Prediction Markets Are Literally Free Money. [Code Included]

We've done well in the major leagues, but just how far can we dominate in the minor leagues?

Making your research public has many benefits, one of which is that you get to take nostalgic walks down memory lane to see how far you’ve come. But sometimes, an old idea catches your attention.

Back in September 2022, I was first introduced to prediction markets through Kalshi’s Daily S&P 500 bracket market: I Figured Out How to Predict the Stock Market — and Still Lost Money.

This market is a wager on a range of prices for the S&P 500 Index to close at. For example, at anytime during trading we can wager that the S&P 500’s closing price will be in the range of 4,000 to 4,025.

In the first experiment, we ran a crude Monte-Carlo algorithm with historical data to estimate the optimal range and we made bets accordingly. Further, if the price appeared to be moving outside of the range throughout trading, we made another bet to hedge losses:

This went well for a brief period — however, eventually came the day where there was a significantly large move that blew past the hedge, causing us to realize losses on both positions:

After this, we quickly moved on and never revisited it — until now.

Unbeknownst to me at the time, this bet type was a crude form of short volatility trading and not just a standard speculative gamble. In the year since, we have developed exponentially more powerful tools and a significantly deeper understanding of volatility in financial markets. So, it’s only natural that we use our new toolage to correct our mistakes and come out ahead.

In a few moments, you’ll see multiple demonstrations why this research is titled as such and you’ll gain the ability to execute it yourself.

So, without further ado, let’s get right into it.