Read e-book online Applied Asset and Risk Management: A Guide to Modern PDF

By Marcus Schulmerich

ISBN-10: 3642554431

ISBN-13: 9783642554438

ISBN-10: 364255444X

ISBN-13: 9783642554445

This ebook is a advisor to asset and chance administration from a pragmatic perspective. it's founded round questions prompted by way of the worldwide occasions at the inventory markets because the center of the decade:

- Why do crashes take place whilst in concept they need to no longer?

- How do traders care for such crises when it comes to their probability size and administration and subsequently, what are the consequences for the selected funding ideas?

The booklet offers and discusses varied ways to finance and making an investment, i.e., smooth portfolio thought and behavioral finance, and gives an summary of inventory industry anomalies and historic crashes. it's meant to function a entire advent to asset and threat administration for bachelor’s and master’s scholars during this box in addition to for younger execs within the asset administration undefined. A key a part of this booklet is the routines to additional exhibit the innovations awarded with examples and a step by step company case. An Excel dossier with the calculations and options for all 17 examples in addition to all enterprise case calculations should be downloaded at extras.springer.com.

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Read or Download Applied Asset and Risk Management: A Guide to Modern Portfolio Management and Behavior-Driven Markets PDF

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Extra info for Applied Asset and Risk Management: A Guide to Modern Portfolio Management and Behavior-Driven Markets

Sample text

The first column is labeled A (month) and the second B (monthly portfolio performance). Applying Excelr functions, the portfolio return, the benchmark return and alpha are calculated as follows below. Please 5 Chincarini and Kim (2006). 12=18/ 1g 14 1 Risk Measures in Asset Management • Annualized alpha ˛ p:a: in cell D21: 2:77 % D B21 C 21 End of Example 1 Until now, we have calculated the historical returns. However, every investor is even more interested in the returns of the future. But while the past return of an asset can always be expressed as a certain number, we do not know the future asset return with certainty and, therefore, treat it as a random variable.

Knowing that, in practice, only three relative returns are insufficient to get a meaningful volatility value, this example is only for illustrative purposes. k Calculation for the percentage returns rXYC for each subperiod k D 1; 2 and 3 D N: e 110 e 100 D 10 % e 100 e 122 e 110 D 10:91 % D e 110 e 136 e 122 D 11:48 %: D e 122 1 rXYC D 2 rXYC 3 rXYC Calculation of the arithmetic average of the percentage returns in the three subperiods: r XYC D D 1 2 3 C rXYC C rXYC rXYC N 10 % C 10:91 % C 11:48 % D 10:80 %: 3 According to Eq.

39 40 Esch et al. (2005, p. 42). Hull (2009, p. 284). We assume 252 trading days per year. 3 Traditional Risk and Risk-Adjusted Return Measures 43 • If the covariance is negative, then one asset tends to have high (low) returns when the other one has low (high) returns. For example, high oil prices negatively affect airlines. Hence, the covariance between the returns of airline stocks and oil prices is negative. • If the covariance is zero, then there is no linear relation between the asset returns: knowledge of the return of one asset will not lead to any knowledge about the return of the other asset.

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Applied Asset and Risk Management: A Guide to Modern Portfolio Management and Behavior-Driven Markets by Marcus Schulmerich


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