Original Research Article
Year: 2016 | Month: April | Volume: 3 | Issue: 4 | Pages: 51-56
Circular Methods on Forecasting Risk & Return of Share Market Investments
W.G. S. Konarasinghe1, N. R. Abeynayake2, L.H.P.Gunaratne3
1.Postgraduate Institute of Agriculture, University of Peradeniya, Sri Lanka.
2Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP), Sri Lanka.
3Department of Agricultural Economics and Business Management, Faculty of Agriculture, University of Peradeniya, Peradeniya, Sri Lanka.
Corresponding Author: W.G. S. Konarasinghe
Statistical measurements developed on covariance of two or more random variables or autocorrelation of a random variable were used in forecasting stock returns. Capital Asset Pricing Model (CAPM) is a model based on covariance analysis. Vector Auto Regression Model and Auto Regressive Integrated Moving Average Models are models based on auto correlation. Risk of returns was measured by standard deviation or beta factor of CAPM. Literature reveals the incapability of CAPM in measuring risk and return. Time series data are generally auto correlated; as such standard deviation is not a suitable measurement for risk of returns. This study was focused to develop suitable models for forecasting risk and returns of share market investments. Two new forecasting techniques; Circular Model and Circular Indicator were developed. Circular Model was based on Fourier transformation, Circular Indicator was based on Newton’s law of uniform circular motion. Suggested methods were tested by using Sri Lankan share market returns. Results revealed the success of both methods in Sri Lankan context. It is recommended to test the suggested methods on more share markets. Also the methods can be tested on wave like patterns find in fields of medicine, agriculture, meteorology etc.
Key Words: Circular Model, Circular Indicator, Fourier Transformation.