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Developing A Dynamic Interest Rate Risk Management Program

January 11, 2013
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So you have the responsibility to update the interest rate risk management program for your institution. As if you didn’t already have enough to do! The effectiveness of your redesigned IRR program depends to a great extent on your response to five key questions. First, what are you attempting to measure and how will it be measured? Second, what is your philosophy toward interest rate risk? Third, should your measurement system be static or dynamic? Fourth, what kinds of interest rate shocks should you use in stress testing your institution? Fifth, what thought processes will you use to establish policy limits for interest rate risk. The first three questions will be discussed in this article. The fourth and fifth topics will be discussed in part 2 of this series in the next issue of the newsletter.

Interest Rate Risk – What Are We Attempting to Measure?

Let’s face it! The definition of interest rate risk used by managers and regulators isn’t the same! Managers tend. to focus on the effect of a movement in rates on income over the next quarter, semiannual period, or year. The manager’s viewpoint is understandable. Managers are accountable to directors for putting net income on the bottom line. Anything that would mess with the bottom line net income is appropriately a concern of management.

On the other hand, regulators focus on liquidation value. If it becomes necessary to liquidate an institution, they are concerned about what price they’ll receive for the institution’s assets and whether they will have to tap the insurance fund to pay off the depositors.

With the regulatory focus on liquidation value, it's not too surprising that our interest rate risk measurement tools are moving away from gap analysis and toward market value measurement tools like duration analysis, discounted cash flow, and option-adjusted spread analysis. But the movement to tools measuring the regulatory definition of interest rate risk raises an interesting issue for managers. Do you change your focus from income to market value as an IRR measurement tool? Or do you adopt a measurement system that measures the effect of rate shocks on both income and market value?

Measurement systems that measure both income and market value risk best meet the needs of both managers and regulator. No matter how hard the regulator pounds away at the importance of market value analysis, your board will hold you responsible for what you put on the bottom line. So your measurement system needs to focus on the effect of rate shocks on income for management purposes. Your system also needs to focus on the effect of rate shocks on market value for regulatory compliance purposes.

Your IRR Objective – Minimize or Manage?

The objective of many financial institutions is to maintain interest rate risk at a level as close to zero as possible. Such an approach would certainly keep a smile on the face of the institution’s primary regulator.

But in an environment of generally low loan/deposit ratios, lots of liquidity, and no interest rate risk, an institution may have difficulty putting enough money on the bottom line to keep directors happy. Minimizing interest rate risk can lead to a real world demonstration of the old saying “No risk, no return!”

Other management teams take a more aggressive approach. They take on interest rate risk if it improves their ability to accomplish long-range profitability, growth, capitalization, and dividend goals. These managers set policy limits that keep potential losses due to adverse movements in market rates at affordable levels. They see interest rate risk in the same way they see credit risk – an opportunity to make money through effective risk management. Financial institutions, for the most part, choose from the following four approaches.

The Retail Liability Driven Approach – Lets not portfolio assets unless our depositors offer the right kind of funding”

This approach is the most conservative and traditional approach. An institution’s managers pursuing this strategy raise virtually all of their funding in the retail markets. Because their objective is to maintain zero interest rate risk, they place retail loans in their portfolio only when ideally suited retail funding is available. Any loans that don’t match up against the institution’s retail funding are originated and sold in the secondary market or no loans are made.

In today’s market, long-term CDs are hard to find. Regulators, especially bank and credit union regulators, tend to treat transaction accounts as relatively short-term’ sources of funding. As a result, managers in institutions pursuing the retail liability strategy primarily portfolio variable rate loans and fixed rate loans with relatively short-term maturities. Long-term fixed rate loans like mortgages are only made if they conform to secondary market standards and are immediately sold in the secondary market. The retail liability approach minimizes interest rate risk. Such a strategy can result in low loan/deposit ratios and less than optimal net income by limiting the list of acceptable loans.

The Economist Approach I believe I can make money forecasting rates”

The economist approach begins with an interest rate forecast. Whether the rate forecast is the institution’s or from someone they trust is irrelevant. It is crucial the management team believe there is a better than average chance rates will move in the direction of the forecast. They make their money by running the institution so it will benefit when rates move in the forecast direction. As Figure 4 indicates, those taking the Economist approach will run a positively rate sensitive institution when they believe rates will rise and a negatively rate sensitive institution when they believe rates will fall. The table also shows how a properly set up institution would appear to gap analysis, income simulation, duration, and MVPE oriented measurement systems.

In one form of the economist approach managers of institutions use the slope of the yield curve to enhance net income. As this article was written, the treasury yield curve appeared as shown in Figure 5. Because the yield curve was positively sloping, an institution could make money by booking longer duration assets funded by shorter duration liabilities. In Figure 5, the institution books five-year duration assets (priced off five-year Treasury yields of 5%). It funds them with four-year duration liabilities (priced off four-year treasury yields of 4.5%). As long as rates remain fiat it will pick up the 50 bp spread in the yield curve as additional income.

Managers of institutions using the yield curve to enhance income are making an implied rate forecast. If long-term rates are higher than short-term rates, the market is predicting that rates will rise. Managers using short-term funding for long-term assets are betting that the market’s rate forecast is wrong. If rates rise, institutions will suffer a decline in both income and market value.

For the economist approach to work, rate forecasts have to be accurate more than 50% of the time. If rate forecast accuracy is less than 50%, managers in institutions employing the Economist’s approach will show less profit over the long haul.

The Farin & Parliment Retail/Wholesale Approach

The F&P approach recognizes that retail customers are risk-averse because most have no effective way of hedging their interest rate risk. How many ARM customers will see their salaries increase to cover their increased mortgage payments in a rising rate environment? The F&P approach also recognizes that retail customers are willing to pay a premium for what they consider to be desirable options (annual and lifetime caps, prepayment options, conversion options, early withdrawal options, etc.).

With rates at the bottom of the cycle, loan customers, particularly nonconforming loan customers, are willing to pay a premium for fixed-rate loans. They need to be bribed heavily with rate, caps, and other incentives to accept adjustable rate loans. Retail deposit customers are often willing to accept treasury or sub-treasury rates on short-term CDs but require a significant premium over treasury before committing funds to long-term CDs.

Under the F&P approach, the institution’s managers accept all retail instruments that are well priced considering their risk characteristics. They accept fixed rate loans for portfolio purposes, especially nonconforming loans offering significant spreads over secondary market rates. They also accept short-term CDs and core deposits, as long as they can find them at sub-treasury rates. They don’t pay up for long-term CDs.

“But this is insane,” you say. “Long-term assets funded by short-term liabilities!” Let’s look at the rest of this approach. Those pursuing the F&P approach use pricing to control the level of short-term liabilities. They use the wholesale markets to offset the interest rate risk they are incurring in the retail markets. This may mean investing primarily in short-term securities to balance long-term loans. Using the F&P approach may also mean raising long-term funding to balance short-term deposits through wholesale market sources like FHLB advances. More sophisticated institutions may use instruments like interest rate swaps and caps.

The objective of the F&P strategy is not to bring interest rate risk to zero. Rather, the management team is attempting to maximize performance while keeping interest rate risk within its policy limits. Review the MCNB case in the previous issue. It compares a retail liability approach to the F&P approach for a $100 million institution. The results are startling.

To the extent managers employing the F&P approach take on interest rate risk and rates move in an adverse direction, declines in income and market value will occur. The damage is limited by setting and maintaining compliance with appropriate policy limits.

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The Uncovered Option Approach

Under the uncovered option approach, financial institutions place a substantial portion of the asset side of their balance sheet in financial instruments with imbedded options. Such embedded options as prepayment options, caps, and conversion options cause a financial instrument’s cash flows to be substantially different in one rate environment than in another. They receive a higher yield on these instruments to compensate for the risk associated with the option. They fund the assets with similar duration liabilities that do not have the same options. Because they receive a higher rate on the asset side and do not have to compensate their funding sources for options on the liability side, they pick up additional spread.

Depending on the imbedded options, significant movements in market rates in either direction could result in declines in net income and liquidation value.

An example of an uncovered option strategy was discussed in the duration article in the May-June issue of the newsletter. An institution funds a seven-year duration fixed-rate MBS with a seven-year duration pool of FHLB advances at a positive spread. However, as Figure 6 shows, rate movements affect prepayments on the MBS but not the advances. Because of the duration drift of the asset, the institution’s MVPE drops with rate shocks in both directions.

Uncovered option strategies are found to a greater or lesser extent in all retail financial institutions. Thrifts, because of their heavy mortgage concentration, typically have more uncovered option risk than banks and credit unions. Managing this kind of risk requires fairly sophisticated measurement systems and well-conceived policy limits.

What strategy is best for your institution? Should you minimize interest rate risk with the retail liability approach? Try the economist approach? Use the F&P approach? Incur some uncovered option risk? Or should you employ some combination of the three depending on customer demand, your willingness to take on risk, and your confidence in your rate forecasts? It is helpful to examine the potential effect of each approach under a variety of rate environments before making your decision. Dynamic modeling is the only technique that allows you to test a strategy before it is implemented.

Static Vs Dynamic Interest Rate Risk Measurement

Most management teams measure interest rate risk based on their most recent set of financial reports. For example, managers might set policy limits for 6 month and 1-year cumulative gap/asset ratio of +/-15%. Early each month they compute their gap/asset ratios based on financial reports for the end of the previous month. A comparison of the monthly gap/ asset ratios to the policy limits determines whether the institution was in compliance at the end of the month.

Such static measures of interest rate risk are not terribly useful in evaluating alternative interest rate risk management strategies. For example, say ABC’s managers are considering four alternative interest rate risk management strategies. Under static measurement systems, ABC’s managers can’t determine whether a strategy is effective until after it has been implemented. By then it’s too late to try the three alternative strategies. The window of opportunity for their implementation has closed.

Regulatory interest rate risk measurement systems are always static. Whether they are as unsophisticated as a gap report or as sophisticated as the output from the OTS Market Value Model, regulatory interest rate risk measurement tools never consider the institution’s strategy. The regulator lacks the information necessary to model the institution’s strategy.

Dynamic techniques use a computer simulation model to evaluate the potential impact of a strategy before the strategy is implemented. ABC’s managers use the model to project the results of implementing the first strategy and compare the results to its financial goals and IRR policy limits. The same analysis is performed for the remaining three strategies. Once the risk/return trade-offs associated with all four strategies have been modeled, ABC’s managers implement the strategy with the best risk/return characteristics.

Using Dynamic Modeling to Select A Strategy – An Example

Assume that ABC institution’s managers have established a goal for return on assets (ROA) of 1.4%. They expect rates to remain flat over the next year and have decided to test ABC’s performance over a range in interest rate movements from a 300 bp rise to a 200 bp fall.

In approving their policy limits for ROA fluctuation (Figure 7), ABC’s board had a dual objective. First, they wanted to maximize ROA in the expected rate environment. Second, they wanted management to limit interest rate risk so that adverse movements in rates drop expected ROA by no more than 0.20%. Note that the policy limits allow negative ROA fluctuations in both directions. In approving the limits, the board is saying, “We don’t care whether management runs a positively or negatively rate sensitive institution. Just don’t let expected ROA drop more than 20 bp for plausible changes in market rates.”

The management team has modeled Strategy 1 under all three rate environments. They cheer when they see the results from the flat rate environment. The ROA goal of 1.40% is achieved under Strategy 1 for the expected rate environment. Unfortunately, the 40 bp drop to 1.0% in the rising rate environment is more than ABC’s policy limit allows. The strategy must be rejected as being too risky.

Strategy 2 involves taking on considerably less interest rate risk than Strategy 1. When modeled, Strategy 2 shows a 1.00% ROA in all three rate environments. Isn’t this the perfect interest rate risk strategy? All risk of ROA fluctuation is removed by the strategy! The management team can expect a regulatory pat on the back if Strategy 2 is implemented. They would also deserve a boot in the rear from their board of directors!

The problem with Strategy 2 is apparent if we evaluate interest rate risk strategies the same way we evaluate insurance policies. In selecting between insurance policies we ask two questions. First, what’s the premium? Second, does it provide the necessary level of protection? The insurance premium associated with selecting Strategy 2 over Strategy 1 is the 0.40% reduction in ROA in the expected rate environment. The benefit of Strategy 2 should be better performance (protection) should an adverse rate environment occur. With Strategy 2 the ROA in the rising rate environment (1.0%) is no better than with Strategy 1. If Strategy 2 is implemented, ABC would pay a 40 bp ROA premium for no adverse rate environment protection. That’s a lousy insurance policy, even though it brings ABC within its ROA policy limits. Fortunately, ABC’s managers consider two other alternatives.

Modeling results show that implementing Strategy 3 would cause some interest rate risk exposure. But with ROA falling only 20 bp from 1.35%inthe expected environment to 1.15% in the rising rate environment, ABC would be within its policy limit. In comparison to Strategy 1, Strategy 3 would involve paying a 5 bp ROA premium for 15 bp of protection in an adverse rate environment. Strategy 3 is a decent insurance buy.

Strategy 4 reduces interest rate risk even more than Strategy 3. In comparison to Strategy 1, Strategy 4 requires a 10 bp ROA premium for 20 bp worth of protection another decent insurance buy.

Which strategy should ABC choose? In deciding between Strategy 3 and 4, ABC would. need to consider more than the ROA impact. How does ABC’s performance under Strategy 3 and 4 compare to its other financial goals like capital, growth, and stockholder dividends? Given that Strategy 4 involves taking on less risk than Strategy 3, how risk adverse is the management team and board? Are the two strategies consistent with ABC’s mission statement and operating strategy? Do they involve financial instruments or techniques outside the expertise of ABC’s management team and board of directors? A review of the quantitative results from the simulation model and the qualitative answers to the above questions should lead to the selection of the most appropriate strategy.

Using a dynamic approach to strategy selection requires the use of a simulation model. “But aren’t simulation models expensive?” Not in comparison to the potential cost of not using a simulation model in deciding between alternative strategies. Without the simulation results in Figure 3, ABC’s management may elect to implement Strategy 2 because it results in the lowest interest rate risk exposure. They may reject Strategy 3 and 4 in spite of the fact ROA for both strategies is better in all three rate environments than for Strategy 2. For a $100 million institution, Strategy 2’s 40 bp ROA premium in the expected rate environment would come to $400 thousand per year! Compare that to the cost of a good simulation model (typically $5-15 thousand).

This article provides answers to three of the five questions posed. First, in designing an interest rate system for your institution’s future you should make sure the system measures the effect of rate shocks on both income and market value. Second, it should have adequate flexibility to allow you to take on interest rate risk when you wish and minimize interest rate risk when you don’t. Third, the system should use dynamic measurement of interest rate risk so you can test the risk/ return trade-offs between alternative strategies before implementation.

Of course, adoption of a dynamic approach to interest rate risk management requires that an institution select appropriate rate environments for stress testing the institution. Income and market value policy limits must be chosen that keep interest rate risk exposure at an acceptable level. In part 2 of this article, we will outline an approach for dealing with these crucial issues.

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