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.
16,761 documents
The document asks how to model the distribution of ending wealth from a starting investment when an asset’s arithmetic mean return and standard deviation are known. It suggests running repeated simulations in a spreadsheet and plotting their cumulative…
The document compares simulated returns from a multivariate BEKK process and geometric Brownian motion with observed stock returns. The author finds that default BEKK output appears too volatile and that both approaches fail to reproduce the excess kurtosis…
The document considers how to project a sparse monthly series over a one-year horizon when only two years of history are available. The measure is described as a person’s skill, but the suggested modeling considerations also apply to short time series more…
The document explains purging in financial machine learning through a prediction task that uses current stock returns to forecast the next day’s market return. The accepted answer illustrates the issue with a label based on a multi-day future return: labels…
The document explains why a European option on an arithmetic basket of correlated stocks generally lacks a direct Black–Scholes formula under geometric Brownian motion: the basket is a sum of lognormally distributed prices, which is not itself lognormal. It…
The document asks how to interpret a test for anticipation effects in a Difference-in-Differences study. It distinguishes this concern from the parallel-trends assumption, which the author describes as commonly assessed by jointly testing whether lead…
The document outlines a progression of methods for testing strategies that depend on timely execution, especially passive orders and cross-market hedging. For liquidity-taking strategies, top-of-book data may support conservative size assumptions that can…
The document asks how to choose stop-loss and take-profit thresholds from trade outcomes and expected profit estimates. It points to operations research and stochastic processes, and presents differing views: one answer argues that thresholds may be…
The document considers how to construct dollar bars when only minute OHLCV data is available. One proposal estimates each minute’s traded value by multiplying volume by an average price, then combines minutes until their estimated dollar value reaches a…
The document asks how to calculate an ex-ante Sharpe ratio from simulated return paths: from compounded total returns across paths, or by calculating a Sharpe ratio along each path and averaging those ratios. The response emphasizes that the conventional…
The document asks whether range-based estimators such as Garman–Klass can be combined with EWMA or ARCH-family models, and whether a dynamic volatility model is still needed when using such estimators. The response points to research that incorporates…
The document considers how to choose both a signal threshold and the future return horizon when evaluating a trading hypothesis. It warns that searching many combinations can amount to data mining and produce overfit results, while acknowledging that there…
The document raises a research concern: option pricing models may be proposed without being tested against market data or compared with established alternatives. It notes that affordable options data can be difficult to obtain, while arguing that empirical…
This document describes a simulation problem: generating several correlated variables from a Sobol quasi-random sequence in MATLAB. The author contrasts a Cholesky-based transformation of standard normal draws with an attempted method that transforms Sobol…
The document surveys software options for developing and evaluating trading strategies in C++. It names QuantLib, Boost, Armadillo, Intel MKL, Eigen, and TA-Lib for quantitative, numerical, and technical-analysis work. It also mentions TradeStation for…
The discussion addresses where to obtain several years of daily implied volatility data for large-cap stocks for backtesting. It suggests Interactive Brokers as a possible source, while noting that access requires a market data subscription. A separate reply…
The document outlines questions and practical choices involved in studying how earnings surprises relate to stock behavior. A study can measure how often firms beat or miss expectations, the size of the gap, price moves around announcements, later…
The document describes a simulation in which Poisson counts determine how many exponential random variables to draw for each component, after which weighted component sums produce one value per path. The original example uses nested Python loops and targets…
The document asks whether Quandl’s Wiki Continuous Futures series are already adjusted for contract rolls and how to handle them in rolling train-and-test backtests. It distinguishes continuous series from explicitly back-adjusted data: the presence of a…
The document addresses how to simulate the terminal price of a geometric Brownian motion (GBM). It distinguishes the arithmetic mean and variance of the resulting lognormal price from the parameters required by a lognormal random-number generator, which are…
The document explains why a futures backtest needs to model the transition from an expiring contract to a later-dated contract. A price difference between those contracts is not itself a trading gain or loss: a live trader closes the expiring position and…
The post considers how to compare profit factors across forex strategy runs when trades arrive in bursts. The author proposes treating nearby orders as one cluster and weighting each trade according to the number of subsequent orders within a short window. A…
The document distinguishes an ex ante return estimate based on assumed parameters from an ex post calculation using realized mean and risk. It gives a simple normal-distribution method for estimating the probability that a return falls below zero:…
The document describes a Monte Carlo check of a continuously rebalanced delta hedge for a European call under the Black–Scholes model. The simulated portfolio gains are formed from the option delta and successive underlying-price changes. The initial…