NumerAI: Week 4

My fourth week was just submitting my results from my vanilla neural network. I didn’t get enough time to actually work through my era neural network. I am also concerned that once I do get it working it will take more work on the weekends to run it as I have to find the matching eras.

257 Results

While I won’t know my real results (the action of my model predictions versus the real life market movement) I did get the results from the “test” data. It wasn’t great. I was in the bottom 15%. I expected this so it wasn’t a big deal.

CORR Rank4850/6229 (+246)
CORR Reputation-0.0944 (+.0033)
MMC Reputation-0.0955 (+.0029)
FNC Reputation-0.0957 (+.0021)
Current Reputation (Build over the last 20 rounds)

Validation Sharpe0.636314.97%
Validation Corr0.016020.05%
Validation FNC0.011232.74%
Corr + MMC Sharpe0.512411.01%
MMC Mean0.004175.73%
Corr With Example Preds0.4026
Diagnostic Results

NumerAI: Week 3

My third week included getting my results back (bottom 15%) and looking at different ways that I can use the feaures.

256 Results

While I won’t know my real results (the action of my model predictions versus the real life market movement) I did get the results from the “test” data. It wasn’t great. I was in the bottom 15%. I expected this so it wasn’t a big deal.

CORR Rank5096/6025
CORR Reputation-0.0977
MMC Reputation-0.0984
FNC Reputation-0.0978
Current Reputation (Build over the last 20 rounds)
Validation Sharpe0.636314.97%
Validation Corr0.016020.05%
Validation FNC0.011232.74%
Corr + MMC Sharpe0.512411.01%
MMC Mean0.004175.73%
Corr With Example Preds0.4026
Diagnostic Results

Data Analysis

The first thing I am looking at doing is trying to figure out “what” each column/section means. In doing so I was checking to see what the average of each column was and it turns out it is 0.5.