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.
5,922 documents
This report reviews crypto and blockchain venture investment during the first quarter of 2022, covering capital raised, deal counts, funding stages, valuations, deal sizes, and sector mix. It finds that investment dollars remained strong despite declines in…
The document estimates how a U.S. spot Bitcoin ETF could widen investor access and affect Bitcoin demand. It argues that ETFs may offer lower fees, better liquidity and tracking, familiar brokerage access, and regulated custody compared with existing…
This quarterly report surveys crypto hedge fund performance, assets under management, venture fundraising, deal activity, and the market backdrop in Q1 2024. It separates hedge funds into fundamental, quant directional, and market neutral strategies,…
The document explains Bitcoin’s scarcity, issuance schedule, and historically low correlations with several traditional asset classes, then examines how a Bitcoin allocation affected a diversified portfolio. The authors tested a quarterly rebalanced mix of…
This report reviews crypto and blockchain venture activity in the fourth quarter of 2025 and across the year. It tracks capital invested, deal counts, financing stage, valuations, company categories, founding cohorts, geography, and fundraising by venture…
This quarterly report analyzes investment into crypto startups and fundraising by crypto venture funds in Q3 2024. It draws on public filings, external data providers, and the publisher’s fund database to examine deal volume, capital invested, stage,…
This report surveys crypto hedge funds and venture fundraising through 2023. It describes the market backdrop, fund closures and track records, the concentration of assets among larger managers, and the rebound in hedge-fund assets under management. It…
This report explains how public companies use digital assets, mainly bitcoin and ether, as a core treasury strategy. It defines equity premium to net asset value, mNAV, at-the-market share issuance, private investments in public equity, and bitcoin yield,…
This analysis examines the reversal in bitcoin treasury companies’ share-price flywheel as bitcoin fell and equity premiums to bitcoin net asset value compressed. The authors describe how a premium can let a company issue shares and buy more bitcoin…
This project tests a mean-reversion pairs strategy on Mexican stocks. It screens an initial equity universe for complete price histories and minimum average trading volume, then tests within-industry pairs for cointegration with an augmented Dickey-Fuller…
The article introduces principal component analysis (PCA) as a way to reduce the dimensionality of financial data while retaining much of its variation. It explains eigenvectors and eigenvalues as directions and magnitudes of transformation, then connects…
The article describes a workflow for using generative language models to assemble a thematic universe of healthcare companies involved in artificial intelligence. It starts with S&P 500 constituents, filters for healthcare firms, gathers company news, and…
This article organizes suggested reading for people learning algorithmic trading. Its categories span market microstructure, statistics and econometrics, technical analysis, options, advanced statistics, machine learning, Python, and portfolio management.…
The document explains how to explore portfolio allocations by repeatedly assigning random weights to four U.S. financial-sector stocks, calculating each portfolio’s annualized return and standard deviation, and comparing the results. It defines three…
This webinar description explains how high-frequency prices can extend portfolio risk analysis beyond the low-frequency data commonly used in portfolio metrics. The proposed approach uses intraday observations to estimate risk and support portfolio…
This event overview outlines a two-day NSE workshop on algorithmic trading, with material spanning strategy research, trading technology, regulation, and portfolio management. Topics include execution methods such as time- and volume-weighted orders,…
This interview describes David U. Ordiz’s progression from discretionary Bund futures trading to systematic research and portfolio management. His approach focuses on intraday algorithms seeking short-term trend or counter-trend moves across index futures,…
The article explains Linear Discriminant Analysis (LDA) as a supervised method for classifying observations and estimating the probability of belonging to a class. It contrasts LDA with logistic regression and describes LDA’s use of Bayes’ theorem, class…
This article uses simple betting examples to explain expected value as the probability-weighted average of gains and losses. It shows how a favorable payoff structure can produce positive expectation even when a win is uncertain, while a symmetric…
The article introduces the Kalman filter as a recursive method for estimating a changing, partly unobserved state by combining model predictions with noisy measurements and their uncertainty. It explains concepts including normal distributions, variance,…
The article explains algorithmic trading as using defined instructions to generate signals and place or manage orders, then argues that learning it requires programming, market knowledge, analysis and backtesting. Its practical example describes reading…
This project tests active management of a Big Tech stock portfolio against equal-weight buy-and-hold and monthly rebalancing baselines. It uses online linear regression, principal component features, and a Kalman filter to estimate each stock’s value…
This article surveys an end-to-end approach to applying machine learning and artificial intelligence to trading. It advocates starting with a trading objective, selecting a model only when it adds value, and interpreting model outputs in the context of…
The guide distinguishes statistical independence, correlation, and cointegration, concepts that are often confused when assessing diversification and trading relationships. Independence means observing one variable does not change the probability…