What is Drawdown in Trading?
Short answer: Drawdown is the peak-to-trough decline in your portfolio before it recovers.
You bought at $10,000. Portfolio climbed to $15,000. Then dropped to $9,000. That’s a 40% drawdown — measured from the $15,000 peak to the $9,000 trough.
Why it matters more than you think:
| Drawdown | Gain Needed to Recover |
|---|---|
| 10% | 11% |
| 25% | 33% |
| 50% | 100% |
| 75% | 300% |
A 50% loss requires a 100% gain just to break even. The math is brutal and asymmetric.
The emotional side: Drawdowns don’t just hurt your portfolio — they hurt your decision-making. Most blown accounts aren’t from bad trades; they’re from panic selling at the bottom of a drawdown.
Mark’s take: We track drawdown exposure in real-time. Knowing how deep you are helps you decide: ride it out, or cut losses before the hole gets deeper.
Maximum Drawdown vs Volatility: What’s the Difference?
Short answer: Volatility measures the bumpiness of the ride. Maximum drawdown measures the worst crash.
Volatility:
- How much an asset swings day-to-day
- Measured as standard deviation of returns
- Goes both ways — up and down
- Tells you about average conditions
Maximum Drawdown (MDD):
- The single worst peak-to-trough drop in history
- Only measures downside
- Tells you about worst-case conditions
- What actually blows up accounts
The trap: Two assets can have identical volatility but wildly different max drawdowns. Asset A swings 5% daily but trends steadily. Asset B swings 5% daily but occasionally flash-crashes 60%.
Same volatility. Very different risk.
Example from crypto:
- BTC volatility: ~60-80% annualized
- BTC max drawdown: -83% (2017-2018 cycle)
Volatility tells you the normal experience. Max drawdown tells you the worst experience. Plan for both.
Which matters more? Depends on your goal:
- Volatility matters for position sizing and leverage
- Max drawdown matters for survival and psychology
Tail Risk and Fat Tails Explained
Short answer: Tail risk is the danger of extreme events that “shouldn’t” happen based on normal statistics — but do.
Normal distributions lie to you:
Standard finance models assume returns follow a bell curve. Most days are average, extremes are rare, and really extreme events are nearly impossible.
Reality: Markets have “fat tails” — extreme events happen far more often than the bell curve predicts.
What fat tails look like:
| Event | Normal Distribution Says | Reality |
|---|---|---|
| 3-sigma move (3 std dev) | Once every 1.5 years | Multiple times per year |
| 5-sigma move | Once every 4,776 years | Every few years |
| 10-sigma move | Basically never | 2008, 2020 March, crypto regularly |
Why it happens:
- Leverage — Forced liquidations cascade
- Herding — Everyone runs for the exit at once
- Illiquidity — No buyers when everyone sells
- Feedback loops — Selling begets more selling
In crypto: Fat tails aren’t the exception — they’re the norm. A “once in a century” move in stocks is a “once a quarter” move in altcoins.
What to do about it:
- Never use models that assume normal distributions for risk
- Size positions assuming the “impossible” will happen
- Keep dry powder for fat-tail events (both crashes and rips)
VaR vs CVaR Explained
Short answer: VaR tells you the door to the danger zone. CVaR tells you how bad it gets once you’re inside.
Value at Risk (VaR):
- “What’s the worst loss I’ll see 95% (or 99%) of the time?”
- Example: “95% VaR of $10,000” means on 95% of days, you won’t lose more than $10K
- Tells you where the threshold is
Conditional Value at Risk (CVaR) / Expected Shortfall:
- “When I do cross that VaR threshold, what’s the average loss?”
- Example: “Your CVaR at 95% is $25,000” means when bad days happen, expect ~$25K losses
- Tells you how bad “bad” really is
Why CVaR matters more:
VaR has a fatal flaw: it ignores what happens in the worst 5% of cases.
Imagine two portfolios:
- Portfolio A: 95% VaR = $10K, worst case ever = $12K
- Portfolio B: 95% VaR = $10K, worst case ever = $500K
Same VaR. Wildly different actual risk. CVaR catches this.
Practical example:
You’re trading a leveraged altcoin position.
- VaR says: “95% of days, you won’t lose more than 15%”
- CVaR says: “On that bad 5%, expect to lose 40% on average”
VaR got you in the door. CVaR tells you whether you can survive what’s on the other side.
Expected Shortfall in Risk Management
Short answer: Expected Shortfall (ES) is another name for CVaR — the average loss when things go wrong.
Regulators and risk managers increasingly prefer ES over VaR because it:
- Captures tail risk (what happens in extreme scenarios)
- Is “subadditive” (diversification always helps, mathematically)
- Doesn’t ignore the worst-case scenarios
How to think about it:
VaR answers: “How bad could a normal bad day be?” Expected Shortfall answers: “How bad could a really bad day be?”
Calculating it (simplified):
- Look at your return distribution
- Find the worst X% of outcomes (usually 5% or 1%)
- Average those losses
That average is your Expected Shortfall.
In practice:
| Metric | Your Portfolio |
|---|---|
| 95% VaR (daily) | -$5,000 |
| 95% Expected Shortfall | -$12,000 |
Translation: Most bad days cost you up to $5K. But on truly bad days, expect $12K average losses.
Why Mark tracks this: Trend analysis isn’t just about direction — it’s about risk regime. When volatility expands and momentum weakens, expected shortfall rises. That’s when you tighten stops or reduce size, before the tail event hits.
Putting It All Together: A Risk Framework
Here’s how these concepts connect:
- Volatility tells you how bumpy the normal ride is
- Drawdown tells you how deep the current hole is
- Max Drawdown tells you the worst historical hole
- VaR tells you where “bad” starts (the threshold)
- CVaR/Expected Shortfall tells you how bad “bad” actually gets
- Fat Tails remind you that “impossible” events happen regularly
The hierarchy of risk awareness:
- Amateur: “This is volatile but I can handle it”
- Intermediate: “I know my max drawdown exposure”
- Advanced: “I’ve sized for my CVaR, not just my VaR”
- Professional: “I assume fat tails and plan for the ‘impossible’”
Mark gives you visibility into where you stand — so you can make informed decisions before the market makes them for you.
Risk management isn’t about avoiding losses. It’s about surviving them. [See how Mark tracks risk regimes →]