Long Volatility

Yes! If implied volatility (IV) rises, your options become more valuable even without stock movement. This is the 'vega' profit. For example, if you buy a straddle and XVI rises from 12 to 16, your position gains ~10-15% just from IV expansion, regardless of stock price.

Your maximum loss is the premium paid for the options. If you buy a A$300 straddle, the most you can lose is A$300 (if the stock is exactly at the strike at expiration). This makes long vol a defined-risk strategy.

Use IV Rank (current IV compared to past year's range) and IV Percentile (% of days IV was lower). IV Rank below 30% or IV Percentile below 25% generally indicates cheap volatility. Also compare XVI to its historical range (12-18 is typically low).

Because you don't know which direction the stock will move! If you're confident about direction, use directional strategies. If you just know the stock will move (but not which way), a straddle/strangle profits from either direction. The cost is higher, but you don't need to guess direction.

Theta decay erodes your position daily. An A$300 straddle might lose A$5-10 per day to theta. If the stock stays still for 2 weeks, you might lose A$70-140 (20-45%). This is why long vol needs catalysts - pure time passage hurts you.

The straddle price approximates the expected move. If ATM straddle costs A$5 on a A$100 stock, the market expects a 5% move. More precisely: Expected move ≈ Straddle price × 0.85 (for options near expiration). Compare to historical moves to assess if this is cheap or expensive.

It depends on your thesis. If playing for IV expansion pre-event, exit before the event (capture vega, avoid IV crush). If playing for the actual move, hold through - but accept that IV crush may offset some gains. Many traders take partial profits pre-event, hold rest for the move.

You maintain a long option position and hedge the delta with stock. As stock rises, delta becomes positive - sell stock to neutralize. As stock falls, delta becomes negative - buy stock to neutralize. Each round-trip captures the 'gamma' as profit. Success requires: active management, tight spreads, and realized vol exceeding implied vol.

Use straddle when: Expecting moderate move, want maximum gamma, can afford higher premium. Use strangle when: Expecting very large move, want lower cost/risk, accept wider breakevens. Strangles cost ~50% less but need ~20% bigger move to profit.

Options: (1) Cut loss at 50% and move on - thesis was wrong. (2) Roll to later expiration - give more time if thesis intact. (3) Sell one leg (turn straddle into directional) - if you now have a directional view. (4) Hold for catalyst if still approaching. Key: Have rules before entry, not after.

Sell XJO straddle/strangle (short index vol). Buy straddles on major constituents (BHP, CBA, CSL, NAB - top 4-5 stocks). Weight single-stock positions by their index weight. You're betting realized correlation will be lower than implied. Risk: Correlation spikes in crisis cause losses on both sides.

From index variance relationship: Index variance ≈ Σw²σ² + ρ × (Total variance - Σw²σ²). Solve for ρ: ρ = (σ_index² - Σw²σ²) / (Σ cross-terms). If implied ρ > historical ρ, dispersion may be attractive. Tools exist to calculate this from option chains.

Generally 30-60 DTE balances gamma exposure against theta decay. Shorter DTE (14-21) has high gamma but brutal theta. Longer DTE (90+) has lower gamma but manageable theta. For events: Choose expiration just after the catalyst to capture the move with adequate time.

Allocate 0.5-1% of portfolio annually to rolling puts or straddles. Use 3-month OTM puts rolled quarterly. Target 10-15% OTM for moderate protection or 20% OTM for tail-only protection. Accept that most periods you lose premium (insurance cost), but outlier events pay massively.

Yes. ML can identify vol regime shifts from microstructure data (order flow, correlation patterns, options flow) with higher accuracy than simple rules. Features: VIX term structure, put/call ratios, realized/implied vol spread, cross-asset correlations. Challenge: Overfitting and regime changes.