Quant Mashup - Quantt

Testing for Mean Reversion: ADF, Hurst Exponent and Half-Life [Quantt]

A time series is mean-reverting if it tends to return to a stable long-run level after being displaced from it. In pure form, that means the process has a well-defined unconditional mean and a variance that does not grow without bound; shocks decay rather than accumulate. This is the opposite of a(...)

The Ornstein-Uhlenbeck Process in Finance: Theory, Simulation and Calibration [Quantt]

What Is the Ornstein-Uhlenbeck Process? The Ornstein–Uhlenbeck (OU) process is the simplest continuous-time model of a mean-reverting random process. It was introduced in 1930 by Leonard Ornstein and George Uhlenbeck as a physical model of the velocity of a Brownian particle experiencing friction(...)

The Sharpe Ratio of Pure Noise [Quantt]

This week we backtested 2,000,000 trading strategies. Every one of them was pure noise. We generated the returns ourselves with a random number generator, so we know, with complete certainty, that the true Sharpe ratio of every single strategy is exactly zero. The best ones still looked brilliant.(...)

Lazy Prices, Lazy Investors - and the 22% Alpha Hidden in 10-Ks That Nobody Reads [Quantt]

Cohen, Malloy and Nguyen's Lazy Prices paper found that small year-on-year changes in 10-K filings predict large negative returns. Here is what the paper actually says, and how Snowflake Cortex AI and Semantic Views collapse the original eight-year engineering pipeline into an afternoon's(...)

Selling Volatility: The Most Seductive Backtest in Finance [Quantt]

Here is a strategy with a thirty-year track record. Sell one-month at-the-money put options on the S&P 500, collateralised by Treasury bills. Roll monthly. That is the entire strategy. The CBOE PutWrite Index (PUT) tracks exactly this approach. From June 1986 through December 2018, it returned(...)

Landing Your First Role - Breaking Into Quant Finance [Quantt]

Why Breaking In Feels So Hard (and Why It Is Still Achievable) If you are trying to get your first role in quantitative finance, you have probably noticed two things: Job descriptions often look intimidating Everyone online seems to have a PhD, a perfect CV, or both That can make the whole path feel(...)

New Contributor: Scaling Python Financial Models on AWS [Quantt]

How to take a Python financial model from running 150 scenarios in a Lambda function to processing over a million using AWS Step Functions, Batch, and Fargate — without managing a single server. From Laptop to a Million Scenarios You've built a financial model in Python. It runs beautifully(...)