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A user asks why a BigQuant query for Ping An Bank returns values in the thousands when the stock trades around the teens. The supplied workflow selects the A-share instrument, then builds a forward label from the close five sessions ahead divided by the next…
This report summary examines whether separating overnight returns from intraday returns can improve equity reversal factors in China’s A-share market. It links the market’s T+1 trading convention with a possible low-open, rising-intraday pattern that may…
This research summary argues that a fund’s track record can mix the results of successive managers, obscuring changes in style and investment approach. It proposes constructing a separate index for each manager from funds solely attributed to that manager,…
This article argues that training one stock-selection model on all market data may struggle with noisy observations and changing factor behavior. Its proposed approach is to classify market conditions and maintain strategies suited to different regimes:…
This report describes a Chinese equity risk model built on a standard multifactor framework and informed by the Barra approach. It estimates stock return covariance through factor return covariance and specific return variances. The model adjusts these…
This post outlines an A-share stock-selection framework that uses eight cross-sectionally ranked features covering valuation, momentum and reversal, and liquidity. A LightGBM regression model predicts relative returns over a five-trading-day horizon; the…
This research summary compares ten equity valuation measures, including book-to-price, earnings-to-price, sales-to-price, dividend yield, growth-adjusted earnings multiples, cash-flow yields, and EBITDA relative to enterprise value. It describes what each…
This note reconstructs a Chinese ETF rotation strategy that selects a small pool of relatively uncorrelated assets, including equity index ETFs and gold. Every five trading days, it compares each fund’s 20-day return, holds the strongest when that return is…
This research note examines whether intraday stock market snapshots can support factors for stock selection. Snapshot data records prices, volumes, trade counts, and order-book quotes at regular intervals; the note contrasts it with trade-by-trade data and…
This overview surveys several ways to rank or select equities using quantitative models. It groups approaches into factor and risk models, statistical methods, machine learning, macroeconomic inputs, and behavioral signals. Examples include combining value,…
The study examines whether WTI crude futures trading before weekly US Energy Information Administration inventory releases is consistent with informed trading. It compares announcement outcomes with analyst expectations and analyzes intraday prices and…
The article introduces random forests as an ensemble of decision trees and explains how bootstrap sampling and random feature selection create diversity among trees. It reviews classification and regression trees, impurity measures, pruning, regression…
This report summary describes two models for China’s nonferrous metals sector: macroeconomic and industry-data timing for the sector, and multifactor stock selection within it. For timing, it uses mean t-tests to identify candidate indicators for both…
This research review examines whether actively managed U.S. equity funds can generate CAPM alpha without weakening the coskewness of their returns with the market. It explains why investors who value positive skew may care about coskewness alongside…
This article explains factor investing as the practice of expressing a market hypothesis in a measurable rule, rather than focusing first on programming. It distinguishes factors used to select securities from those used to time trades. To illustrate the…
The note introduces quantitative investing as a standardized process that uses data, mathematical rules, and a model to make investment decisions. It contrasts this approach with discretionary stock selection based on personal feelings, describing how a…
The article sketches a basic intraday T+0 approach for a stock expected to move within a relatively narrow range for some time. It proposes setting a price-amplitude threshold and making frequent small-lot trades to capture gains from oscillations. The…
This study examines how analyst coverage and earnings forecast revisions relate to the negative association between idiosyncratic volatility (IVOL) and future stock returns in Chinese A-shares. It measures IVOL from residual volatility in a Fama–French…
This weekly report summarizes several Chinese equity strategies for May 2018, including multi-factor index enhancement, short-horizon price-volume, AI stock selection, Smart Beta, event-driven selection, ESG, similarity matching, and an R-breaker trading…
This announcement describes the launch of a collaborative factor research group and outlines how participants will share and preserve their work. The organizers propose regular progress summaries, periodic research reports, and presentations, with factors…
This excerpt analyzes how China’s carbon-reduction targets and global renewable deployment could create work for construction companies in power generation, storage, and grid infrastructure. It describes engineering opportunities in wind and solar projects,…
This research summary examines whether intraday data can improve sector-rotation signals, focusing on realized skewness and the share of volatility attributable to downside moves. It describes constructing these measures from high-frequency observations and…
The document reviews Chinese A-share stocks with very large gains from two perspectives. First, it surveys high-return stocks by year since 2009 and considers market conditions, company size, recent listings, and corporate restructuring as possible…
The document defines industry leader stocks as companies with strong analyst coverage and fundamentals that are closely related to those of other firms in their industry. It reports that analysts tend to cover more heavily companies whose fundamentals move…