.5 yuan; the sample code uses a price interval from 18 to 19…
This report reviews the relative performance of Chinese quantitative equity funds and considers what rising assets under management mean for strategy design. It attributes the period’s advantage for index-enhanced and quantitative long products largely to…
This research summary presents asset allocation as a continuing process: define investor objectives, set an investment strategy, implement it, and review performance. Objectives specify the desired return, acceptable risk, and other investor needs. The…
A BigQuant forum question asks how to select the ten stocks with the strongest return over the previous calendar year on the first trading day of a new year. The user’s current approximation compares prices about 250 trading days apart, but they want a…
This report reviews Chinese market and exchange-traded product developments for the week of March 30 to April 3, 2020. It summarizes moves in domestic equity indexes, bond yields, precious metals, currencies, and traded ETP categories. Equity and…
This post discusses portfolio risk measurement and argues that return volatility and Value at Risk do not capture losses beyond their usual thresholds. It proposes Expected Shortfall, also called ES, to measure extreme losses in the tail beyond a confidence…
This literature summary describes a stock-market return forecasting method that decomposes returns into dividend yield, profit growth, and price-to-earnings multiple growth. It says the source study uses the different time-series properties of these…
The document explains how to decide whether to remove sector exposures from equity factor portfolios. It splits a stock characteristic into a within-sector component, which ranks companies against peers, and an across-sector component, which captures…
This strategy maintains a portfolio split between a broad US stock ETF and a long-term Treasury ETF. It targets a 60% stock allocation and 40% bond allocation, checks prices daily, and submits trades to move holdings toward those weights. The code schedules…
This article presents a broad framework for choosing and assessing quantitative trading strategies. It recommends matching a strategy to an investor’s temperament, available time, preferred trading frequency, capital, programming skills, and goals. It argues…
This document summarizes two external research papers. The first concerns allocating capital among private fund strategies within a fund-of-funds portfolio, using multi-objective linear programming to derive allocation weights. The second examines the ratio…
This overview presents basic ways to assess broad equity-market conditions and limit portfolio exposure during potential declines. It describes moving-average crossovers as timing signals, with a shorter average crossing above a longer one treated as bullish…
Risk parity allocates portfolio weights so that assets contribute more evenly to total portfolio risk, rather than assigning capital according to expected returns or equal dollar amounts. The document outlines a workflow: estimate asset volatilities and…
This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…
This review surveys three directions in factor investing: refining established factor methods, incorporating new data and models, and using factors as a basis for asset allocation. It describes improving value signals with multiple valuation measures,…
The document explains backtesting as the simulation of a strategy on historical market data to assess returns, risk, and stability. It outlines a workflow from obtaining and checking data, coding rules, and setting dates, capital, fees, and slippage through…
The report argues that ranking fund managers can reduce redundant information when one manager oversees several similar funds. It proposes tracking manager style across market capitalization, value versus growth, industry concentration, individual-stock…
This document explains an index trading mode that maintains a portfolio across a configured set of cryptocurrencies. When the bot starts, it checks which assets are held and their portfolio weights. If an asset is missing or its weight differs from the…
This research summary presents cash-flow duration as a framework for understanding why equity characteristics such as value, profitability, investment, low beta, and dividend payout are associated with returns. Duration measures the timing of a company’s…
This article presents a multi-asset allocation framework that combines traditional asset selection with allocation to systematic factors. It maps macroeconomic variables and style factors to asset classes, estimates exposures with time-series regressions,…
This research note discusses how to turn equity alpha signals into portfolio forecasts and combine multiple factors. It suggests converting factor z-scores into expected returns using average results from repeated cross-sectional regressions, and favors…
This article discusses practical decisions for running systematic strategies live, including how to enter a system initially, define the active futures contract during roll periods, choose markets, manage capital, handle outages or unexpected events, prepare…
This Qlib documentation describes a workflow for generating, storing, training, and collecting multiple research tasks. A task can include a model, dataset, and recorded outputs. Task generators such as RollingGen can create tasks for different date…
This overview introduces risk parity as an asset-allocation approach and places it alongside the classical mean-variance framework. Mean-variance optimization seeks portfolios that maximize expected return for a given risk level or minimize risk for a target…