244ccaaf0b
The strategy class we never tried: harvest structural premia + risk system, not predict. Diversified futures + risk-parity/vol-target/trend; clean 5-asset-class version (ES/ZN/GC/CL/BTC). Result: plain 60/40 (Sharpe +0.72, 2010-2026) BEATS risk-parity+vol-target (+0.46) and RP+trend (+0.33, trend hurts); 5-asset+crypto RP only ties 60/40 and loses to buy-hold equity. Meta-pattern now complete in BOTH games: simple beats/equals sophisticated in prediction AND harvesting. Constructive deliverable: a simple premium harvest (60/40 / risk-parity) IS a real deployable robust strategy (~0.5-0.72 Sharpe, low DD, no prediction, minimal complexity). The engine's sophistication was never the return-generator -- deployable path is light (harvest + risk overlay), engine's value is infra/discipline/product. (Also: CAISO intraday gate blocked by OASIS plumbing.) Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
#!/usr/bin/env python3
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"""Fetch CAISO day-ahead (DAM) + real-time (RTM) hourly LMP for one hub (free OASIS, no key).
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The RT-vs-DA spread is the forecast-error-driven, less-seasonal intraday opportunity. Monthly
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chunks with backoff (OASIS rate-limits hard). Aggregates RT to hourly. Caches per chunk.
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Saves data/surfer/caiso/{dam,rtm}.json as {hour_key: price}.
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"""
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import io
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import json
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import os
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import time
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import urllib.request
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import zipfile
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NODE = "TH_NP15_GEN-APND"
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OUT = "data/surfer/caiso"
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MONTHS = [(2024, m) for m in range(1, 13)]
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def oasis(qn, market, y, m):
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s = f"{y}{m:02d}01T08:00-0000"
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ny, nm = (y + 1, 1) if m == 12 else (y, m + 1)
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e = f"{ny}{nm:02d}01T08:00-0000"
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u = (f"http://oasis.caiso.com/oasisapi/SingleZip?queryname={qn}&startdatetime={s}"
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f"&enddatetime={e}&version=1&market_run_id={market}&node={NODE}&resultformat=6")
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for a in range(5):
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try:
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raw = urllib.request.urlopen(urllib.request.Request(u, headers={"User-Agent": "curl/8"}), timeout=90).read()
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z = zipfile.ZipFile(io.BytesIO(raw))
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txt = z.read(z.namelist()[0]).decode()
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return txt
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except Exception as ex:
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time.sleep(12 * (a + 1))
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return None
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def parse_hourly(txt):
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lines = txt.strip().split("\n")
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hdr = lines[0].split(",")
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if "LMP_TYPE" not in hdr:
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return {} # error report / wrong format
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iT = hdr.index("LMP_TYPE")
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iV = hdr.index("MW") if "MW" in hdr else (hdr.index("PRC") if "PRC" in hdr else -1)
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if iV < 0:
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return {}
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iD = hdr.index("OPR_DT"); iH = hdr.index("OPR_HR")
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agg = {}
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for ln in lines[1:]:
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c = ln.split(",")
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if len(c) <= max(iT, iV, iD, iH):
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continue
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if c[iT] != "LMP":
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continue
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k = f"{c[iD]}H{int(c[iH]):02d}"
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agg.setdefault(k, []).append(float(c[iV]))
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return {k: sum(v) / len(v) for k, v in agg.items()}
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def fetch(market, qn):
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os.makedirs(OUT, exist_ok=True)
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out = {}
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for y, m in MONTHS:
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cf = f"{OUT}/{market}_{y}{m:02d}.json"
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if os.path.exists(cf):
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out.update(json.load(open(cf))); continue
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txt = oasis(qn, market, y, m)
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if not txt:
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print(f" {market} {y}-{m:02d}: FAILED"); continue
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h = parse_hourly(txt)
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json.dump(h, open(cf, "w")); out.update(h)
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print(f" {market} {y}-{m:02d}: {len(h)} hrs")
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time.sleep(6)
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return out
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def main():
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dam = fetch("DAM", "PRC_LMP"); rtm = fetch("RTPD", "PRC_RTPD_LMP") # 15-min RT pre-dispatch
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json.dump(dam, open(f"{OUT}/dam.json", "w")); json.dump(rtm, open(f"{OUT}/rtm.json", "w"))
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print(f"DONE: DAM {len(dam)} hrs, RTM {len(rtm)} hrs")
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if __name__ == "__main__":
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main()
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