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.
4,574 documents
The document explains how to create currency-pair features from three fitted time-series models: a state-space filter that estimates a slowly changing price level, a two-state hidden Markov model for dollar volatility regimes, and an ARIMA model whose…
This notebook reviews a selected foreign-exchange strategy and its holdout lineage using registered research artifacts. It reproduces the choice from a frozen validation candidate set, ranking eligible solvent backtests by validation Sharpe with a…
This notebook explains how to construct one-, five-, and 21-session forward spot returns for a fixed FX-pair universe. It first maps four-hour bars into trading sessions using a New York rollover calendar, then builds returns without removing rows before…
This notebook runs the already selected FX strategy specification against registered holdout predictions. It preserves the strategy’s signal, allocation, risk controls, rebalance rule, costs, and account settings; the prediction set and price-frame identity…
This notebook presents a current audit comparing VectorBT Pro and VectorBT OSS with ML4T on supported real-data strategy workloads. Both VectorBT editions participate in ETF allocation, USD-quoted foreign-exchange allocation, and a US equity panel. Pro also…
This audit compares Backtrader and Zipline with ML4T on real strategy cases, using only asset and contract combinations that each engine and the frozen data bundle can represent natively. It covers ETF allocation and a US equity panel for both engines, plus…
This notebook assesses whether four-hour spot FX data can support a daily cross-sectional strategy that ranks currency pairs using momentum and carry, buys the strongest, and sells the weakest. It does not fit a model or make forecasts. Instead, it checks…
This configuration describes a daily long-short strategy across 20 FX pairs. It sets a New York close decision time, next-bar execution, equal-weight sizing, and ranking signals based on momentum or carry. It also specifies spread and swap-point costs,…
This document describes a shared workflow for training temporal convolutional networks on daily FX pair data. A model consumes a fixed-length sequence, and a missing expected day makes any window crossing that gap ineligible. The runner derives the valid…
This case study compares declared fixed and trailing stop rules for FX positions. It first selects one parent strategy per label from a sealed validation cohort, then varies only the position risk rule. Because stops respond to price movements within a…
This deployment demonstration retrains a Ridge model on historical daily data for a cross-section of major FX pairs, fetches current bars through an Interactive Brokers paper session, ranks the pairs, and builds a long basket. It walks through connecting to…
This document describes a foreign exchange OHLCV dataset covering G10 majors and crosses, with daily and four-hour bars from OANDA. It outlines how the data can be downloaded, loaded, filtered by pair or date range, and explored through coverage summaries…
This document develops a daily feature panel for ranking twenty currency pairs at the New York 5 PM close. It distinguishes rankable signals, such as standardized multi-horizon returns and channel position, from market-state measures such as volatility,…
This notebook examines linear-model regularization for predicting returns across currency pairs. It distinguishes collinearity among input features from dependence among the assets: currency pairs share underlying currencies, so their returns and rankings…
This notebook converts FX pair predictions into baseline trading results. At each decision time it ranks pairs, takes equal-sized long and short sleeves, and runs the selected prediction configurations and checkpoints through an existing backtest engine.…
This notebook describes how to create holdout predictions for an FX strategy after its configuration has already been selected using validation results. It resolves the highest-Sharpe validation backtest among admitted candidates that remained solvent, then…
This notebook reconstructs the selected FX pairs configuration from a frozen validation candidate set, then assesses its validation and holdout evidence. Selection uses the highest eligible validation Sharpe, with a deterministic backtest identity…
This intraday strategy limits entries to a specified London session window on weekdays. It goes long after three consecutive rising candles and short after three consecutive falling candles. Entries are managed with percentage-based stop-loss and take-profit…
This QuantConnect example shows how to define custom data readers for the NIFTY index and USD/INR, then add both series to an algorithm. The NIFTY reader parses daily OHLC values from a remote CSV source, while the currency reader parses daily closes. The…
This mean-reversion strategy fades price extensions beyond Bollinger Bands. It describes bands built from a 20-period simple moving average and two standard deviations: a move below the lower band is used to enter long, while a move above the upper band is…
This strategy combines moving average direction across hourly, four-hour, and daily charts into a weighted trend score, giving more influence to longer timeframes. Long and short entries also require price to be on the corresponding side of the hourly fast…
This example shows how to retrieve historical market data before live algorithm updates and use it to initialize indicators. It subscribes to two forex pairs at second resolution, creates fast and slow exponential moving averages for EUR/USD, and requests…
This script pairs a time-of-day filter with liquidity and breakout conditions to enter long or short trades. It defines a liquidity event as price exceeding a prior 30-bar high or falling below a prior 30-bar low, then requires a close crossing the preceding…
This strategy combines RSI, CCI, and Williams %R readings to identify possible short- to medium-term reversals. It opens a long position when all three indicators are in oversold territory and a short position when all three are overbought. The stated…