Volatility and Drawdowns

“Risk” is one of the most used and least defined words in finance. For most people it simply means: how much could I lose? Professionals measure it more precisely, with tools worth knowing – including their weaknesses.

Volatility: how much things swing#

The most common risk measure is volatility. It measures how widely an investment’s returns scatter around their average – statistically, the standard deviation. Some typical annual volatilities:

What does that mean in practice? If returns are roughly normally distributed, about two-thirds of yearly results fall within one standard deviation of the average and about 95% within two. A stock market with a 7% expected return and 16% volatility therefore delivers somewhere between −9% and +23% in two out of three years – and in one year in twenty, something outside −25% to +39%.

The simulator shows how differently a single year can unfold with the same expected return:

Drawdown: how deep can it go?#

Volatility treats moves up and down the same. Investors don’t: nobody complains about a surprise gain. What hurts is the drawdown – the loss from the last peak to the trough. The maximum drawdown is the largest such loss in a period.

The math of recovery#

Gains and losses aren’t symmetrical. Lose 50% and you’re left with half – which then has to double to get you back:

That’s why it’s so important to avoid large losses you can’t sit out – through diversification, a sensible mix of stocks and bonds, and by steering clear of excessive leverage.

Crashes in history#

Major stock markets have fallen hard several times:

Including dividends and with broader diversification, recovery times were often shorter – after 1929, for example, reinvested dividends and the falling price level of the 1930s meant real wealth recovered well before 1954. Still, the table makes the point: if you own stocks, expect to see half your portfolio’s value disappear on paper at some point.

Fat tails: when the improbable happens#

Many risk models assume returns are normally distributed – they follow the familiar bell curve. Reality has fatter tails: extreme days happen far more often than the bell curve predicts.

On 19 October 1987, “Black Monday”, the Dow fell 22.6% in a single day. Under a normal distribution with the volatility of the time, such a day would have been so improbable that it should never have happened in the history of the universe. It happened anyway.

The lesson: volatility is a useful measure for normal times. For crises, scenarios and historical drawdowns are often the more honest tools.

Time changes risk – but not the way many think#

Over a single day, the stock market is close to a coin flip. Over a year, the US market has risen in about three out of four years. Over 20-year periods, there have historically been few stretches in which broadly diversified stocks lost money in real terms. Longer holding periods reduce the probability of a loss.

At the same time, the range of possible outcomes widens. And there are markets like Japan after 1990, where even 20 years weren’t enough. “Nothing can go wrong in the long run” is too simple. The truth is: time is a powerful ally, especially combined with broad international diversification.

Summary#

Volatility measures normal swings; drawdown measures the painful fall from a peak. Gains and losses are asymmetric, which makes big losses so dangerous. Historically, even broad stock markets have lost half their value, and extreme events are more common than simple models assume. Risk can’t be eliminated – but it can be measured, diversified and dosed so you can stick with it in hard times.