Test of herding behaviour in the Johannesburg stock exchange : application of quantile regression model
- Ababio, Kofi Agyarko, Mwamba, John Muteba
- Authors: Ababio, Kofi Agyarko , Mwamba, John Muteba
- Date: 2017
- Subjects: Asymmetry , Herding Behaviour , Quantile Regression Model
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/250909 , uj:26156 , Citation: Ababio, K.A. & Mwamba, J.M. 2017. Test of herding behaviour in the Johannesburg stock exchange : application of quantile regression model. Journal of Economic and Financial Sciences, 10(3):457-474.
- Description: Abstract: The current study searches for evidence of herding behaviour in South Africa’s financial industry using an alternative approach. As a departure from the conventional test methodologies, the current study adopts the quantile regression model in estimating the empirical data on daily stock returns from January 2010 to September 2015. Employing the median as an alternative measure of average market portfolio returns, the study finds evidence of herding behaviour in the banking and real estate sectors during the sample period. Herding behaviour shows asymmetry and investors in the banking sector exhibit the herding behaviour when the market is falling (bear phase), whereas in the real estate sector, investors exhibited the herding behaviour when the market is rising (bull phase). However, in the entire financial industry, the empirical results show evidence of herding behaviour only during the extreme market period (bull phase).
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- Authors: Ababio, Kofi Agyarko , Mwamba, John Muteba
- Date: 2017
- Subjects: Asymmetry , Herding Behaviour , Quantile Regression Model
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/250909 , uj:26156 , Citation: Ababio, K.A. & Mwamba, J.M. 2017. Test of herding behaviour in the Johannesburg stock exchange : application of quantile regression model. Journal of Economic and Financial Sciences, 10(3):457-474.
- Description: Abstract: The current study searches for evidence of herding behaviour in South Africa’s financial industry using an alternative approach. As a departure from the conventional test methodologies, the current study adopts the quantile regression model in estimating the empirical data on daily stock returns from January 2010 to September 2015. Employing the median as an alternative measure of average market portfolio returns, the study finds evidence of herding behaviour in the banking and real estate sectors during the sample period. Herding behaviour shows asymmetry and investors in the banking sector exhibit the herding behaviour when the market is falling (bear phase), whereas in the real estate sector, investors exhibited the herding behaviour when the market is rising (bull phase). However, in the entire financial industry, the empirical results show evidence of herding behaviour only during the extreme market period (bull phase).
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Empirical examination of herding behaviour in the Johannesburg stock exchange : a sectoral analysis
- Ababio, Kofi A., Mwamba, John M.
- Authors: Ababio, Kofi A. , Mwamba, John M.
- Date: 2017
- Subjects: Herding behaviour , Financial sector , Asymmetry
- Language: English
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/386771 , http://hdl.handle.net/10210/244763 , uj:25314 , Citation: Ababio, K.A. & Mwamba, J.M. 2017. Empirical examination of herding behaviour in the Johannesburg stock exchange : a sectoral analysis.
- Description: Abstract: This paper uses the daily stock returns from January 2010 to September 2015 to investigate the presence of herding behavior and its dynamics on the South African financial sector. The paper makes use of the median as an alternative proxy to the mean in estimating market average returns. We found evidence in support of herding behaviour in the general financials and the real estate sectors of the Johannesburg Stock Exchange (JSE) during normal market period. Investors in the banking and the insurance sectors were found to show rational investment decisions during all market periods.
- Full Text:
- Authors: Ababio, Kofi A. , Mwamba, John M.
- Date: 2017
- Subjects: Herding behaviour , Financial sector , Asymmetry
- Language: English
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/386771 , http://hdl.handle.net/10210/244763 , uj:25314 , Citation: Ababio, K.A. & Mwamba, J.M. 2017. Empirical examination of herding behaviour in the Johannesburg stock exchange : a sectoral analysis.
- Description: Abstract: This paper uses the daily stock returns from January 2010 to September 2015 to investigate the presence of herding behavior and its dynamics on the South African financial sector. The paper makes use of the median as an alternative proxy to the mean in estimating market average returns. We found evidence in support of herding behaviour in the general financials and the real estate sectors of the Johannesburg Stock Exchange (JSE) during normal market period. Investors in the banking and the insurance sectors were found to show rational investment decisions during all market periods.
- Full Text:
Are housing price cycles asymmetric? evidence from the US States and metropolitan areas
- André, Christophe, Gupta, Rangan, Muteba Mwamba, John W.
- Authors: André, Christophe , Gupta, Rangan , Muteba Mwamba, John W.
- Date: 2019
- Subjects: Asymmetry , House prices , US economy
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/404226 , uj:33890 , Citation: André, C., Gupta, R. & Muteba Mwamba, J.W. 2019. Are housing price cycles asymmetric? evidence from the US States and metropolitan areas. International Journal of Strategic Property Management. Volume 23 Issue 1: 1–22. , DOI: https://doi.org/10.3846/ijspm.2019.6361 , ISSN 1648-715X
- Description: Abstract: This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.
- Full Text:
- Authors: André, Christophe , Gupta, Rangan , Muteba Mwamba, John W.
- Date: 2019
- Subjects: Asymmetry , House prices , US economy
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/404226 , uj:33890 , Citation: André, C., Gupta, R. & Muteba Mwamba, J.W. 2019. Are housing price cycles asymmetric? evidence from the US States and metropolitan areas. International Journal of Strategic Property Management. Volume 23 Issue 1: 1–22. , DOI: https://doi.org/10.3846/ijspm.2019.6361 , ISSN 1648-715X
- Description: Abstract: This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.
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