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
This brief description presents XXDPO_Candle, an indicator that displays processed price time series as candlesticks. Its stated rationale is that representing indicator values in candle form may make the information more useful for analysis in some…
The document describes the Kaufman Adaptive Moving Average (KAMA), an adaptive smoothing indicator. It provides a recursive update in which the prior average moves toward the current applied price according to a smoothing constant. That constant is derived…
This document introduces a ring-buffer class for calculating the Efficiency Ratio (ER), an input used by the Adaptive Moving Average. It describes initialization options, including the ER period, buffer capacity, and indexing convention, and provides methods…
The document describes an analyzer for assessing whether several trading systems diversify one another. It groups closed trades by magic number, aggregates profit and loss at a chosen daily, weekly, or monthly interval, and compares the sum of each system’s…
The post reports two errors encountered while analyzing the high-frequency factor hf_volume_diff_large_order: the software formed only four groups when five were requested, and it reported factor-value coverage below the minimum threshold. The author says…
The script outlines a VIX-style calculation from options prices. It estimates a forward level from the call-put price difference at the strike with the smallest disparity, selects the adjacent strike not above that forward, and aggregates out-of-the-money…
This directory surveys software used in quantitative research and algorithmic trading across languages including Python, R, Julia, Java, and Matlab. It groups tools by task, covering numerical computing and data analysis, technical indicators, pricing and…
This note describes an account-monitoring indicator that displays the account’s current status in the main chart window and plots a profit curve in a subwindow. Users can choose to follow total account profit or profit associated with a selected magic…
This note describes a stock risk factor based on the Sharpe ratio over a 20-day period. It defines the measure as annualized stock return minus a risk-free rate, divided by the stock return standard deviation. The stated risk-free rate is 0.04. The factor is…
This report summarizes a Binance BTC-USDT daily-candle backtest covering January 2019 through January 2021. The strategy recorded 155 closed trades and one open trade. The displayed metrics include an 89.77% net profit, 22.4% maximum drawdown, 37.64% annual…
The screen selects Chinese stocks with turnover between 3% and 12%, a 2021 listing year, and at least one limit-up event within the past month. The article frames turnover as a liquidity filter and a recent limit-up as a sign of market attention or…
This code describes a C-vine copula wrapper intended for statistical arbitrage research. It fits candidate vine structures to quantile-transformed data, restricts the candidate ordering according to a chosen target variable, and selects the structure with…
Holt’s double exponential smoothing is presented as a method for estimating a level and a linear trend, then forecasting future values by extending those estimates across the requested horizon. The level and trend estimates at each time depend on the current…
The document describes a True Strength Index oscillator paired with two sequentially smoothed signal lines, called shadows. It lists adjustable inputs for the price source and its period, two TSI smoothing periods, each shadow’s averaging period and method,…
This Chinese-language strategy note surveys ways to connect macro conditions, company fundamentals, valuation, and sector performance. It describes a credit and earnings framework for market regimes, a rolling stock-bond yield spread as a relative valuation…
This indicator counts bullish and bearish candles over a configurable number of bars and expresses the counts as percentages. It presents the relative balance between the two candle types as a way to gauge trend conditions: readings near an even split are…
This report examines Bitcoin spot liquidity across six market regimes, focusing on the October liquidation cascade. It tracks order book depth at several distances from mid-price, exchange volume shares, and a composite resilience measure based on depth…
This indicator description explains a smoothed form of the Average Directional Movement Index (ADX), a measure associated with trend strength. It exposes five adjustable settings: the ADX period, primary and secondary smoothing factors, and thresholds for…
This overview introduces the Fama-French five-factor asset pricing model as an extension of the three-factor model. It describes the market risk premium, size, value, profitability, and investment-style factors, and explains each as a return spread between…
The document presents a SQL query for calculating a stock’s five-day price return and ranking that return against other stocks on the same date. It uses a window function to retrieve each instrument’s close from five trading rows earlier, then computes the…
The document introduces naive Bayes as a classification method that applies Bayes’ theorem while assuming predictor features are conditionally independent given the class. It explains the roles of the class prior, feature likelihood, feature prior, and…
The document explains how to restrict a Chinese stock machine-learning dataset to shares that closed at their daily price limit, or to shares that hit the limit on the previous trading day. It describes filtering factor data by limit-status value and using a…
This indicator constructs price levels corresponding to RSI thresholds of 70 and 30 by reverse engineering the RSI calculation. A smoothed price average serves as the channel’s middle reference. When price crosses above the upper level or below the lower…
This guide explains how to monitor a StockRanker model’s validation performance during training. It recommends preparing a validation dataset, either from a separate data module or by reusing the training data, and connecting it to the model’s validation…