Add files via upload

2025-07-23 14:44:57 +01:00
parent a030b61f4f
commit 7d02222da7
14 changed files with 1036 additions and 0 deletions
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+import os
+import requests
+import random
+import streamlit as st
+import numpy as np
+import pandas as pd
+from dateutil import parser
+from oandapyV20 import API
+from oandapyV20.endpoints.pricing import PricingInfo
+from cip import theoretical_forward, deviation_bps
+from streamlit_autorefresh import st_autorefresh
+
+# Auto-refresh every 5 seconds
+st_autorefresh(interval=5_000, key="refresh")
+
+# Page configuration
+st.set_page_config(page_title="FX Arbitrage Dashboard", layout="wide")
+
+# --- Credentials via Streamlit secrets & Endpoints ---
+# Create a file at ~/.streamlit/secrets.toml (or ./fx_arbitrage/.streamlit/secrets.toml) with:
+#
+# [oanda]
+# token      = "<YOUR_OANDA_TOKEN>"
+# account_id = "<YOUR_OANDA_ACCOUNT_ID>"
+#
+# [slack]
+# webhook = "<YOUR_SLACK_WEBHOOK_URL>"
+#
+# Streamlit will auto-load this file into st.secrets
+OANDA_TOKEN      = st.secrets["oanda"]["token"]
+OANDA_ACCOUNT_ID = st.secrets["oanda"]["account_id"]
+SLACK_WEBHOOK    = st.secrets.get("slack", {}).get("webhook", "")
+PRACTICE_SWAP_API = "https://api-fxpractice.oanda.com"
+
+# Initialize OANDA client for spot data
+client = API(access_token=OANDA_TOKEN, environment="practice")
+
+# --- Sidebar controls ---
+st.sidebar.header("Settings")
+override_provider = st.sidebar.selectbox(
+    "Forward-Rate Provider", ["Manual", "Swap-Points"]
+)
+manual_bps = st.sidebar.slider(
+    "Manual forward offset (bps)", -10.0, 10.0, 0.0, step=0.1
+)
+threshold_bps = st.sidebar.number_input(
+    "Deviation threshold (bps)", 0.5, 10.0, 1.0, step=0.5
+)
+stop_loss_bps = st.sidebar.number_input(
+    "Stop-loss threshold (bps)", 0.0, 20.0, 2.0, step=0.5
+)
+spread_bps = st.sidebar.number_input(
+    "Spread cost per trade (bps)", 0.0, 5.0, 0.1, step=0.1
+)
+tenor_days = st.sidebar.number_input(
+    "Tenor days", 1, 90, 30
+)
+pairs = st.sidebar.multiselect(
+    "Currency pairs", ["EUR_USD", "GBP_USD", "USD_JPY"], default=["EUR_USD", "GBP_USD", "USD_JPY"]
+)
+
+# Initialize histories
+if 'history' not in st.session_state:
+    st.session_state.history = {pair: [] for pair in pairs}
+if 'fwd_history' not in st.session_state:
+    st.session_state.fwd_history = {pair: [] for pair in pairs}
+
+# --- Utility functions ---
+def fetch_spot(pair):
+    pricing = client.request(
+        PricingInfo(accountID=OANDA_ACCOUNT_ID, params={"instruments": pair})
+    )
+    bid = float(pricing["prices"][0]["bids"][0]["price"])
+    ask = float(pricing["prices"][0]["asks"][0]["price"])
+    return (bid + ask) / 2
+
+
+def fetch_swap_point(pair):
+    """Fetch the daily swap-point for the given tenor."""
+    url = f"{PRACTICE_SWAP_API}/v3/accounts/{OANDA_ACCOUNT_ID}/instruments/{pair}/swap_rates"
+    headers = {"Authorization": f"Bearer {OANDA_TOKEN}"}
+    resp = requests.get(url, headers=headers)
+    if resp.status_code != 200:
+        return 0.0
+    for r in resp.json().get("swapRates", []):
+        if r.get('tenor').endswith('D') and int(r.get('tenor')[:-1]) == tenor_days:
+            lr = float(r.get("longRate", 0))
+            sr = float(r.get("shortRate", 0))
+            return lr - sr
+    return 0.0
+
+
+def simulate_pnl(spot0, obs_fwd, days, sims=500):
+    pnls = []
+    for _ in range(sims):
+        path = spot0
+        daily = []
+        for _ in range(days):
+            shock = random.uniform(-0.005, 0.005)
+            path *= (1 + shock)
+            daily.append(1e6 * (path - obs_fwd))
+        pnls.append(daily)
+    return np.array(pnls)
+
+# --- Data collection & metrics ---
+data_rows = []
+for pair in pairs:
+    spot_mid = fetch_spot(pair)
+
+    # Determine observed forward
+    if override_provider == "Manual":
+        theo_fwd = theoretical_forward(spot_mid, 0.025, 0.005, tenor_days)
+        obs_fwd = theo_fwd * (1 + manual_bps / 10_000)
+    else:
+        swap_pts = fetch_swap_point(pair)
+        obs_fwd = spot_mid + swap_pts * tenor_days / 360
+        theo_fwd = theoretical_forward(spot_mid, 0.025, 0.005, tenor_days)
+
+    dev_bps = deviation_bps(obs_fwd, theo_fwd)
+
+    # update histories
+    hist = st.session_state.history[pair]
+    hist.append(dev_bps)
+    if len(hist) > 50:
+        hist.pop(0)
+    st.session_state.history[pair] = hist
+
+    fh = st.session_state.fwd_history[pair]
+    fh.append(obs_fwd)
+    if len(fh) > 50:
+        fh.pop(0)
+    st.session_state.fwd_history[pair] = fh
+
+    # signal
+    if dev_bps > threshold_bps:
+        sig = "Rich → Sell forward"
+    elif dev_bps < -threshold_bps:
+        sig = "Cheap → Buy forward"
+    else:
+        sig = "No arbitrage"
+
+    # PnL calculation
+    cost = spread_bps / 10_000 * 1_000_000
+    raw_pnl = (obs_fwd - theo_fwd) * 1_000_000
+    pnl = raw_pnl - cost
+    stop_amt = stop_loss_bps / 10_000 * 1_000_000
+    if pnl < -stop_amt:
+        pnl = -stop_amt
+
+    data_rows.append({
+        "Pair":             pair,
+        "Spot Mid":         f"{spot_mid:.6f}",
+        "Observed Forward": f"{obs_fwd:.6f}",
+        "Theoretical Fwd":  f"{theo_fwd:.6f}",
+        "Deviation (bps)":  f"{dev_bps:+.2f}",
+        "Signal":           sig,
+        "PnL ($)":          f"{pnl:,.0f}"
+    })
+
+    if SLACK_WEBHOOK and sig != "No arbitrage":
+        requests.post(SLACK_WEBHOOK, json={"text": f"Arb alert: {pair} {dev_bps:+.2f}bps → {sig}"})
+
+# --- Summary Metrics ---
+col1, col2, col3, col4 = st.columns(4)
+# parse PnL values from data_rows
+pnls = [float(r["PnL ($)"].replace("$","").replace(",","") ) for r in data_rows]
+total_pnl = sum(pnls)
+win_rate  = np.mean([1 if v>0 else 0 for v in pnls]) * 100
+max_dd     = min(pnls)
+current_dev= data_rows[0]["Deviation (bps)"]
+col1.metric("Total PnL", f"${total_pnl:,.0f}")
+col2.metric("Win Rate", f"{win_rate:.1f}%")
+col3.metric("Max Drawdown", f"${max_dd:,.0f}")
+col4.metric("Current Dev", f"{current_dev} bps")
+
+# --- Display dashboard ---
+st.title("FX Arbitrage Dashboard — Live")
+st.dataframe(pd.DataFrame(data_rows), use_container_width=True)
+st.markdown("**Auto-refreshes every 5s**")
+
+# Deviation & Forward History
+st.subheader("Deviation History (bps)")
+for pair in pairs:
+    st.line_chart(pd.DataFrame({pair: st.session_state.history[pair]}))
+
+st.subheader("Observed Forward History")
+for pair in pairs:
+    st.line_chart(pd.DataFrame({pair: st.session_state.fwd_history[pair]}))
+
+# PnL Distribution
+st.subheader(f"PnL Distribution at Day {tenor_days}")
+for pair in pairs:
+    spot_mid = fetch_spot(pair)
+    if override_provider == "Manual":
+        theo_fwd = theoretical_forward(spot_mid, 0.025, 0.005, tenor_days)
+        obs_fwd = theo_fwd * (1 + manual_bps / 10_000)
+    else:
+        swap_pts = fetch_swap_point(pair)
+        obs_fwd = spot_mid + swap_pts * tenor_days / 360
+    sims = simulate_pnl(spot_mid, obs_fwd, tenor_days, sims=1000)
+    st.write(f"{pair} PnL Histogram")
+    st.bar_chart(pd.Series(sims[:, -1], name=pair))
+
+# --- Equity Curve ---
+st.subheader("Equity Curve (last 50 bars)")
+for pair in pairs:
+    # compute per-bar PnL from history and forward history
+    pnl_series = []
+    for obs, dev in zip(st.session_state.fwd_history[pair], st.session_state.history[pair]):
+        spot_val = fetch_spot(pair)
+        theo_val = theoretical_forward(spot_val, 0.025, 0.005, tenor_days)
+        raw = (obs - theo_val) * 1_000_000
+        cost = spread_bps/10_000 * 1_000_000
+        pnl_val = raw - cost
+        stop_amt = stop_loss_bps/10_000 * 1_000_000
+        pnl_series.append(max(pnl_val, -stop_amt))
+    equity = np.cumsum(pnl_series)
+    st.line_chart(pd.DataFrame({pair: equity}))
+
+