Add granularity tracking, drop intermediate columns, add SQL schema

Track granularity (M1/M5) through the pipeline so rows are
distinguishable after upload. Drop helper columns (tr, typical_price,
pv) from the feature DataFrame. Add SQL schema with composite PK on
(time, instrument, granularity).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

sql/create_fx_candles.sql

@@ -0,0 +1,20 @@
+CREATE TABLE fx_candles (
+    time         TIMESTAMPTZ   NOT NULL,
+    instrument   TEXT          NOT NULL,
+    granularity  TEXT          NOT NULL,
+    open         DOUBLE PRECISION,
+    high         DOUBLE PRECISION,
+    low          DOUBLE PRECISION,
+    close        DOUBLE PRECISION,
+    volume       INTEGER,
+    ret          DOUBLE PRECISION,
+    logret       DOUBLE PRECISION,
+    sma_3        DOUBLE PRECISION,
+    sma_20       DOUBLE PRECISION,
+    ema_20       DOUBLE PRECISION,
+    rsi_14       DOUBLE PRECISION,
+    vol_20       DOUBLE PRECISION,
+    atr_14       DOUBLE PRECISION,
+    vwap_20      DOUBLE PRECISION,
+    PRIMARY KEY (time, instrument, granularity)
+);