MMC Payouts Adjustment Proposal

Data Science
24

Some code to check your historical payout using only CORR or MMC or CORR+MMC:

#!/usr/bin/env python3

import numerapi
import matplotlib.pyplot as plt
import pandas as pd
import sys
import numpy as np

api = numerapi.NumerAPI()

# metrictoplot = 'corr'
# metrictoplot = 'mmc'
# metrictoplot = 'comb'
# metrictoplot = 'all'

metrictoplot = sys.argv[1]

username_list = ['integration_test', 'sugaku']

fig1 = plt.figure()
cmap = plt.cm.get_cmap('tab20b', len(username_list)*3)
i = 0
for user in username_list:
	print("Collecting data for: ", user)
	user_df = pd.DataFrame(api.daily_submissions_performances(user)).sort_values(by="date").groupby("roundNumber").last()
	start_round=np.min(user_df.index)
	end_round=np.max(user_df.index) # most recent resolved round
	stake_corr = 1.0 # initial stake
	stake_mmc = 1.0
	stake_comb = 1.0
	for r in range(start_round, end_round):
		if r in user_df.index:
			corr_score = user_df.loc[r, "correlation"]
			mmc_score = user_df.loc[r, "mmc"]
		else:
			corr_score = 0.0
			mmc_score = 0.0
		if np.isnan(user_df.loc[r, "correlation"]) or np.isnan(user_df.loc[r, "mmc"]):
			corr_score = 0.0
			mmc_score = 0.0
		if corr_score:
			stake_corr *= 1.0 + corr_score*1.0
			stake_mmc *= 1.0 + mmc_score*2.0 #2x leverage for mmc
			stake_comb *= 1.0 + corr_score+mmc_score
		user_df.loc[r, "weekly_stakes_corr"] = stake_corr
		user_df.loc[r, "weekly_stakes_mmc"] = stake_mmc
		user_df.loc[r, "weekly_stakes_comb"] = stake_comb

	color = cmap(float(i)/len(username_list))

	if metrictoplot == "corr":
		plt.title('Expected CORR payout for models', fontsize=17)
		user_df.weekly_stakes_corr.plot(label=user, color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_corr"], user, color=color, fontweight="bold")
	if metrictoplot == "mmc":
		plt.title('Expected MMC payout for models', fontsize=17)
		user_df.weekly_stakes_mmc.plot(label=user, color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_mmc"], user, color=color, fontweight="bold")
	if metrictoplot == "comb":
		plt.title('Expected CORR+MMC payout for models', fontsize=17)
		user_df.weekly_stakes_comb.plot(label=user+'_comb', color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_comb"], user+'_COMB', color=color, fontweight="bold")
	if metrictoplot == "all":
		plt.title('Expected CORR and MMC payout for models', fontsize=17)
		user_df.weekly_stakes_corr.plot(label=user+'_corr', color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_corr"], user+'_CORR', color=color, fontweight="bold")
		user_df.weekly_stakes_mmc.plot(label=user+'_mmc', color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_mmc"], user+'_MMC', color=color, fontweight="bold")
		user_df.weekly_stakes_comb.plot(label=user+'_comb', color=color)
		plt.text(end_round-0.75, user_df.loc[r, "weekly_stakes_comb"], user+'_COMB', color=color, fontweight="bold")
	i += 1

plt.grid(linestyle='--', linewidth=0.5, color="black")
plt.xlabel('Round number')
plt.ylabel('Expected payout factor')
plt.xticks(np.arange(start_round, end_round, 1), rotation=60)
ax = plt.gca()
ax.set_facecolor((0.9, 0.9, 0.9))
plt.show()

sys.exit()
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