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.
243 documents
This notebook compares equity and futures commission models alongside several slippage models, emphasizing that their units and assumptions differ. Percentage fees stay constant as a share of notional, while minimums, fixed charges, per-share fees, and tier…
This document describes training a Proximal Policy Optimization agent to liquidate a fixed order over a defined horizon. It evaluates the learned pacing policy against TWAP and an Almgren-Chriss schedule using the same simulated market paths, enabling paired…
This notebook measures how well the Lee-Ready method infers trade aggressor direction using Nasdaq order-by-order messages with venue-provided aggressor labels as ground truth. It reconstructs the limit order book from adds, modifications, cancellations,…
This notebook measures how transaction costs affect a fixed CME futures strategy configuration. It selects the reported configuration through a shared validation-stage process, carries its risk overlay into the cost runs, and applies a declared grid of…
This notebook explains how to rebuild a limit order book from DataBento market-by-order messages for a single NASDAQ symbol and trading day. It models each order, aggregates orders into price levels, and maintains separate bid and ask sides. Correct message…
This notebook compares ways to hedge a short European call when rebalancing is discrete and trades incur proportional costs. It defines self-financing terminal P&L, then trains a neural hedger to minimize expected shortfall under Heston simulated prices. The…
This notebook compares single-objective hyperparameter tuning with a multiobjective search for LightGBM prediction models. The baseline maximizes validation information coefficient (IC). The NSGA-II search instead maximizes IC while minimizing normalized…
This notebook runs a selected NASDAQ-100 microstructure configuration on its registered holdout predictions. The model, allocator, concentration, rebalance schedule, risk overlay, and cost assumptions are inherited from earlier work and applied unchanged;…
This notebook explains how to select one strategy from a fixed set of US equity backtests and assess the resulting strategy on a separate holdout period. It validates that candidates share the required data and protocol identities, then ranks them by…
This notebook demonstrates an operational workflow for connecting a shared backtest and live strategy to an Interactive Brokers paper-trading session. It checks account identity and state, requests historical bars to initialize indicators, subscribes to…
This feasibility analysis checks whether a daily long-short equity ranking strategy can be researched with the available US stock panel. It examines point-in-time universe construction using price and trailing turnover thresholds, compares proportional…
This notebook audits an annual-report corpus before it is indexed for financial research. It measures the delay between a fiscal period end and the public filing date, showing why point-in-time applications must use the publication date. It also identifies…
This shared analysis module describes ways to estimate trading frictions across asset classes. It includes high-low and return-autocovariance estimators for bid-ask spreads, rolling average volume measures, and regression approaches for calibrating…
This notebook tests how a selected US firm characteristics strategy responds when its transaction cost assumption changes. It holds the strategy configuration fixed and reruns validation backtests across a declared grid of commission and slippage levels,…
This notebook develops a unit-aware framework for estimating trading costs across equities, crypto perpetuals, futures, ETFs, and foreign exchange. It distinguishes share volume, contract volume, base-asset volume, and price-update counts, converting…
This case study assesses a weekly S&P 500 options short straddle using registered backtests. It selects a configuration from a nominated liquid universe, ranks candidates on validation, and evaluates the chosen configuration on holdout data without using…
This analysis reconstructs NASDAQ limit-order lifecycles from ITCH messages, following orders from submission to their first cancellation-related event or execution. It distinguishes adds, deletes, partial cancels, replacements, and executions, then measures…
This audit record defines how several backtesting frameworks are compared with ML4T across real strategy case studies and a synthetic stress workload. It specifies the comparison rules for ordered fills, timestamps, account-money values, quantities, and…
This notebook presents correctness and runtime comparisons for VectorBT Pro and VectorBT OSS against ML4T on supported case-study strategies. It covers ETF allocation, USD-quoted foreign exchange, and a US equity panel for both editions; VectorBT Pro also…
This notebook demonstrates how a fixed dollar order can impose very different costs across stocks because its size relative to available trading volume matters. It applies a square-root market-impact model to a long-when-positive momentum strategy using…
This document explains how to construct forward-return and direction labels for NASDAQ-100 intraday research. It defines the return using an explicit execution convention: observe a bar close, enter at the next bar, and measure the outcome over a configured…
This chapter outlines post-deployment governance for machine-learning trading systems. It separates technical failures, where identical inputs produce different outputs, from statistical decay, where outputs no longer predict returns. Its framework combines…
This notebook tests Lee-Ready trade classification against aggressor-side labels in Nasdaq order-by-order data. It reconstructs the limit order book from add, modify, cancel, fill, and reset messages, then aligns each trade with the contemporaneous best bid…
This notebook measures how trading costs affect strategies already selected through signal, allocation, and risk-overlay stages. It fixes one validation-selected configuration per label before varying costs, so the resulting curves isolate the effect of the…