Pairs Trading FTSE-DAX

Yes! Australian brokers offer UK100 and GER40 CFDs. European session is 5:00 PM - 1:30 AM AEDT, which is evening/night trading in Australia. Set alerts and manage positions during Australian morning.

For CFDs, you can start with A$10,000-20,000 due to leverage. For full position sizing and proper risk management, A$50,000+ is recommended. Size positions so each pair risks no more than 2-3% of account.

Pairs trading has different risks. Market risk is hedged (market neutral), so drawdowns are typically smaller (10-15% vs 30-40%). But there's correlation risk - if the relationship breaks, both legs can move against you.

Daily monitoring is recommended. Check z-score, correlation, and regime at European close. The trade typically lasts 5-15 days. Set alerts for z-score thresholds and correlation warnings.

If 30-day correlation drops below 0.70, exit the trade regardless of z-score. Correlation breakdown means the statistical relationship is failing. Accept a small loss rather than hoping for recovery.

Use Engle-Granger test: Regress FTSE on DAX, then run ADF test on residuals. p-value < 0.05 means cointegrated. In Python: `from statsmodels.tsa.stattools import coint; score, pvalue, _ = coint(ftse, dax)`.

Yes, use rolling hedge ratio (60-day lookback). β changes over time. For more precision, use Kalman filter for dynamic estimation. Static hedge ratios from long history may be outdated.

Most traders accept currency as part of the spread (simpler approach). The hedge ratio partly captures it. For pure spread exposure, hedge GBP/EUR position separately. For trades < 2 weeks, currency impact is usually small.

Half-life < 15 days is ideal for FTSE-DAX. 8-12 days is optimal. If half-life exceeds 25 days, the pair is reverting too slowly - reduce size or skip. Half-life > 40 days is near random walk.

Yes, but it's complex. You can use options on FTSE and DAX for defined risk. Long spread: Buy FTSE calls, buy DAX puts. But managing two option legs with different expirations and Greeks is challenging.

Use pykalman in Python. Model hedge ratio as hidden state that evolves over time. Tune process noise (trans_cov) for adaptation speed - higher = faster but noisier. Typical range: 0.0001 to 0.01. Backtest to optimize.

Geopolitical events (Brexit), monetary policy divergence (ECB vs BoE), sector-specific shocks (UK financials crisis), or fundamental economic divergence. Monitor correlation and cointegration monthly. Relationship usually restores within 3-12 months.

Combine uncorrelated pairs: FTSE-DAX (European), SPX-NDX (US), BHP-RIO (commodities). Check pair-to-pair correlation (<0.3 ideal). Use risk budgeting for allocation. Max 4-6 pairs active. Total portfolio risk 8-10%.

Entry Z = ±2.0 to ±2.5 is optimal. Higher threshold = fewer but better trades. Exit at Z = 0 for full mean reversion. Analysis shows Z = ±2.5 achieves 72% WR vs 65% at Z = ±2.0. Trade-off: fewer opportunities.

Monitor: 1) 30-day rolling correlation (warning if < 0.80), 2) Rolling half-life (warning if doubles), 3) Monthly cointegration test (warning if p-value > 0.05). Combine into regime score. Reduce exposure when score deteriorates.