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 addresses how to incorporate technical indicators, such as RSI, ATR, and moving averages, alongside historical returns when assigning portfolio weights. Its central suggestion is to use a model that converts selected inputs into expected returns…
The document frames selecting a fixed number of assets with low mutual correlation as a subset optimization problem. It defines a score based on the squared correlations among chosen assets and describes a Threshold Accepting search: start from a candidate…
The post formulates Kelly sizing for multiple simultaneous bets whose returns may be correlated. It represents the outcomes as a joint return vector with a probability density and the bet sizes as a vector. Expected logarithmic wealth is then expressed as an…
The document considers rolling portfolio optimization when some assets have shorter histories and therefore lack observations within the full estimation window. It begins from the pairwise structure of a covariance matrix: each asset pair may have a…
The document distinguishes two ways to build low-volatility equity portfolios: ranking stocks by standalone volatility or beta, and minimizing portfolio variance using a covariance matrix subject to constraints. It asks whether optimized minimum-volatility…
The document distinguishes money management as the broad activity of managing an investor's assets from asset allocation and portfolio optimization as parts of that activity. It describes decisions at three levels: strategic allocation across broad asset…
The document asks how to set market capitalization weights for a Black–Litterman portfolio holding international and emerging-market equities, gold, long-term Treasury bonds, and real estate. Its central advice is not to use the market values of the ETFs…
The document explains how to estimate asset exposures to factors and how to interpret factor-attributed returns in an Arbitrage Pricing Theory framework. For a single factor, exposure is the covariance between factor and asset returns divided by the factor’s…
The document explains how to choose a representative benchmark when a trading strategy is opaque but has extensive historical data. A clear strategy, such as one holding only long positions in technology stocks, can be compared with a closely related market…
The document asks why portfolio beta is often calculated as the weighted sum of the component betas instead of being estimated directly from the portfolio’s aggregate return. It gives the definition of an asset’s beta as its covariance with the market…
The document outlines a workflow for constructing and evaluating factor models of asset returns. Begin by selecting factors with an economic rationale, then gather factor and test-asset data. For portfolio-based factors, construction choices include…
The document considers whether performance ratios should penalize upside volatility as well as losses. It identifies the Sortino ratio as a downside-focused alternative to the Sharpe ratio and also discusses expected shortfall, conditional value at risk, and…
The document describes a historical simulation for a sovereign bond portfolio. Each bond is repriced under country yield curves shifted by historical scenarios, with shifts applied across markets together to retain their co-movement. Scenario price returns…
The discussion examines why a stock can have value even when its company pays no dividend and an investor holds too few shares to influence management. Replies describe several sources of value: expected future cash flows, retained earnings, buybacks,…
The discussion compares optimizing over the S&P 500 with optimizing over the broader S&P 1500. Because the smaller index is contained within the larger one, the larger-universe optimization can reproduce any feasible S&P 500 portfolio by assigning zero…
The document derives portfolio risk and marginal risk contributions under a factor model. Asset returns are represented by factor exposures plus specific residual risk, giving the asset covariance matrix as the factor covariance projected through the loading…
The document describes a two-asset portfolio exercise using monthly prices to calculate returns, means, variances, standard deviations, covariance, and correlation. The investor uses those inputs to trace a mean-variance frontier, identify the…
The document compares two neural-network asset pricing models that use firm characteristics and macroeconomic variables to estimate time-varying stochastic discount factors and tangency portfolios. It reports differing out-of-sample performance, portfolio…
The document asks how to combine separately calculated long and short portfolio returns to compare their performance visually with an index. It defines each side’s return as a weighted average of constituent returns, normalized by the sum of weights within…
The document presents a question about constructing a self-financing portfolio that replicates a call option in a two-period binomial tree. The investor has option payoffs at the terminal date, arbitrage-free option prices at the intermediate nodes, and the…
The document asks when the Kelly criterion is optimal outside familiar distributional assumptions. One response derives the criterion from repeated bets: under suitable long-run frequency assumptions, the growth rate is governed by expected log wealth, and…
The question describes extreme long and short weights produced when mean returns are scaled by an inverse covariance matrix and then normalized to sum to one. The displayed covariance matrix has positive eigenvalues, so the example is not explained by a…
This document raises a portfolio optimization question about setting an aspirational skewness target in a mean-variance-skewness-kurtosis framework. The example code maximizes a weighted sum of each asset’s individual skewness, subject to fully invested,…
The document asks whether the probability density of portfolio returns can be obtained by weighting and adding the return densities of its constituent assets. It starts from the familiar expression for portfolio return as a weighted sum of asset returns,…