• 02 March 2022
  • Oguz S. Ersan, CFA

Rising Rates and Risk Measurements

Inflation has reached a 40-year high with consumer prices and wages reaching excessive levels, competing in a wage-price spiral. With inflation running well above the 2% target, 2022 will consist of the Federal Reserve fighting for their credibility. It is anticipated that the Fed will raise interest rates at consecutive policy meetings for the first time since 2006, and a half-percentage-point increase, which has not been done since 2000, has not been fully ruled out. Some investors are fearful that Fed Chairman Jerome Powell will lead the economy into a recession in the effort to quell inflation. The Fed hasn’t had to combat inflation of this magnitude since the 1980’s, and historically when inflation has been this high, the Fed has not been able to push it down without a subsequent recession. Even with the Fed’s efforts, inflation may remain high due to factors outside of the Fed’s control, such as worsened shipping delays and supply chain issues from the pandemic. As an investor, it is critical to have an experienced portfolio manager guiding your investments. Portfolio managers must implement risk management techniques to evaluate the potential impact that these negative events can have on your portfolio, and to ensure that you are not exceeding your desired risk tolerance. Risk measurements and models, including VaR, modified versions of VaR, scenario analysis, and stress testing can provide insights focused on these concerns.

Skillful portfolio managers may utilize risk models in combination with their judgement to exploit the strengths and limitations of your portfolio. VaR, or value at risk, is the minimum loss of portfolio value that would be expected to occur a specific percentage of the time over a certain period of time. This is easier to understand with an example. A 5% daily VaR of $1,000 would mean that on 5% of days, a portfolio is expected to lose at least $1,000.  Portfolio managers have the flexibility to choose the best  percentage threshold and time horizon (e.g., daily, monthly, yearly, etc.) to meet their requirements.

An effective portfolio manager must understand the advantages of VaR, but also its limitations. VaR is a simple, yet valuable risk measure that allows one to see the potential losses that can danger a portfolio. There is a substantial amount of information shown in a single number. This number can provide a basis for risk comparison across asset classes and portfolios to see where the majority of risk is emanated from. This allows a portfolio manager to see adjustments they may need to make to realign its VaR, or they may realize that a reallocation of the portfolio is necessary. Although useful, VaR does require discretionary choices, such as choosing the data sources. There also may be more extreme, “left-tail events” that occur which VaR may not capture. VaR also has difficulty taking illiquid assets into account and is often understated for these assets. It is also important to understand that VaR does not portray the worst-case scenario and that losses can exceed it. It is also sensitive to correlation risk. Correlation risk is the risk that when markets are under extreme stress, correlations among assets tend to rise which can significantly decrease diversification benefits in a portfolio. VaR can be oversimplified, and these limitations are not unique to this specific risk measure. However, if a portfolio manager fully understands this, they can still receive valuable information. Rather than using VaR by itself, risk management is most effective with a combination of risk measurements and models.

A portfolio manager cannot obtain all the necessary information through one single risk measure; there are numerous variations of VaR that aim to provide additional information where VaR lacks. CVaR, also referred to as conditional VaR, expected tail loss, or expected shortfall, represents the average loss that would occur in the left tail of the distribution whereas traditional VaR only represents the minimum loss. For example, consider the aforementioned portfolio with a 5% VaR of $1,000. The CVaR of this portfolio will be more than $1,000. VaR represents the minimum loss on the worst 5% of days whereas CVaR represents the average loss on those same days. CVaR can be more useful to a portfolio manager than VaR since it captures more information about the extreme left tail of the distribution. IVaR, or incremental VaR, determines how the VaR will change if a certain position size in the portfolio is altered relative to the other positions or if a position is added or removed. If a portfolio manager wants to increase a holding in the portfolio, they would recalculate the VaR under the assumption that this change has been made. The IVaR is calculated by finding the difference between the before VaR and the after VaR, which reflects how VaR is affected due to this certain change. A portfolio manager can compare the new VaR, whether it is higher or lower, and make any changes they see as beneficial for the portfolio. MVaR, or marginal VaR, can be used to determine how each asset contributes to the VaR; it measures the change in VaR when a very small alteration is made in a portfolio position. Although IVaR and MVaR are both risk measurements that determine the impact of an anticipated change, MVaR is more focused on smaller changes within the portfolio. The last variation of VaR is the ex-ante tracking error, also known as relative VaR. The ex-ante tracking error delineates the degree to which the performance of a portfolio may deviate from its benchmark. Although VaR and its variations support the risk management process, a portfolio manager must also understand the factors that are driving the risk.

Scenario analysis and stress testing can allow portfolio managers to analyze the risk drivers and address the shortcomings of other probabilistic risk measures. A scenario analysis can look at any event and evaluate how a portfolio may perform under these conditions. This risk model has two different methods: historical and hypothetical. A historical scenario analysis looks at what the return on a portfolio would be if a repeat of an event in history, such as The Great Inflation, were to occur. To determine this return, the value of each portfolio position is calculated before and after the changes to see the effect. This analysis can be run over a timeline to include different actions the portfolio manager may make throughout this event to alleviate the potential repercussions. Alternately, a stress test allows the portfolio manager to change multiple variables at once. This allows a portfolio manager to apply extreme, negative stress to a portfolio and assess the impact. This is a productive way to reflect on the impact that certain adverse market movements may have on a portfolio. However, it is unlikely that a historical event would happen in the exact way that it once did. The solution to this is a hypothetical scenario analysis, where one can evaluate the impact of an event that has not previously occurred on an investment portfolio. To construct a reliable hypothetical scenario, one must complete a reverse stress test, which involves targeting exposures to determine how they behave in different environments. Scenario analysis and stress testing provide an opportunity to review the potential impact from events and to understand the risk exposures. There is no certainty to how the markets will behave, and hypothetical scenario analysis, in combination with the other risk measurements, can provide a portfolio manager with a framework to best prepare for varying market conditions.


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