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 describes a proposed statistical arbitrage workflow: enumerate combinations of assets, estimate hedge weights by regressing one asset on the others, and seek a spread with substantial high-frequency variation but little low-frequency drift. A…
The discussion asks whether it is useful to solve a second optimization problem near the solution of a nonconvex problem, particularly when the two problems use different solvers. The response connects this idea to several established numerical optimization…
This discussion recommends literature for readers with a mathematical background who want to study optimization in finance. The suggestions range from treatments of efficient frontier calculations and Markowitz portfolio construction to a technical book…
The document explains how to derive the weight for one asset in a two-asset risk-budgeting portfolio. Each asset's contribution to portfolio volatility is set to its assigned budget, with budgets expressed as shares that sum to one. To remove portfolio…
This question concerns a quadratic program for portfolio weights that fails with an error reporting inconsistent constraints. The setup uses an identity objective matrix, zero linear term, return data for 15 assets, a fully invested constraint, and…
The document asks how to describe scarce capacity for holding inventory or investments. Its examples include dealership lots, oil storage, warehouses, and an investment portfolio where an existing holding may need to be sold to fund a more attractive…
The document surveys ways principal component analysis may inform equity strategies and portfolio construction. One cited approach removes common return components and seeks mean reversion in the residual returns of individual securities. It also mentions…
The document presents a lump-sum allocation problem: divide capital among segments with different deferral periods, interest rates, and payment durations so that each segment reaches the same ending value. The proposed method defines each segment's growth…
The document answers a question about calculating weekly turnover for a portfolio that rebalances regularly. It gives a basic measure: take the smaller of total purchases or total sales and divide by the portfolio’s market value. This convention measures one…
The document outlines a linear programming formulation for selecting securities to fund a known schedule of future payments at minimum initial cost. It recommends expressing required payments as a cumulative total through each month, then doing the same for…
The document asks how to calculate the future value of an account funded by an initial contribution and regular additions, given a share price, a constant annual return, and a fixed number of periods. The response concludes that the ordinary or due annuity…
The response outlines a practical portfolio construction process for a large stock universe: screen holdings to a manageable set, estimate or model their covariance, impose linear portfolio constraints, and choose an objective that balances risk, alpha, and…
The document surveys ways to turn value investing into measurable stock-selection signals. It lists valuation measures such as dividend yield, earnings yield, price-to-book, return on equity, and accrual-based earnings quality, alongside related signals…
The document considers how to visualize a fund or portfolio that contains both positive-valued holdings and small negative items such as accrued fees or foreign-exchange hedging marks. The questioner prefers a pie-like representation and is looking for an…
The document addresses how to estimate Value at Risk for a portfolio that receives regular contributions and is rebalanced between a risky asset and a risk-free bond. Its central distinction is between external cash flows and investment performance: deposits…
The document explains how the Rockafellar-Uryasev formulation turns CVaR optimization into a linear program. A reader asks how VaR is calculated within the optimization and whether the constraint defining each scenario's excess loss is redundant because that…
The document considers how to model dependence when individual market series have heavy-tailed, approximately Student t marginals. It explains that a conventional multivariate t distribution imposes a t copula with a shared degrees-of-freedom parameter,…
The document explains that two stocks’ average returns do not determine their correlation. Correlation measures how paired returns move together over observations, while averages describe each series’ central value. The example gives two return series with…
The document explains why portfolio skewness and kurtosis objectives do not fit standard quadratic programming. Variance is quadratic in portfolio weights, but skewness and kurtosis involve third- and fourth-order terms, respectively, so flattening tensors…
The document considers adding vanilla interest rate swaps to an existing Monte Carlo VaR process for foreign exchange and commodities. The proposed simplified method estimates volatility and correlation from daily changes in par swap rates, simulates rate…
The document asks how to estimate future values for a portfolio containing a stock, a long-term coupon bond, and a European call option. It provides example daily inputs for the stock price, required yield, volatility, and short-term interest rate, and asks…
The document examines whether imposing sector neutrality erases the information in a stock trading signal. In its example, two technology stocks receive positive positions based on a contrarian signal, then the positions are adjusted to sum to zero. With…
The document develops a proposed way to approximate how estimation errors in two assets’ variances and their correlation affect the estimated variance of a weighted portfolio. It starts from the standard two-asset portfolio variance formula, expresses…
The document explains why weights from PortfolioAnalytics’ rebalancing optimizer can differ from weights produced by a separate call to its portfolio optimizer. Rebalancing occurs at specified data endpoints, and at each endpoint the rolling window…