\section{LLM approach}

\textcolor{red}{Dennis is confused. Charlie, if this is your prompt, please move to your section.}






To compute non-parametrically the p-value of the 10 and 15 minute predictions.

Take the overall fraction of true +1s and the overall fraction of true -1s (ignore the 0s). Let's say total number of true +1 and -1 is N. [Ed: isn't N the total number of predictions?]
count := 0
Do 10000 times
 * make N random +1/-1 predictions based on the above fractions
 * Accrandom = compute the accuracy (predicted +1 intersect true +1) + (predicted -1 intersect true -1)/N
 * if accrandom > observed accuracy then count+= 1
end do
p-value is count/N [Ed: count/10000?]




Tasks for July 12:

Charlie: put in the new prompts, run the p-value code (perhaps with Anthony's help), ask for competitive LLM articles from Anthony. Volatility prediction.
Description of where you obtained the data (both time series and article data).

Allen: Thousands of article and confusion matrix for the above times.

Beakal: More experimental results. Commit data to github.

Eli: Your sections and Real data to Beakal.

Zakaria: Try exchange rate. And use the classification of profit rate.

Ermiyas: Expand the data.