# Applications of Simulation-Based Methods in Finance: The Use of ModelRisk Software

• 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.

### References

[1] Acerbi, C. 2002. Spectral measures of risk: a coherent representation of subjective risk aversion. Journal of Banking and Finance, 26:1505–1518.
[2] Bondarenko, O. 2003. Statistical Arbitrage and Securities Prices. Review of Financial Studies, 16: 875–919.
[3] Calin, O. 2012. An introduction to stochastic calculus with applications. On-line lecture notes.
[4] Rockafellar, R. T., and Uryasev, S. 2000. Optimization of conditional value-at-risk. Journal of Risk, 3: 21-41.
[5] Sarykalin, S., Serraino, G., and Uryasev, S. 2008. Value-at-risk vs. conditional value-at-risk in risk management and optimization. Tutorials in Operations Research. C @ Informs: 270-298.
[6] Vose, D. 2010. Risk analysis: a quantitative guide. Wiley.
[7] Wang, X. Q., and Gao, B. 2012. Dynamic measurement and evaluation on foreign exchange risks of international construction projects. Proceedings of the 2012 IEEE IEEM. USA.
[8] Ye, S., and Tiong, R. L. K. 2000. Npv-at-risk method in infrastructure project investment evaluation. Journal of Construction Engineering and Management, 3: 227-233.
Published
2016-11-29
How to Cite
HABIBI, Hamed; HABIBI, Reza. Applications of Simulation-Based Methods in Finance: The Use of ModelRisk Software. Journal of Advanced Studies in Finance, [S.l.], v. 7, n. 1, p. 82-89, nov. 2016. ISSN 2068-8393. Available at: <https://journals.aserspublishing.eu/jasf/article/view/499>. Date accessed: 23 jan. 2022.
Citation Formats
Section
Journal of Advanced Studies in Finance

### Keywords

arc-sine laws; CNPVaR; dynamic and quadratic programming; exchange rate risk; first passage of time; optional sampling theorem; statistical arbitrage