Abstract
The main goal of this paper is to investigate the random walk hypothesis in Fiji using monthly data from January 2000 to October 2017. Applying augmented Dickey Fuller (ADF 1979, 1981) and Phillips-Perron (1988), Zivot-Andrews (1992), and Narayan and Popp (2010) unit root tests, this study finds that stock prices is best characterized as non-stationary. The estimated multiple structural break dates in the stock prices corresponds with devaluation of Fijian dollar by 20 percent in 2009 and General Elections in September 2014, which Fiji First Party won by majority votes. The empirical results indicate that stock prices are best characterized as a unit root (random walk) process, indicating that the weak-form efficient market hypothesis holds in Fiji’s stock market. Hence, it will be difficult to predict future returns based on historical movement of stock prices in Fiji’s stock market.
Highlights
The topic of whether stock prices can be described as a random walk or mean reverting process is not new and has been subject of significant debate over the past few decades
Applying augmented Dickey Fuller (ADF 1979, 1981) and Phillips-Perron (1988), Zivot-Andrews (1992), and Narayan and Popp (2010) unit root tests, this study finds that stock prices is best characterized as non-stationary
The estimated multiple structural break dates in the stock prices corresponds with devaluation of Fijian dollar by 20 percent in 2009 and General Elections in September 2014, which Fiji First Party won by majority votes
Summary
The topic of whether stock prices can be described as a random walk or mean reverting process is not new and has been subject of significant debate over the past few decades. If stock prices are best characterized as mean reverting (trend stationary) process, this implies any shock will have temporary impact and series will return to its trend path over time and it would be possible to forecast stock prices based on historical stock prices (Narayan and Smyth 2007, Tiwari and Kyophilavong 2014). This allows investors to formulate trading strategies to earn abnormal returns (Narayan 2008, Lee, Lee, and Lee 2010)
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