The discussion distinguishes uncertainty in portfolio allocations from uncertainty in the inputs used to construct them. Mean-variance optimization can produce a precise allocation from estimated returns and covariances even when those parameters are poorly…
Knowledge library
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.
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2,738 documents
The document describes a backward path-integral scheme for pricing an American put on a log-price grid. At each time step, it discounts and integrates the next-step option value against a Gaussian propagator for log prices, then applies the early-exercise…
The document collects suggestions for obtaining historical index membership and constituent prices at monthly intervals. It points to professional data terminals and services, including Bloomberg, where index members can be queried with a date override and…
The thread addresses implementation questions for two-step estimation of a dynamic conditional correlation GARCH model. In the second-stage likelihood, the log of the determinant of the conditional correlation matrix is a scalar, as is the quadratic form…
The discussion distinguishes two research questions that can look similar but require different outcomes. To compare volatility estimators as forecasting inputs, regress a later realized-volatility measure on each estimator available at the forecast date. A…
The discussion compares evaluating a strategy through trade or portfolio returns with simulating a starting capital amount and measuring ending equity or annualized return. It argues that the appropriate view depends on the strategy and how closely the…
The document presents a QuantLib Python calibration attempt for a time dependent Heston model that fails with a Boost assertion. The code builds a volatility surface, creates a piecewise time dependent model, attaches an analytic pricing engine, and…
The document explains why counting losses beyond Value at Risk on the same sample used to estimate the quantile cannot validate a VaR model. For a historical VaR estimate based on past profit and loss observations, the proposed approach is to use a rolling…
The document examines a reported average duration of roughly 25 minutes for continuous ETH price rises or falls, measured in five-minute intervals over three months. The response recommends defining what would count as unusual and comparing the observation…
The document compares two ways to generate paired Brownian increments with a specified negative correlation and time-step variance. One approach draws independent standard normal samples and transforms one using the target correlation; the other draws…
The responses survey reinforcement learning (RL) applications in quantitative finance, with portfolio allocation as the main example. They describe critic-only methods, which choose actions using learned value estimates; actor-only methods, which optimize…
The note derives an unconditional-expectation form of expected shortfall from its definition as the negative conditional mean of returns in the loss tail. It uses the indicator of the event that a return falls below the VaR threshold, then applies the…
The document addresses Monte Carlo valuation of a call option on a zero-coupon bond under the Vasicek short-rate model. It first challenges the question’s stated closed-form benchmark, deriving a bond-option price using the Vasicek bond pricing function and…
The document compares two ways to scale daily trading profit and loss: dividing by the previous day’s gross portfolio value or by the account’s initial equity. These choices describe different things. The prior-day value expresses each day’s gain relative to…
The document addresses how a technically capable beginner can move from trading infrastructure and market knowledge toward designing strategies. It describes strategy as a broad category, ranging from simple rules based on price gaps to models using…
The document explains how to test whether an event day produced abnormal stock returns across a group of companies. It uses a market model fitted over an estimation window, then defines the daily average abnormal return as the cross-sectional mean across the…
The document describes a QuantLib calibration problem for the G2++ interest-rate model in a negative-rate environment. The reported error arises because the cap helper uses shifted lognormal volatility with zero displacement, which requires the strike plus…
The document describes how to enumerate every sequence of up, middle, and down moves in a trinomial tree. Its example uses recursive depth-first search: extend a partial path with each of the three moves until the desired number of steps is reached, then…
The accepted answer explains how to minimize conditional value-at-risk, also called expected tail loss, using a scenario-based linear program. It introduces portfolio weights, a variable representing the value-at-risk threshold, and one auxiliary variable…
The document describes a simulation designed to compare covariance transformations for minimum-variance portfolio construction. For each lookback window, the author samples portfolios of 100 assets, estimates a sample covariance matrix, transforms it, and…
The document frames an out-of-sample estimation question for a cointegration pairs strategy. In sample, the proposed workflow applies the Engle–Granger two-step procedure, estimates a hedge coefficient for the spread, and standardizes that spread using its…
The discussion collects several ways to transform stock prices for analysis. Suggested measures include log prices, price deviations from a mean, standardized deviations using a standard deviation, log-price deviations from a mean, log returns, percentage…
The discussion considers a daily strategy that holds positions for one day while using an indicator built from a five-year price history. Because adjacent indicator readings share much of the same input data, they are strongly serially dependent. The…
The document asks which risk-free rate to use when constructing a maximum Sharpe ratio portfolio from a rolling estimation window of monthly returns. It frames the problem within mean-variance portfolio theory, where the Sharpe ratio measures expected…