M. E. Alaei
PhD Student of Probability Theory and Mathematical Statistics, Yerevan State University, Yerevan, Armenia.
*Corresponding author: M. E. Alaei
Abstract
New statistical functions have been proposed that allow using known data on the past behavior of prices of any commodity to determine the state of the financial market. These new statistics are more general than the volatility and contain an estimate of volatility within them. These new statistical functions depend on the valuations of the European options and the Asian options, as well as the difference between these valuations and the sample realization. Black-Scholes formulas were used for statistical estimation. In this paper, we also used some propositions obtained by the author in previous works. An automated system has been built that monitors the state of the market and warns situations when the behavior of the commodity price function is critical. The system was tested on the example of oil price behavior at the period of time from December 1, 2006 to February 28, 2009 and gave good results, clearly recording the 2008 crisis.
References
[1] J. C. Hull. (2008). Options, futures and other derivatives. Prentice Hall, London.
[2] M. E. Alaei. (2017). Black-Scholes formula for Asian option with several futures. Armenian journal of mathematics, vol. 9, no. 2, pp. 84-92.
[3] H. S. Sukiasyan, M. E. Alaei. (2019). On the behavior of two types of expectations of a random process with Log-normal distribution. Journal of contemporary mathematical analysis (Armenian academy of sciences), vol. 54, no. 5, pp. 313-318.
[4] M. E. Alaei. (2017). On Numerical comparison between European and Asian options. Caspian journal of computational and mathematical engineering, no. 1, pp. 44-57.
[5] F. Black, M. Scholes. (1973). The pricing of options and corporative Liabilities. Journal of Political Economy, vol. 4, pp. 637-659.
How to cite this paper
Automated System for Monitoring the State of the Financial Market
How to cite this paper: M. E. Alaei. (2022) Automated System for Monitoring the State of the Financial Market. Journal of Applied Mathematics and Computation, 6(2), 263-266.
DOI: http://dx.doi.org/10.26855/jamc.2022.06.011
