INTERNATIONAL JOURNAL OF APPLIED SCIENCES AND MATHEMATICAL THEORY (IJASMT )
E- ISSN 2489-009X
P- ISSN 2695-1908
VOL. 8 NO. 2 2022
DOI: https://doi.org/10.56201/ijasmt.v8.no2.2022.pg38.50
Amadi, Innocent Uchenna and Wobo Gideon Omezurike
In this paper, different methods for estimation of parameters of Weibull distribution were examined using Mean Square Error (MSE) as a criterion for selecting the best model. The Method of Moments exceeded other methods. In the same circumstance, the estimated results were logically extended to form a matrix that would help in predicting different commodity price processes by exploring the properties of fundamental matrix solution where we obtained predicted stock prices and asset returns for 12 months. Finally, from the fundamental matrix system a theorem was developed and proved to show different levels of changes as it affects stock market in terms of short-run and long-run respectively.
Weibull distribution, stock market prices, Fundamental matrix solution and Estimation
[1] Weibull, W.(1951). A statistical Distribution of wide applicability. Journal of applied
mechanics,18,239-296.
[2] Egwim,K.C.,Eke,C.N.,Onuoha,D.O.,Igbo,C.A (2015).Comparative Analysis of Methods of
Estimating 2-parameter Weibull Distribution. Journal Of Natural Sciences Research Vol
5,2,10-16.
[3] Nwobi, F.N and Ugomma,C.A(2014).A comparison of Methods for the Estimation of
Weibull Distribution parameters.Metodoloskizvezki,vol.11,1,65-78.
[4] Al- Fawzein, Mohammed (2000). Methods For Estimating The Parameters of Weibull
Distribution, king Abdulaziz, city fox Science and Technology, Saudi Arabia
[5] Kritzman, M. L.Y.Page, S. and Rigobon,R.(2011). Principal components as a measure of
systemic risk. Journal of portfolio management, 37:112-126.
[6] Abodolsadeh, N. and Moslem, P. (2011). Financial modeling by ordinary and stochastic
differential equations. World Applied Sciences Journal, 13 (11): 2288-2295.
[7] Adeosun, M.E. , Edeki, S.O. and Ugbebor, O.O.(2015).Stochastic Analysis of stock Market
price models: A case study of the Nigeria stock exchange. WSEAS transaction on
Mathematics,14
[8] Andersen, T. G., Chung, H. J. and Sorensen, B. E. (1999). Efficient method of moments
estimation of a stochastic volatility model: A monte Carlo Study. Journal of Econometrics.
91,pp 61 – 87.
[9] Davies, I. Amadi, I.U and Ndu, R.I(2019).Stability Analysis of Stochastic Model for Stock
Market Prices. International journal of Mathematics and Computational Methods ,4,79-86.
[10] Dmouj, A.(2006). Stock price modeling: Theory and practice, BIM paper
[11] Fama, E. F. (1965).The behavior of stock-market price. Journal of Business vol. 38Issue 1,
34 – 105.
[12] Osu, B. O. (2012). Predicting the value of an option base on an option price. Journal of
mathematical comp, No.4 1091 – 1100.
[13] Osu, B. O; Amamgbo, O. R. and Adeosun M. E. (2012). Investigating the effect of capital
flight on the Economy of a developing nation via the NIG Distribution. Journal of
computation and modeling, vol. 2, No. 1, 77 – 92.
[14] Osu, B.O. and Okoroafor, A.C.(2007).On the measurement of random behavior of stock
price changes. Journal of mathematical science Dattapukur,18(2),131-141.
[15] Straja, S. R. (2005). Stochastic modeling of stock prices. PhD Montgomery investment
technology, Inc. 200 Federal street Camden, NJ 08103.www.fintools.com.
[16] Amadi I.U. Igbudu, R. and Azor, P.A.(2021). Stochastic Analysis of the Impact of Growth-
Rates on Stock Market Prices in Nigeria. Asian Journal of Economics, Business and
Accounting, 21(24), 9-21.