Verified Document

Loan Risk Management Term Paper

Portfolio Risk Management In today's competitive banking environment, an important challenge is to ensure adequate diversification of revenue sources across products, market segments and market and credit risks (Sturzinger). Banks must assess their risk appetite and risk capacity as basic components of the budgeting and planning processes and identify their vulnerabilities through risk management techniques.

Risk is defined as uncertainty of returns from a portfolio (Credit-stress testing, 2002). The volatility of a portfolio's returns indicates the level risk and is influenced by many risk factors. Therefore, one of the risk manager's primary goals is to measure the influence of each risk factor on the volatility of portfolio returns and to manage the composition of the portfolio so that the volatility of its returns is reduced. The risk manager also has to measure the influence of the risk factors on each other. Determining the effects of multiple risk factors and quantifying the influence of each is a complex task, but portfolio risk management techniques can help. Some examples of risk management techniques discussed in this paper include: performance analysis, value-at-risk models, stress testing, Monte Carlo simulation, and heuristic controls, each having individual strengths and weaknesses.

Performance Analysis

Historical performance analysis provides insight of how a portfolio has performed over time. However, older data has limited value for forecasting risk because the structure of the portfolio and the market environment are constantly changing (Brooks, Beukes, Gardner, and Hibbert, 2002). Daily and monthly performance data, on the other hand, can be useful as explained by these authors. Risk managers can slice and dice performance data in different ways to identify performance problems and gain a better understanding of their cause and how perceived concentrations of risk are or aren't being rewarded. For example, an examination of a rolling sixty-day tracking error and relative performance plot can act as an early warning system provided that the risk manager does not over react to short-term spikes in tracking errors. This later tendency may cause excessive portfolio turnover and distraction from adding value over the long-term. Despite its usefulness as a portfolio risk technique, performance analysis is often overlooked by risk managers.

Value-at-Risk (VaR) Model

Value at risk is an estimate of the largest loss that a portfolio is likely to suffer during all but truly exceptional periods (Hopper). VaR can be used to assess the potential loss on a portfolio of assets generally or the user can specify any horizon and frequency of loss that fits a particular circumstance. As an example, Hopper describes a bank that specifies a horizon of one day and sets the frequency of maximum loss to ninety-eight percent. A VaR calculation might reveal that the maximum loss is $1 million. This means that, on average, in ninety-eight trading days out of 100, the loss on the portfolio will not exceed $1 million over a one-day horizon. However, on two trading days in 100, losses will, on average, exceed $1 million.

The method of calculating VaR depends on the horizon chosen and on the kinds of assets in the portfolio. According to Hopper, one method may yield good results with portfolios consisting of stocks, bonds, and currencies over a short horizon, but the same method may not work well over longer horizons such as a month or a year. And, portfolios that contain derivatives require methods that are different than those used to analyze portfolios of stocks, bonds, or currencies may be needed.

When properly used, VaR can give an institution an idea about the maximum losses it can expect to incur on its portfolio a certain fraction of the time (Hopper). Using results, an institution can judge how it should re-allocate the assets in its portfolio to achieve the risk level it desires. But VaR methodology is often improperly used, leading to poor risk-management decisions. This happens for one of two reasons: either the VaR is incorrectly calculated or the VaR is correctly calculated but irrelevant to the institution's real risk-management goals.

Stress Testing

Risk statistics work well for estimating risk during normal market conditions, but they cannot predict the occasional, unexpected crises that result in extreme market shocks (Stress testing, RiskMetrics Goups). Stress testing allows portfolio managers to assess how badly things could go during a crisis and to assure that losses do not exceed their loss-tolerance level. Analyses of historical stress scenarios...

To illustrate historical stress scenarios, RiskMetrics Group provides examples for a portfolio consisting of sixty percent equities and forty percent fixed income that resulted in the largest one- and five-day portfolio losses:
Worse-Case Scenario Portfolio Example

Crisis

1-day loss

5-day loss

Black Monday

19-Oct-87

-2.2%

-5.9%

Gulf War

3-Aug-90

-0.9%

-3.8%

Mex Peso Fallout

23-Jan-95

-1.0%

-2.7%

Asian Crisis

27-Oct-97

-1.9%

-3.6%

Russia Devaluation

27-Aug-98

-3.8%

-2.6%

Source: RiskMetrics Goup

In addition to historical scenarios, another approach to stress testing is to invent an extreme scenario based on what the portfolio manager thinks might go wrong in the world.

Both historical scenarios and the invention of scenarios have weaknesses (Stress testing, RiskMetrics Group). The problem with historical scenarios is that history is unlikely to repeat itself while inventing scenarios is inadequate because no one has a crystal ball for predicting the future.

Monte Carlo Simulation

Monte Carlo simulation is a method by which portfolio managers can anticipate the probability of meeting specific financial goals at certain time periods in the future. This is accomplished by generating thousands of possible scenarios that investments might take. More technically, Monte Carlo finds the best approximate answers or distributions of probable answers to problems with many variables and/or many possible outcomes (Davidson). It requires many simulations with randomly valued variables to achieve accuracy. Because of the multiple simulations, the method takes time, especially for highly complex instruments or large portfolios, with a direct trade-off to be made between speed and accuracy.

In banking there are many situations when conventional portfolio theory does not allow the risk manager to fully understand the complete distribution of returns (Brooks, Beukes, Gardner, and Hibbert, 2002). Instances where Monte Carlo simulation might be useful are:

Analyzing portfolios containing instruments with asymmetric returns such as options.

Understanding credit migration impact on the distribution of portfolio returns, credit losses and defaults.

Studying the impact of different specifications for the time variation in share price volatility on portfolio returns.

Examine the impact of fixed trading rules such as a stop loss within a hedge fund set up.

Investigating the returns from performance fee structures.

The major disadvantage of Monte Carlo simulation is its complexity, but it does a good job of explaining risk exposures because it provides specific examples of events that are of concern.

Heuristic Controls

Information about future potential losses and about the likelihood they will occur usually has to be put together for every individual case with a good deal of design work and risk managers avoid the use of heuristics (Schubert, 2003). However, risk managers can exploit previous work through the application of different heuristics or cognitive rules of thumb that assume the available information is incomplete and selective and that the probability estimates derived from it will therefore be distorted. Good heuristic controls recognize that experts may over- or under- estimate probabilities depending on their personality, background and experience, and on the way they formulate the problem. And, with any heuristic, simplification is achieved at the price of systematic error.

Conclusion

For many reasons, bank managers require adequate measures and assessment of risk. Risk management techniques such as performance analysis, value-at-risk models, stress testing, Monte Carlo simulation, and heuristic controls may provide banking institutions with better insight in identifying the sources of market risk, leading to a better understanding and analysis of how their own risk profiles may evolve over time in terms of profit and loss variations (Avraamides). However, as explained in this paper, it is very difficult to establish how accurate any risk management technique will be because of the strengths and weaknesses of each method and, therefore, portfolio managers can only…

Sources used in this document:
Bibliography

Avraamides, S. The handbook of world stock, derivative & commodity exchanges. Retrieved January 26, 2005 from Web site: http://www.exchange-handbook.co.uk/articles_story.cfm?id=5632

Brooks, M., Beukes, L., Gardner, D. And Hibbert, J. (2002, June 26-28). Predicting tracking errors -- the search continues. Retrieved January 26, 2005 from Web site: http://www.actuaries.org.uk/files/pdf/library/proceedings/fin_inv/2002/Brooks.pdf

Credit-stress testing. (2002, January 31). Monetary Authority of Singapore. Retrieved January 26, 2005 from Web site: http://www.mas.gov.sg/regulations/download/ConsultativepaperonCST.pdf

Davidson, C.. Turbo-charged models. Retrieved January 26, 2005 from Web site: http://216.239.57.104/search?q=cache:GU8uTKXvAV8J:www.derivatech.com/Publications/Risk%2520Monte%2520Carlo%252002_2002.pdf+%22monte+carlo+simulation%22+and+risk+and+banks& hl=en
Hopper, G.P. Value at risk: A new methodology for measuring portfolio risk. Retrieved January 26, 2005 from Stern School of Business Web site: http://pages.stern.nyu.edu/~igiddy/valueatrisk.htm
Schubert, R. (2003, January). Analyzing and managing risk -- an opportunity for banks. News for Banks. UBS. Retrieved January 25, 2005 from Web site: http://66.102.7.104/search?q=cache:98qKN9TAoOYJ:www.ubs.com/1/ShowMedia/bank_for_banks/news/archive%3FcontentId%3D28297%26name%3Dnewsletter_jan2003.pdf+%22heuristic%22+and+risk+and+bank& hl=en
Stress testing. RiskMetrics Group. Retrieved January 26, 2005 from Web site: http://briefing.riskgrades.com/clients/briefing/edu_course.cgi?href=Module4-L6.html
Sturzinger, W. Risks and its permutations. News for Banks. UBS. Retrieved January 25, 2005 from Web site: http://66.102.7.104/search?q=cache:98qKN9TAoOYJ:www.ubs.com/1/ShowMedia/bank_for_banks/news/archive%3FcontentId%3D28297%26name%3Dnewsletter_jan2003.pdf+%22heuristic%22+and+risk+and+bank& hl=en
Cite this Document:
Copy Bibliography Citation

Related Documents

Risk Management in Banks: Reference
Words: 4399 Length: 16 Document Type: Article Review

Hence, we decided to take differnet bank groups and companies (previously highlighted in the pie-charts) and compared the net growth of these selected bank groups in the finanical years of 2006 and 2007. Note that these net profits were claculated with the number of increase or decrease in the overall loans investments in these bank groups. An important thing to note here is that while bank credit is increasing in

Risk Management Analysis: Essential Tools
Words: 2853 Length: 10 Document Type: Research Paper

Most developed economies, however, allow the market to set exchange rates, only influencing currency values through indirect means such as the increased or reduced sale of bonds to foreign entities and individuals, or through other means of international wealth exchange. Essentially, all manipulations of exchange rates and actions based on predictions of exchange rates are focused on the forward exchange rate, or the predicted rate of exchange between two

Risk Management Tools: Interest Rate Futures, Interest
Words: 1113 Length: 3 Document Type: Essay

risk management tools: interest rate futures, interest rate options, forward rate agreement and interest rate swaps. Interest Rate Futures An interest rate futures contract is a financial derivative. It allows the buyer of the contract to lock in a future investment rate. Like all derivatives, interest rate futures are based on an underlying security, which is a debt obligation that moves in value as interest rates change (Ord, 2011). The interest rate

Analyzing the Risk Management
Words: 3962 Length: 10 Document Type: Term Paper

Risk Management Plan for Exxon Mobil A risk management process is a systematic application of management policies for the purpose of identifying, analyzing, evaluating and mitigating any possible risks within an organization. The following paper focuses on formulation of risk management plan for Exxon Mobil, one of the world's most renowned oil and gas companies. The risks would be identified and selected applicable to this firm and after their evaluation, a

Systemic Risk Management in the
Words: 1514 Length: 5 Document Type: Thesis

Real time information needs to be synthesized with traditional balance sheet approaches in order that regulators and industry leaders have a better sense of the systemic risk in the system. Measuring risk is the first step. Beyond that, risk management systems must be implemented. These have not changed much lately -- they still focus on liquidity and portfolio diversification. Derivative instruments in particular run the risk of distorting the

Lehman Brothers and Risk Management
Words: 1160 Length: 4 Document Type: Research Paper

Lehman Brothers and Risk Management This report examines the Lehman Brothers collapse and discusses issues of investment bank risk management. The report considers factors which contributed to Lehman's failure, from financial engineering as practiced by CEO Richard Fuld and other executives to lax auditing by Ernst & Young to the influence of an industry characterized by excessive risk-taking. In particular, the report focuses on the presence of inherent conflicts of interest,

Sign Up for Unlimited Study Help

Our semester plans gives you unlimited, unrestricted access to our entire library of resources —writing tools, guides, example essays, tutorials, class notes, and more.

Get Started Now