Drawdown

Quick Reference

Perdita cumulativa dal picco precedente. Misura quanto capitale perdi durante losing streaks.

Definizione

Drawdown = (Peak Value - Current Value) / Peak Value

Maximum Drawdown = Peggiore drawdown mai sperimentato in un periodo.

Esempio

Capital progression:
$100,000 → $120,000 (new peak) → $90,000 (drawdown) → $130,000 (new peak)

Drawdown = ($120,000 - $90,000) / $120,000 = 25%

Quando raggiungi $130,000, drawdown torna a 0%.

Tipi di Drawdown

Maximum Drawdown (Max DD)

Peggiore calo peak-to-trough nella storia:

Max DD = Worst (Peak - Trough) / Peak

Esempio: Strategy con max DD 40% ha perso 40% del capital nel worst period.

Average Drawdown

Media di tutti i drawdown periods: - Più rappresentativo di typical experience - Max DD può essere outlier

Current Drawdown

Drawdown attuale dal most recent peak: - 0% = sei a new high - >0% = sei underwater

Drawdown vs Volatility

Non sono la stessa cosa!

Volatility: Misura quanto returns variano Drawdown: Misura cumulative losses

Esempio: - Alta volatilità + positive drift = drawdown contenuti - Bassa volatilità + negative skew = drawdown catastrofici

Expected Drawdowns

Per Volatility Target

Con SR 0.5, zero skew, target volatility:

Vol Target Typical Max DD 10% Prob DD
12.5% -15% -9%
25% -30% -19%
50% -60% -38%
100% -90% -62%

Lesson: Higher vol target = much deeper drawdowns!

Per Skew Type

Stesso SR 0.5, vol 25%:

Zero skew: - Typical max DD: -30% - Smooth recovery

Negative skew: - Typical max DD: -35% - Sharp drops, slow recovery

Positive skew: - Typical max DD: -35% - Gradual decline, sharp recovery

Recovery Time

Time to new high dopo drawdown:

Formula approssimata:

Recovery Time ≈ DD% / (SR × Vol Target)

Esempio (30% DD, SR 0.5, Vol 25%):

Recovery ≈ 30% / (0.5 × 25%) = 2.4 anni

Long time!

Psychological Impact

Typical Reactions

10% DD: Uncomfortable ma manageable 20% DD: Dubbi sulla strategia 30% DD: Strong urge to quit 40%+ DD: Panic, likely abandon system

This is normal human behavior!

Managing Psychology

  1. Know expected DD beforehand: No surprises
  2. Size positions appropriately: Lower vol = smaller DD
  3. Track average DD, not just max
  4. Plan response in advance: "At -30% I will review, not panic-exit"

Drawdown e Sharpe Ratio

Higher SR non garantisce lower DD:

Strategy A: SR 0.8, negative skew - Average DD: -20% - Max DD: -60% (rare tail event)

Strategy B: SR 0.4, positive skew - Average DD: -25% - Max DD: -35%

Strategy B psychologically easier despite lower SR!

Underwater Period

Time spent below previous peak:

Anche con profitable system: - 30-50% del tempo underwater typical - Long periods senza new highs normal

Don't panic se sei underwater per mesi.

Drawdown Limits

Hard stops (not recommended): - Exit system at -X% DD - Problem: Spesso esci al bottom, miss recovery

Soft monitoring: - Review system at -X% DD - Check se qualcosa broken - But: Don't auto-exit based on DD alone

Reducing Drawdowns

Lower Volatility Target

Vol 50% → 25% = Halve expected drawdowns

Trade-off: Halve expected returns too!

Positive Skew Strategies

Trend following, breakout: - Smoother DD profiles - Easier psychologically

Diversification

Multiple uncorrelated strategies: - Reduce DD substantially - Best risk/return improvement

Drawdown Control

Dynamic position sizing può aiutare:

Bad idea: Cut size when in DD (lock in losses) Good idea: Cut size when volatility spikes (prevents future DD)

Difference crucial!

Monitoring Drawdown

Track: 1. Current DD 2. Time underwater 3. Average DD (rolling) 4. Max DD to date

Compare to expected DD from backtests.

Red flag: Actual DD >> Expected DD suggerisce problema.

Drawdown Examples

2008 Financial Crisis

Typical quant fund: - Max DD: -40% to -60% - Recovery: 2-4 years

Lesson: Even good systems have severe DD.

COVID March 2020

Equity long-only: - Max DD: -35% - Recovery: 6 months (V-shaped)

Lesson: Fast DD can have fast recovery.

Calmar Ratio

Alternative performance metric:

Calmar = Annual Return / Max DD

Focuses on DD instead of volatility.

Problema: Based su single worst event (noisy).

Errori Comuni

  • Equating DD to risk: Vol è better continuous measure
  • Panic at expected DD: -30% DD può essere normale per strategy
  • Comparing only max DD: Average DD more representative
  • Ignoring time underwater: Long periods normale
  • Stop-loss based on DD: Usually exit at worst time
  • Assume small vol = small DD: Negative skew can cause large DD anche con low vol

Concetti Correlati

  • [[Skew]] - negative skew aumenta DD risk
  • [[Volatility Targeting]] - riduce DD volatility
  • [[Kelly Criterion]] - optimal sizing considera DD probability
  • [[Risk Adjusted Returns]] - DD alternative metric