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.
16,761 documents
The document presents a fitting issue in a GARCH(1,1) model estimated on return data: some datasets yield an ARCH coefficient alpha of zero and a GARCH coefficient beta near 0.999. It includes a model specification with a constant mean, no autoregressive…
The document asks whether option pricing models should be judged only by how closely their estimates match traded prices. It contrasts market-price fit, often measured with an error metric such as RMSE, with the possibility that market prices may not…
The document explains why a current Bloomberg BSYM equity list may not show every ticker historically associated with a company. Its examples involve the letter V, which has been used by both Vivendi and Visa at different times, and Chrysler's former DCX…
The document explores how to build a trading system from traditional chart patterns and machine learning. It raises choices about classification targets, whether patterns should be labels or inputs, and whether a model can identify patterns directly from…
The document frames a selection problem in an online game’s item market: prices fall when a double-experience event increases supply, and the trader wants to buy during the event and sell about a month later. The proposed starting point is to compare each…
The document discusses ways to reduce runtime when calibrating a Heston model with Monte Carlo simulations in MATLAB. The author reports using a four-core computer, 10,000 scenarios, 1,000 time steps, and `fminsearch`, with a run taking roughly half an hour…
The document asks how to convert an empirically estimated monthly expected shortfall into an annual figure. Its example estimates a lower-tail expected shortfall by averaging the worst observations in a monthly return sample, then considers two possible…
The discussion asks how to choose the number of historical candles used to estimate a spread z-score in a crypto perpetual swap pairs strategy. The question notes that different pairs appear to perform best with different window lengths in both backtests and…
The document addresses how to obtain daily bond total returns in Bloomberg, where total return includes price movement and coupon income. It notes that the equity field used as an example has no direct bond counterpart in the described workflow. The…
The document distinguishes how to combine monthly returns over a multi-period horizon. For arithmetic returns, each period’s gross return is chained multiplicatively, then one is subtracted to express the result as a cumulative percentage return. Simply…
This exchange addresses a reported annualized tracking error between Vanguard’s BND bond ETF and the Bloomberg U.S. Aggregate index over a ten-year monthly-return sample. The question treats the measured difference as evidence that passive bond investing may…
The document asks how to compare two simple regression-based trading models when the model with higher R-squared has weaker backtest results. It describes one predictor with a higher in-sample fit measure and average returns, and another with lower fit but…
The question asks whether the square-root-of-time scaling associated with diffusion in the heat equation also appears in financial price models connected to Black–Scholes. The proposed quantity is the typical distance traveled over a time interval, which…
The document asks what best practices and regulatory references should guide internal operational risk models for Basel Pillar 2, including models that produce value-at-risk or a similar capital measure. It lists components associated with the loss…
This document is a broad reading list for research on cointegration, statistical arbitrage, and pairs trading. It points readers toward foundational work on cointegration testing and error correction, empirical studies of relative-value strategies, and books…
The discussion considers how to calculate monthly cash flows across a large portfolio of loans with varied terms, including rate resets, caps, floors, balloon payments, and prepayment assumptions. Suggested approaches include using a financial software…
The note diagnoses repeated or biased-looking Monte Carlo samples caused by constructing new Mersenne Twister random number generators inside each loop iteration. Its remedy is to create the generator once before the loop and draw successive values from that…
The note explains how to include an ETF in a Monte Carlo portfolio VaR model when its full holdings are unknown. Its proposed approach is to treat the ETF as one instrument and model its returns like those of an individual stock, rather than estimating and…
The document explains how a binary strategy signal becomes a sequence of trading orders in a simple moving-average backtest. The signal represents the desired position: zero means holding no shares, while one means holding a share. Taking the signal's first…
The document asks how to generate monthly forecasts for interest rates, inflation, and unemployment while preserving their relationships in Monte Carlo simulations. It describes using a covariance matrix to represent the variables’ joint dependence, then…
The discussion separates signal generation in a realistic backtest from statistical inference about predictive relationships. For price-based rules such as moving-average crossovers or Bollinger Bands, the answers advise using the original historical prices,…
The document asks how to divide a fixed history between parameter development and out-of-sample validation when deciding whether to add an independent strategy to a portfolio. It offers no universally supported split: the best choice depends on the data and…
The document surveys public and commercial sources for historical nominal yield curves across countries. It distinguishes fitted constant-maturity zero-coupon or par curves from generic benchmark bond yields, which usually track on-the-run securities and are…
The document describes a factor attribution exercise for a backtested equity strategy. The researcher aggregates strategy returns monthly, obtains monthly Fama–French factor returns, and runs a multivariate regression. The resulting fit is low, prompting…