A note on the technology herd : evidence from large institutional investors
- Uwilingiye, Josine, Cakan, Esin, Demirer, Rıza, Gupta, Rangan
- Authors: Uwilingiye, Josine , Cakan, Esin , Demirer, Rıza , Gupta, Rangan
- Date: 2019
- Subjects: Herding , Institutional investors , Causality
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/399899 , uj:33350 , Citation: Uwilingiye, Josine & Cakan, Esin & Demirer, Riza & Gupta, Rangan. (2018). A Note on the Technology Herd: Evidence from Large Institutional Investors. Review of Behavioral Finance, forthcoming.. 10.1108/RBF-08-2017-0086.
- Description: Abstract: This paper examines intentional herding among institutional investors with a particular focus on the technology sector that was the driver of the “New Economy” in the United States during the dot-com bubble of the 1990s. Using data on technology stockholdings of 115 large institutional investors, we test the presence of herding by examining linear dependence and feedback between individual investors’ technology stockholdings and that of the aggregate market. Unlike other models to detect herding, we use Geweke (1982) type causality tests that allow us to disentangle spurious herding from intentional herding via tests of bidirectional and instantaneous causality across portfolio positions in technology stocks. After controlling information based (spurious) herding, our tests show that 38 percent of large institutional investors tend to intentionally herd in technology stocks. The findings support the existing literature that investment decisions by large institutional investors are not only driven by fundamental information, but also by cognitive bias that is characterized by intentional herding.
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- Authors: Uwilingiye, Josine , Cakan, Esin , Demirer, Rıza , Gupta, Rangan
- Date: 2019
- Subjects: Herding , Institutional investors , Causality
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/399899 , uj:33350 , Citation: Uwilingiye, Josine & Cakan, Esin & Demirer, Riza & Gupta, Rangan. (2018). A Note on the Technology Herd: Evidence from Large Institutional Investors. Review of Behavioral Finance, forthcoming.. 10.1108/RBF-08-2017-0086.
- Description: Abstract: This paper examines intentional herding among institutional investors with a particular focus on the technology sector that was the driver of the “New Economy” in the United States during the dot-com bubble of the 1990s. Using data on technology stockholdings of 115 large institutional investors, we test the presence of herding by examining linear dependence and feedback between individual investors’ technology stockholdings and that of the aggregate market. Unlike other models to detect herding, we use Geweke (1982) type causality tests that allow us to disentangle spurious herding from intentional herding via tests of bidirectional and instantaneous causality across portfolio positions in technology stocks. After controlling information based (spurious) herding, our tests show that 38 percent of large institutional investors tend to intentionally herd in technology stocks. The findings support the existing literature that investment decisions by large institutional investors are not only driven by fundamental information, but also by cognitive bias that is characterized by intentional herding.
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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.
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- 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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Dynamic relationship between oil price and inflation in South Africa
- Balcilar, Mehmet, Uwilingiye, Josine, Gupta, Rangan
- Authors: Balcilar, Mehmet , Uwilingiye, Josine , Gupta, Rangan
- Date: 2018
- Subjects: Oil prices , Inflation , Causality
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278201 , uj:29849 , Citation: Balcilar, M., Uwilingiye, J. & Gupta, R. 2018. Dynamic relationship between oil price and inflation in South Africa.
- Description: Abstract: The oil price-inflation relationship has been at the center of attention among economists and policy makers, especially after 1970’s oil shocks that resulted to a significant increase in the inflation rate in number of countries around the world. In this study, we aim to investigate the evolving relationship between oil price and inflation in South Africa, using time series data starting from January 1922 to July 2013. We fit both asymmetric and symmetric dynamic conditional correlation exponential GARCH (DCC-EGARCH) models to the data, and we find oil price to have a positive relationship with inflation and further, the asymmetric EGARCH shows that the positive shocks have higher impact on inflation than negative shocks of the same magnitude. Moreover, we observe that the correlation has been decreasing gradually over time despite the significant increase in oil consumption in South Africa over time and higher world oil price that keeps on rising. The less significant oil price- inflation relationship, observed in recent years, can be attributed to the South African Reserve Bank commitment to stabilize inflation expectation in the presence of external shocks.
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- Authors: Balcilar, Mehmet , Uwilingiye, Josine , Gupta, Rangan
- Date: 2018
- Subjects: Oil prices , Inflation , Causality
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278201 , uj:29849 , Citation: Balcilar, M., Uwilingiye, J. & Gupta, R. 2018. Dynamic relationship between oil price and inflation in South Africa.
- Description: Abstract: The oil price-inflation relationship has been at the center of attention among economists and policy makers, especially after 1970’s oil shocks that resulted to a significant increase in the inflation rate in number of countries around the world. In this study, we aim to investigate the evolving relationship between oil price and inflation in South Africa, using time series data starting from January 1922 to July 2013. We fit both asymmetric and symmetric dynamic conditional correlation exponential GARCH (DCC-EGARCH) models to the data, and we find oil price to have a positive relationship with inflation and further, the asymmetric EGARCH shows that the positive shocks have higher impact on inflation than negative shocks of the same magnitude. Moreover, we observe that the correlation has been decreasing gradually over time despite the significant increase in oil consumption in South Africa over time and higher world oil price that keeps on rising. The less significant oil price- inflation relationship, observed in recent years, can be attributed to the South African Reserve Bank commitment to stabilize inflation expectation in the presence of external shocks.
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Economic policy uncertainty and herding behaviour : evidence from the South African housing market
- Cakan, Esin, Demirer, Riza, Gupta, Rangan, Uwilingiye, Josine
- Authors: Cakan, Esin , Demirer, Riza , Gupta, Rangan , Uwilingiye, Josine
- Date: 2019
- Subjects: Herding , Housing Market , South Africa
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/399907 , uj:33351 , Citation: Esin Cakan & Riza Demirer & Rangan Gupta & Josine Uwilingiye, 2019. "Economic Policy Uncertainty and Herding Behavior: Evidence from the South African Housing Market," Working Papers 201921, University of Pretoria, Department of Economics.
- Description: Abstract: This paper examines the link between economic policy uncertainty and herding behaviour in financial markets with an application to the South African housing market. Building on the evidence in the literature that herding behaviour driven by human emotions is not only limited to financial markets, but is also present in real estate investments, we examine the presence of herding in this emerging market via static and dynamic herding tests. While the static model fails to detect herding in the South African housing market, a dynamic model based on a two-regime Markov switching specification shows evidence of herding during the high volatility regime only, consistent with the notion that herd behaviour is primarily driven by increased market uncertainty. Extending our analysis via quantile regressions, we further show that higher quantiles of policy uncertainty are associated with greater likelihood of being in the herding regime, thus establishing a link between policy uncertainty and herding behaviour. Overall, our findings suggest that policy uncertainty can serve as a driver of market inefficiencies, which in our case, is associated by the presence of herding.
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- Authors: Cakan, Esin , Demirer, Riza , Gupta, Rangan , Uwilingiye, Josine
- Date: 2019
- Subjects: Herding , Housing Market , South Africa
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/399907 , uj:33351 , Citation: Esin Cakan & Riza Demirer & Rangan Gupta & Josine Uwilingiye, 2019. "Economic Policy Uncertainty and Herding Behavior: Evidence from the South African Housing Market," Working Papers 201921, University of Pretoria, Department of Economics.
- Description: Abstract: This paper examines the link between economic policy uncertainty and herding behaviour in financial markets with an application to the South African housing market. Building on the evidence in the literature that herding behaviour driven by human emotions is not only limited to financial markets, but is also present in real estate investments, we examine the presence of herding in this emerging market via static and dynamic herding tests. While the static model fails to detect herding in the South African housing market, a dynamic model based on a two-regime Markov switching specification shows evidence of herding during the high volatility regime only, consistent with the notion that herd behaviour is primarily driven by increased market uncertainty. Extending our analysis via quantile regressions, we further show that higher quantiles of policy uncertainty are associated with greater likelihood of being in the herding regime, thus establishing a link between policy uncertainty and herding behaviour. Overall, our findings suggest that policy uncertainty can serve as a driver of market inefficiencies, which in our case, is associated by the presence of herding.
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Investor happiness and predictability of the realized volatility of oil price
- Bonato, Matteo, Gkillas, Konstantinos, Gupta, Rangan, Pierdzioch, Christian
- Authors: Bonato, Matteo , Gkillas, Konstantinos , Gupta, Rangan , Pierdzioch, Christian
- Date: 2020
- Subjects: Investor happiness , Oil market , Realized volatility
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/460631 , uj:40997 , Citation: Bonato, M. et al. 2020. Investor happiness and predictability of the realized volatility of oil price. , DOI: 10.3390/su12104309
- Description: Abstract: We use the the heterogeneous autoregressive realized volatility (HAR-RV) model to analyze both in sample and out-of-sample whether a measure of investor happiness predicts the daily realized volatility of oil-price returns, where we use high-frequency intraday data to measure realized volatility. Full-sample estimates reveal that realized volatility is significantly negatively linked to investor happiness at a short forecast horizon. Similarly, out-of-sample results indicate that investor happiness significantly improves the accuracy of forecasts of realized volatility at a short forecast horizon. Results for a medium and a long forecast horizon are insignificant. We argue that our results shed light on the role played by speculation in oil products and the potential function of oil-related products as a hedge against risks in traditional financial assets.
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- Authors: Bonato, Matteo , Gkillas, Konstantinos , Gupta, Rangan , Pierdzioch, Christian
- Date: 2020
- Subjects: Investor happiness , Oil market , Realized volatility
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/460631 , uj:40997 , Citation: Bonato, M. et al. 2020. Investor happiness and predictability of the realized volatility of oil price. , DOI: 10.3390/su12104309
- Description: Abstract: We use the the heterogeneous autoregressive realized volatility (HAR-RV) model to analyze both in sample and out-of-sample whether a measure of investor happiness predicts the daily realized volatility of oil-price returns, where we use high-frequency intraday data to measure realized volatility. Full-sample estimates reveal that realized volatility is significantly negatively linked to investor happiness at a short forecast horizon. Similarly, out-of-sample results indicate that investor happiness significantly improves the accuracy of forecasts of realized volatility at a short forecast horizon. Results for a medium and a long forecast horizon are insignificant. We argue that our results shed light on the role played by speculation in oil products and the potential function of oil-related products as a hedge against risks in traditional financial assets.
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Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors
- Gupta, Rangan, Modise, Mampho P., Uwilingiye, Josine
- Authors: Gupta, Rangan , Modise, Mampho P. , Uwilingiye, Josine
- Date: 2017
- Subjects: Equity Premium , Predictive Regressions , Forecast Combinations
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/248055 , uj:25775 , Citation: Gupta, R., Modise, M.P. & Uwilingiye, J. 2017. Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors.
- Description: Abstract: This paper uses a predictive regression framework to examine the out-of-sample predictability of South Africa’s equity premium, using a host of financial and macroeconomic variables. We employ various methods of forecast combination, bootstrap aggregation (bagging), diffusion index (principal component) and Bayesian regressions to allow for a simultaneous role of the variables under consideration, besides individual predictive regressions. We assess both the statistical and economic significance of the individual predictive regressions, combination methods, bagging, principal components and Bayesian regressions. Our results show that forecast combination methods and principal component regressions improve the predictability of the equity premium relative to the benchmark autoregressive model of order one (AR(1)). However, the Bayesian predictive regressions are found to be the standout performers with the models outperforming the individual regressions, forecast combination methods, bagging and principal component regressions, both in terms of statistical (forecasting) and economic (utility) gains.
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- Authors: Gupta, Rangan , Modise, Mampho P. , Uwilingiye, Josine
- Date: 2017
- Subjects: Equity Premium , Predictive Regressions , Forecast Combinations
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/248055 , uj:25775 , Citation: Gupta, R., Modise, M.P. & Uwilingiye, J. 2017. Out-of-Sample Equity Premium Predictability in South Africa: Evidence from a Large Number of Predictors.
- Description: Abstract: This paper uses a predictive regression framework to examine the out-of-sample predictability of South Africa’s equity premium, using a host of financial and macroeconomic variables. We employ various methods of forecast combination, bootstrap aggregation (bagging), diffusion index (principal component) and Bayesian regressions to allow for a simultaneous role of the variables under consideration, besides individual predictive regressions. We assess both the statistical and economic significance of the individual predictive regressions, combination methods, bagging, principal components and Bayesian regressions. Our results show that forecast combination methods and principal component regressions improve the predictability of the equity premium relative to the benchmark autoregressive model of order one (AR(1)). However, the Bayesian predictive regressions are found to be the standout performers with the models outperforming the individual regressions, forecast combination methods, bagging and principal component regressions, both in terms of statistical (forecasting) and economic (utility) gains.
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The impact of oil price on South African GDP growth : A Bayesian Markov Switching - VAR analysis
- Balcilar, Mehmet, Van Eyden, Reneé, Uwilingiye, Josine, Gupta, Rangan
- Authors: Balcilar, Mehmet , Van Eyden, Reneé , Uwilingiye, Josine , Gupta, Rangan
- Date: 2014
- Subjects: Macroeconomic fluctuations , Oil price shocks , Bayesian Markov switching VAR
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/248831 , uj:25879 , Citation: Balcilar, M. et al. 2014. The impact of oil price on South African GDP growth : A Bayesian Markov Switching - VAR analysis.
- Description: Abstract: One characteristic of many macroeconomic and financial time series is their asymmetric behaviour during different phases of a business cycle. Oil price shocks have been amongst those economic variables that have been identified in theoretical and empirical literature to predict the phases of business cycles. However, the role of oil price shocks to determine business cycle fluctuations has received less attention in emerging and developing economies. The aim of this study is to investigate the role of oil price shocks in predicting the phases of the South African business cycle associated with higher and lower growth regimes. By adopting a regime dependent analysis, we investigate the impact of oil price shocks under two phases of the business cycle, namely high and low growth regimes. As a net importer of oil, South Africa is expected to be vulnerable to oil price shocks irrespective of the phase of the business cycle. Using a Bayesian Markov switching vector autoregressive (MS-VAR) model and data for the period 1960Q2 to 2013Q3, we found the oil price to have predictive content for real output growth under the low growth regime. The results also show the low growth state to be shorter-lived compared to the higher growth state.
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- Authors: Balcilar, Mehmet , Van Eyden, Reneé , Uwilingiye, Josine , Gupta, Rangan
- Date: 2014
- Subjects: Macroeconomic fluctuations , Oil price shocks , Bayesian Markov switching VAR
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/248831 , uj:25879 , Citation: Balcilar, M. et al. 2014. The impact of oil price on South African GDP growth : A Bayesian Markov Switching - VAR analysis.
- Description: Abstract: One characteristic of many macroeconomic and financial time series is their asymmetric behaviour during different phases of a business cycle. Oil price shocks have been amongst those economic variables that have been identified in theoretical and empirical literature to predict the phases of business cycles. However, the role of oil price shocks to determine business cycle fluctuations has received less attention in emerging and developing economies. The aim of this study is to investigate the role of oil price shocks in predicting the phases of the South African business cycle associated with higher and lower growth regimes. By adopting a regime dependent analysis, we investigate the impact of oil price shocks under two phases of the business cycle, namely high and low growth regimes. As a net importer of oil, South Africa is expected to be vulnerable to oil price shocks irrespective of the phase of the business cycle. Using a Bayesian Markov switching vector autoregressive (MS-VAR) model and data for the period 1960Q2 to 2013Q3, we found the oil price to have predictive content for real output growth under the low growth regime. The results also show the low growth state to be shorter-lived compared to the higher growth state.
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