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 considers the data needed for a Dynamic Nelson-Siegel relative-value model, with emphasis on whether zero-coupon rates reflect traded instruments or are interpolated. For US Treasuries, coupon and principal STRIPS are identified as traded…
The document asks whether a portfolio optimization problem can use an equality constraint on the sum of absolute position weights instead of the usual equality constraint on their signed sum. The distinction is that the L1 constraint fixes total absolute…
The document argues that optimal trade size is not determined by a price forecast alone, even when leverage is treated as unlimited. Position changes should follow from an objective that balances expected alpha against portfolio risk and trading costs,…
The document presents a finite-horizon Merton investment-consumption problem with wealth invested in a risky asset and reduced by consumption. Under CRRA power utility, it states an optimal risky allocation proportional to risk tolerance and gives a…
The document explains how to represent and calculate returns for an equal-dollar long-short portfolio. Dollar neutrality means the current market values of the long and short sides have equal magnitude; a short position still has a market value even though…
The document addresses how to select a risk-free return when portfolio performance is measured monthly. Its central point is that a five-year Treasury yield does not provide a known risk-free return over a one-month holding period: the bond’s market price…
The document considers whether combining a strategy with 20% annualized volatility and one with 15% volatility, when their returns have zero correlation, can produce a portfolio with volatility below 15%. The accepted response uses the portfolio variance…
The document considers how to measure relationships between hedge fund returns when distributions are skewed and heavy-tailed, with particular interest in how funds behave together during market declines. It explains why Pearson correlation may be…
The document proves an identity for the variance of a portfolio return. Starting from the portfolio return as a weighted sum of constituent returns, expand its variance into a double sum of weighted pairwise covariances. Covariance is linear in either…
The document explains why a portfolio can beat a benchmark even when its estimated CAPM beta is below one. In a time-series regression of excess portfolio returns on excess benchmark returns, beta measures sensitivity to benchmark movements; it does not by…
The document surveys Python tools for strategy research, backtesting, portfolio analysis, and live trading. It describes backtrader in the most detail: it supports event-style and vectorized runs, multiple assets and strategies, varied data sources and…
The document explains how minimum-variance and minimum-tracking-error portfolio problems relate to quadratic programming and second-order cone programming. It clarifies that expressing a continuous convex risk constraint as a cone constraint does not remove…
The document explains how to test whether a signal predicts returns by sorting securities into portfolios according to the signal, then comparing high-signal and low-signal groups. A spread portfolio is formed by going long the high group and short the low…
The document considers how to size three long and short currency positions to target a specified annual portfolio volatility while allocating risk equally. The proposed procedure first scales each currency position separately so that each standalone position…
The document asks how to infer the expected returns that would produce a given fully invested portfolio under mean-variance optimization, given its weights, risk aversion, and return covariance matrix. The accepted answer gives a simple relation: implied…
The document asks why investors are shown historical price and fund-return data if past performance does not guarantee future results. The responses offer several uses: assessing a manager's record relative to a benchmark, examining consistency or hit rates,…
The document distinguishes factor returns from the risk premia estimated by the second stage of a Fama-MacBeth regression. After estimating assets’ factor loadings in time-series regressions, the second stage regresses cross-sectional returns on those…
The document poses a portfolio mapping problem that arises when factor returns are whitened and then reduced or transformed into secondary factors. It distinguishes the time series of original factor returns from the matrix of asset portfolios associated…
The document examines whether portfolio Value-at-Risk can be derived by treating asset returns as multivariate t distributed. It explains that each individual component of a multivariate t vector has a univariate t marginal with the same degrees of freedom.…
The document surveys ways to estimate covariance matrices when a portfolio universe contains many assets. It identifies two broad approaches: shrinkage, which reduces estimation noise in a conventional sample covariance matrix, and factor models, which…
This exchange considers how to update expected asset returns when rebalancing a Markowitz portfolio day by day. The question proposes incorporating each new observation into the historical sample and recalculating the expected returns and portfolio weights.…
The document describes several ways to select bonds for a butterfly trade, depending on the rationale for the position. For a relative-value or mean-reversion trade, a trader can assess whether the middle maturity looks unusually rich or cheap against the…
The document distinguishes dollar neutrality from market neutrality and addresses how to benchmark a dollar-neutral strategy with nonzero market beta. Equal dollar amounts on the long and short sides do not necessarily cancel market exposure. The response…
The note reframes the search for an equal-weighted basket of a fixed number of stocks with minimum volatility as a portfolio optimization problem rather than an ordinary knapsack problem. Portfolio variance depends on the full covariance matrix, including…