Applications of Least Mean Square (LMS) Algorithm Regression in Time-Series Analysis

Giovanis, Eleftherios (2008): Applications of Least Mean Square (LMS) Algorithm Regression in Time-Series Analysis.

Abstract

In this paper we present a very brief description of least mean square algorithm with applications in time-series analysis of economic and financial time series. We present some numerical applications; forecasts for the Gross Domestic Product growth rate of UK and Italy, forecasts for S&P 500 stock index returns and finally we examine the day of the week effect of FTSE 100 for a short period. A full programming routine written in MATLAB software environment is provided for replications and further research applications.

• Item Type: MPRA Paper
• Language: English
• Keywords: LMS; Least Mean Square Algorithm; MATLAB; time-series; stock returns; gross domestic product; forecast
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes

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