Build on the signal layer

curl https://api.pulsesignals.ai/v1/sentiment/NVDA \
  -H "Authorization: Bearer rgp_live_..." \
  -H "Accept: application/json"

# backtest.ipynb — AI sentiment signal vs. forward returns
import pandas as pd
from pulse_signals import Client

client = Client(api_key="rgp_live_...")

# Pull 6 months of sentiment + price
df = client.sentiment("NVDA", period="6m").to_frame()

# Simple signal: long when sentiment > 60, flat otherwise
df["signal"] = (df["sentiment"] > 60).astype(int)
df["fwd_ret"] = df["price"].pct_change().shift(-1)
df["strategy"] = df["signal"] * df["fwd_ret"]

equity = (1 + df["strategy"].fillna(0)).cumprod()
print("Total return:", round((equity.iloc[-1] - 1) * 100, 1), "%")