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 seeks research on how manager reputation, track record, and skill relate to mutual-fund and hedge-fund returns and investor flows. Its answer names two mutual-fund studies on costly investor search and managerial risk-taking incentives. A second…
The document explains a CAPM derivation that relates an asset’s expected return to its covariance with the market portfolio. Beta is the asset-market covariance divided by market variance. Rewriting the expected-return equation shows that the risk term can…
The document considers utility functions for optimal portfolio allocation that are increasing and strictly concave, with marginal utility tending to infinity near zero wealth and to zero as wealth grows. It notes that isoelastic utility, including power and…
The document considers whether investors with a persistent strategic allocation, such as a balanced equity and bond portfolio, should add option based protection against severe losses. Its motivation is asymmetric: a large loss may threaten an investor’s…
The discussion addresses how to allocate a long/short fund's compounded return to its long and short segments. Separately compounding each segment and combining the results fails because the portfolio compounds on the combined gains and losses. The exchange…
The document explains a passage about the market portfolio in the Capital Asset Pricing Model (CAPM), focusing on why an omitted risky investment may fall in price and how its expected return can then rise. The accepted response emphasizes that the argument…
The document explains ways to monitor how strongly a stock portfolio moves as a group. It distinguishes a simple average of pairwise correlations from a portfolio-level measure derived from variance. One approach computes portfolio return variance from asset…
The exchange asks how to compare modeled strategy returns when mean and standard deviation fail to capture important differences in the shape of their distributions. It proposes stochastic dominance as a framework for identifying when one return distribution…
The document explores practical estimation questions in the Fama-French family of factor models. It describes estimating a stock's factor loadings with a time-series regression, then asks how to forecast factor premiums when historical averages may not be…
The document asks why a small positive position in a risky asset improves expected utility when its mean return exceeds the risk-free rate. It decomposes end-of-period wealth into a shifted mean and a zero-mean gamble. The expected utility of that gamble is…
The document asks how to calculate ex post Sharpe ratios for decile portfolios formed from monthly returns and held for twelve months. It contrasts measuring excess returns over the full holding period with calculating monthly excess returns and annualizing…
The document surveys ways to stabilize global minimum-variance portfolio weights when the sample covariance estimate produces extreme allocations. It gives the unconstrained solution in terms of the inverse covariance matrix and describes an equivalent…
The document explains why an off-diagonal covariance in a portfolio risk matrix is difficult to interpret on its own. Covariance combines the scales of both assets’ returns, so its value is not directly a percentage or a count of standard deviations.…
The document asks how to include dividends when regressing the returns of two assets against a target asset, and how to interpret the regression for return and volatility estimates. Its concrete guidance is to avoid an ex-dividend price jump by approximating…
The document discusses how to build price histories for calculating Value at Risk on a portfolio that may include interest-rate, commodity, and equity futures. Its central concern is that contract rolls, changing liquidity, and commodity seasonality can…
The document explains why standard asset pricing models associate expected return with systematic risk rather than asset-specific risk. In the single-index model, each asset’s return combines market exposure with an independent residual. A portfolio-variance…
The document raises a portfolio-choice problem: how to allocate wealth between a risky market asset and a risk-free asset when utility rewards expected return and penalizes return variance. It gives a quadratic mean-variance utility function with a…
The document explains how to calculate the weights of a tangency portfolio from expected excess returns and the inverse covariance matrix. Multiplying the inverse covariance matrix by the excess return vector produces an unnormalized vector of asset…
The document asks how to maximize expected portfolio return while keeping risk, such as value at risk, under a chosen ceiling. The answer points to an R package with portfolio optimization routines for expected shortfall and its long-short variant,…
The document poses a mean-variance portfolio optimization problem with expected return as the reward and a quadratic penalty for risk. It adds a linear inequality requiring the portfolio’s exposure to a specified vector to meet a threshold. The covariance…
The document asks how to assign a portfolio’s yield change to separate bond purchases when the order of those purchases should not affect their attributed contributions. It describes a sequential approach: calculate the yield change after each purchase and…
The document compares ways to incorporate downside deviation, or semivariance, into portfolio optimization. It considers modifying each asset’s returns by replacing observations above a target with zero, using a covariance matrix whose diagonal contains…
This question explores an asset allocation strategy for four equity indices using excess-return forecasts from separate ARMA(1,0)-GARCH(1,1) models. The researcher wants portfolio weights to reflect expected returns and second-, third-, and fourth-order…
The document derives the covariance between returns on two portfolios from the asset-level covariance matrix. Each portfolio return is a weighted sum of individual asset returns. Applying covariance’s linearity in each argument expands portfolio covariance…