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.
16,761 documents
This brief forum exchange answers whether VeighNa, also known as vn.py, requires Tushare as the sole source of historical A-share data for backtesting. The response says the framework supports multiple data services and points readers to its documentation…
This tutorial explains how to use Python notebooks for quantitative research, from collecting and saving exchange candlesticks to plotting price and trading-activity measures and testing strategies across symbols. It demonstrates paginated retrieval of…
The article presents a notebook-based workflow for quantitative research: obtain exchange candlestick history through an API, store and inspect it with pandas, plot price and trade-flow measures, and build a Python backtest for multiple spot or perpetual…
This module constructs a continuous futures series by identifying contract roll dates and calculating the price gap between the expiring contract and the next contract. It accumulates those gaps through time and can align the adjusted series at its end. A…
This document describes an Expert Advisor built around a moving average with a fixed period of 55. Users can adjust its timeframe, horizontal shift, smoothing method, and applied price. The EA checks for signals only when a new bar forms and during a…
The document describes a daily stock screen for Chinese main-board shares. It selects non-ST stocks with turnover between 3% and 12%, a daily gain above 1%, and more than one year since listing. The stated rationale is to combine active trading and positive…
This configuration defines a Qlib workflow for training a Temporal Fusion Transformer model on Alpha158 features for CSI 300 stocks. It sets Chinese market data from 2008 through mid-2020, using 2008–2014 for training, 2015–2016 for validation, and 2017–2020…
The article compares five open-source tools for automating cryptocurrency trading: OctoBot, FreqTrade, Hummingbot, Jesse, and Superalgos. It describes their stated strengths, including strategy options, exchange compatibility, testing support, customization,…
This Qlib documentation describes visual reports for evaluating intraday portfolios and prediction models. Portfolio reports display benchmark and portfolio cumulative returns, returns with and without transaction costs, turnover, drawdowns, and cumulative…
This Expert Advisor uses fast and slow moving averages to determine direction. It opens a buy when the fast average is above the slow average by a configurable minimum distance, and a sell under the opposite condition. The EA can close or retain existing…
This Expert Advisor opens trades when a colored Sidus indicator arrow appears at a bar’s close. Its entry logic is therefore driven by the indicator’s directional signals, with the signal confirmed only after the bar completes. The document describes the…
This research outline proposes allocating among equity industries by tracking the behavior of different market participants. It motivates industry rotation with the observation that returns can diverge substantially across sectors and styles, so broad asset…
The document describes a commodity futures strategy that ranks 28 markets by changes in Twitter-derived sentiment. It calculates daily sentiment from keyword-matched posts using a financial sentiment dictionary, then forms equal-weighted long and short…
This strategy organizes research and trading for same-day-expiration bear call spreads through separate agents. A researcher gathers account and market information, checks the listed expiration, contract Greeks, and bid-ask quality, then identifies a short…
This brief support note addresses a BigQuant workflow where a ranking strategy appears to backtest normally but produces no rebalance signals in simulated trading. It points to configuration and data-window checks: bind the code-list module’s end date to…
This Chinese equity screen combines three conditions: at least five moving averages are described as converging, the tradable share float is no more than 5.5 billion shares, and the ten-day return is positive but below 35%. The article frames this…
This stock screen combines turnover between 3% and 12% with seven consecutive sessions in which the closing price falls, then filters for a daily price change below 2.6% and above -5%. The article presents the rule as a way to find stocks after a sustained…
This document describes a MetaTrader 5 class for rebuilding closed trades from their opening and closing deals in account history. The history is selected over a time range and organized by close time; callers can then enumerate reconstructed trades or…
This paper description presents a learnable scheduler for sequence-learning problems with related prediction tasks, such as forecasting returns at different future horizons. During training, the scheduler chooses an auxiliary task based on the current model…
This forum post presents a workflow for combining predictions from three model outputs. It merges the datasets on instrument and date, preserves columns that are not already present, renames each model’s prediction column, and computes their arithmetic mean…
This Chinese-language question and answer explains why a strategy’s apparently strong later years in a long backtest may not reproduce the same pattern when tested over those years alone. It identifies several possible causes rather than prescribing a single…
The Laguerre indicator described here plots a weighted trendline in a separate chart window and is presented as a possible aid for simple entry and exit signals. It is custom-built and does not depend on the standard MetaTrader indicators. The page says…
The document describes a Chinese equity screening rule that starts with stocks classified in the metaverse theme, applies a minimum threshold for circulating market capitalization, then ranks candidates by the day’s auction amount and selects the five…
The document describes TradingSlippage as an execution cost applied during backtesting to SMART_LIMIT fills. It says slippage can be supplied at the strategy level, with separate lists for buy and sell orders. This lets a researcher model an assumed cost on…