Project

Final Term Project

Directions: Read the following Case and answer all the questions. Please submit your work to the Dropbox by midnight Sunday CT.

Following is a portfolio consisting of 50 bonds with a market value of $ 99,999,999 as of April 29, 2011:

Table 1: 50-bond Portfolio

Identifier Description Sector Market Value
003723AA ABN AMRO BANK NV Corp. Financials 1,422,596
251591AY DEVELOPERS DIVERS REALTY Corp. Financials 644,344
381427AA GOLDMAN SACHS CAPITAL II Corp. Financials 2,761,546
58551TAA MELLON CAPITAL IV Corp. Financials 3,102,915
912810PW US TREASURY BONDS Treasury 804,588
912810QA US TREASURY BONDS Treasury 7,505,533
912810QK US TREASURY BONDS Treasury 4,048,097
912828PA US TREASURY NOTES Treasury 3,378,751
912828PF US TREASURY NOTES Treasury 20,596,365
00104BAC AES EASTERN ENERGY Corp. Utilities 1,206,446
02360XAL AMERENENERGY GENERATING Corp. Utilities 737,343
165167BS CHESAPEAKE ENERGY CORP Corp. Utilities 880,013
125896BG CMS ENERGY Corp. Utilities 1,337,697
665772CE NORTHERN STATES PWR MINN Corp. Utilities 907,113
797440BM SAN DIEGO GAS & ELECTRIC Corp. Utilities 856,840
FGB08000 FHLM Gold Guar Single F. 30yr MBS Agency 3,040,911
FGB07001 FHLM Gold Guar Single F. 30yr MBS Agency 780,262
FGB06402 FHLM Gold Guar Single F. 30yr MBS Agency 1,004,579
FGB07002 FHLM Gold Guar Single F. 30yr MBS Agency 4,235,068
FGB05403 FHLM Gold Guar Single F. 30yr MBS Agency 1,531,707
FGB06003 FHLM Gold Guar Single F. 30yr MBS Agency 1,537,027
FGB06004 FHLM Gold Guar Single F. 30yr MBS Agency 700,545
FGB05011 FHLM Gold Guar Single F. 30yr MBS Agency 690,585
FNA07098 FNMA Conventional Long T. 30yr MBS Agency 1,014,899
FNA08000 FNMA Conventional Long T. 30yr MBS Agency 1,883,297
FNA05402 FNMA Conventional Long T. 30yr MBS Agency 1,854,853
FNA06402 FNMA Conventional Long T. 30yr MBS Agency 1,311,433
FNA07002 FNMA Conventional Long T. 30yr MBS Agency 2,563,939
FNA05003 FNMA Conventional Long T. 30yr MBS Agency 684,085
FNA05403 FNMA Conventional Long T. 30yr MBS Agency 3,469,103
FNA06003 FNMA Conventional Long T. 30yr MBS Agency 1,715,870
FNA05010 FNMA Conventional Long T. 30yr MBS Agency 843,855
FNA05011 FNMA Conventional Long T. 30yr MBS Agency 1,173,465
GNB04411 GNMA II Single Family 30yr MBS Agency 2,509,580
91311QAD UNITED UTILITES PLC Corp. Industrials 848,272
02051PAC ALON REFINING KROTZ Corp. Industrials 630,655
101137AD BOSTON SCIENTIFC Corp. Industrials 1,656,030
12527GAA CF INDUSTRIES INC Corp. Industrials 1,499,778
582834AM MEAD CORP Corp. Industrials 787,191
651715AF NEWPAGE CORP Corp. Industrials 1,603,501
723787AG PIONEER NATURAL RESOURCES Corp. Industrials 1,045,275
749685AQ RPM INTERNATIONAL INC Corp. Industrials 642,823
784635AM SPX CORPORATION Corp. Industrials 766,621
915436AF UPM-KYMMENE CORP Corp. Industrials 648,265
962166AV WEYERHAEUSER CO Corp. Industrials 871,588
45950KBJ INTL FINANCE CORPORATION Gov. Related 1,198,808
45905CAA INTERNATL BANK RECON DEV-GLOBA Gov. Related 1,200,080
46513E5Y ISRAEL STATE OF-GLOBAL Gov. Related 1,911,761
500769BR KREDIT FUER WIEDERAUFBAU-GLOBA Gov. Related 1,012,672
500769CH KREDIT FUER WIEDERAUFBAU-GLOBA Gov. Related 941,429

Table 2: Asset Class

The benchmark for the manager who has constructed this portfolio is a composite index consisting of one-third each of the Barclays Capital U.S. Treasury index, Barclays Capital U.S. Credit Index, and Barclays Capital U.S. MBS index. First, in regards to the Barclays Capital U.S. Treasury index, this index measures the performance of U.S. Treasury securities. Second, in regards to the Barclays Capital U.S. Credit Index, this index includes both corporate and non-corporate sectors where the corporate sectors are industrial, utility, and finance that include both U.S. and non-U.S. corporations. The non-corporate sectors are sovereign, supranational, foreign agency, and foreign local government. The index is calculated monthly on price-only and total-return basis. All returns are market value-weighted inclusive of accrued interest. Third, in regards to the Barclays Capital U.S. MBS index, this index measures the performance of investment grade fixed-rate mortgage-backed pass-through securities of GNMA, FNMA, and FHLMC.

Asset Class Portfolio Benchmark
Total 100.0 100.0
Treasury ? 33.3
Government Related ? 6.8
Corporate Industrials ? 13.9
Corporate Utilities ? 2.9
Corporate Financials ? 9.7
MBS Agency ? 33.3

Table 3.1: Analytics for the 50-bond Portfolio and the Benchmark

Table 3.1 provides information about the relative exposure to interest rate risk as measured by duration, spread risk as measured by spread duration, and call/prepayment risk as measured by vega, as well as the convexity.

Analytics Portfolio Benchmark Difference
Duration 6.87 5.37 1.50
Spread Duration 6.77 5.27 1.50
Convexity 0.47 0.00 0.47
Vega ​0.01 ​0.03 0.02
Spread(bps) 355 55 300.00

Table 3.2: Contribution to Duration by Asset Class for the 50-bond Portfolio

Table 3.2 provides information about the portfolio’s relative risk exposure to interest rate risk.

Duration Contribution Portfolio Benchmark Difference
Total 6.87 5.37 1.50
Treasury 3.62 1.78 1.84
Government Related 0.92 0.41 0.51
Corporate 1.10 1.74 –0.63
Securitized 1.23 1.45 –0.22

Table 4: Monthly Tracking Error for Risk Factors

Risk Factor Categories Isolated Risk/Tracking Error
Curve 40.8
Swap Spreads 2.5
Volatility 2.8
Spread Government Related 5.3
Spread Corporate 30.6
Spread Securitized 5.8

Table 5: Volatility table.

This table provides the breakdown of the standard deviation of the returns for the portfolio and the benchmark

Volatility Portfolio Benchmark Tracking Error
Systematic 141.9 117.4 37.9
Idiosyncratic 19.3 4.8 18.7
Total 143.2 ? ?
Duration Beta ?

Table 6: Detailed Monthly Tracking Error for the 50-Bond Portfolio by Risk Factor Group

The “risk factor group” table provides information about the portfolio risk across the different categories of risk factors. Shown are the systematic risk and the idiosyncratic risk and six components of systematic risk. The “contribution to TEV” column shows the isolated tracking error. The contribution to tracking error for each group of risk factor is shown in the “liquidation effect on TEV” column.

Risk Factor Group Isolated TEV Contribution to TEV Liquidation Effect on TEV TEV Elasticity (%)
Total 42.3 42.3 –42.3 1.0
Systematic Risk 37.9 33.2 –22.4 0.8
Curve 40.8 23.4 –4.3 0.5
Swap Spreads 2.5 0.2 –0.1 0.0
Volatility 2.8 0.5 –0.4 0.0
Spread Government Related 5.3 0.0 0.3 0.0
Spread Corporate 30.6 10.0 0.8 0.2
Spread Securitized 5.8 –0.8 1.1 0.0
Idiosyncratic Risk 18.7 9.1 –4.2 0.2

Questions

The purpose of this project is to describe in detail the risk characteristics of the 50-bond Portfolio. Your instructor drew up the following list of questions that should be covered to be able to discuss the portfolio’s risk relative to the benchmark. In your analysis, be sure to discuss where it seems like the manager is taking views on the market.

1. Use the data in Table 1 to calculate the missing weights for each class asset that appear in Table 2. After completing the missing weights, start your analysis of table 2 by comparing the portfolio to that of benchmark in terms of the allocation to the major sectors of the benchmark (i.e., overweighting/underweighting). Discuss your results.

2. Do you think the portfolio manager can use the percentage allocation to each sector (i.e., Asset class table) to evaluate the portfolio’s exposure to various risk factors? Explain?

3. Use the data in Table 3.1 and 3.2 to assess the portfolio risk relative to the benchmark? Make sure to discuss the sources of risk (i.e., interest rate risk, spread risk, and call & prepayment risk). Before starting your analysis, explain the differences among interest rate risk, spread risk, and call & repayment risk.

4. What is tracking error? What is meant by tracking error due to systematic risk factors? What is meant by isolated tracking error? Briefly explain what is meant by yield curve risk, swap spread risk, volatility risk, government-related spread risk, corporate spread risk, and securitized spread that are listed in table 4 and the (monthly) volatility of these risk factor categories?

5. Compute the isolated systematic tracking error for the portfolio given the monthly tracking error for each risk factor exposure in Table 4? Discuss the implications of your results for the risk exposure of this portfolio. Make sure to assume a zero correlation between any pair of risk factors when calculating the portfolio isolated systematic tracking error.

6. Why is the tracking error more important than portfolio variance of returns when a portfolio manager’s performance is measured versus a benchmark?

7. You are reviewing table 5 that indicates that a portfolio tracking error is 143.2 basis points. It is also reported that the tracking error due to systematic risk is 141.9 basis points and the tracking error due to non-systematic risk is 19.3 basis points. Why doesn’t the sum of these two tracking error components total up to 161.2 basis points?

8. Calculate the total risk for the benchmark using the values in the “volatility” Table (i.e., Table 5) and portfolio tracking error (volatility of net position). Complete the related blank in Table 5.

9. How can a multi-factor risk model be used to monitor and control portfolio risk? Explain whether you agree or disagree with the following statement “It is the tracking error not the idiosyncratic risk (as measured by the standard deviation of the idiosyncratic returns) that the manager must consider in portfolio construction and monitoring”. Use Table 5 to support your argument.

10. Compute the duration beta using the values in the “analytics” table (Table 3.1). Complete the related blank in Table 5. Explain your answer.

11. Based on the information given in Table 6, what are the major risk exposures of the 50-bond portfolio? Explain your answer.

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