Sortino Ratio: Problems and Solutions Featured

Risk assessment is a crucial aspect of investment analysis, and various metrics help investors gauge the performance of their portfolios. One such metric is the Sortino Ratio, which provides valuable insights, especially in the context of non-normal distributions of returns.

Understanding the Sortino Ratio

The Sortino Ratio, an alternative to the more common Sharpe Ratio, delves into risk-adjusted returns. While the Sharpe Ratio utilizes standard deviation as a measure of risk, the Sortino Ratio takes a different approach, focusing on the downside deviation. This makes it particularly relevant for financial instruments with non-normal return distributions. The primary advantage of the Sortino Ratio lies in its suitability for non-normal return distributions. Financial instruments often deviate from a normal distribution, making standard deviation an unreliable risk measure. The Sortino Ratio addresses this by emphasizing downside deviation, providing a more accurate assessment of risk.

Two Approaches to Calculation

When calculating the Sortino Ratio, two methods are commonly employed. The first method utilizes the Downside Deviation, measuring the standard deviation of negative returns. The second method involves the Target Downside Deviation, which assesses returns below a specified target. This latter approach proves beneficial for instruments without negative returns.

Evaluating the Sortino Ratio as a Comparative Measure

In today's discussion, we shift our focus to the practical application of the Sortino Ratio as a comparison tool for selecting assets with desirable risk-return profiles. The key assumption is straightforward: a robust risk statistic should yield similar values for assets with comparable risk-return profiles and distinct values for those with differing risk-return profiles. While we won't delve into direct comparisons with other statistical measures, our exploration aims to assess the effectiveness of the Sortino Ratio in distinguishing assets based on their risk-return characteristics. This analysis delves into whether the Sortino Ratio truly serves as a reliable comparative tool, offering investors valuable insights for optimal decision-making in their portfolios.

Setting the Test Model

To ascertain the effectiveness of the Sortino Ratio as a comparison tool, we conducted a the following study. First, we selected seventeen ETFs with closely aligned Sortino values in the range 0.152 - 0.153 over a common trailing period of 36 months. Then, we calculated supplementary risk statistics, including Value at Risk (VaR) at 95% confidence, Maximum Drawdown, Mean Return, and other prominent ratios such as Sharpe, Omega, and Calmar.

Drilling Down into Test Results

The cumulative return chart and the related risk statistics reveal intriguing and somewhat unexpected findings. A cursory glance at the chart below highlights highly diverse risk-return profiles among all the funds, challenging their categorization as similar performing instruments.

Sortino Ration Challenges

The accompanying statistics table reinforces this observation, showcasing a range of mean returns from 0.3% to 0.75% and Maximum Drawdowns spanning from -11% to -30%. This prompts the realization that relying solely on the Sortino Ratio for asset selection is insufficient.

Funds Sortino RoR,% Sharpe Omega Calmar VaR,% MaxDD,% TUW
Vanguard Balanced ETF Portfolio 0.153 0.303 0.096 1.098 0.214 -3.957 -15.193 24.000
WisdomTree Live Cattle ETC 0.152 0.318 0.104 1.116 0.310 -5.045 -11.087 21.000
BetaShares Martin Currie Real Income ETF 0.152 0.525 0.099 1.200 0.303 -5.652 -17.505 20.000
Xtrackers MSCI USA ETF 2C EUR 0.152 0.639 0.099 1.227 0.236 -8.952 -26.620 24.000
UBS FS MSCI ACWI SF USD A acc ETF 0.152 0.576 0.098 1.208 0.223 -8.114 -25.643 24.000
iShares Convertible Bond ETF Comm 0.154 0.129 0.102 0.855 0.211 -1.900 -6.984 26.000
SPDR® MSCI ACWI ETF 0.153 0.576 0.098 1.208 0.224 -8.083 -25.554 24.000
UBS(Lux)FS MSCI World SRI USD Adis 0.153 0.684 0.096 1.236 0.214 -8.735 -30.756 24.000
iShares S&P US Mid-Cap ETF (CAD-Hedged) 0.152 0.694 0.092 1.229 0.291 -7.915 -22.589 24.000
BMO Global Consumer Staples H CAD ETF 0.153 0.371 0.089 1.131 0.391 -4.051 -9.760 8.000
Avantis International Small Cap Val ETF 0.153 0.636 0.096 1.232 0.239 -7.314 -25.876 27.000
AdvisorShares DW FSM US Core ETF 0.153 0.596 0.098 1.221 0.232 -7.376 -25.460 24.000
Vanguard Growth ETF 0.153 0.819 0.097 1.269 0.232 -9.631 -33.130 24.000
First Trust Utilities AlphaDEX® ETF 0.152 0.628 0.093 1.217 0.399 -6.601 -15.222 19.000
iShares MSCI ACWI ETF 0.152 0.580 0.097 1.207 0.224 -8.055 -25.695 24.000
JPMorgan BetaBuilders MSCI US REIT ETF 0.153 0.747 0.092 1.230 0.239 -7.060 -29.325 24.000

Should We Use the Sortino Ratio?

It is essential to clarify that we do not assert that the Sortino Ratio is an inherently flawed statistic to be avoided. Just like any risk measure, it has its pros and cons, but let's save that discussion for another time.The key takeaway is that an effective method of asset comparison should not rely on a single statistic but rather on a combination of multiple metrics, each targeting different risk aspects of the assets under consideration.

Risk Shell’s Solution: The FlexiRank™ Framework

To address the challenges of comparing and ranking assets, we introduce the FlexiRank™ framework, one of Risk Shell key componebts. This solution empowers end-users to create synthetic ranking criteria, combining various common risk statistics. This way it effectively mitigates the limitations associated with relying on single statistics for comparison purposes.

Learn More About FlexiRank™

For a deeper understanding of the FlexiRank™ concept and how it revolutionizes asset comparison, we invite you to join our dedicated webinar. Explore a dynamic framework that enhances your ability to compare and rank assets, providing a comprehensive and nuanced perspective on risk and return.

 

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