scholarly journals Random Walk in Emerging Asian Stock Markets

2016 ◽  
Vol 9 (1) ◽  
pp. 20
Author(s):  
Muneer Shaik ◽  
S. Maheswaran
Keyword(s):  
Random Walk ◽  
Unit Root ◽  
Stock Prices ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Unit Root Tests ◽  
Optimal Test ◽  
Market Prices ◽  
Crisis Period ◽  
Random Walk Hypothesis

<p>The random walk hypothesis is an important area of research in finance and many tools have been proposed to investigate the behaviour of the fluctuations in stock prices. However, a detail study on emerging Asian stock markets which employ the various unit root tests has not been done. In this paper, we employ six different unit root tests such as the Augmented Dickey and Fuller test (1979), Phillips and Perron test (1988), Kwiatkowski-Phillips-Schmidt-Shin test(1992), Dickey-Fuller GLS (ERS) test (1996), Elliot-Rothenberg-Stock Point-Optimal test (1996) and Ng and Perron (2001) unit root tests on 10 emerging Asian stock markets to detect for the presence of a random walk in stock prices. We have conducted the unit root tests during different sub-sample time periods of global financial crisis to check for robustness. To be specific, we have found that during the overall sample period (2001-2015) 8 out of 10 Asian stock markets and during the pre-crisis period (2001-2007) all the 10 Asian stock market prices do follow random walk according to the unit root tests under consideration. However, during the crisis &amp; post-crisis period (2008-2015) we have found only 5 out of 10 Asian markets follow the random walk movement based on unit root tests.</p>

Do Asian Stock Markets Follow a Random Walk? Evidence from LM Unit Root Tests with One and Two Structural Breaks

2007 ◽  
Vol 10 (01) ◽  
pp. 15-31 ◽  
Author(s):  
Hooi Hooi Lean ◽  
Russell Smyth
Keyword(s):  
Random Walk ◽  
Lagrange Multiplier ◽  
Unit Root ◽  
Stock Prices ◽  
Structural Breaks ◽  
Structural Break ◽  
Unit Root Test ◽  
Unit Root Tests ◽  
Asian Countries ◽  
Random Walk Hypothesis

This paper applies univariate and panel Lagrange Multiplier (LM) unit root tests with one and two structural breaks to examine the random walk hypothesis for stock prices in eight Asian countries. The results from the univariate LM unit root tests and panel LM unit root test with one structural break suggest that stock prices in each country is characterized by a random walk, but the findings from the panel LM unit root test with two structural breaks suggest that stock prices in the eight countries are mean reverting.

scholarly journals Random Walk Hypothesis for Stock Prices in Fiji

2021 ◽  
Vol 13 (2) ◽  
pp. 79-88
Author(s):  
Janesh Sami
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Unit Root ◽  
Stock Prices ◽  
Structural Break ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Random Walk Hypothesis ◽  
Augmented Dickey Fuller ◽  
Historical Movement

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.

scholarly journals An Empirical Investigation of the Random Walk Hypothesis in the Nigerian Stock Market

2021 ◽  
Vol 4 (1) ◽  
pp. 62-77
Author(s):  
DA Kuhe ◽  
J Akor
Keyword(s):  
Random Walk ◽  
Stock Market ◽  
Stock Returns ◽  
Unit Root ◽  
Stock Prices ◽  
Null Hypothesis ◽  
Serial Correlation ◽  
Ratio Test ◽  
Variance Ratio ◽  
Random Walk Hypothesis

The Random Walk Hypothesis (RWH) states that stock prices move randomly in the stock market without following any regular or particular pattern and as such historical information contained in the past prices of stocks cannot be used to predict current or future stock prices. Hence, stock prices are unpredictable and that investors cannot usurp any available information in the market to manipulate the market and make abnormal profits. This study empirically examines the random walk hypothesis in the Nigerian stock market using the daily quotations of the Nigerian stock exchange from 2nd January, 1998 to 31st December, 2019. The study employs Augmented Dickey-Fuller unit root test, the random walk model, Ljung-Box Q-statistic test for serial dependence, runs test of randomness, and the robust variance ratio test as methods of analyses. The result of the study rejected the null hypotheses of a unit root and random walk in the stock returns. The null hypothesis of no serial correlation in the residuals of stock returns was also rejected indicating the presence of serial correlation/autocorrelation in the residual series. The result of the runs test rejected the null hypothesis of randomness in the Nigerian stock returns. The results of the variance ratio test under homoskedasticity and heteroskedasticity assumptions both strongly rejected the null hypothesis of a random walk for both joint tests and test of individual periods. Based on the results of the four tests applied in this study, it is concluded that the Nigerian daily stock returns under the period of investigation do not follow a random walk and hence the null hypothesis of a random walk is rejected. The results of the study further revealed that the Nigerian stock market is weak-form inefficient indicating that prices in the Nigerian stock market are predictable, dependable, consistently mispriced, inflated, liable to arbitraging and left unprotected to speculations and market manipulations. The study provided some policy recommendations

scholarly journals UNIT ROOT TEST WITH HIGH-FREQUENCY DATA

2021 ◽  
pp. 1-59
Author(s):  
Sébastien Laurent ◽  
Shuping Shi
Keyword(s):  
Random Walk ◽  
Unit Root ◽  
High Frequency ◽  
Asset Prices ◽  
Composite Index ◽  
Mean Reversion ◽  
Unit Root Tests ◽  
High Frequency Data ◽  
Frequency Data ◽  
Intraday Data

Deviations of asset prices from the random walk dynamic imply the predictability of asset returns and thus have important implications for portfolio construction and risk management. This paper proposes a real-time monitoring device for such deviations using intraday high-frequency data. The proposed procedures are based on unit root tests with in-fill asymptotics but extended to take the empirical features of high-frequency financial data (particularly jumps) into consideration. We derive the limiting distributions of the tests under both the null hypothesis of a random walk with jumps and the alternative of mean reversion/explosiveness with jumps. The limiting results show that ignoring the presence of jumps could potentially lead to severe size distortions of both the standard left-sided (against mean reversion) and right-sided (against explosiveness) unit root tests. The simulation results reveal satisfactory performance of the proposed tests even with data from a relatively short time span. As an illustration, we apply the procedure to the Nasdaq composite index at the 10-minute frequency over two periods: around the peak of the dot-com bubble and during the 2015–2106 stock market sell-off. We find strong evidence of explosiveness in asset prices in late 1999 and mean reversion in late 2015. We also show that accounting for jumps when testing the random walk hypothesis on intraday data is empirically relevant and that ignoring jumps can lead to different conclusions.

scholarly journals Crisis determination and financial contagion: an analysis of the Hong Kong and Tokyo stock markets using an MSBVAR approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haytem Troug ◽  
Matt Murray
Keyword(s):  
Hong Kong ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Current Data ◽  
Financial Contagion ◽  
Macroeconomic Factors ◽  
Content Type ◽  
Crisis Period ◽  
Dynamic Relationship ◽  
Using Data

PurposeThe purpose of this paper then, is to add to the existing literature on financial contagion. While a vast amount of the debate has been made using data from the late 1990s, this paper differentiates itself by analysing more current data, centred around the most recent global financial crisis, with specific focus on the stock markets of Hong Kong and Tokyo.Design/methodology/approachEmploying Pearson and Spearman correlation measures, the dynamic relationship of the two markets is determined over tranquil and crisis periods, as specified by an Markov-Switching Bayesian Vector AutoRegression (MSBVAR) model.FindingsThe authors find evidence in support of the existence of financial contagion (defined as an increase in correlation during a crisis period) for all frequencies of data analysed. This contagion is greatest when examining lower-frequency data. Additionally, there is also weaker evidence in some data sub-samples to support “herding” behaviour, whereby higher market correlations persist, following a crisis period.Research limitations/implicationsThe intention of this paper was not to analyse the cause or transmission mechanism of contagion between financial markets. Therefore future studies could extend the methodology used in this paper by including exogenous macroeconomic factors in the MSBVAR model.Originality/valueThe results of this paper serve to explain why the debate of the persistence and in fact existence of financial contagion remains alive. The authors have shown that the frequency of a time series dataset has a significant impact on the level of observed correlation and thus observation of financial contagion.

WHY DO EMERGING STOCK MARKETS EXPERIENCE MORE PERSISTENT PRICE DEVIATIONS FROM A RANDOM WALK OVER TIME? A COUNTRY-LEVEL ANALYSIS

2009 ◽  
Vol 14 (S1) ◽  
pp. 3-41 ◽  
Author(s):  
Kian-Ping Lim ◽  
Robert D. Brooks
Keyword(s):  
Random Walk ◽  
Stock Prices ◽  
Stock Markets ◽  
Stock Price ◽  
Private Property ◽  
Structural Characteristics ◽  
Income Group ◽  
Market Liquidity ◽  
High Income Group ◽  
Country Level

This paper employs the rolling bicorrelation test to measure the degree of nonlinear departures from a random walk for aggregate stock price indices of fifty countries over the sample period 1995–2005. We find that stock markets in economies with low per capita GDP in general experience more frequent price deviations than those in the high-income group. This clustering effect is not due to market liquidity or other structural characteristics, but instead can be explained by cross-country variation in the degree of private property rights protection. Our conjecture is that weak protection deters the participation of informed arbitrageurs, leaving those markets dominated by sentiment-prone noise traders whose correlated trading causes stock prices in emerging markets to deviate from the random walk benchmarks for persistent periods of time.

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