Pub Date : 2020-10-12DOI: 10.1080/10293523.2020.1814047
Leon Li
ABSTRACT Volatility indexes provide a tool for investors to speculate and trade on market sentiment regarding future volatility. The risk of trading on volatility indexes can be measured by their second moments, namely, variance and correlation. This study considers the four representative volatility indexes published by the CBOE: stock market volatility index (VIX), crude oil volatility index (OVX), foreign exchange rate volatility index (EVZ), and gold price volatility index (GVZ). To examine their risk, we develop an extended multivariate Markov switching ARCH (MSARCH) model in which regime-switching variances, correlations, and variance-correlation relations are designed. Our empirical sample consists of the four volatility indexes from June 2008 to April 2020 for 612 weekly observations (Wednesday to Wednesday). For the conditional variances, we find evidence of regime-switching processes (switching between low and high volatility regimes) for the individual volatility index returns, with the exception of the GVZ. The estimated probability of the high volatility regime may be used to track economic distress and uncertainty shocks. These results provide evidence for volatility-of-volatility risk. For the conditional correlations, we find a regime-switching relation between variances and correlations. That is, the highest correlation appears when the paired volatility markets are simultaneously experiencing a state of high volatility. By contrast, when the paired volatility markets are encountering different volatility states, the correlation is weaker. These results indicate that the volatility-of-volatility risk is a factor affecting the dynamics of correlations between volatility indexes.
{"title":"Risk of investing in volatility products: A regime-switching approach","authors":"Leon Li","doi":"10.1080/10293523.2020.1814047","DOIUrl":"https://doi.org/10.1080/10293523.2020.1814047","url":null,"abstract":"ABSTRACT Volatility indexes provide a tool for investors to speculate and trade on market sentiment regarding future volatility. The risk of trading on volatility indexes can be measured by their second moments, namely, variance and correlation. This study considers the four representative volatility indexes published by the CBOE: stock market volatility index (VIX), crude oil volatility index (OVX), foreign exchange rate volatility index (EVZ), and gold price volatility index (GVZ). To examine their risk, we develop an extended multivariate Markov switching ARCH (MSARCH) model in which regime-switching variances, correlations, and variance-correlation relations are designed. Our empirical sample consists of the four volatility indexes from June 2008 to April 2020 for 612 weekly observations (Wednesday to Wednesday). For the conditional variances, we find evidence of regime-switching processes (switching between low and high volatility regimes) for the individual volatility index returns, with the exception of the GVZ. The estimated probability of the high volatility regime may be used to track economic distress and uncertainty shocks. These results provide evidence for volatility-of-volatility risk. For the conditional correlations, we find a regime-switching relation between variances and correlations. That is, the highest correlation appears when the paired volatility markets are simultaneously experiencing a state of high volatility. By contrast, when the paired volatility markets are encountering different volatility states, the correlation is weaker. These results indicate that the volatility-of-volatility risk is a factor affecting the dynamics of correlations between volatility indexes.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"50 1","pages":"1 - 16"},"PeriodicalIF":0.9,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1814047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44552191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1080/10293523.2020.1814046
Javier Rojo‐Suárez, A. Alonso‐Conde
ABSTRACT We test both the conditional and unconditional versions of the consumption capital asset pricing model (CCAPM) on the Johannesburg Stock Exchange, for the period 1988–2018, and compare its performance with that of the CAPM and the Fama-French three- and five-factor models. We use the consumer confidence index as an instrument to parameterise shifts in betas over time in conditional models. In order to study the robustness of the results at a higher frequency than that of consumption data, we use the mimicking portfolio of the stochastic discount factor tied to the model. Our results show that in all cases the conditional CCAPM performs satisfactorily, outperforming both the CAPM and the Fama-French three-factor model. These results suggest that South African consumption growth and consumer sentiment help explain a large fraction of the expected returns in the Johannesburg Stock Exchange.
{"title":"Consumer sentiment and time-varying betas: Testing the validity of the consumption CAPM on the Johannesburg Stock Exchange","authors":"Javier Rojo‐Suárez, A. Alonso‐Conde","doi":"10.1080/10293523.2020.1814046","DOIUrl":"https://doi.org/10.1080/10293523.2020.1814046","url":null,"abstract":"ABSTRACT We test both the conditional and unconditional versions of the consumption capital asset pricing model (CCAPM) on the Johannesburg Stock Exchange, for the period 1988–2018, and compare its performance with that of the CAPM and the Fama-French three- and five-factor models. We use the consumer confidence index as an instrument to parameterise shifts in betas over time in conditional models. In order to study the robustness of the results at a higher frequency than that of consumption data, we use the mimicking portfolio of the stochastic discount factor tied to the model. Our results show that in all cases the conditional CCAPM performs satisfactorily, outperforming both the CAPM and the Fama-French three-factor model. These results suggest that South African consumption growth and consumer sentiment help explain a large fraction of the expected returns in the Johannesburg Stock Exchange.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"303 - 321"},"PeriodicalIF":0.9,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1814046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48448894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-01DOI: 10.1080/10293523.2020.1794309
O. Aybar, M. Bilgin, S. Öztürk
ABSTRACT Globalisation and financial liberalisation have made financial markets more correlated and connected. In this context, it has become extremely important to understand the connectedness and correlation among different financial markets and commodities. This paper attempts to extend applicable empirical studies by examining the connectedness between volatilities of commodity convenience yields and zero-coupon inflation swap rates. We conduct our study by using both the spillover index methodology provided by Diebold and Yilmaz (2009, 2012) as well as Barunik and Krehlik’s (2018) methodology to decompose the index to its frequencies for short-, medium and long-term dynamics. Although, empirical results based on Diebold and Yilmaz’s (2012) methodology show that high total connectedness exists between the variables for the whole time period, our results based on Barunik and Krehlik’s (2018) approach shows that this connectedness exists only in the long-term. The results also indicate that the connectedness dynamics change when the effect of cross-correlations is considered.
{"title":"Time dynamics of connectedness between commodity convenience yields and zero-coupon inflation swap rates","authors":"O. Aybar, M. Bilgin, S. Öztürk","doi":"10.1080/10293523.2020.1794309","DOIUrl":"https://doi.org/10.1080/10293523.2020.1794309","url":null,"abstract":"ABSTRACT Globalisation and financial liberalisation have made financial markets more correlated and connected. In this context, it has become extremely important to understand the connectedness and correlation among different financial markets and commodities. This paper attempts to extend applicable empirical studies by examining the connectedness between volatilities of commodity convenience yields and zero-coupon inflation swap rates. We conduct our study by using both the spillover index methodology provided by Diebold and Yilmaz (2009, 2012) as well as Barunik and Krehlik’s (2018) methodology to decompose the index to its frequencies for short-, medium and long-term dynamics. Although, empirical results based on Diebold and Yilmaz’s (2012) methodology show that high total connectedness exists between the variables for the whole time period, our results based on Barunik and Krehlik’s (2018) approach shows that this connectedness exists only in the long-term. The results also indicate that the connectedness dynamics change when the effect of cross-correlations is considered.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"289 - 302"},"PeriodicalIF":0.9,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1794309","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46926706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/10293523.2020.1806466
Elze-Mari Roux, J. de Villiers
ABSTRACT In this article we offer a simplified version of the alternative retirement planning model we originally proposed (De Villiers & Roux, 2019). Our method focuses on determining the sustainable lifestyle level (SLL) that an individual can currently afford while still saving enough towards retirement to sustain this lifestyle level up to retirement and beyond. The model is simplified by assuming that the real rate of return on retirement savings before retirement will be the same as the withdrawal rate of income from the accumulated savings during retirement. This method yields a much simpler SLL relationship in that it is more generally applicable albeit possibly less accurate. This approach should improve communication of the extent of the retirement savings challenge, possibly leading to better savings outcomes.
{"title":"A simplified approach to estimate the sustainable lifestyle level for retirement planning","authors":"Elze-Mari Roux, J. de Villiers","doi":"10.1080/10293523.2020.1806466","DOIUrl":"https://doi.org/10.1080/10293523.2020.1806466","url":null,"abstract":"ABSTRACT In this article we offer a simplified version of the alternative retirement planning model we originally proposed (De Villiers & Roux, 2019). Our method focuses on determining the sustainable lifestyle level (SLL) that an individual can currently afford while still saving enough towards retirement to sustain this lifestyle level up to retirement and beyond. The model is simplified by assuming that the real rate of return on retirement savings before retirement will be the same as the withdrawal rate of income from the accumulated savings during retirement. This method yields a much simpler SLL relationship in that it is more generally applicable albeit possibly less accurate. This approach should improve communication of the extent of the retirement savings challenge, possibly leading to better savings outcomes.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"232 - 242"},"PeriodicalIF":0.9,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1806466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43574103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/10293523.2020.1783864
Daniel Page, D. McClelland, C. Auret
ABSTRACT Idiosyncratic momentum, like price momentum, is a trading strategy that considers a share’s recent relative performance over the short to medium term. Idiosyncratic momentum differs from price momentum as it uses residual returns post-orthogonalization on a single or multi-factor asset pricing model. Recent literature has shown that idiosyncratic momentum consistently outperforms price momentum on a risk-adjusted basis, is less prone to long-term reversal and has been proven successful in regions that have previously shown to have a non-existent price momentum premium. Previous studies attribute the success of idiosyncratic momentum to ‘underreaction’, whereby market participants tend to underreact to idiosyncratic momentum signals. We attempt to determine whether idiosyncratic momentum displays the same positive attributes found in international literature. We find that idiosyncratic momentum is superior to price momentum in terms of performance and explanatory power. The results reject a risk-based explanation of idiosyncratic momentum as minimising factor exposure (by using residual returns) improves performance. However, we find limited evidence of underreaction driving idiosyncratic momentum. Notwithstanding the lack of an a priori exposition of idiosyncratic momentum’s existence, the results provide concrete evidence of idiosyncratic momentum’s superiority over price momentum on the JSE, a finding important for both practitioners and academics alike.
{"title":"Idiosyncratic momentum on the JSE","authors":"Daniel Page, D. McClelland, C. Auret","doi":"10.1080/10293523.2020.1783864","DOIUrl":"https://doi.org/10.1080/10293523.2020.1783864","url":null,"abstract":"ABSTRACT Idiosyncratic momentum, like price momentum, is a trading strategy that considers a share’s recent relative performance over the short to medium term. Idiosyncratic momentum differs from price momentum as it uses residual returns post-orthogonalization on a single or multi-factor asset pricing model. Recent literature has shown that idiosyncratic momentum consistently outperforms price momentum on a risk-adjusted basis, is less prone to long-term reversal and has been proven successful in regions that have previously shown to have a non-existent price momentum premium. Previous studies attribute the success of idiosyncratic momentum to ‘underreaction’, whereby market participants tend to underreact to idiosyncratic momentum signals. We attempt to determine whether idiosyncratic momentum displays the same positive attributes found in international literature. We find that idiosyncratic momentum is superior to price momentum in terms of performance and explanatory power. The results reject a risk-based explanation of idiosyncratic momentum as minimising factor exposure (by using residual returns) improves performance. However, we find limited evidence of underreaction driving idiosyncratic momentum. Notwithstanding the lack of an a priori exposition of idiosyncratic momentum’s existence, the results provide concrete evidence of idiosyncratic momentum’s superiority over price momentum on the JSE, a finding important for both practitioners and academics alike.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"180 - 198"},"PeriodicalIF":0.9,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1783864","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45124956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/10293523.2020.1806467
Hannes du Plessis, P. van Rensburg
ABSTRACT Risk-based portfolio construction methods focus on optimally extracting information from the covariance matrix of asset returns, as opposed to utilising forecasts of expected returns, in determining the portfolio allocation. This improves their robustness to estimation error in means, but this does not mean that they are immune to errors in estimating volatilities and correlations. Using a covariance matrix decomposition that allows separately estimated volatility and correlation models to be recomposed into different models of the covariance matrix, this study examines the empirical performance impact of using an enhanced estimator of the covariance matrix, relative to using the historical sample covariance estimator in the context of six risk-based portfolio optimisations, in a long-only constrained equity market setting. It finds that sensitivity to covariance estimation varies significantly among risk-based portfolio types and that outperformance of the sample historical covariance estimator is possible, but rare. As components of the covariance estimate, among volatility models the EWMA volatilities perform best and GARCH models, poorly. Among correlation models, the Rotationally Invariant Estimator of Bouchaud, Bun, and Potters (2016) shows strong performance, along with the classic Ledoit and Wolf (2003) Single Market Model Estimator.
基于风险的投资组合构建方法侧重于从资产收益的协方差矩阵中最优提取信息，而不是利用预期收益的预测来确定投资组合的配置。这提高了它们对均值估计误差的鲁棒性，但这并不意味着它们对估计波动率和相关性的误差免疫。使用协方差矩阵分解，允许单独估计的波动率和相关模型被重组为协方差矩阵的不同模型，本研究检验了使用协方差矩阵的增强估计器的经验性能影响，相对于使用历史样本协方差估计器在六个基于风险的投资组合优化的背景下，在一个只做多的约束股票市场设置。研究发现，对协方差估计的敏感性在基于风险的投资组合类型之间存在显著差异，并且样本历史协方差估计器的优异表现是可能的，但很少。作为协方差估计的组成部分，在波动率模型中，EWMA波动率表现最好，而GARCH模型表现较差。在相关模型中，Bouchaud, Bun, and Potters(2016)的旋转不变估计器以及经典的Ledoit和Wolf(2003)单一市场模型估计器表现出较强的性能。
{"title":"Risk-based portfolio sensitivity to covariance estimation","authors":"Hannes du Plessis, P. van Rensburg","doi":"10.1080/10293523.2020.1806467","DOIUrl":"https://doi.org/10.1080/10293523.2020.1806467","url":null,"abstract":"ABSTRACT Risk-based portfolio construction methods focus on optimally extracting information from the covariance matrix of asset returns, as opposed to utilising forecasts of expected returns, in determining the portfolio allocation. This improves their robustness to estimation error in means, but this does not mean that they are immune to errors in estimating volatilities and correlations. Using a covariance matrix decomposition that allows separately estimated volatility and correlation models to be recomposed into different models of the covariance matrix, this study examines the empirical performance impact of using an enhanced estimator of the covariance matrix, relative to using the historical sample covariance estimator in the context of six risk-based portfolio optimisations, in a long-only constrained equity market setting. It finds that sensitivity to covariance estimation varies significantly among risk-based portfolio types and that outperformance of the sample historical covariance estimator is possible, but rare. As components of the covariance estimate, among volatility models the EWMA volatilities perform best and GARCH models, poorly. Among correlation models, the Rotationally Invariant Estimator of Bouchaud, Bun, and Potters (2016) shows strong performance, along with the classic Ledoit and Wolf (2003) Single Market Model Estimator.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"243 - 268"},"PeriodicalIF":0.9,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1806467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47420846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-02DOI: 10.1080/10293523.2020.1806480
A. Charteris, K. McCullough
ABSTRACT Fund fact sheets are intended to provide investors with information necessary to make investment decisions. For passive funds, the inclusion of cumulative returns for the fund and benchmark enable investors to measure the fund’s tracking performance using tracking difference. However, fund managers rely on tracking error to measure tracking performance, which is rarely presented. We evaluate the differences between these two metrics to ascertain whether the use of one or the other measure by investors could impact their investment decision. Results reveal that tracking error and tracking difference capture different elements of tracking performance, with varying rankings across the two measures for a sample of United States (US) funds. The empirical findings are robust to an adjustment for serial correlation, periods of extreme market volatility and varying measurement horizons. Recommendations for industry practice are made in light of these findings.
{"title":"Tracking error vs tracking difference: Does it matter?","authors":"A. Charteris, K. McCullough","doi":"10.1080/10293523.2020.1806480","DOIUrl":"https://doi.org/10.1080/10293523.2020.1806480","url":null,"abstract":"ABSTRACT Fund fact sheets are intended to provide investors with information necessary to make investment decisions. For passive funds, the inclusion of cumulative returns for the fund and benchmark enable investors to measure the fund’s tracking performance using tracking difference. However, fund managers rely on tracking error to measure tracking performance, which is rarely presented. We evaluate the differences between these two metrics to ascertain whether the use of one or the other measure by investors could impact their investment decision. Results reveal that tracking error and tracking difference capture different elements of tracking performance, with varying rankings across the two measures for a sample of United States (US) funds. The empirical findings are robust to an adjustment for serial correlation, periods of extreme market volatility and varying measurement horizons. Recommendations for industry practice are made in light of these findings.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"269 - 287"},"PeriodicalIF":0.9,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1806480","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46594279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-26DOI: 10.1080/10293523.2020.1776503
C. Auret, A. Sayed
ABSTRACT Given the rapidly changing nature of financial markets, volatility indices often influence the trading behaviour of market participants, as they identify market patterns, predict market risk and gauge market sentiment. This paper examines the effects of uncertainty on the expectations of South African white maize futures traders and on volatility at a daily level. Uncertainty effects are measured using three volatility indices: The SAVI Top 40, the SAVI Dollar and the SAVI White Maize. Investor expectations in the South African white maize futures market are proxied by three momentum indicators, the moving average convergence divergence (MACD), the relative strength index (RSI) and the rate of change (ROC). Volatility is estimated using a fitted GARCH (1,1) model of South African white maize futures closing prices. A time-varying vector autoregressive (VAR) framework is used to examine the reactions of each of the three momentum indicators to shocks from each of the three volatility indices. The results confirm that changes in uncertainty influence the expectations of South African white maize futures momentum traders; and that these resulting trades influence price movements, resulting in increased volatility.
摘要鉴于金融市场的快速变化，波动性指数通常会影响市场参与者的交易行为，因为它们可以识别市场模式、预测市场风险并衡量市场情绪。本文研究了不确定性对南非白玉米期货交易员的预期和每日波动性的影响。不确定性影响使用三个波动性指数来衡量：SAVI Top 40、SAVI Dollar和SAVI White玉米。投资者对南非白玉米期货市场的预期由三个动量指标代表，即移动平均收敛-发散（MACD）、相对强度指数（RSI）和变化率（ROC）。使用南非白玉米期货收盘价格的拟合GARCH（1,1）模型来估计波动性。使用时变向量自回归（VAR）框架来检查三个动量指标中的每一个对三个波动率指标中的每个的冲击的反应。研究结果证实，不确定性的变化影响南非白玉米期货动量交易者的预期；以及由此产生的交易影响价格波动，导致波动加剧。
{"title":"The effects of uncertainty on investor expectations and volatility in the South African white maize futures market","authors":"C. Auret, A. Sayed","doi":"10.1080/10293523.2020.1776503","DOIUrl":"https://doi.org/10.1080/10293523.2020.1776503","url":null,"abstract":"ABSTRACT Given the rapidly changing nature of financial markets, volatility indices often influence the trading behaviour of market participants, as they identify market patterns, predict market risk and gauge market sentiment. This paper examines the effects of uncertainty on the expectations of South African white maize futures traders and on volatility at a daily level. Uncertainty effects are measured using three volatility indices: The SAVI Top 40, the SAVI Dollar and the SAVI White Maize. Investor expectations in the South African white maize futures market are proxied by three momentum indicators, the moving average convergence divergence (MACD), the relative strength index (RSI) and the rate of change (ROC). Volatility is estimated using a fitted GARCH (1,1) model of South African white maize futures closing prices. A time-varying vector autoregressive (VAR) framework is used to examine the reactions of each of the three momentum indicators to shocks from each of the three volatility indices. The results confirm that changes in uncertainty influence the expectations of South African white maize futures momentum traders; and that these resulting trades influence price movements, resulting in increased volatility.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"165 - 179"},"PeriodicalIF":0.9,"publicationDate":"2020-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1776503","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45401226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-02DOI: 10.1080/10293523.2020.1742999
Carlos de Jesus, G. Willows, A. M. Olivier
ABSTRACT The study of return prediction is fundamental to investors. However, inconclusive evidence exists as to whether returns on the South African (SA) stock market may be explained by movements in SA or international macroeconomic variables. This study investigates integration between macroeconomic variables and the JSE ALSI. Using a monthly dataset from 1995–2016, the study is able to update the determination of integration relationships and reduce the ‘noise’ prevalent in prior research. Unit root, correlation, integration, causality and a vector error correction model were applied. The study identified that the ALSI was statistically significant in explaining SA inflation. The direction and significance of this relationship is of interest to investors and financial economists. If the ALSI has a predictive relationship with inflation, then market performance could impact the decisions made to raise or drop the Repo rate. In addition to the determination of the integration relationships, this study informs researchers on the efficiency and predictability of the SA market.
{"title":"The influence of the market on inflation, not the other way around","authors":"Carlos de Jesus, G. Willows, A. M. Olivier","doi":"10.1080/10293523.2020.1742999","DOIUrl":"https://doi.org/10.1080/10293523.2020.1742999","url":null,"abstract":"ABSTRACT The study of return prediction is fundamental to investors. However, inconclusive evidence exists as to whether returns on the South African (SA) stock market may be explained by movements in SA or international macroeconomic variables. This study investigates integration between macroeconomic variables and the JSE ALSI. Using a monthly dataset from 1995–2016, the study is able to update the determination of integration relationships and reduce the ‘noise’ prevalent in prior research. Unit root, correlation, integration, causality and a vector error correction model were applied. The study identified that the ALSI was statistically significant in explaining SA inflation. The direction and significance of this relationship is of interest to investors and financial economists. If the ALSI has a predictive relationship with inflation, then market performance could impact the decisions made to raise or drop the Repo rate. In addition to the determination of the integration relationships, this study informs researchers on the efficiency and predictability of the SA market.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"49 1","pages":"79 - 91"},"PeriodicalIF":0.9,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10293523.2020.1742999","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42621740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-02DOI: 10.1080/10293523.2020.1755928
Sagi Akron, Ender Demir, Roi D. Taussig
ABSTRACT This study proposes a real options exercise mechanism as a novel explanation for the asymmetric volatility phenomenon. We suggest that asymmetric volatility stems from the exercise of real call options following positive shocks and the exercise of real put options after negative shocks. Furthermore, we uniquely link asymmetric volatility to real options and firm’s growth opportunities. Using US market return data from the period spanning 1926–2018, this paper demonstrates that following a positive market shock generating return volatility, growth-firms exercise more real call options than value-firms. This further alleviates growth-firms’ volatility response, thereby resulting in higher asymmetric volatility. Book-to-market portfolio analyses provide significant empirical evidence that the firm’s growth opportunities intensify the asymmetric volatility phenomenon.
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