Austin Levenberg
Quantitative finance · interactive research
Four sites, each an interactive tool for a corner of the market — backtest a portfolio, pull apart a published factor, explore the volatility premium across asset classes, or look up how any stock moves around earnings. Three of them also settle a specific research question along the way, and two of those answers turned out to be “no.” Everything runs on free, public data and market-adjusted methods, and every negative result is reported as plainly as the positive ones.
Portfolio Lab
PortfoliosBacktest any asset allocation against a century of monthly returns, paste your own holdings for a factor-based reality check, compare classic strategies side by side, or model periodic contributions.
Regresses any mix on the Fama–French five factors plus momentum, shows how much the start date flattered the record, and reads the risks back in plain English.
portfolio-lab.austinlev.dev →Anomaly Replication Lab
Equity factorsExplore 18 famous published stock-return factors — open any one's full history and factor exposures, build a weighted composite of several, or set your own assumption for how many signals have been tested and watch which survive the correction.
The through-line: the average premium falls about three-quarters after the paper is published, and only a handful clear the honest significance bar.
factors.austinlev.dev →Volatility Risk Premium Lab
VolatilityCompare option-implied volatility to what actually followed — across the S&P 500, Nasdaq, crude oil and gold, broken out by year, by volatility regime, and by trend — then stress-test a short-premium strategy against every crash in the sample.
Implied has run ~3.7 points above realized for the S&P 500: a real, out-of-sample-stable premium with a sharply left-skewed tail that goes negative in every crash.
vrp.austinlev.dev →Earnings Gap Research
Earnings eventsLook up how any S&P 500 stock has behaved around its earnings — the gap, the drift, the volatility — filter thousands of events, keep a watchlist, and compare names head to head.
The headline test — does the size of the earnings-day gap predict what comes next? — is a clean null result, after correcting for costs and multiple testing.
earnings-gap.austinlev.dev →
Thinking about bundling these into one app.
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