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 first-person account describes experiments with a volatility-triggered scalping strategy and a moving-average momentum strategy. The initial scalping rule used Average True Range to set a trading threshold and compared recent price action, but its…
The guide explains how to estimate return variance for a single asset, covariance between asset returns, and total variance for a portfolio. It begins with historical returns, using their average as an expected-return estimate and variance or standard…
The project builds a long-only daily strategy across nine SPDR sector ETFs using short- and long-term exponential moving average crossovers. It reallocates capital quarterly based on each ETF’s relative quarterly return, aiming to direct more capital toward…
This article explains how exchange-traded funds pool securities into units traded on exchanges, then surveys market, sector, dividend, style, commodity, currency, and bond ETFs. It describes their potential uses, including broad diversification, targeted…
This project tests whether a Random Forest classifier using six technical indicators can generate useful long-only signals for ten South African Top40 stocks. The indicators cover trend, oscillation, volatility, and volume. The study trains separate models…
The article recounts a portfolio project that selects 22 stocks from 11 sectors of the S&P 500. It assigns weights using each asset’s standard deviation and rebalances quarterly: riskier stocks receive less exposure, while less volatile stocks receive more.…
This profile describes a student project that builds a diversified portfolio from 22 S&P 500 stocks across 11 sectors. The allocation is rebalanced quarterly using each stock’s standard deviation: higher-volatility stocks receive smaller weights, while…
The document introduces swing trading as holding positions for days to weeks to capture price moves between local highs and lows. It contrasts this horizon with day trading, describes swings as occurring within broader price trends, and favors…
The article surveys ways to choose trade size, beginning with account risk, the amount of capital exposed to loss, and trade risk, the distance between entry and a stop. It contrasts fixed units, fixed dollar amounts, fixed percentages of account value, and…
The document argues that strategies should be evaluated as components of an investment portfolio, rather than judged only as standalone systems. Standard measures such as CAGR, Sharpe ratio, and maximum drawdown summarize performance but do not show the…
This event overview outlines advanced algorithmic trading topics covered in a two-day NSE management program for financial institution leaders and experienced practitioners. Its strategy survey includes high-frequency trading, market making, structural and…
This project describes a long-only strategy that seeks to capture overnight price gaps in Indian equities. It enters at the close after a session with a larger true range than the previous session, a positive close-to-open move, and a daily change within a…
Expected Shortfall (ES), also called Conditional Value at Risk, measures the average loss in the tail beyond a chosen Value at Risk (VaR) threshold. The article explains the distinction: VaR identifies a loss cutoff at a confidence level, while ES estimates…
This project report explains portfolio diversification through Modern Portfolio Theory and introduces measures including alpha, beta, standard deviation, R-squared, and the Sharpe ratio. It describes the Fama-French three-factor model as an extension of CAPM…
The document outlines a session about private equity secondary markets: transactions in existing investments, with coverage of seller and buyer types, their motivations, and factors that may make a secondary investment attractive compared with a primary one.…
This tutorial presents a workflow for adapting Pyfolio, a Python library for portfolio performance and risk analysis. It outlines the library’s reporting features, including return and risk statistics, rolling measures, drawdowns, and tear sheets, then…
This article introduces factor investing as portfolio construction based on characteristics associated with differences in investment returns and risks. It distinguishes macroeconomic factors, such as growth, interest rates, and inflation, from style…
The article explains Value at Risk (VaR) as a loss threshold for a portfolio over a specified horizon and confidence level. It distinguishes losses measured relative to the expected value from absolute losses, then describes historical or non-parametric…
Monte Carlo simulation estimates a range of possible outcomes by repeatedly applying a model to randomly sampled inputs. The document distinguishes fully random sampling, sampling from a normal distribution, and randomizing trade order, and favors fully…
This project compares a Monte Carlo portfolio allocation approach with a mean-reversion pair-trading strategy on Indian equities. It uses three stocks from each of five sectors and evaluates portfolios with Sharpe, Sortino, and Calmar ratios. For allocation,…
This overview explains how different crises can affect markets and industries in different ways. It distinguishes natural disasters, technological failures, rumors, and man-made events, and reviews historical episodes in which markets fell sharply before…
The article explains mutually exclusive events as outcomes that cannot occur together and contrasts them with independent events, which may occur simultaneously without being related. It uses coin flips to introduce the probability of alternative outcomes,…
The document explains how to size positions so instruments with different price volatility make more balanced contributions to portfolio risk. It first distinguishes account capital from notional exposure, including how margin and contract multipliers can…
The article surveys ways artificial intelligence is being used in quantitative finance, including automated trading, risk analysis, portfolio management, market prediction, fraud detection, and high-frequency trading. It describes how quant work has shifted…