Knowledge library

This notebook applies TabM, a weight-sharing neural ensemble, to stock-return targets built from equity-option features. Its members use a common two-layer network backbone, with separate activation scaling vectors and output heads whose predictions are…

This dataset note describes a diversified collection of exchange traded funds used in a momentum strategy and a broader sequence of financial research examples. It provides daily open, high, low, close, and volume observations beginning in 2006, grouped…

This notebook applies TabM to a flat table of US stock features, positioning it between penalized linear models and tree ensembles. Each ensemble member shares a neural network backbone but has its own scaling vector and output layer; averaging member…

This notebook fits ridge, lasso and elastic-net models to a broad set of established US stock characteristics, including value, profitability, investment, momentum, size, risk and liquidity measures. It evaluates raw monthly returns, a cross-sectionally…

This analysis applies correlation-based principal component analysis to returns from sector exchange-traded funds. Standardizing returns before decomposition gives each sector unit variance, so the leading components describe co-movement rather than being…

This notebook describes how to parse IEX DEEP historical feed messages and maintain a limit order book using aggregated price-level updates. It extracts depth changes, best bid and ask quotes, and trade reports, then uses reconstructed snapshots to examine…

This notebook compares equal-weight, positive-score-weighted, and conformal-width-weighted allocations for top-ranked ETFs and CME futures. It estimates entity-specific split-conformal interval widths from residuals in earlier validation folds, excluding…

This notebook compares three ways to convert signed return predictions into binary positions: a fixed zero cutoff, a trailing percentile of each symbol’s own scores, and a cross-sectional percentile across symbols. It measures signal activation and state…

This document presents a supervised autoencoder as a control for conditional latent-factor models. It maps firm characteristics directly to forward returns while compressing 57 inputs through a narrow bottleneck. Comparing it with a conditional autoencoder…

This notebook explains how stock splits and cash dividends disrupt raw historical price series and distort calculated returns. It demonstrates backward adjustment, in which historical prices are rescaled for subsequent corporate actions, and applies the…

This notebook uses ETF features and forward returns to demonstrate classical ordinary least squares inference before turning to prediction-focused methods. It examines coefficient tests and standard errors, then diagnoses heteroscedasticity, residual…

This NASDAQ-100 study examines how transaction costs affect a frequently rebalanced equity strategy. It separates two possible responses to costs: restricting the traded universe to more liquid, lower-cost names, and reducing rebalance frequency. Keeping…

This notebook presents PCMCI as a way to discover lagged relationships in multivariate financial time series without specifying a causal graph in advance. It applies the method to ETF and volatility-index returns, compares its conditional analysis with…

This tutorial turns ETF cross-sectional signals into long-only, equal-weight top-ten portfolios and compares Ridge regression and logistic classification with momentum and equal-weight baselines. Models are fitted on walk-forward training windows, with a…

This study tests whether the poor fit of a linear model to monthly US stock returns comes from its squared-error objective. It holds the unwinsorized forward-return target, features, and walk-forward folds fixed while comparing boosted tree models trained…

This notebook introduces NLinear as a baseline for predicting stock returns from ordered feature windows. Each example contains 60 consecutive sessions for one stock. For every feature, the model subtracts its latest value, maps the resulting history to a…

This reference describes two public SEC filing sources for studying equity positions and insider activity. Quarterly 13F reports provide institutional holdings, either for a curated set of managers or through bulk data covering a full filing window. Form 4…

This notebook reconstructs the prevailing national best bid and offer (NBBO) for each AAPL trade during the regular session on March 16, 2020. It chronologically combines quote and trade events, carries the latest bid and ask forward, and removes trades…

This notebook fits TabM neural models to an S&P 500 options short-straddle return target and compares three model capacities on the same feature panel used by linear and boosting approaches. TabM shares a neural backbone across ensemble members, while…

This notebook evaluates position-level controls for an S&P 500 equity-and-options allocation, comparing fixed stop losses, trailing stops, and time exits with each strategy's own no-overlay baseline. It selects an eligible strategy lineage using validation…

This document demonstrates Instrumented PCA, in which asset factor loadings are modeled as linear functions of characteristics observed before the return. It uses alternating least squares to estimate the characteristic-to-loading map and realized factors,…

This document describes a reproducible US equities benchmark drawn from the Chen, Pelger, and Zhu asset-pricing replication archive. It contains roughly 1.2 million monthly stock observations from 1967 through 2016, with 46 firm characteristics,…

This document explains how TSMixer processes a stock’s recent feature history as a sessions-by-features matrix. Its blocks mix information down feature columns across time, then across features within each session. Stacking blocks lets those operations…

This notebook uses registered walk-forward GBM predictions for ETFs and CME futures to compare equal weighting, inverse conformal-width weighting, and weighting proportional to positive prediction scores. It calibrates entity-specific Mondrian…