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 compares two proposed approaches for monthly minimum-variance stock portfolios: estimating individual variances with GARCH while using historical covariances, and modeling returns with daily Fama–French factors and regression residuals. It asks…
The document explains why adding a fund’s monthly arithmetic return contributions does not generally produce its contribution to a portfolio’s compounded return over a longer period. Monthly contribution is calculated as the fund’s portfolio weight times its…
The document considers a stock-selection score that awards points for improving return on equity, gross margin, sales, and leverage, as well as price above its 200-day average and a sequence of rising lows. It suggests testing whether the score relates to…
The document considers whether a long-only basket of stocks can reproduce the inverse returns of an ETF without short positions. The accepted answer argues that a long-only stock portfolio has positive market beta, so it cannot synthetically provide the…
The discussion considers how to select a cross-sector subset from a larger stock index while reducing concentration across sectors. Its main guidance is to begin by identifying how the index itself is constructed, since a market-cap-weighted benchmark and an…
The discussion distinguishes the Security Market Line (SML), which relates expected return to beta, from the Capital Market Line (CML), which relates expected return to total risk for combinations of the risk-free asset and the market portfolio. In the CAPM…
The discussion asks how to turn a filtered correlation matrix back into a covariance matrix when filtering has changed its diagonal entries. It compares two normalizations: reset the cleaned correlation matrix diagonal to one before rescaling by the original…
For an equally weighted portfolio of n shares, the document expands portfolio variance into diagonal variance terms and off-diagonal covariance terms. The diagonal contains n individual variances, so their contribution is 1/n times the mean variance across…
A position in an emerging-market currency against the US dollar also carries exposure to movements in the dollar relative to other developed currencies. To isolate the desired emerging-currency risk, the note proposes estimating hedge weights with multiple…
The document addresses why minimum variance weights can be used to estimate a factor return, even though factor models are often associated with explaining common variation. Its explanation distinguishes common factor exposure from diversifiable…
The document explains a geometric and economic interpretation of a pricing cash flow using linear pricing. Under the law of one price, the price of a payoff basket is the corresponding linear combination of its component prices. A linear pricing function can…
The document asks whether quarterly historical WACC should use a quarter-specific tax rate, a trailing-twelve-month rate, or another measure when quarterly rates are volatile. One response argues that WACC and its inputs may be difficult or impossible to…
The document asks where to obtain historical GICS sector fundamentals, particularly point-in-time price-to-book ratios. Reconstructing those values from individual companies would require knowing which securities belonged to each sector at each date, making…
The document explains exposure bounds as limits on how much a portfolio optimizer may allocate to an asset or asset class. Illustrative ranges include minimum and maximum weights for equities and bonds. Such constraints restrict the optimizer’s feasible…
A stock’s beta to an index is not generally equal to its index weight. The document derives beta from the covariance between each stock’s return and the index return, divided by the index return’s variance. Given index weights and the covariance matrix of…
The document explains how to calculate the variance of a portfolio made from any number of random asset returns. It expresses portfolio variance as the sum of each weighted asset’s variance and the pairwise covariance contributions, with each term scaled by…
The document asks whether a portfolio’s annualized return can be decomposed into annualized contributions from its individual assets. It defines each period’s portfolio return as the sum of asset returns weighted by their portfolio weights, then annualizes…
The discussion examines why a replication of the Fama–French five factor study for Europe produced different average excess returns for the same stated period and portfolio sorts. The researcher subtracts the Europe dataset's risk free rate from each of 25…
The document compares Gaussian and Student-t copulas in a three-variable portfolio setup. It describes simulating copula samples, transforming each uniform marginal through a Student-t distribution, summing the resulting values, and examining empirical…
The document shows how to calculate a fixed monthly contribution that grows to a target future value. It converts the investment horizon from years to months and converts the stated annual growth rate into a periodic monthly rate. With no initial lump sum,…
A synthetic collateralized debt obligation packages credit default swap exposures into a basket whose losses and payments are divided by seniority. Unlike a cash CDO, it does not hold the referenced loans or bonds. Investors can take long or short exposure…
The document considers how to calculate portfolio weights when cash is used to buy a derivative that provides exposure larger than the amount paid. Its example starts with a cash portfolio, spends part of it on a derivative, and asks whether remaining cash…
The document outlines a simulation framework for estimating fixed income portfolio value at risk while accounting for both credit events and interest rate movements. It proposes jointly simulating systemic variables that influence credit outcomes and an…
The document frames security selection as a trade-off between expected return and risk, with the investor’s risk tolerance affecting the choice. For two assets with discrete possible returns and probabilities, it outlines calculating each expected return as…