Downside Risk (Meaning, Example) | What is Downside Risk?

Downside Risk Meaning

The downside risk is a statistical measure that calculates the loss in value of the security due to changes in market conditions and is also referred to as the uncertainty that the realized return can be much less than the anticipated results. Simply put it helps in quantifying the worst-case loss that an investment can lead to if the market changes direction.

Components of Downside Risk

Following are the important components of a downside risk metric

Time Horizon – The most important parameter to analyze any risk metric is the time horizon. This factor becomes even more important for downside risk. The time horizon helps in limiting our analysis for a particular duration of time making our calculation more precise and are models more robust. It should be important to include proper sample space to make sure the time horizon you selected is unbiased and is free from cyclic deviations.
Confidence Interval – Downside risk is a study based on statistical measures. Hence it becomes important that a proper and definite confidence interval is selected as all further calculations will be based on it. This parameter should be defined based on the comfort level of the investor or the institution carrying out the analysis. There is no definite number that is right or wrong, but a benchmark based on which you decide your risk-taking ability.

Downside Risk Formula

There can be many ways to calculate the downside risk. You can use standard deviation, expected shortfall or value at risk which further has multiple methods like historical simulation, variance-covariance, etc. The aim is to calculate what is the maximum you can lose based on the sample space (underlying data) for a particular time horizon and confidence interval.

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For the variance-covariance method, downside risk (VAR) is calculated as:

VAR = – Z( z- value based on confidence interval) X Std. deviation

Example of Downside Risk

Let see the simple example to understand it in a better way.

You can download this Downside Risk Excel Template here – Downside Risk Excel Template

Consider the example of a company ABC whose stock is trading at $ 1000. The following table lists the monthly returns for 1 year.

Let’s calculate the downside risk of this stock based on the past returns and to keep matters simple we will calculate using the mechanism of historical method. Let’s decide the confidence interval and time horizon.

Confidence interval: 75%
Time horizon: 1 year

Returns in sorted order

Calculation of Max Loss

Max Loss = 3

Arranging the returns in sorted order, we will focus on the bottom 25% returns ( max loss) which is 3 ( 75% of 12). Hence the cutoff will be the 4^th return. In simple terms with a 75% confidence interval, we have calculated the downside risk to be -5%.

Refer to the Excel Sheet given above for detail calculation.

Advantages

Helps in Planning for the Worst-Case: If you fail to plan, you are planning to fail. Downside risk helps you in planning for the worst-case scenario by understanding how much investment can lead to losses if the projected view turns out wrong. It is no common fact that investments are made for returns and meeting market free rates, often defined by US treasury bills. But there can be scenarios when things don’t go as expected because of a piece of news or an event not reflected in the market. Consider the example of Yahoo, a search engine giant of the early 90s without any competitor. Everyone was hopeful that this stock will be a multi-bagger but little did everyone knew that a new market leader (Google) was in the making and yahoo will be displaced. Had there been downside risk controls deployed in the systems, losses would have been much less.
DecidingHedging Strategies: As explained above downside risk is more about preparing when the events do not turn out the way as expected. Such estimation is helpful in identifying when to come out of an investment. As they say, keep your profits but book your losses.

Limitations/Disadvantages

A false sense of security: Downside risk is a statistical technique that tries to predict based on past data patterns. Its complexity varies from asset class to asset class. For a simple financial product like equity, it could be as simple as trading prices but for a complex product like credit default swaps, it depends on a lot of parameters like underlying financial bond prices, time to maturity, current interest rates, etc. The model you are using can work 99 times but can fail once too and most often than this will happen when volatility is high, or markets are crashing. In short, it will fail when you need it the most. Hence due to model risk, downside risk can provide you with a false sense of security
Inconsistent results across models: Downside risk is as good as the model used and based on the underlying process used, there can be variations in the result even though the underlying assumptions and the sample are the same. This is because each downside risk metric mechanism has its own implicit assumptions which can lead to a different output. For example, both historical simulation and Monte Carlo simulation are Value at risk mechanisms but the result derived through them based on the same underlying data can differ.

Important Points to Note

Risk reduction strategies: Calculating downside risk helps one in identifying the correct hedging strategy. Investors and institutions should understand the financial product they are dealing in and then select a suitable downside risk metric as per their comfort and capability.
Each asset class has different downside risk. For vanilla financial products like equity and fixed income, the downside risk is fairly easy to calculate and limited. However, for financial products like options or credit default swaps, the downside is difficult to calculate and unlimited.

Conclusion

Nobody likes losses but the lessons from the past have taught us that financial products are unpredictable. In times of distress like the 2008 economic recession or 2001 dot com bubble, the volatility, and the correlation between the asset classes increases. Most often than not, it catches investors off-guard leading to huge losses and catastrophic events. Downside risk, as a preventive measure, helps in eliminating or preparing better for such scenarios.