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.
1,747 documents
This notebook applies TabM, a weight-sharing neural ensemble, to a panel of cryptocurrency perpetual-futures features. Its members share a neural backbone but have separate scaling vectors and output layers, combining efficient ensembling with nonlinear…
This notebook frames a focused test: whether a learned sequence representation of perpetual-funding features improves on hand-built summaries of the premium, the gap between perpetual and spot prices. It compares NLinear, which applies a linear mapping to…
This notebook turns model rankings into simple crypto perpetual portfolios. At each funding timestamp, an entry rule selects contracts from the top or bottom of the ranking and assigns equal weights. Equal weighting provides a reference point: comparisons…
This notebook compares validation predictions from multiple model families for perpetual-futures funding research. It explains that information coefficient measures rank association between predictions and subsequent returns, AUC measures ranking for up or…
This notebook uses double machine learning to estimate whether a perpetual-futures premium z-score is associated with the following eight-hour return after adjustment for six pre-treatment controls. It compares effects across high- and low-volatility regimes…
This notebook builds features for a cross-sectional hypothesis: unusually costly long positioning in perpetual futures may precede relative weakness as crowded trades unwind. It transforms funding rates and premium-index data into levels, historical…
This notebook implements a long-only RSI mean-reversion rule for BTC/USDT perpetual bars using an event-driven backtesting engine. It aggregates intraday observations into UTC daily bars, calculates a simple rolling gain-and-loss RSI, enters when the…
This document develops features for studying whether crowded positioning in crypto perpetual futures predicts relative returns. It explains the funding payment’s direction, the role of the premium index, and why raw funding or premium values may need…
This exploratory analysis profiles hourly OHLCV data for Binance perpetual contracts alongside an eight-hour premium index. It checks dataset coverage, changing contract membership, units, missing values, and raw-bar OHLC consistency. The premium is stored…
The document presents crypto price ranges as the result of interactions between market context and the cost of leveraged positioning. It focuses on the four-hour timeframe as a way to assess that context and describes perpetual-futures funding as a force…
The paper applies generalized extreme value theory to tail returns in bitcoin futures markets to examine forced liquidation risk, leverage, and margin levels for both long and short positions. Its empirical analysis uses BitMEX perpetual futures. It reports…
This study investigates recurring bursts in volatility and trading volume around one-minute, five-minute, and quarter-hour boundaries in cryptocurrency markets. It analyzes trade data from six Binance perpetual contracts and uses the changing roundness of…
The paper derives no-arbitrage prices for perpetual futures, contracts without an expiration date whose prices are linked to spot through periodic funding payments. It treats linear, inverse, and quanto contracts in both discrete and continuous time. The…
This study examines how funding rates can keep cryptocurrency perpetual futures aligned with a target value. It develops replicating portfolios that issuers can use to hedge their exposure and also considers path-dependent funding rates as a practical…
The study proposes a reinforcement learning portfolio manager for a high-risk setting. It combines two-sided transactions with lending and borrowing, uses a profit-and-loss reward, and aims to improve downside risk management and capital use. Its…
The document examines whether crypto perpetual futures can be applied to binary event claims that settle at zero or one. It derives a terminal-equity problem: a leveraged long that remains open through an adverse zero settlement can leave an account short of…
This paper proposes a theoretical control framework for market making in zero-maker-fee perpetual futures markets. A market maker chooses bid and ask spreads and manages inventory through hedging across two exchanges. The framework decomposes profit and loss…
This paper extends optimal market making to perpetual contracts where funding rates evolve stochastically. Because a market maker’s inventory affects both price exposure and funding cash flows, the authors formulate a joint inventory and funding control…
The document examines the trade-off between the chance that a maker order fills and the return after it fills. Its evidence comes from a live trading experiment on the Binance Bitcoin perpetual, where the analysis considers order-book mechanics, queue size…
The paper examines the relationship between BitMEX inverse perpetual swap contracts and their associated funding rates. It reports that funding rates are heteroskedastic and uses Granger causality analysis to assess directional relationships between funding…
This document explains how perpetual futures differ from fixed-maturity contracts: they provide leveraged exposure without rollover or direct ownership, but have no maturity date forcing convergence to spot. A periodic funding payment between longs and…
The paper models the yield strategy of a decentralized stablecoin that combines staked Ethereum with an equal-sized short position in ETH perpetual futures. The matched legs aim to reduce exposure to ETH spot-price changes while earning staking rewards and,…
The study tests whether seven major Bitcoin perpetual-futures liquidation cascades show critical slowing down before the event. It analyzes detrended price data alongside leverage and order-flow measures, tracking rolling variance and lag-one autocorrelation…
This paper formalizes decentralized finance mechanisms that provide lending pools for perpetual futures trading. It calls these mechanisms Perpetual Demand Lending Pools (PDLPs), describing a general target-weight approach that extends mechanisms used in…