The Sortino ratio measures how much return an investment earns for each unit of downside risk. It takes the average return above a risk-free rate and divides it by the standard deviation of negative returns only. Upside swings are not counted as risk. This guide covers the formula, a worked example, the score ranges, the difference from the Sharpe ratio, and the limits to keep in mind when comparing funds or trading strategies.
TL;DR
- The Sortino ratio is (return minus risk-free rate) divided by downside deviation. Only losses below a target count as risk.
- Under Schwab's guideline, above 1.00 is good, above 2.00 is very good and above 3.00 is excellent.
- Sharpe penalizes all volatility. Sortino penalizes only harmful volatility. The choice depends on what the investor wants to control.
- The target return, the data period and the return distribution all change the result. Read the ratio next to maximum drawdown and recovery metrics.
Table of Contents
- What the Sortino ratio is
- The formula
- A worked example
- What counts as a good Sortino ratio
- Sortino vs Sharpe: what each one captures
- The target return changes the answer
- How to use Sortino on trading strategies
- Limits to keep in mind
- Perspective
- Reviewing Sonic AI's gold record
- FAQ
- Sources
What the Sortino ratio is
The Sortino ratio is a risk-adjusted return metric. It answers one question: how much return did an investment deliver for the downside risk it took?
The Corporate Finance Institute describes it as additional return per unit of downside risk. The calculation uses the difference between average return and the risk-free rate, divided by the standard deviation of negative returns.
Most investors do not mind a month that beats expectations by a wide margin. They mind months that lose money. A volatility measure that treats a +8% month and a -8% month as equally bad does not match that view. The Sortino ratio was built to fix this by counting only the bad side.
The formula
The standard form is:
Sortino ratio = (R − T) / DD
- R is the actual or expected portfolio return over the period.
- T is the target return. Often this is the risk-free rate. It can also be a minimum acceptable return (MAR), such as 0% or an inflation figure.
- DD is the downside deviation: the standard deviation of returns that fall below the target.
Investopedia gives the same structure: actual or expected return minus the risk-free rate, divided by the standard deviation of the downside.
How downside deviation is built
Downside deviation is where the ratio differs from Sharpe. The steps are:
- Choose the target return for each period.
- For each period, take the shortfall: the target minus the return, if the return is below the target. Otherwise the shortfall is zero.
- Square each shortfall.
- Average the squared shortfalls across all periods, including the periods with zero shortfall.
- Take the square root.
The result is expressed in the same unit as the returns, such as percent per month.
A worked example
The numbers below are hypothetical. They show the mechanics only and are not the result of any real fund or strategy.
Take twelve monthly returns, in percent: +3, +2, -1, +4, +1, -2, +3, +2, 0, +5, -1, +2. Set the target to 0% per month.
Step 1: average return. The twelve values add up to 18, so the average is 1.5% per month.
Step 2: downside deviation. Only three months fall below zero: -1, -2 and -1. Their squares are 1, 4 and 1, which sum to 6. Divide by all twelve months to get 0.5. The square root is about 0.71%.
Step 3: ratio. 1.5 divided by 0.71 gives a Sortino ratio of about 2.12.
Now compare the Sharpe ratio on the same series, with a risk-free rate of 0. The standard deviation of all twelve returns is about 2.06%. Sharpe is 1.5 divided by 2.06, or about 0.73.
The same record scores 0.73 on Sharpe and 2.12 on Sortino. The reason is that the large positive months (+4 and +5) widen the overall standard deviation, and Sharpe counts that widening as risk. Sortino ignores it.
What counts as a good Sortino ratio
A higher number means more return for each unit of downside risk. Schwab's guideline sets these bands:
| Sortino ratio | Reading |
|---|---|
| Below 0 | Returns fell below the risk-free rate or MAR |
| 0.00 to 1.00 | Suboptimal |
| Above 1.00 | Good |
| Above 2.00 | Very good |
| Above 3.00 | Excellent |
The bands come from Schwab's guide to the Sortino ratio. They are rules of thumb, not law. Three points help in applying them.
- Compare like with like. A ratio is most useful when two investments are measured over the same period, with the same target and the same return frequency.
- Fund type matters. Academic studies apply Sortino across very different groups, from 20 country-specific ETFs measured from 2001 to 2006 to Turkish mutual funds from 2008 to 2012. A typical score in one group says little about another.
- A single number is a summary. The path of returns behind it still matters.
Sortino vs Sharpe: what each one captures
The two ratios share a structure. Both divide excess return by a measure of risk. The difference is the risk measure.
| Sharpe ratio | Sortino ratio | |
|---|---|---|
| Risk measure | Standard deviation of all returns | Standard deviation of returns below a target |
| Upside swings | Counted as risk | Not counted |
| Target | Risk-free rate | Risk-free rate or MAR |
| Best fit | Overall volatility matters | Losses matter most |
Schwab notes that, unlike Sharpe, Sortino focuses only on downside volatility. Investopedia frames the choice as one of goals: total volatility or specifically harmful volatility.
Some sources go further. The Corporate Finance Institute calls Sortino the superior metric, since Sharpe penalizes beneficial upward volatility as well.
When the two diverge
The two ratios give similar answers when returns are roughly symmetric. They split apart when a return stream is skewed. A strategy with frequent small gains and rare, controlled losses looks better on Sortino than on Sharpe. A strategy with rare, deep losses looks worse on Sortino, because those losses dominate the downside deviation.
In the real world, rankings often agree anyway. A study of 2,763 hedge funds by Eling and Schuhmacher found that many risk-adjusted measures, Sortino and Sharpe included, produced highly correlated rankings despite their theoretical differences. The same paper cautions that rank correlation alone is not conclusive. During the 2020 pandemic, an analysis of 1,416 Indian equity funds found Sortino results significantly different from Sharpe.
The practical conclusion: use both when the data allows, and look at the cases where they disagree.
The target return changes the answer
The target, or MAR, is the most adjustable input. A higher MAR means more periods fall short, which raises the downside deviation and lowers the ratio. Financial Edge makes this point in its Excel walkthrough.
Brian Rom, quoted in the documentation of the R package PerformanceAnalytics, puts the trade-off plainly. A MAR set too low misses relevant risk. A MAR set too high penalizes sound investments.
A simple rule: pick the target that matches the investor's real goal and keep it fixed across every strategy being compared. A retiree might use a figure tied to inflation or withdrawal needs. A trader might use 0%, meaning any losing period counts as downside.
Path matters as well as the average. Two portfolios with the same average return can leave an investor in very different positions if the losses come early. That is the idea behind sequence of returns risk, and it is one reason downside-focused metrics matter more as an investor starts drawing on a portfolio.
How to use Sortino on trading strategies
Traders can apply the ratio to a strategy's monthly or daily returns in the same way as to a fund's. A few practical steps keep the comparison clean.
- Use the same return frequency. Do not compare a daily-based ratio with a monthly-based one.
- Fix the target. Use 0% or the risk-free rate for every strategy in the comparison.
- Use the full record. Include every month, including the weak ones. Dropping periods removes the downside the ratio exists to measure.
- Check the depth of the worst losses. Sortino summarizes the size and frequency of shortfalls. It does not show how long a recovery took.
For the last point, read the strategy's maximum drawdown and recovery profile. Our guide to max drawdown for gold copy traders explains why a 20% loss needs a 25% gain to recover. The recovery factor guide for gold trading shows how to calculate net profit relative to the worst drawdown.
Win rate is a separate piece of the picture. A high win rate says how often trades close in profit. It does not say how large the losses are when they come. The article on win rate versus expectancy covers how to combine the two.
Limits to keep in mind
The Sortino ratio is a good tool when its assumptions are respected. These are the points analysts raise most often.
- It is built on history. Schwab states that past data may not hold in the future, and that the ratio is less suited to highly volatile investments.
- More data gives steadier readings. Schwab and the Corporate Finance Institute both point to longer samples, with around ten years described as ideal to cover a full business cycle.
- Small samples add estimation error. Downside deviation uses only the returns below the target. With few such observations, the estimate moves around. TrustedQuant discusses this.
- Return distributions are not always normal. Marcos Lopez de Prado notes that Sharpe and Sortino often assume independent, identically distributed normal returns, which can lead to misreading manager skill.
- It is not a full picture alone. Financial Edge advises pairing it with tail risk and maximum drawdown.
The consistent advice is to treat the ratio as one view among several. For an automated gold strategy, that set normally includes maximum drawdown, recovery time, win rate, expectancy and the risk settings applied to the account.
Perspective
We read risk-adjusted metrics as a way to ask a practical question: how much loss did the account have to absorb to earn its gains?
That is why we put drawdown and monthly results at the center of how Sonic AI is presented. Sonic AI trades gold (XAUUSD) only, using an algorithm-driven strategy managed by our team. We report an 80% win rate, drawdown below 1% and 18 consecutive winning months, with results published on MyFXBook so anyone can review the record.
A strategy with few and shallow losing periods is the kind of profile that downside-focused metrics such as Sortino are designed to reward. When a record has few months below the target, the downside deviation is small and the ratio responds to that.
We suggest using Sortino the way it is meant to be used: with a fixed target, the full return series, and drawdown and recovery metrics next to it. Our own write-ups on low drawdown strategy and CopyX risk controls explain how we think about those pieces.
Paulo
Reviewing Sonic AI's gold record
Sonic AI is an auto-trading strategy focused only on gold (XAUUSD). Execution runs through COPYX, which copies trades to a connected account automatically. Users do not need extensive trading knowledge to run it.
The live record, including monthly performance, is available on the Sonic AI live results page. Anyone who wants to apply the steps above can take the monthly figures, set a 0% target and calculate downside deviation and the Sortino ratio directly.
Sonic AI earns through a performance fee on client trading gains. Setup guides are provided on the main site at Sonic AI. Trading gold carries risk, and past results do not guarantee future returns. Consider your own financial situation, and speak with a licensed financial adviser before you commit capital.
FAQ
What is a good Sortino ratio?
Under Schwab's guideline, a Sortino ratio above 1.00 is good, above 2.00 is very good and above 3.00 is excellent. A reading from 0.00 to 1.00 is suboptimal, and a negative reading means returns fell below the target. Compare only ratios measured over the same period with the same target.
Is Sortino better than Sharpe?
Neither is better in every case. Sharpe measures excess return against all volatility. Sortino measures it against downside volatility only. If the concern is losses, Sortino matches that goal more closely. Using both and noting where they disagree gives a fuller view.
What is the minimum acceptable return in the Sortino formula?
The minimum acceptable return is the target below which a return counts as downside. It can be the risk-free rate, 0% or another figure that fits the investor's goal. A higher target raises downside deviation and lowers the ratio, so it should be held constant when comparing.
How much data does the Sortino ratio need?
Longer records give steadier estimates, because downside deviation relies on the subset of returns below the target. Schwab points to around ten years as ideal for covering a full business cycle. Whatever the length, pair the ratio with maximum drawdown and recovery metrics.
Sources
- Sortino Ratio: A Comprehensive Definition and Calculation, Investopedia
- How to Use the Sortino Ratio, Charles Schwab
- Sortino Ratio Overview, Corporate Finance Institute
- Sortino Ratio Formula, Financial Edge
- SortinoRatio, PerformanceAnalytics documentation
- Eling and Schuhmacher, hedge fund performance measures
- Lopez de Prado, How Long Does It Take to Recover from a Drawdown?
- Examining Sharpe Ratio, ASR, Sortino, Treynor and Information Ratio
- Performance and persistence of exchange-traded funds
- Turkish investment funds portfolio performance study
- Why Your Risk-Adjusted Returns Lie, TrustedQuant