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Applications of Simulation Based Methods in Finance The Use of ModelRisk Software

Author

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  • Hamed HABIBI

    (Faculty of Science and Engineering Curtin University Perth)

  • Reza HABIBI

    (Iran Banking Institute Central Bank of Iran Tehran)

Abstract

This paper has two parts The first part considers the statistical arbitrage detection using the simulation based approaches The statistical arbitrage is the opportunity of attaining gain at future with a high probability with zero investment at the current time Simulated methods relies on the direct use of three famous theorems in the field of stochastic process namely i the arc sine laws ii the first passage of time and iii optional sampling theorem It is very important for investors to use the simulated approaches by user friendly software like the ModelRisk of Excel which is done in this note In the second part the conditional NPVaR CNPVaR of a cash flow stream in the presence of exchange rate risk The distribution of risk factors are assumed to be a specified location scale distribution The application of dynamic programming and quadratic programming are studied

Suggested Citation

  • Hamed HABIBI & Reza HABIBI, 2016. "Applications of Simulation Based Methods in Finance The Use of ModelRisk Software," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 7(1), pages 82-89.
    • Handle: RePEc:srs:jasf00:v:7:y:2016:i:1:p:82-89
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    Cited by:

    1. Yonggu Kim & Eul-Bum Lee, 2018. "A Probabilistic Alternative Approach to Optimal Project Profitability Based on the Value-at-Risk," Sustainability, MDPI, vol. 10(3), pages 1-24, March.

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