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
The document introduces a quantitative way to assess an individual stock before deciding whether to buy it and how much capital to allocate. Rather than forecasting which stocks will be attractive, the proposed diagnostic approach looks backward at how the…
This Chinese equity strategy screens for stocks whose opening price is above the previous close and whose five-day closing-price average is above its ten-day average. It ranks qualifying candidates by price-to-earnings ratio in ascending order and selects…
This research note summarizes evidence that changes in the wording and structure of company filings can contain information about future operating performance and equity returns. The underlying study compares the text of SEC annual and quarterly reports with…
This report summary examines how market and style conditions may affect equity market-neutral strategies. Such strategies select stocks using fundamental or price-and-volume signals, then hedge broad market exposure with index futures or short selling. Their…
The article explains why a factor’s strong historical returns may come from an unintended exposure to market capitalization or liquidity. It uses large-order sell value as an example: because the measure is an absolute amount, it tends to be larger for…
This research summary describes an equity selection process built from daily price and volume data. Genetic programming searches for candidate factors, using RankIC to favor linear relationships or mutual information to seek nonlinear ones. To focus on…
This exchange explains how to handle a stock that remains in a backtest portfolio after it leaves the benchmark universe. The example concerns a strategy restricted to CSI 300 constituents: a stock bought while it belonged to the index may still be held…
This brief explanation addresses why applying a one-period lag to closing prices can return a missing value. If the available data begins on the current day, the prior day’s close is outside the dataset, so there is no value for the lag operation to…
This forum excerpt concerns constructing training labels for a Chinese stock dataset and asks why label extraction produces an empty training set. The displayed expression derives a future return from a later close divided by a later open, assigns a…
This article examines how the length of an AI model’s training window can affect an equity strategy. It compares manually rolled long windows spanning several years with shorter windows ranging from a month to a few years, and recommends evaluating each…
This brief Chinese market report summarizes A-share sector performance, index and sector valuations, market breadth, fund positioning, and an intermediate-term LLT model. It reports the strongest and weakest sectors, notes declining valuations across several…
This research summary examines whether market conditions and macro variables can predict the next month’s long-short reversal-factor returns in Chinese equities. It identifies market funding sensitivity, turnover, volatility, and bid-ask spread as…
This BigQuant forum post describes a factor-research problem: detect a recent stock event, then later compare price with a level from the event day. The example defines an event using volume more than twice the prior value and a return above a stated…
This brief BigQuant support exchange addresses a simulation error reported as having no data remaining after missing rows are dropped. The user had already tried extending the feature-extraction lookback by several different periods, without resolving the…
The post asks why a daily stock-ranking strategy sells positions in backtests but appears only to buy them in simulation. Its code includes a trailing stop based on a percentage below the highest observed price since purchase, then manages capital and ranks…
This brief BigQuant support exchange explains an error raised when a time-series minimum function receives a window argument that is not an integer. The example first derives a value from the position of the highest high within a fixed lookback, then passes…
The document explains a data-processing approach for high-frequency factors that are first aggregated from intraday observations to daily values and then smoothed over multiple days. Instead of loading the full intraday history needed for the rolling window…
This note describes a single-security, multi-day approach to constructing intraday volume factors. For each trading day, the proposed measures calculate the share of full-day volume transacted within selected intervals. The intervals cover early trading,…
This short exchange addresses how to sell stock shares according to the age of each entry. The example strategy opens separate lots in the same stock on consecutive days, then intends to close each lot after a specified holding period. That requires tracking…
This note describes a reproduction of a Guosen Securities quantitative research report on daily momentum factors that combine individual stock and industry returns. Its central idea is to use the relationship between a stock’s performance and its industry’s…
This April 2020 market note combines a long-term trend assessment, short-term liquidity view, sector preferences, and tracking of A-share fund flows. It says a market breadth model had turned bearish and describes weakening turnover and a declining stock of…
The report proposes combining company-level stock selection with industry allocation for Chinese equities. Its coupling model uses each stock’s historical beta to its industry as a dynamic weight: more industry-sensitive stocks receive more influence from…
This summary of a Changjiang Securities study explains a stock-selection factor based on the balance between active and passive buying. Active buying occurs when an investor’s order trades against displayed sell orders; passive buying places a limit order…
This research summary argues that factor signals weaken over time, so holding a monthly portfolio unchanged can leave later-period capital exposed to less informative signals. It proposes measuring a factor’s decay speed through the half-life of its…