Do Malaysian house prices follow a random walk? Evidence from univariate and panel LM unit root tests with one and two structural breaks

2013 ◽  
Vol 45 (18) ◽  
pp. 2611-2627 ◽  
Author(s):  
Hooi Hooi Lean ◽  
Russell Smyth
Keyword(s):  
Random Walk ◽  
Unit Root ◽  
Structural Breaks ◽  
House Prices ◽  
Unit Root Tests

scholarly journals Structural Breaks and Explosive Behavior in the Long-Run: The Case of Australian Real House Prices, 1870–2020

2021 ◽  
Vol 15 (1) ◽  
pp. 72-84
Author(s):  
Vicente Esteve ◽  
Maria A. Prats
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
House Prices ◽  
Unit Root Tests ◽  
Annual Data ◽  
Bubble Behavior ◽  
Long Period ◽  
Long Run ◽  
Long Time

Abstract In this article, we use tests of explosive behavior in real house prices with annual data for the case of Australia for the period 1870–2020. The main contribution of this paper is the use of very long time series. It is important to use longer span data because it offers more powerful econometric results. To detect episodes of potential explosive behavior in house prices over this long period, we use the recursive unit root tests for explosiveness proposed by Phillips et al. (2011), (2015a,b). According to the results, there is a clear speculative bubble behavior in real house prices between 1997 and 2020, speculative process that has not yet been adjusted.

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.

Survey on structural breaks and unit root tests

2020 ◽  
Vol 58 ◽  
pp. 96-141
Author(s):  
A. Skrobotov ◽  
◽  
Keyword(s):  
Unit Root ◽  
Structural Breaks ◽  
Unit Root Tests

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.

A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?

2021 ◽  
Vol 3 (2) ◽  
pp. 80-92
Author(s):  
Sara Muhammadullah ◽  
Amena Urooj ◽  
Faridoon Khan
Keyword(s):  
Interest Rate ◽  
Unemployment Rate ◽  
Unit Root ◽  
Structural Breaks ◽  
Inflation Rate ◽  
Structural Break ◽  
Unit Root Test ◽  
Unit Root Tests ◽  
Gdp Growth ◽  
Macroeconomic Indicators

The study investigates the query of structural break or unit root considering four macroeconomic indicators; unemployment rate, interest rate, GDP growth, and inflation rate of Pakistan. The previous studies create ambiguity regarding the stationarity and non-stationarity of these variables. We employ Zivot & Andrews (1992) unit root test and Step Indicator Saturation (SIS) method for multiple break detection in mean. GDP growth and inflation rate are stationary at level whereas unit root tests fail to reject the null hypothesis of the unemployment rate and interest rate at level. However, Zivot and Andrew unit root test with a single endogenous break indicates that the unemployment rate and interest rate are stationary at level with a single endogenous break. On the other hand, the SIS method reveals that the series are stationary with multiple structural breaks. It is inferred that it is inappropriate to take the first difference of the unemployment rate and interest rate to attain stationarity. The results of this study confirmed that there exist multiple breaks in the macroeconomic variables considered in the context of Pakistan.

scholarly journals STUDY OF TESTS FOR TREND IN TIME SERIES

2021 ◽  
Vol 39 (2) ◽  
pp. 311-333
Author(s):  
Denise de Assis PAIVA ◽  
Thelma SÁFADI
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
Consumer Price Index ◽  
Unit Root Tests ◽  
Metropolitan Region ◽  
Maximum Temperature ◽  
Pettitt Test ◽  
Using Data ◽  
Time Series Methodology

The time series methodology is an important tool when using data over time. The time series can be composed of the components trend (Tt), seasonality (St) and the random error (at). The aim of this study was to evaluate the tests used to analyze the trend component, which were: Pettitt, Run, Mann-Kendall, Cox-Stuart and the unit root tests (Dickey-Fuller, Dickey-Fuller Augmented and Zivot and Andrews), given that there is a discrepancy between the test results found in the literature. The four series analyzed were the maximum temperature in the Lavras city, MG, Brazil, the unemployment rate in the Metropolitan Region of S~ao Paulo (RMSP), the Broad Consumer Price Index (IPCA) and the nominal Gross Domestic Product (GDP) of Brazil. It was found that the unit root tests showed similar results in relation to the presence of the stochastic trend for all series. Furthermore, the turning point of the Pettitt test diverged from all the structural breaks found through the Zivot and Andrews test, except for the GDP series. Therefore, it was found that the trend tests diverged, obtaining similar results only in relation to the unemployment series.

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