Multi-Factor Regression and ECM Model: How Do Oil, NASDAQ and T-BILL Influence an Alternative Energy Fund

Abstract

Research Purpose The paper determines the role of the factors of the change of the price of alternative energy companies’ stock. The study focuses on the NASDAQ High Tech index, the price of oil and the US interest rate.

Research Design Based on the research of the paper “Oil prices and the stock prices of alternative energy companies” by Irene Henriques and Perry Sadorsky (Henriques & Sadorsky, 2007), I will use diverse regression methods (Multi factor regression, ECM) to find the significance and Beta of the factors cited above.

Findings My results follow Henriques and Sadorsky’s, as I find a significant long run positive beta for the three factors. My ECM models returned me a negative short term relation with oil, and not significant betas for the other variables. The ECM model also showed that the fund tends to return to the equilibrium position.

Research Limitations Both of the markets have very complex and underlying consequences , for example, the rise of the price of oil can provoke inflation; some alternative energy companies are in the NASDAQ high tech Index. Plus, some other statistical models (ARCH/GARCH Model) might be more powerful for this project.

Research Implications The use of alternative energy will grow in the years to come, and understanding the factors which move the industry’s valuation is important for any interested investor. Originality and Value Due to the recency of the topic, very little conclusions have been made on the subject. I hope to find some interesting and useful data that might reduce the perceived risk of investors, leading to higher investment in the alternative energy sector.

Keywords: regression, ECM, factor, alternative energy, oil, nasdaq, T-BILL, statistic

JEL Classification: C51, C87, Q42