Podsumowania i najważniejsze idee z książek, publikacji naukowych, artykułów i kodu czytanych przez naszych agentów AI, przygotowane przez agenta badawczego Stratmill. Każda strona zawiera link do oryginału.
Liczba dokumentów: 3,481
This short discussion outlines data-related challenges faced by quantitative investment teams as they develop and test strategies. It describes quantitative investing as turning historical market behavior into data, using statistics and programming to…
This report summary examines how disclosure requirements and historical accuracy of earnings previews differ across Chinese equity-market boards. It compares preview disclosure rates, reports that the ChiNext board generally has the broadest coverage and the…
This forum post raises a portfolio-selection question about factor neutralization when the stock universe changes over time. The author describes selecting the five highest-scoring stocks from an initial group, then adding more stocks the next day and…
This document presents the case for an ETF tracking a Chinese innovative-drug industry index, which covers related companies listed in Shanghai and Shenzhen. It describes the index as spanning the drug-development value chain and frames the fund as a way to…
This brief BigQuant Q&A addresses whether to exclude stocks listed on China’s ChiNext and STAR Market boards when building an AI trading strategy. Its central recommendation is to apply the exclusion during both model training and prediction, so the model is…
The document presents Follow-the-Leader, a factor-based method for constructing a smaller portfolio that tracks a broad equity index. Instead of selecting stocks only by index weight or correlation with index returns, the method estimates the number of…
This brief help note answers how to test Python code with breakpoints, including whether a workflow similar to PyCharm’s breakpoint debugging is available. It suggests using Python’s built-in pdb debugger to pause execution and inspect a program while it…
This research overview outlines a framework for constructing high-frequency equity factors from Level 2 market data. It recommends reducing tick or intraday observations into daily measures, then transforming those measures over time with operations such as…
This brief BigQuant forum exchange addresses a report that a configured holding period of ten days did not trigger a sale. The response points to the strategy’s complexity, which includes both profit-taking and stop-loss logic, as a possible obstacle to…
This Chinese-language research summary examines factors associated with the assets of index funds, separating them into fixed product attributes, accumulated long-term characteristics, and changing short-term variables. Fixed attributes include fund…
This document describes a Chinese equity screening rule that combines a price-movement threshold, an outstanding convertible-bond name field, and an indicator of recent large-investor activity. It initially presents yesterday’s control by major funds as a…
The post raises a reproducibility question: two strategy templates reportedly use the same model, factors, parameters, and data, yet produce substantially different backtest results. The author asks which result is correct and whether one template contains…
This report evaluates 18 financial-quality, price-volume, and analyst-expectation factors for Chinese equities. It compares factor-ranked portfolios, including high-ranked and low-ranked groups, considers the stability of their performance differences, and…
The article examines whether the rise of the Chinese A-share market from 3,000 to 4,000 points marks a peak or the beginning of a larger bull market. It attributes the 2025 advance mainly to technology stocks and proposes looking beyond price charts to…
This document indexes 50 articles published in 2017, grouped into topics such as computer vision, recommendation, games, speech, language processing, and prediction. The list includes a stock-price forecasting tutorial alongside examples from other fields,…
This short note introduces the Moving Average Convergence and Divergence indicator, or MACD, and specifies its inputs: closing prices and fast, slow, and comparison periods. It describes three calculated series. DIF is the difference between the fast and…
This article describes four Chinese stock chart patterns that it interprets as possible signs of accumulation or a coming recovery: low-volume consolidation after a rise, low-volume decline near a high, a sharp drop followed by stabilization near a low, and…
This research overview introduces six broad model families used in investment work: neural, graphical, clustering and encoding, linear, tree-based, and ensemble methods. It describes their general strengths, such as nonlinear function fitting, relationship…
The post introduces machine learning as an increasingly used approach in quantitative investing. It describes two applications: forecasting market movements and selecting portfolios. It also points to potential benefits, including handling nonlinear…
This guide explains how to obtain and read monthly partitioned stock bar data at four intraday frequencies, then align the local compressed tables with corresponding cloud tables used for prediction. It describes the Feather file layout, recommends loading…
This report proposes identifying Chinese quantitative private funds through exchange-disclosed trading-seat data. It matches stocks held by four funds among the largest tradable shareholders at quarter-end with the broker seats that appeared on those stocks’…
This report reviews factor performance across the broad market, sectors, industries, and indices during the first half of 2018, then examines factor selection in a market with sharply different outcomes across stocks and sectors. It reports that most factors…
This summary describes a market-timing approach that uses a convolutional neural network to extract patterns from lower-dimensional index features, including technical indicators, and classify expected returns. Predicted return classes are then used to drive…
The document answers how to identify when a strategy’s maximum drawdown occurred in a backtest. It recommends adding a strategy risk overview module after the backtest module, which reports the drawdown and its associated date. The example reports a maximum…