Stochastic Modeling in Economics & Finance by Dupacova, by Jitka Dupačová, Jan Hurt, Josef à těpán (auth.)

By Jitka Dupačová, Jan Hurt, Josef à těpán (auth.)

Stochastic Modeling in Economics & Finance by means of Dupacova, Jitka, damage, J., Stepan, J.. . Springer, 2002 .

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Stochastic Modeling in Economics & Finance by Dupacova, Jitka, Hurt, J., Stepan, J.. (Springer,2002) [Hardcover]

Stochastic Modeling in Economics & Finance by way of Dupacova, Jitka, harm, J. , Stepan, J. . . Springer, 2002 .

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Additional resources for Stochastic Modeling in Economics & Finance by Dupacova, Jitka, Hurt, J., Stepan, J.. (Springer,2002) [Hardcover]

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See also [109]. 5 Stress Testing Often it is of interest for an investor to know what will happen if the market conditions attain their extremes, either in positive or negative direction from the investor's point of view. Of course, the more unfavorable, the more important they are for the investor's decision making, and they resemble VaR (in the sense of maximum possible loss) to some extent. A possible method to see what will happen is based on a scenario analysis. Stress testing starts with a construction of sce~iarios covering the extreme situations involved.

The user should carefully input the data with proper plus or minus signs for inflows and outflows, respectively. 7 Example (Installment Savings). 036. What will be the total of principal and interest at the end? 003, T = 36. 069 so that FV = 190349. a. This results in the total savings FV = 193273. Give an explanation as an exercise. 8 Example and Exercise (Loans). , compounded monthly. The question is, how much you can borrow under these conditions. 006, FV = 0, T = 36. 29, you can borrow PV = 161454.

If p is the rate of return instead, and p, a its characteristics, then the value at risk in (20) - (26) is expressed in terms of the initial investnient Po as unit, in other words, the niaximum possible loss (in dollars) is -pPo - au,Po. 2 Nonparametric VaR If only little is known about the analytical (parametric) form of the returns' distributions but a sufficient amount of (historical) data is available, then a proper method for the risk analysis may be based on a nonparametric approach. Suppose that the observed returns during a given period (one year, say) are R1, .

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