Pair Trading Strategy

Random stock pairs lack the statistical relationship needed for mean reversion. You need stocks that are fundamentally related (same sector, similar business) and statistically proven to have a cointegrated relationship. Without this, the spread can diverge permanently and never revert, causing losses.

For share-based pairs: roughly A$30,000-50,000 to trade 2-3 pairs with proper position sizing and borrow/short arrangements. For CFD-based pairs: less, due to leverage, but financing costs accrue. The key is having enough to diversify across multiple pairs while keeping each pair's risk at 2% of capital.

This is the main risk in pair trading. You have a stop loss at Z = 3.5 - if the spread widens beyond this, exit the trade accepting the loss. Also investigate why the spread diverged - it could be a structural break (M&A news, demerger, etc.) that means the pair is no longer valid.

Yes, but shorting shares requires a margin loan and arranging stock borrow (securities lending), and only stocks on the approved short-sell list can be covered-shorted under ASIC rules. CFDs are easier for two-sided shorting with built-in leverage. Start with whatever you're comfortable with, prioritising liquid instruments.

Daily monitoring of Z-score and correlation is recommended. Weekly deep review of cointegration status. Set alerts for Z-score approaching exit targets (0.5) or stop levels (3.5). Pair trades are not set-and-forget - active monitoring is essential.

Avoid new entries 3-5 days before either stock's results (most ASX large-caps report half-yearly, around February and August). For existing positions, consider reducing size or tightening stops. Results can cause temporary divergence that eventually reverts, but can also trigger stop losses. Some traders close all pairs during peak reporting season.

Shares: no expiry, can hold indefinitely, sized precisely, but shorting needs a margin loan and borrow. CFDs: built-in leverage, easy two-sided shorting and precise sizing, but financing costs accrue. Options (ASX ETOs): defined risk and leverage, but theta decay, Greeks complexity, and you must check option liquidity. Choose based on holding period, capital, and comfort with derivatives.

Investigate the cause: stock-specific news (a clinical/FDA issue, management change, demerger) may be permanent for that stock. Market-wide fear causing divergence is usually temporary. If correlation drops below 0.60 for >2 weeks without an obvious temporary cause, assume the relationship may have broken and exit.

Ratio spread is generally better - it's normalised for different price levels and more stable over time. Price spread works for similar-priced stocks. Beta-adjusted spread is most accurate for proper hedging. Start with ratio spread, graduate to beta-adjusted for precision.

Optimal is 5-8 pairs for diversification without over-complexity. Too few (1-2) = concentrated risk. Too many (>10) = difficult to monitor and manage, with diminishing marginal benefit. Ensure sector diversification - maximum 2 pairs from the same sector.

Generate all sector pairs from liquid stocks. Filter sequentially: correlation > 0.70, cointegration p < 0.10, half-life 3-25 days, stable relationship. Rank remaining pairs by composite score (cointegration strength, half-life, stability, liquidity). Walk-forward validate. Rerun quarterly.

For pair selection: XGBoost/Random Forest classification (profitable vs not). For entry timing: gradient boosting with Z-score features + momentum + regime. For exit: reinforcement learning or supervised regression. Ensemble ML with traditional rules - use ML to filter, not replace, fundamental logic.

Calculate volatility (std dev of daily P&L) for each pair. Weight = 1/Volatility, normalised to sum to 100%. Lower-volatility pairs (banking) get more capital, higher-volatility (resources/tech) get less. Rebalance monthly. This equalises risk contribution across pairs.

Track: (1) average correlation among ASX 200 constituents (high = trending), (2) A-VIX level (>25 = elevated risk), (3) market breadth (extreme = trending, mixed = mean-reverting). Combine into a regime score. Adapt allocation and thresholds based on regime.

Execute the less liquid leg first. Use algorithmic execution (TWAP/VWAP) for large sizes. Place limit orders to capture bid-ask. Track slippage and execution cost - should be <20% of expected profit. For very large positions, consider spreading execution over multiple days or using options/CFDs.