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Discriminating the Pivot Points using Discriminant Function

R. Subathra

Abstract


Discriminant analysis is an exploratory classification technique to discriminate the data in to two or more groups using an optimal plane. The pivot points are used to identify the potential turning points while trading in futures, commodities and stock markets. This work applies Discriminant analysis to compare the performances of the pivot points computed using Standard method, Woodie’s method and DeMark’s method and.  The categorical trend variables generated with these three pivot points are the dependent variables in this study. With multiple technical indicators as explanatory variables the performances of the three types of pivots are compared using the daily prices of NIFTY50, NIFTY-AUTO, NIFTY-IT,NIFTY-PHARMA BANK NIFTY for this purpose.. The credibility of the results is tested with various performance measures and out of sample tests of the fitted discriminant functions


Keywords


Area Under Curve, Average True Range, DeMarks Pivot Point, Linear Discriminant Analysis, Moving Average Convergence and Divergence, Quadratic Discrimnant Function, Relative Strength Index, Standard Pivot Point, Technical Indicators, Volatility Indicator,

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References


Altman, E.I., (1968). “Financial ratios, discriminant analysis and the prediction of corporate bankruptcy”. Journal of Finance, 23:.589-609.

Chen.G and H.Tsurumi (2010). Probit and logit model selection. Communications in Statistics - Theory and Methods, 40, 159-175.

Connor, M.C. (1973).”On the usefulness of Financial Ratios to Investors in Common Stock”. The Accounting Review: 339- 352, April.

Haines, L. M. et.al. (2007).”D-optimal Designs for Logistic Regression in Two Variables, mODa8-Advances in Model-Oriented Designed and Anaysis” : Physica-Verlag HD. p.91-98.

Horrigan, James O. (1965). “Some Empirical Bases of Financial Ratio Analysis”. The Accounting Review: 284-294 , July.

Huang, Q. Cai, Y., Peng, J. (2007) .”Modeling the Spatial Pattern of Farmland Using GIS and Multiple Logistic Regression: A Case Study of Maotiao River Basin,” Guizhou Province, China. Environmental Modeling and Assessment, 12(1):55-61.

Hur-Yagba, A.A., Okeji, I.F., Ayuba, B. (2015). Analyzing Financial Health of Manufacturing Companies in Nigeria Using Multiple Discriminant Analysis. International Journal of Managerial Studies and Research (IJMSR). Vol.3, Issue7, July 2015. pp 72-81. ISSN 2349-0330 (print) & ISSN 2349-0349(online) www.arcjournals.org.

Kumar P R and Ravi V (2007), Bankruptcy Prediction in Banks and Firms via Statistical and Intelligent techniques: A review”, European Journal of Operation Research, Vol 180, pp. 1-28

Lee, S. (2004). “Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping Using GIS”. Environmental Management.34 (2):223-232.

Melnyk,Z.L. & Mathur, Iqbal .(1972) .Business Risk Homogeneity: A Multivariate Application and Evaluation. Proceedings of the 1972 Midwest AIDS Conference, April.

Nepal, S. K. (2003).”Trail Impacts in Sagarmatha (Mt. Everest) National Park, Nepal: A Logistic Regression Analysis”. Environmental Management, 32(3):312-321.

Ohlson, J. (1980). “Financial ratios and the probabilistic prediction of bankruptcy”. Journal of Accounting Research, 18:109-31.

Oghojafor, B., Mesike, G., Bakarae, R., Omoera, C., & Adeleke, I. (2012). Discriminant Analysis of Factors Affecting Telecoms Customer Churn. International Journal of Business Administration. Vol.3, Issue 2, March 2012. www.sciedu.ca/ijba, http://dx.doi.org/10.5430/ijba.v3n2p59

Okeke, T.C., & Amobi, D.C. (2014). A Discriminant Analysis of Electronic Banking in Nigeria. Journal of Emerging Trends in Economics & Management Science. (JETEMS). Vol. 5, Issue 2. pp 194-200. © Scholarlink Research Institute Journals, 2014. (ISSN: 2141- 7024), jetems.scholarlinkresearch.org

Pardo,J.A., Pardo L, Pardo, M.C (2005) “Minimum Ө-divergence Estimator in logistic regression Models”, Statistical Papers, No 47, 91-108.

Zavgren, C. (1985). “Assessing the Vulnerability to Failure of American Industrial Firms: A Logistic Analysis”. Journal of Business Finance and Accounting, 12 (1):19–45.

Zavgren, C.V., & Friedman, G. E., (1988). Are bankruptcy prediction models worthwhile? An application in securities analysis Management International Review, Vol. 28(1), pp.34-44.

Zmijewski, M.E. (1984). “Methodological Issues Related to the Estimation of Financial Distress Prediction Models”. Journal of Accounting Research, 22:59-82.


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