The difference between using 2521 or 2562 as the number of trading
days in a year
is minor for most individual traders. When calculating daily
volatility:
\[ \sqrt{256} = 16 \] \[ \sqrt{252} \approx 15.88 \]
For example, with an annualized volatility of 60%, the
expected volatility over
30 days is:
\[ \frac{0.6}{\sqrt{256}} \times \sqrt{30} \approx 0.205 \] \[ \frac{0.6}{\sqrt{252}} \times \sqrt{30} \approx 0.207 \]
The difference—around 0.002—is negligible at small scales.
According to GPT, 256 is more commonly used in software tools
for analysis and
simulation. That’s because computers handle powers of 2 more
efficiently using
integer math, which offers faster performance than
floating-point calculations.
So, 256 is often chosen to improve speed, trading a tiny bit of
accuracy for
efficiency.
One thing to note: the error grows with larger numbers. But
for most retail
traders, the impact is minimal unless you’re working with tens
of millions.