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.
5,018 documents
The document asks whether a time-delay neural network (TDNN) could use economic-calendar information to predict forex prices. Its motivating challenge is that news effects may persist beyond the release time and may appear in market movements beforehand, so…
The document asks how to measure and penalize wiggliness when fitting piecewise constant or piecewise linear interpolations. A common smoothness penalty integrates the square of the second derivative, but it does not distinguish these interpolation types…
The document describes several ways banks and financial institutions test portfolio and balance-sheet resilience. These include regulator-provided scenarios, shocks based on past events, and reverse stress analysis, which searches for plausible conditions…
The document presents an intuitive way to connect discrete random walks with heat diffusion, suitable as a starting point for an undergraduate explanation. In the discrete-time picture, heat at a location is distributed among its nearest neighbors at each…
The document considers whether a mathematics PhD graduate should take time to refresh finance and quantitative subjects before applying for quant roles. The response recommends preparing for interviews by reviewing foundational mathematics, probability and…
The document explains how to pursue GARCH-based simulation and forecasting in Python, distinguishing conditional volatility modeling from implied volatility. GARCH models describe the changing conditional variance of asset returns; forecasts and simulated…
The discussion considers whether cryptography and speech recognition methods inform financial forecasting, with the accepted answer reframing cryptography as information theory. It connects Kelly-style allocation to sizing capital across strategies and notes…
The document considers appending a random sample to existing data while specifying its correlation with each existing series. It emphasizes that arbitrary correlations may be infeasible without assumptions about the joint distribution. Under a multivariate…
This note answers whether a credit-scoring variable's Information Value (IV) can exceed one and what happens when a feature perfectly separates good and bad outcomes. IV sums the differences between the good and bad population shares in each category,…
The document asks how to fit a time series with a fixed sum of sine and cosine terms when both coefficients and periodicities are to be chosen. It identifies a difficulty with trying many possible frequencies in trigonometric regression and asks whether an…
The note surveys alternatives to the Gaussian distribution for fitting empirical stock returns, emphasizing heavy tails and the distinction between describing returns and pricing derivatives. It discusses stable Paretian distributions, the Heston…
The document presents an EGARCH specification for changes in a series and its conditional log variance. The mean equation includes seasonal indicators and two regime indicators interacting with seasonal effects. The variance equation includes lagged…
The document presents an integral method for finding the conditional expectation of one component of a trivariate normal vector when two other components are restricted by upper bounds. It first obtains the conditional density of the target variable by…
The document discusses using language models to assist with data cleaning and backtesting, focusing on the difficulty of verifying research logic. Its example is a rolling signal intended to use observations through the prior period; generated code…
The document considers whether bootstrap resampling can create useful alternate histories for tuning trading-system parameters such as moving-average windows and entry or exit thresholds. Its answer emphasizes controlling overfitting through structured…
The document raises a methodological question about directly optimizing a trading rule or neural network with negative Sharpe ratio as its loss. The author sees a clear use in portfolio optimization but questions its behavior for a single asset with bounded…
The question asks how to reduce a continuous time series to a smaller set of recurring pattern states, then model transitions among those states as a Markov chain. This is a regime-detection problem: observations are treated as outcomes associated with…
The document introduces the term quant and offers a broad definition: a quant applies mathematical modeling to financial markets, data, or complex instruments. It also lists a role taxonomy associated with Mark Joshi, including front-office,…
The document collects suggested reading for someone implementing option pricing with Markov chain Monte Carlo methods. One cited paper applies MCMC to continuous-time option models, including constant-volatility, stochastic-volatility, price jump-diffusion,…
The document presents an R implementation of a normal-innovation NGARCH(1,1) model intended for five-minute stock returns. The conditional variance updates from a constant, a lagged variance term, and a squared lagged standardized shock shifted by an…
The document asks whether MATLAB’s `garchset` and `garchfit` interfaces allow dummy or explanatory variables in the conditional variance equation, analogous to regressors in the mean equation. It seeks a way to specify such a model, rather than only adding…
The note discusses whether studying Itô and Malliavin calculus is useful for someone pursuing algorithmic trading. Its central distinction is between quantitative researchers focused on forecasting and risk from market data, and researchers who build or…
The responses distinguish parameters estimated from data from hyperparameters chosen to configure a model. A parametric example assumes that two variables follow a specified probability distribution and estimates its means and covariance from observed…
The document surveys several ways to group systematic trading strategies. Strategy families include trend and reversal approaches, price or technical methods, fundamental, yield, growth, and quality signals, as well as arbitrage, market making, sentiment…