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 works through the net delta of a portfolio containing long calls, long puts, and short calls with different strikes and expiries. It explains that each option’s delta must be calculated for its own terms, then multiplied by the position size and…
The document considers how to incorporate market capitalization into a portfolio built with hierarchical risk parity (HRP). Its response distinguishes three approaches: risk contribution methods use volatility and correlation to allocate portfolio risk;…
The document explains why an example of portfolio diversification does not contradict the general result that Value at Risk (VaR) can fail subadditivity. In the cited stock example, the combined portfolio’s VaR is below the sum of the individual VaRs,…
The note explains why an investor might hold an efficient portfolio. By definition, an efficient portfolio offers the highest available return for its level of risk, or equivalently the best risk and return combination within its class. Its appeal follows…
The note gives a practical use of singular value decomposition in quantitative finance: diagnosing a square matrix that cannot be factorized by Cholesky because it is not positive definite. SVD can help assess whether the matrix can be adjusted to become…
The document defines DV01 as the change in a fixed-income portfolio’s value for a one-basis-point change in interest rates. Active DV01 describes that sensitivity relative to a benchmark. A negative active DV01 of the stated size means the portfolio is…
The document proposes a practical framework for combining analyst return paths when their errors share information, change with market conditions, and may include useful contrarian views. It starts from forecast-error covariance: under quadratic loss,…
The note introduces the inverse-volatility portfolio (IVP) as a heuristic allocation that assigns more weight to lower-volatility assets. It contrasts this approach with equal weighting and Markowitz mean-variance methods, which require covariance estimation…
The document outlines a basic way to use a hidden Markov model (HMM) in portfolio allocation. The model estimates latent market states, asset drifts, and state-specific covariance matrices. For each state, the estimated return and risk inputs can then be…
The document explains a proposed way to divide non-maturity deposits into core and non-core balances for interest rate risk modeling. It distinguishes stable balances, which tend to remain on account, from core balances, which are also unlikely to reprice…
The document addresses a misconception about parametric value at risk: that a parametric model necessarily assumes portfolio assets are independent and therefore uncorrelated. Parametric describes a model built around parameters governing a joint probability…
The document asks how copulas connect known marginal distributions to a joint distribution when random variables are dependent. It identifies the joint cumulative distribution as distinct from the product of the marginals, which applies only under…
The document explores how behavioral assumptions about perceived correlations affect mean-variance portfolio optimization. It compares a model that modifies the covariance matrix using parameters for correlation neglect with an alternative that represents…
The document derives the correlation between an asset and a weighted portfolio from constituent weights, volatilities, and pairwise correlations. The covariance between the asset and portfolio is the weighted sum of its covariances with each constituent.…
The document raises a portfolio construction question about weighting common shares by market value when a company also has publicly traded preferred shares. The data source reports separate market values for common and preferred stock, and the investor…
The document surveys competing views on using genetic algorithms (GAs) to find financial trading rules or construct portfolios. The main concern is that searching many combinations can produce rules that fit historical data by chance, with data snooping and…
The document discusses how to compare a trading account with market indices when the account receives deposits or makes withdrawals. Its main procedure assumes cash flows are recorded in the closing balance after that day’s trading. It removes that day’s…
The discussion compares high-beta and low-beta equity portfolios and asks how to judge their risk-adjusted performance. Under CAPM assumptions, an investor can combine the market portfolio with borrowing or lending at the risk-free rate to reach a preferred…
The document gives a Bloomberg Terminal workflow for viewing historical sector weights of an index, using the S&P 500 as its example. It directs users to the index membership function to see constituents, then to the Historical Summary tab, where a chart…
The document explains how to combine the interest-rate sensitivity of discounted insurance claims and recoveries. It treats the cashflows as a portfolio and uses value-weighted durations, with recoveries represented by a negative value. The resulting net…
The document explains why researchers may analyze a fundamental factor by forming portfolios from equities at the high and low ends of its values, rather than regressing returns directly on raw factor values across the whole universe. These groups can reveal…
The document explains why a portfolio’s residual return is uncorrelated with the market return when beta is estimated by ordinary least squares on the same return observations. It writes portfolio returns as an intercept, a market component, and a residual,…
The document distinguishes exact and approximate factor models by the structure allowed for residual covariance. In an exact factor model, the residual covariance matrix is diagonal, so residual movements are uncorrelated across assets. In an approximate…
The discussion presents ways to generate covariance matrices while controlling variance levels. One standard construction separates scale from dependence: place desired standard deviations on a diagonal matrix and combine it with a valid correlation matrix…