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Financial derivative and risk management.

The case is intended to be used for MBA and BBA programs in the elective courses such as derivatives and risk management, financial engineering, financial risk management and portfolio management, and for executives aspiring for the fund manager position in industry. The case could also be used in management development programs on financial risk management.

The case was based on the real life experience of a portfolio manager who was entrusted with the responsibility of maximizing return of the portfolio. With the backdrop of dismal performance of the portfolio, the portfolio manager is looking for opportunity in the context of declaration of result by Infosys Ltd, one of the constituents of the portfolio. So the team headed by Nirakar Chaulia was thinking of development and application of option strategies to exploit the result day (i.e. January 14, 2016) opportunity to improve the performance of the portfolio and also reduce the potential of stock price risk. Moreover, the case was designed to help the students develop and assess different option strategies based on their market intuitions. Also, students would be able to apply the option contracts for managing price risk associated with the underlying asset.

The case would prepare students to develop different strategies to be exploited in different market conditions and assess their performance. Especially, this case was designed to enable the students to understand options as a special kind of derivative in terms of trading and its payoff, how to initiate directional and volatility trading with options, how to apply options to generate income to enhance the portfolio performance and how to develop option strategies for different market conditions and assess their performance.

Teaching note is available for instructors only.

CSS 1: Accounting and Finance.

This short case could be handed out at the end of class discussion on “J&L Railroad” [UVA-F-1053] in preparation for the following class, or if students are more experienced with hedging and option pricing, the instructor may choose to cover both cases in a single class period. It is the companion case to “J&L Railroad” [UVA-F-1053], and presents more technical issues regarding the hedging problem by requiring students to understand option-pricing principles. The board likes the CFO's hedging recommendations, but it wants a more careful analysis of the bank's prices for its risk-management products: the caps and floors. Besides demanding an understanding of option pricing, this case puts particular emphasis on the calculation and use of implied volatility.

It intends to help the learners assess the scenarios of volatility in the Indian capital market which was caused by unpredictable market forces. It also helps in understanding how analysts struggle to predict the direction of the market and what options strategies can be recommended to be deployed by the investors to maximize returns in such compelling scenarios.

This case study presents snapshots of high volatilities caused by the market and economic forces in the Indian capital market. It depicts how analysts struggled to predict the direction of the market; and how high volatility can put them in trouble. It also exemplifies as to how by selecting the apt strategies, investors maximize their immediate returns in a volatile period and can produce large returns in a short time.

The best time to discuss the case is during the completion of options strategies in the course of Derivatives or Portfolio/Investment Management.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 1: Accounting and Finance.

Risk managers have more tools than ever to help protect their companies from risk. Complex financial instruments, intricate mathematical models, and access to massive amounts of data can help the risk manager structure a multifaceted strategy to decrease volatility and protect the company from a catastrophic event. However, these tools have their own risks that can complicate a risk manager's job.

Analyzing corn price volatility helps students understand four best practices for risk managers, regardless of the specific risks they face or the strategies they employ: quantify the company's exposure; understand the nature of the risk; understand how the hedge works in practice; and separate hedging and speculation.

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in Illinois in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the value-at-risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses. The questions in Part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF's risk management. In Part (B) the foundation receives a major donation. As a result, the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund's new portfolio and to perform a portfolio rebalancing analysis.

Understanding the concept of value at risk (VaR); Calculating daily and monthly VaR by two different methods, the historical and the parametric approach; Interpreting the results of VaR calculations; Understanding the role of diversification for managing risk; Evaluating the impact of portfolio rebalancing on the overall risk of a portfolio.

In early January 2008, a senior VP with LAAMCO, a fund of hedge funds known for alternative investments, was conducting due diligence on an equity market-neutral hedge fund. The hedge fund used an option strategy known as a collar (also known as a bull spread or split-strike conversion). The track record of the hedge fund had been stellar. The fund's performance had not only beaten that of the S&P 500 Index over the same period but had done so with much lower monthly return volatility. As part of the due diligence, it was necessary to backtest the collar strategy and try to quantify how much value the manager, BLM Investment Securities, LLC, (BLM) had added. The case is a disguised representation of an actual hedge fund—the true identity of BLM is revealed to students at the end of the case discussion.

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in Illinois in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the value-at-risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses. The questions in Part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF's risk management. In Part (B) the foundation receives a major donation. As a result, the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund's new portfolio and to perform a portfolio rebalancing analysis.

Understanding the concept of value at risk (VaR); Calculating daily and monthly VaR by two different methods, the historical and the parametric approach; Interpreting the results of VaR calculations; Understanding the role of diversification for managing risk; Evaluating the impact of portfolio rebalancing on the overall risk of a portfolio.

The financial success of dairy farms depends critically on the price of their main output, milk. Large volatility in the price of milk poses a considerable business risk to dairy farms. This is particularly true for family-run dairy farms. The question then arises: how can a farm owner hedge the milk price risk? The standard approach to establish a price floor for a commodity such as milk is to purchase put options on commodity futures. At the Chicago Mercantile Exchange, farmers can buy put options on the price of a variety of milk products. However, the price a farm receives for its milk depends on many factors and is unique to the farm. Thus, a farmer cannot directly buy put options on the price he receives for the milk his farm produces. Instead the farmer needs to determine which of the options available for trade at the Chicago Mercantile Exchange offer the best hedge for his own milk price. The assignment in this case is to examine historical data on several prices of milk products and the milk price received by a family-run dairy farm in California. Students need to find the price that is most closely correlated to the farm's milk price and to then choose options with the appropriate strike price that serve as the best hedge for the farm's price risk.

The objective is to expose students to an interesting but simple finance application of linear regression analysis. To solve the case, students must run several simple linear regressions, then use the best regression model they find to make a prediction for the dependent price variable and analyze the prediction interval in order to achieve the desired objective outlined in the case. By completing the case, students will acquire a good understanding of their regression model and its usefulness.

Technology projects are inherently risky; research shows that large IT projects succeed as originally planned only 28 percent of the time. Building flexibility, or real options, into a project can help manage this risk. Furthermore, the management flexibility of options has value, as the downside risk is reduced and the upside is increased. The case is based upon real options analysis for an enterprise data warehouse (EDW) and analytic customer relationship management (CRM) program at a major U.S. firm. The firm has been disguised as Global Airlines for confidentiality reasons. The data mart consolidation or EDW marginally meets the hurdle rate for the firm as analyzed using a traditional net present value (NPV) analysis. However, different tactical deployment strategies help mitigate the risk of the project by building options into the project, and the traditional NPV is expanded by the real option value. Students analyze the different deployment strategies using a binomial model compound option Excel macro, and calculate the volatility using Monte Carlo analysis in Excel. A step-by-step tutorial is provided to teach students how to accomplish the real options analysis for a simplified project, and this tutorial is easily generalized by students to the case scenario. In addition to the tactical options, the case also has the strategic growth option of analytic CRM. Students must therefore analyze both the tactical and strategic growth options and make a management recommendation on funding the project and also recommend an optimal deployment strategy to manage the project risk.

The case teaches real options for technology projects. Students learn how to calculate real option values, where the key input of volatility is obtained by Monte Carlo analysis in Excel. Students also learn that the real option value is “real,” resulting from active management mitigating the risk of the project and improving the upside. Most important, students understand the difference between tactical vs. strategic growth options and the important management issues to consider.

In 2007, Best Buy was the leading electronics retailer in the United States with more than 941 stores, revenue totaling $31 billion, and a market cap of $21 billion. In 2005, Best Buy had adopted a new business model, culture, and customer-segmentation template called Customer Centricity. This move created volatility in the price of Best Buy stock because of the higher-than-expected employee costs that went with this new way of doing business and the difficulty of executing the old and the new business models simultaneously while the new model was rolled out. Best Buy responded to Wall Street's short-term focus in a myriad of ways. It first asked for investor patience, and stressed the strong operating results achieved in Best Buy stores operating under the new model. But in June 2007, after the stock dropped again, the CEO knew he had to decide whether to open more Best Buy stores, increase the company's dividend, or increase the stock-repurchase program.