We provide empirical evidence that the decentralized cryptocurrency exchange can help reach the decentralized consensus of cryptocurrency value. We focus on Binance (the largest centralized cryptocurrency exchange) and Uniswap (the largest decentralized cryptocurrency exchange), and show that investors on Binance and Uniswap trade in response to prices on the two exchanges. More importantly, we find that the size of Uniswap user base exerts an asymmetric impact on investors’ trading. When its size increases, Uniswap user base exerts a larger impact on investors’ trading on Binance towards the Uniswap price, compared to the opposite direction. With a quasi-exogenous shock on Uniswap user base, we establish the causal impact of Uniswap user base on trading. Our results suggest that Uniswap as a decentralized exchange can reflect the consensus of cryptocurrency value that investors believe in because of blockchain’s transparency and trustworthiness. Our findings imply that the decentralized infrastructure built on blockchain and smart contracts can provide an alternative solution to cases where a consensus underwritten by a credible central party is not feasible or too costly to obtain.
{"title":"Trust in DeFi: An Empirical Study of the Decentralized Exchange","authors":"Jianlei Han, Shiyang Huang, Zhuo Zhong","doi":"10.2139/ssrn.3896461","DOIUrl":"https://doi.org/10.2139/ssrn.3896461","url":null,"abstract":"We provide empirical evidence that the decentralized cryptocurrency exchange can help reach the decentralized consensus of cryptocurrency value. We focus on Binance (the largest centralized cryptocurrency exchange) and Uniswap (the largest decentralized cryptocurrency exchange), and show that investors on Binance and Uniswap trade in response to prices on the two exchanges. More importantly, we find that the size of Uniswap user base exerts an asymmetric impact on investors’ trading. When its size increases, Uniswap user base exerts a larger impact on investors’ trading on Binance towards the Uniswap price, compared to the opposite direction. With a quasi-exogenous shock on Uniswap user base, we establish the causal impact of Uniswap user base on trading. Our results suggest that Uniswap as a decentralized exchange can reflect the consensus of cryptocurrency value that investors believe in because of blockchain’s transparency and trustworthiness. Our findings imply that the decentralized infrastructure built on blockchain and smart contracts can provide an alternative solution to cases where a consensus underwritten by a credible central party is not feasible or too costly to obtain.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121651717","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}
Abstract Cryptocurrencies are traded on two types of exchanges – centralized and decentralized. Although trading in the largest cryptocurrencies primarily occurs on centralized exchanges, most newly issued tokens can only be exchanged using decentralized platforms. Volumes in these decentralized exchanges (including automated market makers) has recently increased exponentially. We examine the role of this new and unmonitored market, utilizing an extensive sample of tokens exclusively traded on decentralized platforms. We show significant differences in the listing and trading characteristics of these tokens relative to their centralized equivalents. A small selection of these tokens obtain listing on a centralized exchange during the sample period, which is accompanied by a significant increase in trading activity, consistent with market segmentation. A centralized listing results in a migration of volume away from decentralized platforms, revealing a strong preference by tokenholders for deeper and more liquid markets over the increased security and anonymity offered by decentralized exchanges.
{"title":"Decentralized Exchanges: The 'Wild West' of Cryptocurrency Trading","authors":"Angelo Aspris, Sean Foley, Jiri Svec, Leqi Wang","doi":"10.2139/ssrn.3717330","DOIUrl":"https://doi.org/10.2139/ssrn.3717330","url":null,"abstract":"Abstract Cryptocurrencies are traded on two types of exchanges – centralized and decentralized. Although trading in the largest cryptocurrencies primarily occurs on centralized exchanges, most newly issued tokens can only be exchanged using decentralized platforms. Volumes in these decentralized exchanges (including automated market makers) has recently increased exponentially. We examine the role of this new and unmonitored market, utilizing an extensive sample of tokens exclusively traded on decentralized platforms. We show significant differences in the listing and trading characteristics of these tokens relative to their centralized equivalents. A small selection of these tokens obtain listing on a centralized exchange during the sample period, which is accompanied by a significant increase in trading activity, consistent with market segmentation. A centralized listing results in a migration of volume away from decentralized platforms, revealing a strong preference by tokenholders for deeper and more liquid markets over the increased security and anonymity offered by decentralized exchanges.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126818630","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 aim of this study is to examine an existence of contagion in ASEAN-5 currency markets during COVID-19 period, the type of contagion whether it is pure contagion that happens in the short run only or fundamentals-based contagion in the long run and the country source of this contagion effect. The study starts by imposing structure to the regional exchange rates guided by variable lag Granger causality and variable lag Transfer Entropy, followed by co-integration and Error Correction Model (VECM) within the Structural VAR framework to capture the short run, long run and error correction term (ect) in currency market of ASEAN-5. The next empirical framework used is wavelet analysis specifically wavelet power spectrum and wavelet coherency to capture the multi scale time and frequency domain of currency market volatility and covariance respectively. The VECM findings show there exists long run cointegration in the ASEAN-5 currency markets during COVID-19 and any disequilibrium will be adjusted by Indonesian Rupiah, Malaysia Ringgit and Singapore Dollar at daily rate of adjustments of 6.58%, 1.47% and 2.45% respectively. The wavelet power spectrum provides evidence of short run and long run contagion effect in Indonesia, Malaysia and Singapore currency market, while Philippines and Thailand experience minimal contagion effect in the short run and heightened volatility in the long run for Thailand. No long run contagion effect for Philippines. The wavelet coherency shows contagion effect emanating from Indonesia Rupiah to its neighboring countries in the short and only to Thailand and Malaysia in the long run.
{"title":"Contagion Effect in ASEAN-5 Currency Markets During COVID-19","authors":"Nur Ain Shahrier, Chung Tin Fah","doi":"10.2139/ssrn.3888001","DOIUrl":"https://doi.org/10.2139/ssrn.3888001","url":null,"abstract":"The aim of this study is to examine an existence of contagion in ASEAN-5 currency markets during COVID-19 period, the type of contagion whether it is pure contagion that happens in the short run only or fundamentals-based contagion in the long run and the country source of this contagion effect. The study starts by imposing structure to the regional exchange rates guided by variable lag Granger causality and variable lag Transfer Entropy, followed by co-integration and Error Correction Model (VECM) within the Structural VAR framework to capture the short run, long run and error correction term (ect) in currency market of ASEAN-5. The next empirical framework used is wavelet analysis specifically wavelet power spectrum and wavelet coherency to capture the multi scale time and frequency domain of currency market volatility and covariance respectively. The VECM findings show there exists long run cointegration in the ASEAN-5 currency markets during COVID-19 and any disequilibrium will be adjusted by Indonesian Rupiah, Malaysia Ringgit and Singapore Dollar at daily rate of adjustments of 6.58%, 1.47% and 2.45% respectively. The wavelet power spectrum provides evidence of short run and long run contagion effect in Indonesia, Malaysia and Singapore currency market, while Philippines and Thailand experience minimal contagion effect in the short run and heightened volatility in the long run for Thailand. No long run contagion effect for Philippines. The wavelet coherency shows contagion effect emanating from Indonesia Rupiah to its neighboring countries in the short and only to Thailand and Malaysia in the long run.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128984505","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}
In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-tradable crypto assets using high-frequency data for the period from January 2019 to December 2020. We apply the Diagonal-BEKK model to data from the pre-COVID and COVID-19 periods, and identify significant changes in patterns of co-movements and correlations during the pandemic period. We also employ the Minimum Spanning Tree (MST) and Planar Maximally Filtered Graph (PMFG) methods to study the changes of the crypto asset network structure after the COVID-19 outbreak. While the influential role of Bitcoin in the digital asset ecosystem has been confirmed, our novel findings reveal that due to recent developments in the blockchain ecosystem, crypto assets that can be categorised as dApps and Protocols have become more attractive to investors than pure cryptocurrencies, with dApps exhibiting the highest average degree of correlations with all crypto assets in the sample during the COVID-19 pandemic period.
{"title":"High-Frequency Connectedness between Bitcoin and Other Top-Traded Crypto Assets during the COVID-19 Crisis","authors":"Paraskevi Katsiampa, L. Yarovaya, D. Zięba","doi":"10.2139/ssrn.3871405","DOIUrl":"https://doi.org/10.2139/ssrn.3871405","url":null,"abstract":"In this paper, we analyse co-movements and correlations between Bitcoin and thirty-one of the most-tradable crypto assets using high-frequency data for the period from January 2019 to December 2020. We apply the Diagonal-BEKK model to data from the pre-COVID and COVID-19 periods, and identify significant changes in patterns of co-movements and correlations during the pandemic period. We also employ the Minimum Spanning Tree (MST) and Planar Maximally Filtered Graph (PMFG) methods to study the changes of the crypto asset network structure after the COVID-19 outbreak. While the influential role of Bitcoin in the digital asset ecosystem has been confirmed, our novel findings reveal that due to recent developments in the blockchain ecosystem, crypto assets that can be categorised as dApps and Protocols have become more attractive to investors than pure cryptocurrencies, with dApps exhibiting the highest average degree of correlations with all crypto assets in the sample during the COVID-19 pandemic period.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130375055","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}
I examine the forecasting performance, directional accuracy, rationality and economic value of analyst forecasts and characteristics of investment portfolios built from these forecasts for 30 currency pairs from 2006 to 2020. My results show that analyst forecasts perform worse than forecasts based on a random walk and forward rates and that they are biased and do not provide significant economic value to investors. Forecasts from global systemically important banks do not differ from non-systemically important banks in terms of forecasting ability. Median forecasts may strongly deviate from market expectations, while analyst forecast dispersion is positively associated with future currency returns. Portfolios built from analyst forecasts tend to strongly underperform the dollar factor, value, carry and momentum portfolios and are spanned by them. My findings indicate that expected returns extracted from analyst forecasts are negatively related to realized excess returns in FX markets and thus contribute to the literature on survey-based returns in asset pricing.
{"title":"Analyst Forecasts and Currency Markets","authors":"Florian Mair","doi":"10.2139/ssrn.3751418","DOIUrl":"https://doi.org/10.2139/ssrn.3751418","url":null,"abstract":"I examine the forecasting performance, directional accuracy, rationality and economic value of analyst forecasts and characteristics of investment portfolios built from these forecasts for 30 currency pairs from 2006 to 2020. My results show that analyst forecasts perform worse than forecasts based on a random walk and forward rates and that they are biased and do not provide significant economic value to investors. Forecasts from global systemically important banks do not differ from non-systemically important banks in terms of forecasting ability. Median forecasts may strongly deviate from market expectations, while analyst forecast dispersion is positively associated with future currency returns. Portfolios built from analyst forecasts tend to strongly underperform the dollar factor, value, carry and momentum portfolios and are spanned by them. My findings indicate that expected returns extracted from analyst forecasts are negatively related to realized excess returns in FX markets and thus contribute to the literature on survey-based returns in asset pricing.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132165993","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}
E. Benhamou, D. Saltiel, B. Guez, J. Atif, R. Laraki
Graphical models and in particular Hidden Markov Models or their continuous space equivalent, the so called Kalman filter model, are a powerful tool to make some inference that can be used in decision making contexts. The estimation of their parameters is usually based on the Expectation Maximization approach as this is a natural statistical way to train them. When used for decision making, it may be more relevant to find parameters that are relevant to our decisions rather than just try to fit the model from a statistical point of view. Hence, we can reformulate the determination of graphical model as an inference problem where the true concern is the quality of the decisions from the forecast given by the model. We show that the resulting optimization problem can be reformulated as an information geometric optimization problem and introduce a natural gradient descent strategy that incorporates additional meta parameters. We show that our approach is a strong alternative to the celebrated EM approach for learning in graphical models. Actually, our natural gradient based strategy leads to learning optimal parameters for the final objective function (which is our decision) without artificially trying to fit a distribution that may not correspond to the real one. We support our theoretical findings with the question of decision in financial markets and show that the learned model performs better than traditional practitioner methods and is less prone to overfitting.
{"title":"From Forecast to Decisions in Graphical Models: A Natural Gradient Optimization Approach","authors":"E. Benhamou, D. Saltiel, B. Guez, J. Atif, R. Laraki","doi":"10.2139/ssrn.3813403","DOIUrl":"https://doi.org/10.2139/ssrn.3813403","url":null,"abstract":"Graphical models and in particular Hidden Markov Models or their continuous space equivalent, the so called Kalman filter model, are a powerful tool to make some inference that can be used in decision making contexts. The estimation of their parameters is usually based on the Expectation Maximization approach as this is a natural statistical way to train them. When used for decision making, it may be more relevant to find parameters that are relevant to our decisions rather than just try to fit the model from a statistical point of view. Hence, we can reformulate the determination of graphical model as an inference problem where the true concern is the quality of the decisions from the forecast given by the model. We show that the resulting optimization problem can be reformulated as an information geometric optimization problem and introduce a natural gradient descent strategy that incorporates additional meta parameters. We show that our approach is a strong alternative to the celebrated EM approach for learning in graphical models. Actually, our natural gradient based strategy leads to learning optimal parameters for the final objective function (which is our decision) without artificially trying to fit a distribution that may not correspond to the real one. We support our theoretical findings with the question of decision in financial markets and show that the learned model performs better than traditional practitioner methods and is less prone to overfitting.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133838250","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}
Decentralized Finance (DeFi) offers the promise of an emergent alternative financial architecture that prioritizes disintermediation and decentralization to empower individuals along cryptoanarchist principles. Yet it is mired in considerable difficulties including market manipulation, distortionary incentives, excess short-termism, Ponzi-schemes, and money-laundering challenges that also foment a considerable level of dissuasion against DeFi’s wider adoption. This paper critically evaluates many of these important facets at a time when DeFi is emerging as a disintermediated and experimental financial praxis.
{"title":"Decentralized Finance (DeFi): An Emergent Alternative Financial Architecture","authors":"Usman W. Chohan","doi":"10.2139/ssrn.3791921","DOIUrl":"https://doi.org/10.2139/ssrn.3791921","url":null,"abstract":"Decentralized Finance (DeFi) offers the promise of an emergent alternative financial architecture that prioritizes disintermediation and decentralization to empower individuals along cryptoanarchist principles. Yet it is mired in considerable difficulties including market manipulation, distortionary incentives, excess short-termism, Ponzi-schemes, and money-laundering challenges that also foment a considerable level of dissuasion against DeFi’s wider adoption. This paper critically evaluates many of these important facets at a time when DeFi is emerging as a disintermediated and experimental financial praxis.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114912549","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}
Corporate FX risk management has gained complexity with an increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this paper, we propose a Value-at-Risk (VaR) based model to estimate the optimal hedge ratio for a multi-national corporate that aims to minimize the cost of hedging at a given tolerance level of expected loss arising out of FX movement. The paper illustrates both parametric and historical methods of VaR estimation at a portfolio level as the first step in risk management. As a second step, an efficient-frontier is derived based on the expected VaR level at various hedge ratios and compared with associated hedge cost. The benefits of this approach include: identification of net exposures after correlations among currencies are accounted for in order to avoid duplication of hedges, and condensation of the parameters governing hedging decision into a single, intuitively-appealing number. The paper also highlights the need to frequently update the model’s assumptions as currency correlations and corporate exposures remain dynamic. JEL Classification Codes: C10, F31, G32, M20.
{"title":"Value-At-Risk Based Approach For Currency Hedging","authors":"Rachna Khurana, Umang Khetan","doi":"10.2139/ssrn.3767162","DOIUrl":"https://doi.org/10.2139/ssrn.3767162","url":null,"abstract":"Corporate FX risk management has gained complexity with an increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this paper, we propose a Value-at-Risk (VaR) based model to estimate the optimal hedge ratio for a multi-national corporate that aims to minimize the cost of hedging at a given tolerance level of expected loss arising out of FX movement. The paper illustrates both parametric and historical methods of VaR estimation at a portfolio level as the first step in risk management. As a second step, an efficient-frontier is derived based on the expected VaR level at various hedge ratios and compared with associated hedge cost. The benefits of this approach include: identification of net exposures after correlations among currencies are accounted for in order to avoid duplication of hedges, and condensation of the parameters governing hedging decision into a single, intuitively-appealing number. The paper also highlights the need to frequently update the model’s assumptions as currency correlations and corporate exposures remain dynamic. \u0000 \u0000JEL Classification Codes: C10, F31, G32, M20.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"686 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132584467","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}
Pub Date : 2020-12-17DOI: 10.21511/imfi.17(4).2020.30
Geeta E, Iqbal Thonse Hawaldar, V. BAI G., Mendon Suhan, Rajesha T.M.
Investors invest in a foreign market to reap the benefits of currency differences. The change in the value of underlying assets affects these hedged funds and, at the same time, restricts investors from higher return possible in unhedged funds. This study aims to examine the performance of most actively traded shares in Exchange Traded Fund and any influence, along with tracking the information from the index. This study also analyzes the currency fluctuation and its impact on returns and volatility of ETF and index. The equity ETF, which tracks NASDAQ (NDX 100), is chosen for the study, and the data analysis is carried out using statistical methods such as correlation, regression, and GARCH model. The study utilizes the currency rate data from 2013 to 2018 of USD, GBP, and INR and examines its effect on the NDX (NASDAQ). The study emphasizes whether the ETF as a basket of securities is insensitive to currency rate fluctuations. It is found that the response of ETF to the currency movements is likely due to its underlying index. The study concludes that Motilal Oswal shares in NASDAQ 100 ETF are highly sensitive to the NDX 100 movements; thus, there is no direct impact between ETF and index performance through exchange rate fluctuation.
{"title":"Are Global Exchange Traded Fund Pretentious on Exchange Rate Fluctuation? A Study Using GARCH Model","authors":"Geeta E, Iqbal Thonse Hawaldar, V. BAI G., Mendon Suhan, Rajesha T.M.","doi":"10.21511/imfi.17(4).2020.30","DOIUrl":"https://doi.org/10.21511/imfi.17(4).2020.30","url":null,"abstract":"Investors invest in a foreign market to reap the benefits of currency differences. The change in the value of underlying assets affects these hedged funds and, at the same time, restricts investors from higher return possible in unhedged funds. This study aims to examine the performance of most actively traded shares in Exchange Traded Fund and any influence, along with tracking the information from the index. This study also analyzes the currency fluctuation and its impact on returns and volatility of ETF and index. The equity ETF, which tracks NASDAQ (NDX 100), is chosen for the study, and the data analysis is carried out using statistical methods such as correlation, regression, and GARCH model. The study utilizes the currency rate data from 2013 to 2018 of USD, GBP, and INR and examines its effect on the NDX (NASDAQ). The study emphasizes whether the ETF as a basket of securities is insensitive to currency rate fluctuations. It is found that the response of ETF to the currency movements is likely due to its underlying index. The study concludes that Motilal Oswal shares in NASDAQ 100 ETF are highly sensitive to the NDX 100 movements; thus, there is no direct impact between ETF and index performance through exchange rate fluctuation.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"65 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":"132834309","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 analyse volatility spillovers between the on- and offshore (CNY and CNH) Renminbi exchange rates towards the US dollar (USD). The volatility impulse response (VIRF) methodology introduced by Hafner and Herwatz (2006) is applied to several shocks between January 2012 and December 2019. Furthermore, we propose a novel way of estimating VIRFs based on Bayesian estimation of the MV-GARCH BEKK model. A simple Independence Chain Metropolis-Hastings algorithm allows drawing VIRFs in an efficient manner, allowing to analyse the significance and persistence of volatility shocks and associated volatility spillovers. The VIRF results show that the CNH exchange rate promptly reflects the global market demand and supply, while the CNY exchange rate reacts with a time lag. The VIRF results also show the existence of spillovers between the two markets as the co-volatility increases in response to shocks.
{"title":"Volatility Transmission and Volatility Impulse Response Functions in the Main and the Satellite Renminbi Exchange Rate Markets","authors":"M. Funke, Julius Loermann, Andrew Tsang","doi":"10.1111/roie.12577","DOIUrl":"https://doi.org/10.1111/roie.12577","url":null,"abstract":"We analyse volatility spillovers between the on- and offshore (CNY and CNH) Renminbi exchange rates towards the US dollar (USD). The volatility impulse response (VIRF) methodology introduced by Hafner and Herwatz (2006) is applied to several shocks between January 2012 and December 2019. Furthermore, we propose a novel way of estimating VIRFs based on Bayesian estimation of the MV-GARCH BEKK model. A simple Independence Chain Metropolis-Hastings algorithm allows drawing VIRFs in an efficient manner, allowing to analyse the significance and persistence of volatility shocks and associated volatility spillovers. The VIRF results show that the CNH exchange rate promptly reflects the global market demand and supply, while the CNY exchange rate reacts with a time lag. The VIRF results also show the existence of spillovers between the two markets as the co-volatility increases in response to shocks.","PeriodicalId":413816,"journal":{"name":"Econometric Modeling: International Financial Markets - Foreign Exchange eJournal","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884930","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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