K-Ratio Calculator
Enter your net value (equity) series and time points. We compute the slope of the equity curve via linear regression and the standard deviation of daily (period) returns, then K-Ratio = slope ÷ std(returns).
One value per line or comma-separated. Positive numbers only. First value = earliest period.
Slope of log(equity) vs time ÷ std(period returns)
Linear regression is applied to log(net value) vs time index (0, 1, 2, …). Period returns are log(V_t / V_{t-1}). K-Ratio = slope / std(returns). Higher K-Ratio suggests more consistent growth relative to volatility.
What is the K-Ratio?
The K-Ratio is a performance metric that compares the slope of an equity (net value) curve to the volatility of period returns. You fit a linear regression to the log of net values over time to get a slope (growth rate per period), then divide that slope by the standard deviation of the period-by-period log returns. A higher K-Ratio indicates more consistent growth relative to variability; it is similar in spirit to a Sharpe-like measure but based on the equity curve slope and return volatility directly.
How to use this calculator
- Net value series: Enter your equity or net value at each time point—e.g. end-of-day account values. One number per line or comma-separated. Use at least 3 values.
- Time points: We assume equally spaced periods (0, 1, 2, …). The first value is period 0, the next period 1, and so on.
- The tool computes the slope of log(equity) vs time, the standard deviation of period log returns, and then K-Ratio = slope ÷ std(returns).
Why use our K-Ratio calculator?
All calculations run in your browser—no server round-trip—so you get instant results. Use it to evaluate a strategy or portfolio curve: a higher K-Ratio suggests more stable, consistent growth relative to the volatility of returns. The formula is transparent: linear regression on the log equity curve plus standard deviation of period returns.
Frequently asked questions
What units is the slope in?
The slope is in “per period” units because we regress log(net value) on time index. For daily data, it is the average daily log return implied by the linear fit; for monthly data, the average monthly log return.
Why use log returns?
Log returns are time-additive and symmetric, and the slope of log(equity) vs time has a direct interpretation as growth rate per period. Using the same log returns for the standard deviation keeps units consistent in the K-Ratio.
What is a good K-Ratio?
There is no single “good” value; it depends on your benchmark and risk tolerance. Generally, a higher K-Ratio means more consistent growth per unit of return volatility. Compare strategies or time windows using the same period length (e.g. all daily or all monthly).
Disclaimer: This calculator is for educational and informational purposes only. The K-Ratio does not guarantee future performance. Trading and investing involve risk; manage position size and consult a qualified advisor as needed.
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