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 brief project note reports a modification to an existing quantitative strategy: market capitalization was added to the scoring process and return on equity was removed. The author says the backtest improved after the change, but provides no performance…
The report introduces a Barra-style multi-factor risk and return attribution model for Chinese equities. Its central idea is to explain the returns and risks of many stocks through a smaller set of style factors, making portfolio exposures easier to analyze.…
This explanation defines an asset’s exposure to a factor as its sensitivity to that factor’s returns. It illustrates the idea with a value factor: filter a broad A-share universe, sort stocks by price-to-earnings ratio, and form a long-short portfolio from…
This BigQuant help exchange explains how to select a fixed number of records after ranking a stock universe. The question concerns approximating a CSI 1000 universe when a direct index-membership filter is unavailable and usable daily constituent data is…
This configuration describes a Qlib experiment for CSI 300 equities using a LightGBM regression model. The dataset combines daily features with intraday one-minute data resampled to a daily frequency through a custom handler. The configured label frequency…
This research summary outlines a strategic allocation model that maps Chinese equities and bonds to underlying macroeconomic risks. It uses principal component analysis to define five factors: economic growth, interest rates, credit, term spread, and…
This brief presents a market review for Chinese A-shares during March 23–27, 2020, alongside a report title stating that the strategic long stance remained unchanged. It lists the strongest and weakest industry groups for the week and tracks several breadth…
This advanced tutorial section is intended for readers already familiar with FinRL or its market simulation companion, or who have worked through introductory notebooks. It points to a comparison of three deep reinforcement learning libraries supported by…
This document outlines a simple Chinese A-share strategy that ranks stocks by return on equity and selects the ten highest-scoring candidates. It describes filtering out special-treatment stocks, suspended shares, recently listed companies, and Beijing Stock…
This BigQuant example builds a mainland Chinese stock portfolio by screening for eligible main-board shares and excluding suspended, ST, and recently listed names. It requires positive trailing earnings and dividend yield, caps float market capitalization,…
The article describes a China A-share screening rule that selects main board companies with MACD above its zero line, a daily price gain greater than 1%, market capitalization below 10 billion yuan, and no losses. It presents the conditions as a combined…
This report surveys asset-allocation approaches grouped by their inputs: mean-variance models, risk-allocation models, and subjective methods. It expresses several optimization-based risk models, including mean-variance, risk parity, and maximum…
This example selects stocks from the Chinese equity market using dividend yield, share price, and circulating market capitalization. It first keeps the highest-dividend-yield quarter of the market and stocks priced below 10 yuan, then excludes certain…
The example outlines a periodic rebalancing strategy for a portfolio held across exchange markets. It tracks each asset’s quantity and estimated value, compares that value with a target share of total portfolio value, and places a buy or sell when holdings…
This guide explains how unit-root and cointegration tests can help identify mean-reverting combinations of asset prices. It presents the Augmented Dickey–Fuller test as a test of whether price changes depend on the current level, and relates the estimated…
This Chinese-language report reviews the development of China’s quantitative fund industry across three periods: before 2010, 2010–2015, and 2016 onward. It outlines a strategy landscape spanning market-neutral equity, index enhancement, quantitative stock…
The article reviews a historical-data study comparing value averaging (VA), dollar-cost averaging (DCA), and a randomized contribution schedule across equity, gold, and commodity indexes. DCA invests a fixed amount at regular intervals. VA instead sets a…
The document outlines six assumptions used to simplify asset pricing theory, especially the Capital Asset Pricing Model: competitive and efficient markets, no taxes or transaction costs, risk-averse investors, shared expectations, normally distributed…
The research note describes factor-mimicking portfolios (FMPs) as an alternative representation of alpha factors, with conversion between the two under a given stock covariance structure. It argues that linearly combining alpha signals corresponds to…
This algorithm allocates among five ETFs representing US stocks, foreign stocks, bonds, real estate, and commodities. It ranks them by trailing 12-month rate of change, selects the three with the strongest momentum, and assigns them equal portfolio weights.…
This strategy ranks a universe of country equity ETFs using Shiller’s cyclically adjusted price-to-earnings ratio (CAPE), which compares inflation-adjusted prices with a ten-year average of inflation-adjusted earnings. At each year-end, it selects the…
This Chinese-language research roundup summarizes three studies from overseas literature. The first presents a numerical simulation approach for approximating American option values, with potential application to pricing domestic convertible bonds. The…
This 2020 investment analysis discusses the ChiNext index and Bosera's ETF tracking it. It argues that refinancing policy changes and the stock registration system could improve financing access for technology and growth companies. The index is described as…
This report reviews equity factor performance, emphasizing a February 2018 snapshot and trends over a longer historical period. It compares factor information coefficients, which measure association with subsequent returns, and market neutral long-short…