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.
21,023 documents
The document explains how to estimate asset and portfolio risk from historical returns. It describes calculating average returns, variance, and standard deviation, with standard deviation expressing return dispersion in the same units as returns. It then…
This page describes a BigQuant analysis of the COVID-19 outbreak in Wuhan using historical case data collected for China nationally and its provinces and municipalities. The platform made the dataset available for further analysis and offered a template for…
The document presents a trading account monitor intended to keep performance statistics and a daily target visible. Its stated motivation is behavioral: watching progress and a plan may help a trader notice emotional decisions, including revenge trading…
The Midpoint Oscillator (MPO) is a two-line indicator intended to show price movement relative to the center of its recent high-low range. Its main line compares the latest close with the midpoint of the highest and lowest prices over a configurable lookback…
The document outlines a lesson comparing autoregressive (AR), moving-average (MA), and ARIMA time-series models using CSI 300 index prices and returns. Its stated aim is to explain the modeling workflow and try each approach for fitting and forecasting…
The article presents a framework for explaining changes in trend-following performance through three components: the size of risk-adjusted market trends, the strategy’s efficiency in converting those trends into returns, and the diversification benefit…
The OHLC Volume indicator splits a bar's tick volume into upward and downward streams using proportions derived from the bar's open, high, low, and close. It has no user-set input parameters. The described calculation weights the upward stream by the…
This document introduces a chart indicator called FineTuningMACandle_Chl. It describes two colored channels built from standard deviations of the indicator candles’ high and low values. The listed parameters include the averaging period, multiple ranks and…
The document introduces the Schwager volatility ratio as a technical measure for comparing a security’s current price range with its recent volatility. It defines today’s true range using the day’s high and low together with the previous close, then relates…
This research summary compares industry-level signals built from risk-adjusted returns and moving averages. It reports tests of Jensen’s alpha, Sharpe, Treynor, and Calmar measures across different lookback periods. The six-month Jensen measure behaved as a…
This Chinese stock-selection strategy screens for shares with turnover between 3% and 12%, seven consecutive declining sessions, and prior-day opening-auction turnover above 0.26. The article frames the turnover range as moderate, the losing streak as a…
This overview introduces several major machine-learning approaches and explains their basic purposes. It contrasts linear regression for numeric prediction with logistic regression for classification, then describes neural networks as layered processing…
The article examines whether valuation ratios predict future equity returns or offer a basis for market timing. Using long-run monthly U.S. stock market data, it compares the cyclically adjusted P/E ratio (CAPE) and conventional P/E with realized equity…
This research summary describes stock-selection factors built from Chinese public mutual-fund holdings. Because quarterly reports disclose only the largest positions and holdings data arrive infrequently, the study fills out recent quarterly holdings using…
The document demonstrates a routine for combining shorter-period market records into four-hour OHLCV bars. It first examines timestamps and discards records until it encounters a bar whose hour matches a four-hour boundary. It then processes records in…
This forum post raises a replication problem involving a high-frequency stock return-variance factor described in a Haitong research report. The author says they implemented the report's first two calculation methods in SQL, but obtained results on a very…
This brief description introduces an indicator that plots a moving average calculated with the Square Weighted method, abbreviated SqWMA. It identifies two user-controlled inputs: the calculation period and the applied price used as the series for the…
The notebook describes an evaluation workflow for stock-return prediction models, including linear and neural models as well as a Transformer and an approach combining predictors with a learned router. It ranks predictions cross-sectionally each day,…
The document presents factor-category weighting as a simple neural-network problem. Gradient-based optimization can learn both the weights within categories and the weights across categories from cross-sectional observations. Under certain conditions,…
This strategy tests whether two price series can support a mean-reverting spread. It applies augmented Dickey–Fuller tests to each series and their first differences, then uses a linear regression to estimate a hedge ratio and intercept when the series…
XLineRegression is described as an indicator that creates price levels using a linear regression algorithm. Its inputs include the regression period, the degree of the regression, the price series used in the calculation, a horizontal bar shift, and a step…
This reference describes metrics for evaluating trading strategies from records of equity, fees, trades, trading volume and value, positions, prices, and timestamps. It covers cumulative and annualized returns, Sharpe and Sortino ratios, return relative to…
The indicator estimates the typical price range for each hour of the day on the current instrument. For each chart bar, it subtracts the low from the high, adds that range to the running total for the bar’s hour, and divides by the number of bars counted for…
This indicator combines the ColorZeroLAG moving average with a three-level estimate of trend strength. It uses the standard deviation of the moving average and two configurable thresholds, dK1 and dK2, to determine whether to draw a dot and how large it…