Trends/Statistics and risk

Skewness

Whether big daily moves have been more often up or more often down.

Statistics and riskBest on 3Y, 5YAlso called return skew

Illustration of the skewness shape. It is a sketch, not real price data.

What it shows

Skewness measures the lopsidedness of the daily return distribution. Positive skew means the largest moves have been up. Negative skew means the largest moves have been down. Zero means balanced.

It is calculated from the last 252 daily returns.

How we find it

The same code that draws it on your chart follows these steps, with the same result every time.

Daily returns for 252 days.
Subtract the mean and divide by the standard deviation.
Cube them and average.
Plot as a rolling line.

Starting values: Window 252 bars. These are proposed and will be tuned on real price data before launch.

How to read it

The panel shows skewness.
Above zero: bigger up days.
Below zero: bigger down days.

Status labels you may see

Label	What it means
Positive	Above 0.5.
Balanced	−0.5 to 0.5.
Negative	Below −0.5.

What cancels it

Nothing cancels it.

What traders check next

Kurtosis.
The biggest single days.
Window.

Limits

One huge day dominates.
Needs a long window.
Not stable.

Try it in forecastviz

Open any ticker and choose Statistics and risk → Skewness in the left menu.
Switch between 3Y, 5Y to see how the picture changes.
Compare with Kurtosis and Rolling Sharpe ratio on the same chart.

Open on a ticker

Questions

Why care?

The usual bell-shaped assumptions ignore it.

Do stocks usually have negative skew?

Index returns often do. Individual stocks vary.