We exploit China’s great stock market crash in 2015 to study the effects of government stock purchases. The Chinese government purchased stocks to stabilize the market through state-owned financial institutions collectively called the “National Team”. We find that the intervention led to reduced volatility, trading volume, and price informativeness. These impacts mainly come from the disclosure of the government portfolio.These results are consistent with the heterogeneous beliefs and global game literature, where more consensus reduces trading, and more precise public information undermines information production. The paper suggests some fundamental trade-offs facing government purchase of stocks in a second-best world.
{"title":"Managing China's Stock Markets: The Economics of the National Team","authors":"Tri Vi Dang, Wei Li, Yongqing Wang","doi":"10.2139/ssrn.3546411","DOIUrl":"https://doi.org/10.2139/ssrn.3546411","url":null,"abstract":"We exploit China’s great stock market crash in 2015 to study the effects of government stock purchases. The Chinese government purchased stocks to stabilize the market through state-owned financial institutions collectively called the “National Team”. We find that the intervention led to reduced volatility, trading volume, and price informativeness. These impacts mainly come from the disclosure of the government portfolio.These results are consistent with the heterogeneous beliefs and global game literature, where more consensus reduces trading, and more precise public information undermines information production. The paper suggests some fundamental trade-offs facing government purchase of stocks in a second-best world.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127942127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The 39th largest economy in the world, Bangladesh has a GDP of more than US$300 billion. Its population of more than 160 million people occupies a relatively small area, only 144,000 square kilometers.
Bangladesh experienced significant economic growth during the last two decades. Its financial markets have lagged, however, compared with this economic improvement. Equity market capitalization stood at only 14% of GDP in June 2019. Price performance has also been below par, with an average annual return of only 0.08% in the last decade. Bangladesh’s main sectors are telecommunications, financials, pharmaceuticals, consumer goods, and power and utility, and its top 20 companies make up 54% of the market capitalization. Although local investors dominate the market, foreign institutional investors have increased their participation over the years. They now contribute around 6%–8% to daily transactions.
Compared with its stock market, Bangladesh’s fixed-income market is much smaller. The government bond market accounts for 7.9% of GDP, and the corporate bond market accounts for only 0.01% of GDP. The fixed-income market is denominated in the local currency, the taka (BDT), and the country has not yet explored the opportunity of issuing debt instruments in foreign currency. The largest investors in the Bangladeshi fixed-income market are commercial banks, followed by insurance companies. Even though the taka has been stable for several decades and there are no capital controls, the bond market's foreign investment is at a nascent stage.
With new leadership at the Bangladesh Securities and Exchange Commission, much-needed reforms have begun to gain momentum. Both the equity and debt markets are poised for significant growth in coming years if corporate governance, market integrity, a quality IPO pipeline, technological improvements and listing of debt instruments, and simplified debt issuances can be ensured.
孟加拉国是世界第39大经济体，国内生产总值超过3000亿美元。它的人口超过1.6亿，占地面积相对较小，只有14.4万平方公里。孟加拉国在过去二十年中经历了显著的经济增长。然而，与经济的改善相比，中国的金融市场却落后了。2019年6月，股票市值仅占GDP的14%。价格表现也低于平均水平，过去10年的平均年回报率仅为0.08%。孟加拉国的主要行业是电信、金融、制药、消费品、电力和公用事业，其前20家公司占总市值的54%。虽然本地投资者在市场上占主导地位，但近年来，外国机构投资者的参与度有所增加。它们现在占日常交易的6%-8%。与股票市场相比，孟加拉国的固定收益市场要小得多。政府债券市场占GDP的7.9%，公司债券市场仅占GDP的0.01%。固定收益市场以当地货币塔卡(BDT)计价，该国尚未探索以外币发行债务工具的机会。孟加拉国固定收益市场的最大投资者是商业银行，其次是保险公司。尽管人民币汇率已经稳定了几十年，也没有资本管制，但债券市场的外国投资仍处于起步阶段。随着孟加拉国证券交易委员会(Bangladesh Securities and Exchange Commission)的新领导层上任，亟需的改革已开始获得动力。如果能确保公司治理、市场诚信、优质IPO渠道、技术改进和债务工具上市以及简化债务发行，股票和债券市场都有望在未来几年实现显著增长。
{"title":"The Emerging Asia Pacific Capital Markets: Bangladesh","authors":"Md. Shah Naoaj, Asif Khan, Naveed Ahsan","doi":"10.2139/ssrn.3807438","DOIUrl":"https://doi.org/10.2139/ssrn.3807438","url":null,"abstract":"The 39th largest economy in the world, Bangladesh has a GDP of more than US$300 billion. Its population of more than 160 million people occupies a relatively small area, only 144,000 square kilometers.<br><br>Bangladesh experienced significant economic growth during the last two decades. Its financial markets have lagged, however, compared with this economic improvement. Equity market capitalization stood at only 14% of GDP in June 2019. Price performance has also been below par, with an average annual return of only 0.08% in the last decade. Bangladesh’s main sectors are telecommunications, financials, pharmaceuticals, consumer goods, and power and utility, and its top 20 companies make up 54% of the market capitalization. Although local investors dominate the market, foreign institutional investors have increased their participation over the years. They now contribute around 6%–8% to daily transactions.<br><br>Compared with its stock market, Bangladesh’s fixed-income market is much smaller. The government bond market accounts for 7.9% of GDP, and the corporate bond market accounts for only 0.01% of GDP. The fixed-income market is denominated in the local currency, the taka (BDT), and the country has not yet explored the opportunity of issuing debt instruments in foreign currency. The largest investors in the Bangladeshi fixed-income market are commercial banks, followed by insurance companies. Even though the taka has been stable for several decades and there are no capital controls, the bond market's foreign investment is at a nascent stage.<br><br>With new leadership at the Bangladesh Securities and Exchange Commission, much-needed reforms have begun to gain momentum. Both the equity and debt markets are poised for significant growth in coming years if corporate governance, market integrity, a quality IPO pipeline, technological improvements and listing of debt instruments, and simplified debt issuances can be ensured.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133074834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although liquidity has received wide attention in asset pricing literature over the past decades, how stock liquidity is priced in emerging markets remains unclear. We find that liquidity plays an important role in explaining the cross-section and time-series variation in expected returns by incorporating multi-dimensional liquidity proxies in the spread, depth, and trading activity. The predictive power persists after controlling the several conventional pricing factors. We also find that the high illiquidity quintile generates higher monthly risk-adjusted returns than the low illiquidity quintile, ranging from 3.2% to 8.4% per month. The results are robust to alternative stock liquidity measures and sampling criteria. Our findings highlight the profitability of liquidity-based trading strategy in the Chinese stock market.
{"title":"Is Illiquidity Priced in the Chinese Stock Market?","authors":"Jun Liu, Kai Wu, Lan Zheng","doi":"10.2139/ssrn.3787113","DOIUrl":"https://doi.org/10.2139/ssrn.3787113","url":null,"abstract":"Although liquidity has received wide attention in asset pricing literature over the past decades, how stock liquidity is priced in emerging markets remains unclear. We find that liquidity plays an important role in explaining the cross-section and time-series variation in expected returns by incorporating multi-dimensional liquidity proxies in the spread, depth, and trading activity. The predictive power persists after controlling the several conventional pricing factors. We also find that the high illiquidity quintile generates higher monthly risk-adjusted returns than the low illiquidity quintile, ranging from 3.2% to 8.4% per month. The results are robust to alternative stock liquidity measures and sampling criteria. Our findings highlight the profitability of liquidity-based trading strategy in the Chinese stock market.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"13 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using a dataset on ETFs ownership of stocks in nine Emerging Asian markets, we find that stocks with a higher ETF ownership exhibit a greater commonality in liquidity to other stocks in the same market. The effect increases with the level of ETFs arbitrage activities, supporting the hypothesis that ETFs arbitrage mechanism is the source of commonality in liquidity. We also find that the effect is asymmetric; ETFs exert a stronger influence when stocks’ liquidity decline. These findings are supported by a cross-market analysis, as we show that the effect is larger in market where stocks have more common exposures to ETFs, while tightened capital market condition could also amplify the effect of ETF ownership. Increased financial market openness, on the other hand, may ease the potential systemic impact. ETFs ownership of stocks also increases the commonality in liquidity of stocks across markets. The cross-markets impacts by ETFs present a channel via which financial market integration through ETFs could lead to a build-up of systemic liquidity risks and increase the vulnerability of liquidity shock spill-over to stock markets.
{"title":"Could Etfs Make Stock Markets More Vulnerable to Systemic Liquidity Shock? – Evidence From Emerging Asia","authors":"G. Wu","doi":"10.2139/ssrn.3796791","DOIUrl":"https://doi.org/10.2139/ssrn.3796791","url":null,"abstract":"Using a dataset on ETFs ownership of stocks in nine Emerging Asian markets, we find that stocks with a higher ETF ownership exhibit a greater commonality in liquidity to other stocks in the same market. The effect increases with the level of ETFs arbitrage activities, supporting the hypothesis that ETFs arbitrage mechanism is the source of commonality in liquidity. We also find that the effect is asymmetric; ETFs exert a stronger influence when stocks’ liquidity decline. These findings are supported by a cross-market analysis, as we show that the effect is larger in market where stocks have more common exposures to ETFs, while tightened capital market condition could also amplify the effect of ETF ownership. Increased financial market openness, on the other hand, may ease the potential systemic impact. ETFs ownership of stocks also increases the commonality in liquidity of stocks across markets. The cross-markets impacts by ETFs present a channel via which financial market integration through ETFs could lead to a build-up of systemic liquidity risks and increase the vulnerability of liquidity shock spill-over to stock markets.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121857770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We construct a representative index of largest Indian energy companies listed on the National Stock Exchange (NIFTY 50). We test for presence of regimes, non-linearities, and jumps in the price signal. We benchmark performance against alternative models, including single-regime models and models with no jumps. We then benchmark the quality of regime identification against other indices examined in the literature, such as Nikkei 225 and FTSE 100. Overall, find that our regime-switching model performs well in identifying the regimes in this comparative setting. Based on our model selection criteria, we prefer a regime-augmented model to a model that allows no regime identification. But overall, we prefer a model with jumps and regimes over those that do not allow for jump-diffusion and Markov regime-switching.
{"title":"Regimes, Non-Linearities, and Price Discontinuities in Indian Energy Stocks","authors":"Charles Shaw","doi":"10.2139/ssrn.3750900","DOIUrl":"https://doi.org/10.2139/ssrn.3750900","url":null,"abstract":"We construct a representative index of largest Indian energy companies listed on the National Stock Exchange (NIFTY 50). We test for presence of regimes, non-linearities, and jumps in the price signal. We benchmark performance against alternative models, including single-regime models and models with no jumps. We then benchmark the quality of regime identification against other indices examined in the literature, such as Nikkei 225 and FTSE 100. Overall, find that our regime-switching model performs well in identifying the regimes in this comparative setting. Based on our model selection criteria, we prefer a regime-augmented model to a model that allows no regime identification. But overall, we prefer a model with jumps and regimes over those that do not allow for jump-diffusion and Markov regime-switching.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130417122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Derivatives, and their influence on the dynamics of underlying stock markets, is an interesting topic of debate, which predates their introduction. The unresolved influence of derivatives on their underlying stock markets still intrigues many. In this regard, researchers/stakeholders are still curious about the (de)stabilizing influence of derivatives on the overall market. In disposition of these observations, two contradicting hypothesis have been studied widely and have remained the focus of attention in several theoretical and empirical studies. These hypotheses are explained in several ways. Among many, one explanation refers to the destabilizing influence of derivatives, due to the enhanced involvement of noise traders, after the introduction of derivatives. This aspect remains the topic of discussion for this study. After the formal introduction of the SSFs (Single Stock Futures) in Pakistan, this topic became a cause of concern for the stakeholders of this market as well. Hence, this study attempts to tap into this aspect of the de(stabilization) debate, by proposing a modified version of the famous Sentana & Wadhwani (1982) model. In order to tap the potential shortcomings of the S&W model, this study contributes to the extant literature in several ways: 1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market, due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speaking, the modified version of the model not only extends the original model in terms of its explanation, but also empirically tests this aspect in the Single Stock Futures (SSFs) market of Pakistan. This model tested whether SSFs promote, or inhibit the noise trading post-SSFs. After putting it to test, the newer model did not report any negative or positive impact of the introduction of SSFs on the underlying stocks. This may conclude that the proclaimed (de)stabilizing role of the SSFs, in the context of Pakistan, is not justified. This may also imply that the stringent regulatory frameworks, post the Global Financial Crisis, (GFC) for the resumed SSFs, are not justified and require revision.1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market, due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speakin
{"title":"Noise Trading and Single Stock Futures: Modifying Sentana & Wadhwani's Model","authors":"I. Malik, Attaullah Shah","doi":"10.2139/ssrn.3678509","DOIUrl":"https://doi.org/10.2139/ssrn.3678509","url":null,"abstract":"Derivatives, and their influence on the dynamics of underlying stock markets, is an interesting topic of debate, which predates their introduction. The unresolved influence of derivatives on their underlying stock markets still intrigues many. In this regard, researchers/stakeholders are still curious about the (de)stabilizing influence of derivatives on the overall market. In disposition of these observations, two contradicting hypothesis have been studied widely and have remained the focus of attention in several theoretical and empirical studies. These hypotheses are explained in several ways. Among many, one explanation refers to the destabilizing influence of derivatives, due to the enhanced involvement of noise traders, after the introduction of derivatives. This aspect remains the topic of discussion for this study. After the formal introduction of the SSFs (Single Stock Futures) in Pakistan, this topic became a cause of concern for the stakeholders of this market as well. Hence, this study attempts to tap into this aspect of the de(stabilization) debate, by proposing a modified version of the famous Sentana & Wadhwani (1982) model. In order to tap the potential shortcomings of the S&W model, this study contributes to the extant literature in several ways: 1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market, due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speaking, the modified version of the model not only extends the original model in terms of its explanation, but also empirically tests this aspect in the Single Stock Futures (SSFs) market of Pakistan. This model tested whether SSFs promote, or inhibit the noise trading post-SSFs. After putting it to test, the newer model did not report any negative or positive impact of the introduction of SSFs on the underlying stocks. This may conclude that the proclaimed (de)stabilizing role of the SSFs, in the context of Pakistan, is not justified. This may also imply that the stringent regulatory frameworks, post the Global Financial Crisis, (GFC) for the resumed SSFs, are not justified and require revision.1) It adds the feature of trading volume in the model to analyze and study the potential movement of noise traders from spot to futures market, due to the ease of trading that the futures markets offer, 2) the new, modified model adds a lagged term for returns in order to tap the potential asynchronous inefficiencies, 3) it considers the Generalized Error Distribution (GED) instead of the Gaussian Distribution, in order to realize the fact that returns are not normally distributed. Generally speakin","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133084998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to examine the effect of COVID-19 and policies toward the pandemic on the world’s various stock markets by regions and industries
本研究的目的是检验COVID-19和针对大流行的政策对世界各地区的各种股票市场的影响
{"title":"How COVID-19 and Policies to Combat the Spread of COVID-19 Impact the World Stock Markets","authors":"Che-ling. Chiu","doi":"10.2139/ssrn.3644471","DOIUrl":"https://doi.org/10.2139/ssrn.3644471","url":null,"abstract":"The purpose of this study is to examine the effect of COVID-19 and policies toward the pandemic on the world’s various stock markets by regions and industries","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115416520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper studies how adjustment costs in real estate investments affect portfolio choices of developing economy households. Using novel panel data on Indian households, we document that while most households hold outstanding investments in real estate, the majority of them participated exclusively in financial assets during the five year survey period. We explain these stylized facts by identifying how households allocate their marginal income across various assets. Using local rainfall shocks as a source exogenous variation in household incomes, we empirically establish the presence of adjustment costs in real estate, which drives the infrequent participation of households in this asset class. We further show that the households use financial assets as a transitory asset class on their way to accumulating real estate. Our results are consistent with a theoretical model of portfolio choice where households face an adjustment cost to re-adjust their lumpy real estate holdings.
{"title":"Household Finance in Developing Countries: Evidence from India","authors":"Pawan Gopalakrishnan, S. Ritadhi, Shekhar Tomar","doi":"10.2139/ssrn.3510006","DOIUrl":"https://doi.org/10.2139/ssrn.3510006","url":null,"abstract":"This paper studies how adjustment costs in real estate investments affect portfolio choices of developing economy households. Using novel panel data on Indian households, we document that while most households hold outstanding investments in real estate, the majority of them participated exclusively in financial assets during the five year survey period. We explain these stylized facts by identifying how households allocate their marginal income across various assets. Using local rainfall shocks as a source exogenous variation in household incomes, we empirically establish the presence of adjustment costs in real estate, which drives the infrequent participation of households in this asset class. We further show that the households use financial assets as a transitory asset class on their way to accumulating real estate. Our results are consistent with a theoretical model of portfolio choice where households face an adjustment cost to re-adjust their lumpy real estate holdings.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122741438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research studies private information from extreme price movements or jumps. The authors calculate the private information using a reduced form model from the stochastic volatility jump process and use several statistical robustness tests as well as several frequencies to improve our consistency. This study reveals that private information is significant in explain the existence of jumps in capital markets in Southeast Asia, whereas macroeconomic events cannot explain them. The authors determine empirically that private information in Malaysia, Singapore, Thailand, and Indonesia are not persistent and its value gradually decreases when we use the lower frequency. Based on the Fama–Macbeth regression, this study shows that private information in the capital market has a strong positive relationship with individual returns in Indonesia’s capital market and Thailand’s capital market for all frequencies.
{"title":"Private Information from Extreme Price Movements (Empirical Evidences from Southeast Asia Countries)","authors":"Usman Arief, Z. Husodo","doi":"10.2139/ssrn.3431237","DOIUrl":"https://doi.org/10.2139/ssrn.3431237","url":null,"abstract":"This research studies private information from extreme price movements or jumps. The authors calculate the private information using a reduced form model from the stochastic volatility jump process and use several statistical robustness tests as well as several frequencies to improve our consistency. This study reveals that private information is significant in explain the existence of jumps in capital markets in Southeast Asia, whereas macroeconomic events cannot explain them. The authors determine empirically that private information in Malaysia, Singapore, Thailand, and Indonesia are not persistent and its value gradually decreases when we use the lower frequency. Based on the Fama–Macbeth regression, this study shows that private information in the capital market has a strong positive relationship with individual returns in Indonesia’s capital market and Thailand’s capital market for all frequencies.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"302 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117055277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates bond return predictability and its economic value. Using regression models, we first examine both the statistical and economic significance of bond return predictability in the Chinese market, and analyze the non-Markov and stochastic volatility properties of bond yields. On the basis of the above analysis, we propose a systematic method for constructing non-Markov dynamic term structure models (DTSMs) under a generalized Heath-Jarrow-Morton (HJM) framework with stochastic volatility. Then, we investigate the roles of the non-Markov property and stochastic volatility in bond return predictability and its economic gains realizing. Finally, we analyze the economic drivers of bond return predictability. Empirical results show that bond return predictability in the Chinese market is statistically significant, which also can be converted into significant economic gains. The non-Markov property and stochastic volatility are of critical importance for this conversion process. Moreover, time-varying risk premia driven by the economic environment are the main source of the bond return predictability in the Chinese market, while unspanned stochastic volatility factors also contain much information for future bond returns.
{"title":"Bond Return Predictability and its Economic Value: The Case of China","authors":"Yunpeng Su, Baochen Yang, zhou Fangzhao, Yunbi An","doi":"10.2139/ssrn.3772069","DOIUrl":"https://doi.org/10.2139/ssrn.3772069","url":null,"abstract":"This paper investigates bond return predictability and its economic value. Using regression models, we first examine both the statistical and economic significance of bond return predictability in the Chinese market, and analyze the non-Markov and stochastic volatility properties of bond yields. On the basis of the above analysis, we propose a systematic method for constructing non-Markov dynamic term structure models (DTSMs) under a generalized Heath-Jarrow-Morton (HJM) framework with stochastic volatility. Then, we investigate the roles of the non-Markov property and stochastic volatility in bond return predictability and its economic gains realizing. Finally, we analyze the economic drivers of bond return predictability. Empirical results show that bond return predictability in the Chinese market is statistically significant, which also can be converted into significant economic gains. The non-Markov property and stochastic volatility are of critical importance for this conversion process. Moreover, time-varying risk premia driven by the economic environment are the main source of the bond return predictability in the Chinese market, while unspanned stochastic volatility factors also contain much information for future bond returns.","PeriodicalId":287077,"journal":{"name":"ERN: Asia & Pacific (Emerging Markets) (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133630834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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