Backtesting Predexon signals

import requests
from datetime import datetime, timezone

BASE = "https://api.predexon.com"
HEADERS = {"x-api-key": "YOUR_API_KEY"}

def smart_wallets():
    # Top-100 wallets by realized profit
    return requests.get(
        f"{BASE}/v2/polymarket/leaderboard",
        headers=HEADERS,
        params={"sort_by": "realized_profit", "limit": 100},
    ).json()

def smart_net_flow(token_id, start_sec, end_sec, wallet_set):
    trades = requests.get(
        f"{BASE}/v2/polymarket/trades",
        headers=HEADERS,
        params={
            "token_id": token_id,
            "start_time": start_sec,
            "end_time": end_sec,
            "limit": 1000,
        },
    ).json()
    net = 0.0
    for t in trades:
        if t["maker"] not in wallet_set and t["taker"] not in wallet_set:
            continue
        size = float(t["size"])
        net += size if t["side"] == "BUY" else -size
    return net

import pandas as pd

smart = {w["wallet"] for w in smart_wallets()["wallets"]}

results = []
for t0 in decision_times:                  # e.g. every hour
    pre  = smart_net_flow(TOKEN, t0 - 3600, t0, smart)   # last hour
    p_t0 = price_at(TOKEN, t0)
    p_t1 = price_at(TOKEN, t0 + 14400)     # 4h horizon
    results.append({"t": t0, "flow": pre, "ret": p_t1 - p_t0})

df = pd.DataFrame(results)
print(df.groupby(pd.qcut(df["flow"], 5))["ret"].mean())