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
The document asks how to combine several dollar-neutral portfolios using nonnegative blend weights that sum to one while minimizing total turnover. The answer recommends expressing absolute-value constraints through nonnegative slack variables. A position is…
The document explains why a long-short portfolio can hold substantial cash even when its positions are described as weights of net asset value. Short-sale proceeds increase the account’s cash balance, while the short positions remain liabilities with their…
The discussion addresses sizing long and short stock positions generated by a daily strategy when trades overlap and signals arrive unevenly. One proposed approach budgets exposure using the number of concurrent long and short positions. If a signal has an…
The question concerns estimating covariance and correlation across investment horizons using overlapping historical returns. Rolling windows create serial dependence, which affects estimated volatility and correlation; the author asks whether generalized…
The document explains why high trading volume in a short-term Treasury ETF does not imply large price moves. Volume measures trading activity, while price movement reflects changes in the value of the holdings. Short Treasury securities generally have…
The document considers how to choose buy, sell, or hold actions from historical stock data while accounting for transaction costs, bid-ask spread, and slippage. It cautions that the problem cannot be judged by the apparent size of its search space alone: a…
The discussion distinguishes risk models, which explain return variation and support covariance estimation and hedging, from alpha models, which seek to forecast expected returns. Risk models can use a relatively small set of factors to estimate a large…
The document presents a question about interpreting principal components as portfolios of securities. The questioner applies PCA to a matrix of stock returns, rescales each component’s weights so they sum to one, and then compares the resulting portfolio…
The discussion asks whether portfolio mean and variance can be represented as distributions rather than single estimates. It describes two ways to quantify estimator uncertainty. A Bayesian approach assigns distributions to unknown mean and variance…
The document discusses a mixed-integer formulation for rebalancing a stock portfolio toward mean-variance target weights while limiting the number of traded positions. It represents each trade with a signed change variable and uses a binary indicator to mark…
The document discusses how to evaluate a stock-sorting strategy whose portfolio returns appear to have different Fama–French three-factor alphas. It recommends using Newey–West standard errors to account for autocorrelation and heteroskedasticity, and…
The document considers whether monthly data for a small set of Swedish stocks can support Fama-French portfolio construction and regression. It warns that sorting a limited universe by characteristics may leave only one or two stocks in some portfolios,…
The document discusses two ways to estimate an exchange-traded fund’s fair value from its underlying portfolio. One approach divides the fund’s net assets by shares outstanding to estimate net asset value per share, then compares that figure with the ETF’s…
The document examines whether option-implied volatility can replace historical volatility in mean-variance portfolio optimization. It cautions that vanilla option implied volatility varies by strike and has a specific risk-neutral interpretation tied to…
The document explains why dependence between defaults matters differently across credit products. For a linear portfolio such as a CDS index, the answer says default correlation does not affect the portfolio's payoff in the same way it does for structures…
The document introduces two R packages for maintaining a record of portfolio trades and calculating positions and profit and loss: blotter and PMwR. It focuses on PMwR, showing how trades can be organized as a journal with instrument, date, quantity, and…
The document compares shrinking a sample covariance matrix with shrinking a sample correlation matrix before using the result to forecast variance. Correlation shrinkage can be transformed back using sample variances, while direct covariance shrinkage also…
The document derives a two-variable single-factor model from regressions in which both variables share a common factor and each has an idiosyncratic error. The derivation requires equal factor loadings and equal residual coefficients for the two variables.…
The document gives a recursive method for simulating portfolio value when an initial lump sum is combined with periodic investments. At each step, add the contribution arriving during that period to the previous portfolio value, then apply the next period’s…
The document examines a return attribution regression that includes an intercept, country dummy variables, industry dummy variables, and factor exposures. Country and industry indicators can be linearly dependent, making the design matrix rank deficient and…
The document shows how to turn daily stock probability rankings into an equal-weighted portfolio that holds the five highest-ranked names and rebalances every ten days. The example uses a table of dates, stock names, returns, and model probabilities. The…
The document shows how to compute the covariance of a weighted return index with one of its component assets or with another asset. Using the linearity of covariance, the covariance between a weighted sum and a variable is the sum of each component’s…
The document asks why corporate finance treatments use different discount rates for tax shields. It contrasts a textbook discussion that treats depreciation tax shields as safe nominal cash flows, discounted at the firm’s after-tax borrowing rate, with an…
The document describes the inputs needed for periodic portfolio rebalancing: current weights, updated expected returns or alpha forecasts, forecast uncertainty, transaction costs, risk aversion, objective function, and portfolio constraints. Its central…