release: v0.19.0

examples/16_hashrate_exogene.py

@@ -1,4 +1,4 @@
-"""Example 16: BTC-Hashrate Spread — Exogenous Data Strategy.
+"""Exogenous data — a BTC/hashrate spread as a signal.
 
 Thesis: Bitcoin hashrate is a proxy for miner commitment and network
 security.  When BTC price drops but hashrate holds (or rises), miners
@@ -10,6 +10,15 @@ The strategy normalizes both BTC price and hashrate via EMA ratios
 A rolling z-score of the spread generates the signal: negative z means
 price is cheap relative to hashrate (long), positive means expensive.
 
+Demonstrates:
+  - an exogenous series ASOF-joined onto the bar grid
+  - a spread between two EMA-normalised series as a signal
+  - a rolling z-score turning that spread into a position
+
+Data: shared store — real BTC bars from `data/`, plus a hashrate series
+(fetched, or generated by the sample generator below when absent).
+See examples/README.md.
+
 Exogenous data flow:
     1. Fetch hashrate CSV (or use sample generator below)
     2. Register via  mbt.register_exo("hashrate", df)
@@ -18,6 +27,9 @@ Exogenous data flow:
 
 Prerequisite:
     Binance BTC perp data  +  hashrate exo registered in data/mega/exo/
+
+Usage:
+    python examples/16_hashrate_exogene.py
 """
 
 import time