Pub Date : 2023-05-08DOI: 10.1080/10293523.2023.2198755
Z. Kučerová, S. Kapounek, J. Fidrmuc
ABSTRACT We present a wavelet analysis of retail investor attention and the daily returns of Bitcoin, Ethereum, and Litecoin at five selected crypto exchanges that identifies the fractal dynamics of the short- and long-term persistent processes. The investors’ attention is proxied by the Search Volume Index provided by Google at daily frequency. We detect significant temporal cyclical movements and coherence between cryptocurrency returns and retail investor attention at long investment horizons: from the beginning of 2017 to the middle of 2018 and, to a lesser degree, in 2019. Investment horizons that dominated in 2017 and 2018 were mainly driven by retail investor attention rather than by uncertainty, risk, or stock markets. Therefore, we do not confirm that cryptocurrencies can be considered a safe-haven asset in times of crisis because there is no significant negative comovement between the returns of cryptocurrencies and stock returns or economic uncertainty. Furthermore, the phase shift analysis indicates that attention can serve as a leading indicator for the cryptocurrency returns, particularly in 2017 and 2018. Therefore, retail investors are encouraged to use the Search Volume Index as an early warning indicator in case of sudden changes in the cryptocurrency returns to maximise profits or minimise losses.
{"title":"Time–frequency analysis of cryptocurrency attention","authors":"Z. Kučerová, S. Kapounek, J. Fidrmuc","doi":"10.1080/10293523.2023.2198755","DOIUrl":"https://doi.org/10.1080/10293523.2023.2198755","url":null,"abstract":"ABSTRACT We present a wavelet analysis of retail investor attention and the daily returns of Bitcoin, Ethereum, and Litecoin at five selected crypto exchanges that identifies the fractal dynamics of the short- and long-term persistent processes. The investors’ attention is proxied by the Search Volume Index provided by Google at daily frequency. We detect significant temporal cyclical movements and coherence between cryptocurrency returns and retail investor attention at long investment horizons: from the beginning of 2017 to the middle of 2018 and, to a lesser degree, in 2019. Investment horizons that dominated in 2017 and 2018 were mainly driven by retail investor attention rather than by uncertainty, risk, or stock markets. Therefore, we do not confirm that cryptocurrencies can be considered a safe-haven asset in times of crisis because there is no significant negative comovement between the returns of cryptocurrencies and stock returns or economic uncertainty. Furthermore, the phase shift analysis indicates that attention can serve as a leading indicator for the cryptocurrency returns, particularly in 2017 and 2018. Therefore, retail investors are encouraged to use the Search Volume Index as an early warning indicator in case of sudden changes in the cryptocurrency returns to maximise profits or minimise losses.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49059862","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 : 2023-05-04DOI: 10.1080/10293523.2023.2198765
Su Young Choi, Minyoung Noh, Jaimin Goh, Sooin Kim
ABSTRACT This study examines the relationship between analysts issuing long-term earnings forecasts and firms overinvestment. This research demonstrates that a positive relationship exists between analysts issuing long-term forecasts and firms overinvesting. The relationship between analysts issuing a long-term forecast and firms overinvesting is more significant where asymmetry of information exists. Additionally, we find that a positive relation between overinvestments and long-term analyst forecast publications is more pronounced for firms covered by competent analysts. Finally, analysts benefit from promotion by issuing long-term forecasts in response to the firms’ overinvestment. These findings contribute to the related literature by confirming that investment decisions are considered important in analysts’ long-term earnings forecasts.
{"title":"Do financial analysts publish long-term forecasts in response to firms’ overinvestments?","authors":"Su Young Choi, Minyoung Noh, Jaimin Goh, Sooin Kim","doi":"10.1080/10293523.2023.2198765","DOIUrl":"https://doi.org/10.1080/10293523.2023.2198765","url":null,"abstract":"ABSTRACT This study examines the relationship between analysts issuing long-term earnings forecasts and firms overinvestment. This research demonstrates that a positive relationship exists between analysts issuing long-term forecasts and firms overinvesting. The relationship between analysts issuing a long-term forecast and firms overinvesting is more significant where asymmetry of information exists. Additionally, we find that a positive relation between overinvestments and long-term analyst forecast publications is more pronounced for firms covered by competent analysts. Finally, analysts benefit from promotion by issuing long-term forecasts in response to the firms’ overinvestment. These findings contribute to the related literature by confirming that investment decisions are considered important in analysts’ long-term earnings forecasts.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":" ","pages":""},"PeriodicalIF":0.9,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46430576","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 : 2023-04-03DOI: 10.1080/10293523.2023.2198754
Aron Gottesman
ABSTRACT This paper uses a pooled cross-sectional sample of actively managed US equity mutual funds from 1991–2022 to show that tracking error volatility (TEV) is characterised by reversion. Mutual funds with relatively high (low) TEV tend to reduce (increase) their TEV in subsequent periods, and the degree of reversion is determined by the degree to which TEV is relatively high or low. This suggests that TEV is managed over time to satisfy relative risk budgets. This paper also shows that the previous literature’s finding that mutual funds increase their TEV as their performance declines holds even when taking into consideration that both performance and change in TEV may be jointly determined by TEV level. The results are robust to a variety of measurement periods and methodologies.
{"title":"Tracking error volatility and relative risk budgets","authors":"Aron Gottesman","doi":"10.1080/10293523.2023.2198754","DOIUrl":"https://doi.org/10.1080/10293523.2023.2198754","url":null,"abstract":"ABSTRACT This paper uses a pooled cross-sectional sample of actively managed US equity mutual funds from 1991–2022 to show that tracking error volatility (TEV) is characterised by reversion. Mutual funds with relatively high (low) TEV tend to reduce (increase) their TEV in subsequent periods, and the degree of reversion is determined by the degree to which TEV is relatively high or low. This suggests that TEV is managed over time to satisfy relative risk budgets. This paper also shows that the previous literature’s finding that mutual funds increase their TEV as their performance declines holds even when taking into consideration that both performance and change in TEV may be jointly determined by TEV level. The results are robust to a variety of measurement periods and methodologies.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"174 - 188"},"PeriodicalIF":0.9,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43144299","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 : 2023-04-03DOI: 10.1080/10293523.2023.2179162
Jakub Bandurski, Łukasz Postek
ABSTRACT This article addresses the topic of nonlinear dependencies in the Fama and French three-factor model. Five time-series models, including nonlinear terms, are assessed using US and European data and compared with a benchmark linear model. The analysis found that nonlinear dependencies in the modified Fama and French three-factor model were statistically significant and provided additional explanatory power for the underlying return-generating process. However, these nonlinear dependencies are of secondary importance in the economic sense.
{"title":"Nonlinear dependencies in the Fama and French three-factor model","authors":"Jakub Bandurski, Łukasz Postek","doi":"10.1080/10293523.2023.2179162","DOIUrl":"https://doi.org/10.1080/10293523.2023.2179162","url":null,"abstract":"ABSTRACT This article addresses the topic of nonlinear dependencies in the Fama and French three-factor model. Five time-series models, including nonlinear terms, are assessed using US and European data and compared with a benchmark linear model. The analysis found that nonlinear dependencies in the modified Fama and French three-factor model were statistically significant and provided additional explanatory power for the underlying return-generating process. However, these nonlinear dependencies are of secondary importance in the economic sense.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"106 - 131"},"PeriodicalIF":0.9,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43572229","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 : 2023-04-03DOI: 10.1080/10293523.2023.2198753
Munyaradzi Chawana, I. Botha, Y. Stander
ABSTRACT This paper employs quantile autoregression to investigate the influence of ‘market size’ and ‘industry’ effects on the South African equity market volatility response to return shocks. It is now well documented that equity market volatility exhibits asymmetric response to positive and negative return shocks. This paper provides empirical evidence which shows that the South African equity market asymmetric volatility response is significantly a large company phenomenon and with the exception of the Resources 10 and Financials 15 Indices, there is generally no volatility asymmetric response heterogeneity at the sector level. These results have important implications for investors and fund managers in relation to portfolio construction, risk management and optimal equity risk premium determination.
{"title":"A quantile-based analysis of risk-return dynamics in the South African equity market","authors":"Munyaradzi Chawana, I. Botha, Y. Stander","doi":"10.1080/10293523.2023.2198753","DOIUrl":"https://doi.org/10.1080/10293523.2023.2198753","url":null,"abstract":"ABSTRACT This paper employs quantile autoregression to investigate the influence of ‘market size’ and ‘industry’ effects on the South African equity market volatility response to return shocks. It is now well documented that equity market volatility exhibits asymmetric response to positive and negative return shocks. This paper provides empirical evidence which shows that the South African equity market asymmetric volatility response is significantly a large company phenomenon and with the exception of the Resources 10 and Financials 15 Indices, there is generally no volatility asymmetric response heterogeneity at the sector level. These results have important implications for investors and fund managers in relation to portfolio construction, risk management and optimal equity risk premium determination.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"153 - 173"},"PeriodicalIF":0.9,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42995275","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 : 2023-04-03DOI: 10.1080/10293523.2023.2185188
A. Zainudin, Azhar Mohamad
ABSTRACT This paper examines the impact of COVID-19 on five of the world's most liquid futures markets. The results of our wavelet coherence analysis for spot futures reveal two important findings. First, spot futures coherence movements during the pandemic period are influential at both low and high frequency scales. Second, the spectrogram shows mixed causality directions at all scales of observation in the period before and during the pandemic. In terms of hedging effectiveness, OLS and VECM show improvements in hedging effectiveness. Nevertheless, multiscale analysis with wavelet methods shows that hedging effectiveness depends on the hedge period due to the instability of the spot-futures association during the pandemic period. Our results refute the conventional wisdom among finance scholars that a stronger link between spot and futures markets during the crisis improves hedging effectiveness. We would emphasise that investment baskets and hedge pairs should be reviewed frequently to optimise results.
{"title":"Pandemic impact on the co-movement and hedging effectiveness of the global futures markets","authors":"A. Zainudin, Azhar Mohamad","doi":"10.1080/10293523.2023.2185188","DOIUrl":"https://doi.org/10.1080/10293523.2023.2185188","url":null,"abstract":"ABSTRACT This paper examines the impact of COVID-19 on five of the world's most liquid futures markets. The results of our wavelet coherence analysis for spot futures reveal two important findings. First, spot futures coherence movements during the pandemic period are influential at both low and high frequency scales. Second, the spectrogram shows mixed causality directions at all scales of observation in the period before and during the pandemic. In terms of hedging effectiveness, OLS and VECM show improvements in hedging effectiveness. Nevertheless, multiscale analysis with wavelet methods shows that hedging effectiveness depends on the hedge period due to the instability of the spot-futures association during the pandemic period. Our results refute the conventional wisdom among finance scholars that a stronger link between spot and futures markets during the crisis improves hedging effectiveness. We would emphasise that investment baskets and hedge pairs should be reviewed frequently to optimise results.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"132 - 152"},"PeriodicalIF":0.9,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43311264","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 : 2023-03-27DOI: 10.1080/10293523.2023.2179161
Masudul Alam, M. A. H. Chowdhury, Mohammad Abdullah, Mansur Masih
ABSTRACT We investigate the return and volatility spillovers among NFTs, REITs, and other major financial assets from January 2019 to November 2022, using connectedness approaches. The findings indicate that total return and volatility connectedness increased during the COVID-19 and the Russia–Ukraine war. REITs partially maintained their historical independence from shocks from other assets, while NFTs emerged as the new portfolio diversifiers. Findings suggest that investors can use REITs or a combination of NFTs, OIL, GOLD, and REITs with other assets to hedge against volatile assets during periods of financial turmoil. These findings have significant implications for heterogeneous market participants aiming to identify optimal portfolio diversifiers.
{"title":"Volatility spillover and connectedness among REITs, NFTs, cryptocurrencies and other assets: Portfolio implications","authors":"Masudul Alam, M. A. H. Chowdhury, Mohammad Abdullah, Mansur Masih","doi":"10.1080/10293523.2023.2179161","DOIUrl":"https://doi.org/10.1080/10293523.2023.2179161","url":null,"abstract":"ABSTRACT We investigate the return and volatility spillovers among NFTs, REITs, and other major financial assets from January 2019 to November 2022, using connectedness approaches. The findings indicate that total return and volatility connectedness increased during the COVID-19 and the Russia–Ukraine war. REITs partially maintained their historical independence from shocks from other assets, while NFTs emerged as the new portfolio diversifiers. Findings suggest that investors can use REITs or a combination of NFTs, OIL, GOLD, and REITs with other assets to hedge against volatile assets during periods of financial turmoil. These findings have significant implications for heterogeneous market participants aiming to identify optimal portfolio diversifiers.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"83 - 105"},"PeriodicalIF":0.9,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48898983","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 : 2023-01-02DOI: 10.1080/10293523.2022.2155353
Hyeongjun Kim, Hoon Cho, Doojin Ryu
ABSTRACT Recently, various corporate failure prediction models that use machine learning techniques have received considerable attention. In particular, using a sequence of a company's historical information, rather than just the most recent information, yields better predictive performance by adopting recurrent neural networks (RNNs) and long short-term memory (LSTM) algorithms in the United States market. Similarly, we evaluate whether these results hold in emerging market contexts using listed companies in Korea. We also compare the logistic regression, random forest, RNN, LSTM, and an ensemble model combining these four techniques. The random forest model with recent information outperforms the other models, indicating that corporate failure prediction models for immature markets, unlike those for developed markets, might have to focus more on recent information rather than on the historical sequence of corporate performance.
{"title":"Measuring corporate failure risk: Does long short-term memory perform better in all markets?","authors":"Hyeongjun Kim, Hoon Cho, Doojin Ryu","doi":"10.1080/10293523.2022.2155353","DOIUrl":"https://doi.org/10.1080/10293523.2022.2155353","url":null,"abstract":"ABSTRACT Recently, various corporate failure prediction models that use machine learning techniques have received considerable attention. In particular, using a sequence of a company's historical information, rather than just the most recent information, yields better predictive performance by adopting recurrent neural networks (RNNs) and long short-term memory (LSTM) algorithms in the United States market. Similarly, we evaluate whether these results hold in emerging market contexts using listed companies in Korea. We also compare the logistic regression, random forest, RNN, LSTM, and an ensemble model combining these four techniques. The random forest model with recent information outperforms the other models, indicating that corporate failure prediction models for immature markets, unlike those for developed markets, might have to focus more on recent information rather than on the historical sequence of corporate performance.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"40 - 52"},"PeriodicalIF":0.9,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41474709","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 : 2023-01-02DOI: 10.1080/10293523.2023.2179160
Ö. Alp, Levent Özbek, Bilge Canbaloglu
ABSTRACT This study decomposes the trend-cycle components of the stock market indices of the United States and China in a time series framework over the period of 1980–2021, and 1992–2021 years, respectively. Using the extended Kalman filter (EKF) method, the changing dynamics of stock market prices can be analysed more effectively since stock market prices can have a nonlinear pattern, and the EKF allows estimated system parameters to change over time under the nonlinear state-space model. As the impacts of shocks to trend and cycle on the stock market can be observed more efficiently due to flexible time-varying parameter estimation, the EKF offers more reasonable results than other decomposition tools. The empirical findings of this study prove that the EKF extracts the trend and cycle components by giving quite consistent forecasts for stock market prices in both advanced and emerging market countries.
{"title":"An analysis of stock market prices by using extended Kalman filter: The US and China cases","authors":"Ö. Alp, Levent Özbek, Bilge Canbaloglu","doi":"10.1080/10293523.2023.2179160","DOIUrl":"https://doi.org/10.1080/10293523.2023.2179160","url":null,"abstract":"ABSTRACT This study decomposes the trend-cycle components of the stock market indices of the United States and China in a time series framework over the period of 1980–2021, and 1992–2021 years, respectively. Using the extended Kalman filter (EKF) method, the changing dynamics of stock market prices can be analysed more effectively since stock market prices can have a nonlinear pattern, and the EKF allows estimated system parameters to change over time under the nonlinear state-space model. As the impacts of shocks to trend and cycle on the stock market can be observed more efficiently due to flexible time-varying parameter estimation, the EKF offers more reasonable results than other decomposition tools. The empirical findings of this study prove that the EKF extracts the trend and cycle components by giving quite consistent forecasts for stock market prices in both advanced and emerging market countries.","PeriodicalId":44496,"journal":{"name":"Investment Analysts Journal","volume":"52 1","pages":"67 - 82"},"PeriodicalIF":0.9,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41361785","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}
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