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The debate about the role of speculators in commodity markets has been intensified after the financialization. The current study augments the empirical evidence related to speculators and their impact on volatility of commodity markets. In doing so, the study uses daily data between 12th November 2009 to 30th April 2020 for oil and gold future contracts from Pakistan Mercantile Exchange. The findings suggest that speculative activity positively and significantly affects the returns' volatility. These findings support the destabilizing hypothesis, which argues that speculators create distortions in commodity markets. The findings have important implication for market participants (e.g., absence of welfare gain for hedgers) and regulators.

The complete diversification of idiosyncratic volatility is questionable due to factors such as market imperfections, investor irrationality and managerial decisions. Therefore, the purpose of this study is to investigate the impact of idiosyncratic volatility on average stock returns in the Sri Lankan context. Using the five-factor asset pricing model of Fama and French (2015) along with Exponential Generalised Autoregressive Conditional Heteroskedasticity (EGARCH) estimated idiosyncratic volatility of stocks of firms listed on the Colombo Stock Exchange (CSE), except for firms in banks, finance and insurance sectors, this study reveals a positive and statistically significant association between average stock returns and idiosyncratic volatility for the sample period from September 2004 to March 2018. The empirical findings on firm profitability and investment yield striking evidence on idiosyncratic volatility of stocks from a frontier market perspective, while uncovering the importance of further research on the investor behaviour on asset pricing decisions.

Stock liquidity plays important role in investors’ participation in any nation’s stock market. The global pandemic shock created market illiquidity especially among developing stock market like Nigerian stock market. However, the emergence of global pandemic via COVID-19 pandemic triggered declined market turnover (stock liquidity) which in turn created lack of confidence among stock investors in Nigeria. This study therefore examined the effects of Global pandemic on stock liquidity in the Nigerian stock market using stock turnover and COVID-19 pandemic as measure for stock market liquidity and global pandemic. The study employed expost facto research design using weekly data of both corona-virus pandemic and stock market turnover within the period of March, 2019 to February, 2022. The study employed Exponential GARCH (EGARCH) model and found a considerable negative consequence of Global Pandemic (Covid-19) on stock liquidity, implying that corona-virus pandemic has brought bad information (bad news) which deteriorate the liquidity in the stock exchange market. The study concluded that COVID-19 pandemic shock reduces stock liquidity in Nigerian stock exchange market. The study however recommended that government should put in place more palliative policies such as tax incentive and lowest interest rate on loan to individual and institutional investors which will cushion effect of COVID-19 pandemic and increase investors’ participation in the Nigerian stock market. Also, Nigeria stock market regulators should put in place sound measures that will enhance availability of stock information so as to arouse the interest more and new investors to the Nigerian Stock Market. [ABSTRACT FROM AUTHOR]

Cryptocurrencies have recently emerged as a popular asset class, with investors having high risk appetite and speculative attributes. They are not backed by physical assets, such as commodities or real currencies; they are purely speculative assets having high volatility. Regulatory authorities across the globe have conflicting rules regarding cryptocurrencies. Recent studies on volatility of cryptocurrencies have primarily addressed univariate volatility analysis and volatility spillover between cryptocurrencies and other asset classes, mostly stocks and commodities. This study has three objectives. Firstly, it considers six prominent cryptocurrencies, i.e., Bitcoin, Ethereum, Binance Coin, Cardano, Tether, and Ripple, and examines the nature of asymmetrical volatility in them using EGARCH and TGARCH techniques. Secondly, it examines whether there are volatility spillovers between the cryptocurrencies as well as from one of the most popular global fear indices, i.e., CBOE volatility index, using dynamic conditional correlation (DCC). Thirdly, it further measures the total and directional volatility spillover among the cryptocurrencies using the Diebold-Yilmaz index. This study has found that Ethereum and Ripple may be used to construct a portfolio. There exists long-term volatility spillover among all the cryptocurrencies; however, there is no short-term spillover of volatility. Volatility of Binance Coin, Cardano, and Ripple influence and are influenced the most by volatilities of other cryptocurrencies. [ABSTRACT FROM AUTHOR]

This paper examines the effect of real-time global geopolitical risks (GPRs), acts (GPAs), and threats (GPTs) indices on monthly returns and volatility of several American commodity futures. By modeling volatility via an Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH), we provide evidence that GPRs and GPTs do not only impact but trigger adverse effects on the returns of crude oil, gold, platinum, and silver, while GPAs negatively affect the returns of crude oil, heating oil, platinum, and sugar futures. Furthermore, GPTs have a weak positive effect on corn futures volatility. Overall, our findings provide portfolio diversification benefits by showing how the impact of global GPRs, GPAs and GPTs on portfolio returns could be mitigated. [ABSTRACT FROM AUTHOR]

In agricultural economics, fluctuations in food prices and the factors affecting these fluctuations have always been an important research topic. From production to delivery to consumers, the supply chain of agricultural products has a dynamic structure with continuous changes. In this dynamic process, analyzing the intensive use of energy at each stage has gained more importance with its deepening effects in comparison to the past. This study will empirically explore the volatility spillovers between energy price index and fruit-vegetables price index in the period of 2007-2020 in Turkey using the Kanas and Diebold-Yilmaz approaches. According to the results obtained from the Kanas approach in the study, it has been observed that there is a statistically significant volatility spillover from the energy price index to the vegetable price index, whereas there is no statistically significant volatility spillover to the fruit price index. This finding was supported by the results obtained from the Diebold-Yilmaz approach showing that there is a volatility spillover of 13.52% to the vegetable price index and 0.86% to the fruit price index from the energy price index. [ABSTRACT FROM AUTHOR]

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The People's Bank of China began to discuss the importance of DR007 (the 7-day repurchase rate by deposit-taking institutions at China's interbank market) from 2016. This study compares the performance of the fixed DR007 (FDR007) to that of the other popular policy target rate, the FR007 (the fixed 7-day repurchase rate by both deposit-taking institutions and non-deposit-taking institutions). This is the first known study to make this comparison. Using a variety of methodologies, and based on daily datasets for January 2018 – December 2019, this study concludes that the FDR007 outperforms FR007 with respect to policy target rates. [ABSTRACT FROM AUTHOR]

The January effect, and its impact in the financial world, is one of the most researched calendar irregularities. The purpose of this study is to examine if there is a January influence on the South African stock market. Aggregate and sectorial indices of Johannesburg Stock Exchange (JSE) were examined. We analyse the January effect by Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models. Findings from the mean equation showed a positive January effect for the Top 40 and Basic materials, whilst for the variance equation, a negative January anomaly was found in the Top 40, Health care, Telecommunications, and Technology indices. The January seasonal investment style is recommended for improving returns in Basic materials sector. Investing in the Telecommunications sector in January will assist an investor in portfolio diversification and reduce risk. The findings show that the January effect has shifted to other months. Given the limits of previous research, this study adds to the body of knowledge on calendar anomalies by bringing a South African viewpoint to the debate of the January anomaly and extending the analytic period to 1995-2018. [ABSTRACT FROM AUTHOR]

Understanding calendar trends may aid in the identification of stock market return drivers and the making of smarter investment selections. The study's goal was to see if there is a turn of the month influence on the South African equity market. We analyse Johannesburg Stock Exchange (JSE) indices covering the period 1995 to 2018. The Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models are used to model turn of the month anomaly. The mean equation results of the turn of the month displayed a positive effect for the aggregate and sectorial indices. The variance equation showed no turn of the month effect in the Top 40 and All Shares indices, though the Basic materials sector indicated a positive turn of the month effect. Investing in the telecommunications industry provides the best returns for the turn of the month method. Basic materials should be avoided by investors since it increases their exposure. In the South African equities market, the occurrence of the turn of the month impact invalidates the efficient market theory. We offer value by analysing turn of the month influence sectorial indices for Africa's largest stock market, in contrast to earlier research. [ABSTRACT FROM AUTHOR]

In this study, we utilize various GARCH-type models to estimate and forecast volatility on S&P 500 returns and compare the results between the two financial crises, the GFC of 2008 (Global Financial Crisis of 2008) and the COVID-19 financial crisis. These two financial crises are different from the forming reasons by whether mainly caused by the financial factors. This study also makes the evaluations on the performance of these GARCH-type models in estimating and forecasting volatility, which may provide the efficient models for reference for the research of the volatility of the future potential financial crisis. We find that as for the AIC/BIC assessments on the estimation of volatility, the GJR-GARCH model performs better during the GFC of 2008, while the EGARCH model has the better performance during the COVID-19 financial crisis. With respect to the QLIKE loss function evaluation on the forecasting ability of volatility, the GJR-GARCH model performs better during the GFC of 2008, while symmetric GARCH model has better volatility forecasting ability during the COVID-19 financial crisis.

This study investigates the impact of index futures trading on the spot market volatility for Ho Chi Minh Stock Exchange (HOSE). The data used in this study are daily VN30-Index, future trading volume and open interests covering the period from March 18th, 2015 to January 2nd, 2020. In order to capture the asymmetric effect, the EGARCH(1,1) model is employed in this study. It is found that the introduction of index future trading leads to the increase the spot market volatility. In addition, our empirical findings reveal that the impact of recent news on spot market volatility in the post-index future period is greater that than the pre-index future period; and the market volatility in the post-futures period is more persistent than in the pre-futures period. Moreover, the level of asymmetric effect on the market volatility in the post-index future period is significantly lower than that for the pre-index futures period. Finally, the results derived from the Granger causality test confirm that the bi-directional causality relation between the spot market volatility and the future trading activity exists in HOSE. [ABSTRACT FROM AUTHOR]

The holiday effect is one of the most noticeable seasonal anomalies in financial markets, and it appeals to technical traders who use past data from trading activities to devise profitable strategies. The purpose of this article is to assess the South African equity market's holiday anomaly. The financial data employed consists of market and sectorial indices of the Johannesburg Stock Exchange (JSE) spanning from 1995 to 2018. The holiday effect was modelled by Generalized Auto Regressive Conditional Heteroskedasticity Model (GARCH), exponential GARCH (EGARCH) and threshold GARCH (TGARCH) models. Negative pre-holiday effect was found in aggregate and sectorial indices for the variance equation. The mean and variance equations unveiled a post-holiday effect in market and sectorial indices. Basic materials should be avoided by investors since it increases their exposure. By investing in the Basic Materials sector, the pre-holiday trading strategy can help investors reduce their risk exposure. When it comes to post-holiday seasonal trading, investors should concentrate on the Telecommunications sector to generate higher profits. Investors can minimize losses by avoiding the Industrials sector, which increases risk exposure. In contrast to previous empirical research that focused on aggregate indices, our analysis delineates holiday anomaly for sectorial indices in South African equity. [ABSTRACT FROM AUTHOR]

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Purpose: The research aims to build a suitable model for the conditional mean and conditional variance for forecasting the rate of inflation in Pakistan by summarizing the properties of the series and characterizing its salient features. Design/Methodology/Approach: For this purpose, Pakistan’s Inflation Rate is based upon the Consumer Price Index (CPI), ranging from January 1962 to December 2019 has been analyzed. Augmented Dickey Fuller (ADF) test that was used for testing the stationarity of the series. The ARIMA modeling technique is a conditional mean and GARCH model for conditional variance. Models are selected on AIC and BIC model selection criteria. The estimating and forecasting ability of three ARIMA models with the GARCH (2,2) model has been compared to capture the possible nonlinearity present in the data. To depict the possible asymmetric effect in the conditional variance, two asymmetric GARCH models, EGARCH and TGARCH models have been applied. Findings: Based on statistical loss functions, GARCH (2,2) model is the best variance model for this series. The empirical results reveal that the performance of model-2 is best for all the three variance models. However, the GARCH model is the best as the variance model for this series. This shows that the asymmetric effect invariance is not so important for the rate of inflation in Pakistan. Implications/Originality/Value: The current study was based on the least considered variables and the pioneer in testing the complex relationship through the ARIMA model with GARCH innovation.

In this article, our goal is mixing ARMA models with EGARCH models and composing a mixed model ARMA(R,M)-EGARCH(Q,P) with two steps. The first step includes modeling the data series by using EGARCH model alone, interspersed with steps of detecting the heteroscedasticity effect, estimating the model's parameters, and testing the adequacy of the model. Also, we predict the conditional variance and verify its convergence to the unconditional variance value. The second step includes mixing ARMA with EGARCH and using the mixed (composite) model in the modeling of time series data, predicting future values, and then assessing the prediction ability of the proposed model by using the prediction error criterion. [ABSTRACT FROM AUTHOR]

Using GARCH(p,q) models, in this study our aim is to examine and search the characteristics of volatility of Turkish sugar price. Due to the ARCH effects on price, ARCH(q), GARCH(p,q) and EGARCH(p,q) including these effects on mean and variance equations were estimated. Normal, t-Student, and generalized error distributions with Maximum Likelihood Estimation Method were estimated for these models. Determining the optimal parameters, Marquardt’s algorithm (1963) was used for maximizing the log-likelihood function. Mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute deviation (MAD) were used to determine the fit model for making predicting. In this study, we found the best model as a GARCH (1,1) model. [ABSTRACT FROM AUTHOR]

This paper studies the effect of COVID-19 on the volatility of Australian stock returns and the effect of negative and positive news (shocks) by investigating the asymmetric nature of the shocks and leverage impact on volatility. We employ a generalised autoregressive conditional heteroskedasticity (GARCH) model and extend the analysis using the exponential GARCH (EGARCH) model to capture asymmetry and allegedly leverage. We proxy the news related to the negative effect of COVID-19 on the Australian health system and its economy as bad news, and on the other hand, measures taken by government economic stimulus packages through their monetary and fiscal policies as good news. The S&P ASX200 (ASX-200) index is used as a proxy to the Australian stock market, and we use value-weighted returns of the stocks listed on ASX-200 for the period 27 January 2020 to 29 December 2020. The empirical results suggest the EGARCH model fits better in capturing asymmetry and leverage than the GARCH model in estimating the volatility of the Australian stock returns. However, another interesting finding is that the EGARCH model with volatility equation without news demonstrates a larger (smaller) leverage effect of the negative (positive) shocks on the conditional volatility compared to its variant with the news. [ABSTRACT FROM AUTHOR]

We examine the impact of crude oil price fluctuations on equity markets for four emerging Latin American markets, namely, Argentina, Brazil, Chile, and Mexico. We adopt an approach that examines this relationship in both a time and frequency domains. The co‐spectral analysis confirmed that most of the observable coherence between crude oil and equity returns occurred at relatively short frequencies. The structural vector autoregression (SVAR) results suggest that shocks to crude oil price directed all equity markets into negative territory, though they typically reversed course after approximately twenty‐four months. Although the decomposition of the prediction error variance showed that crude oil prices were weakly exogenous in the SVAR model, in most cases Brazil's equity market may have been responsible for the higher percentage of variations in the remaining indices. The nonlinear Granger causality tests reveal, with the exception of the Merval index, the equity markets under study were responsive to crude oil price shocks. [ABSTRACT FROM AUTHOR]

In this work, we study the famous model of volatility; called model of conditional heteroscedastic autoregressive with mixed memory MMGARCH for modeling nonlinear time series. The MMGARCH model has two mixing components, one is a GARCH short memory and the other is GARCH long memory. the main objective of this search for finds the best model between mixtures of the models we made (long memory with long memory, short memory with short memory and short memory with long memory) Also, the existence of its stationary solution is discussed. The Monte Carlo experiments demonstrate we discovered theoretical. In addition, the empirical application of the MMGARCH model (1, 1) to the daily index DOW and NASDAQ illustrates its capabilities; we find that for the mixture between APARCH and EGARCH is superior to any other model tested because it produces the smallest errors. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the differences between the systematic risk estimated by OLS and it simultaneous estimation with a GARCH errors. The systematic risk of an asset is estimated by the beta coefficient of the market line. According to the OLS hypothesis, the estimators are robust and residuals are white noise process. However various papers show the existence of statistical anomalies (stylized facts) in residuals (heteroskedasticity, autocorrelation and non‐normality) rejecting the BLUE properties of estimators. In order to considerate these anomalies to modelize the hazard in residuals regression, we use ARCH processes class that has proved it efficiency in finance. We estimate simultaneously the parameters of the market line and those of the GARCH process for the 30 perennial equities listed in CAC40 for the daily period 2005 to 2015 and we compare them each other. We select the E‐GARCH model providing the best residuals characteristics and we note significant differences with the OLS Betas particularly for equities with betas greater than 1. On this base, we estimate a linear relationship between the OLS Betas and the E‐GARCH Betas considering this break to modelize the differences between these two kinds of Betas. By this way, Investors can quickly adjust the Beta with this tool without completely reestimating them with GARCH. [ABSTRACT FROM AUTHOR]

In real life, the stock price is always easy to be mispriced after listing, too high or too low. There are numerous reasons behind mispricing. Many scholars believe that the information asymmetry is one of them. In an inefficient market, the information asymmetry is bound to exist and be very high. In order to investigate the impact of registration-based IPO system reforms in mispricing, this paper takes the GEM market as an example to analyze the impact of the GEM market on mispricing. And we proposed a method with fuzzy logic neural network for Growth Enterprise Market analysis for IPO system. After processing data, we use ARIMA and EGARCH model to find the results. The immaturity will result in the negative impact caused by reformation, which will deviate from the goal that makes Chinese stock market become better. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19), the disease caused by the novel coronavirus SARS-CoV-2, has greatly affected financial markets, economies and societies worldwide. This study focusses on the Chinese stock markets. Based on Google Trends data during the period from 1 January 2020 to 12 April 2020, and using the exponential generalised autoregressive conditional heteroskedastic (EGARCH) model, this study finds that the higher uncertainty resulting from the COVID-19 pandemic is significantly associated with the drop in China's composite index, but this impact varies by sectors. Simultaneously, the higher uncertainty due to COVID-19 is significantly associated with greater volatility in stock returns for both the composite index and sector indices. [ABSTRACT FROM AUTHOR]

Technological advancements not only bolstered almost all activities, but also accelerated the spread of information in blinks. Thus, announcements about market volatilities along with subpar financial instruments' performance have led investors to search for alternative assets to cope with amplified uncertainties. Investors in politically unstable economies, like Pakistan, are more prone to the risks of uncertainties so require some safe investments. Previously gold has been investigated as a hedge and safe haven during various economic and market conditions but literature lacks investigation of gold during political uncertainties. So by investigating the role of gold as a hedge and safe haven during political uncertainties against sectors of Pakistan Stock Exchange (PSX), the current study not only contributes to literature, but also contributes to the knowledge of Pakistani investors and asset managers that whether they should consider gold as a diversifier or not. The study incorporates daily gold prices (gold bullion Pkr. per Tola), daily stock prices of PSX sectors and political events of Pakistan for a time span of 2009 to 2019. Appling EGARCH with quantile dummies and event dummies, findings indicate that gold acts as a hedge and safe haven against the stock market and most of its sectors in normal as well as politically uncertain situations. Thus, Pakistani investors must consider gold in asset allocation strategies for having an optimal portfolio that can cope with the risk of acute market conditions and political uncertainties. Findings of current study facilitate Pakistani investors, investment advisors and asset managers to make healthy investment decisions and enjoying the benefits of diversification through inclusion of gold in their portfolios. [ABSTRACT FROM AUTHOR]

Production of big cayenne in Malang Districts has trend increase while consumption has trends decrease make excess supply. Unbalanced supply and demand causes price fluctuation between producers and consumers. Price fluctuations can pose risks and price uncertainties or price changes known as price volatility. The purpose of this research is to analyze price volatility that occurs at the level of producers and consumers of big cayenne in Malang Districts, and analyze the spillover volatility that occurs at the price of producers and consumers big cayenne in Malang Districts. The method used to analyze price volatility is ARCH/GARCH models and the method used to analyze the spillover volatility is EGARCH models. The results showed that the price volatility of big cayenne in Malang Regency at the producer and consumer level is low volatility and the results of spillover volatility showed that the price of big cayenne producers and consumers in Malang Districts occur spillover volatility.

Macroeconomic are important variables influencing volatility in the bond market. Some of the challenges faced such as default risk, liquidity risk, interest rate risk, inflation risk, and exchange rate risk. This study is aimed at examining asymmetric volatility using the EGARCH model and at estimating macroeconomic variables which influence the return of Indonesian Government bonds. The asymmetric volatility can be measured by determining the best order value of the EGARCH model. Based on the findings of the study, EGARCH (2.1) is the best model for assessing volatility in short-term SUN returns, EGARCH (3.1) for medium-term SUN and EGARCH (2.3) for the long term. The asymmetric volatility pertains in the returns of short, medium and long-term government bonds. In addition, the negative information has a greater impact than positive information in the short, medium and long term. The deposit rate and return of the Composite Stock Price Index have a significant positive effect on short, medium and long term bond returns. The effective federal funds rate or FED interest rate has a significant positive effect on the return of short and long-term SUN bonds while in the medium term it has no effect. Exchange rates have a significant negative effect on short, medium and long term bond returns.

This study has the purpose to examine the effect of political events on the volatility of stocks traded on the Indonesia Stock Exchange (IDX). Furthermore, this study also sees whether such political events also influence the shares that have direct links with the participants in presidential elections. The political event being examined was the Indonesian Presidential Election held in 2014. The researchers used the daily data on the shares of all companies listed on the Indonesia Stock Exchange (IDX) in 2014. The hypothesis testing were done using the GARCH (Generalized Auto Regressive Conditional Heteroscedasticity) estimation and its derivatives namely EGARCH (Exponential GARCH) and TARCH (Threshold GARCH). It was found that the 2014 Presidential Election asymmetrically affected stock return volatility on IDX and contrary to the leverage effect, which means that positive shocks (good news) have better influence than negative shocks (bad news). Out of all listed companies that have direct links with participants in the presidential election, 3 companies have their stock volatility affected by this Presidential Election; some with symmetric effect and some others with asymmetric effect.

In recent time the Central Banks cross the globe employ a range of avenues to communicate their monetary policy decisions and explain to financial markets and the general public the reason for their policy actions. This communication, in turn, gives signals to the financial markets regarding the future trajectories of governmental activities. This study therefore investigated the sensitivity of interest rate to MPC communication from 1st January, 2010 to 30th June, 2020 in Nigera. Series of test were carryout and EGARCH was chosen as the appropriate techniques in which dummy variable was used to capture the meeting days in the variance equation. Data of monetary policy were sourced from CBN website. The results of an EGARCH model show that the communications between Central Bank and the money market are considerably informative and therefore assist to reduce market interest rates' volatility. The study has so concluded that the communication from the Central Bank of Nigeria has an impact on the desired direction of interests. One policy implication of this conclusion is that it is clear enough about the desired policy orientation for the future that CBN communique substance of MPC meetings will guide the market in the proper way. This is consistent with the literature that if Central Bank opens the foundations for monetary policy implementation up to the markets, it raises the odds of controlling agents' expectations. Therefore the study recommends that the meeting should be sustained.

January effect means that stock returns are higher in January than in any other month of the year. The aim of this study is to investigate whether there is a January effect on Borsa İstanbul (BIST 100) stock returns and volatility with GARCH, EGARCH and TGARCH models. For this purpose, the daily stock return closing values covering the period of 04.01.2010-18.02.2020 were used. According to the findings, while January effect was observed on stock returns, no effect was found on volatility. In addition, it was determined that negative shocks are more effective than positive shocks in EGARCH and TGARCH models created to determine leverage effect. [ABSTRACT FROM AUTHOR]

One of the implications of the intertemporal capital asset pricing model is that the risk premium of the market portfolio is a linear function of its variance. Yet, estimation theory of classical GARCH-in-mean models with linear-in-variance risk premium requires strong assumptions and is incomplete. We show that exponential-type GARCH models such as EGARCH or Log-GARCH are more natural in dealing with linear-in-variance risk premia. For the popular and more difficult case of EGARCH-in-mean, we derive conditions for the existence of a unique stationary and ergodic solution and invertibility following a stochastic recurrence equation approach. We then show consistency and asymptotic normality of the quasi-maximum likelihood estimator under weak moment assumptions. An empirical application estimates the dynamic risk premia of a variety of stock indices using both EGARCH-M and Log-GARCH-M models. for this article are available online. [ABSTRACT FROM AUTHOR]

Australia—China relations, and especially Chinese influence in Australia, have been the subject of heated debate in Australia since 2016. The central issue is, how to balance concerns over Chinese influence in Australia with the economic benefits of Chinese trade and investment? This study—arguably the first of its kind—answers this question using rigorous empirical modelling. First, it uses Google Trends search results to measure Chinese influence in Australia. Second, it connects Chinese influence, as reflected in Google Trends search results, to financial markets, including stock markets, government bond markets and foreign exchange markets. Weekly data for January 2016–December 2019 are entered into an exponential generalised autoregressive conditional heteroskedastic model. The study finds that the effects of concerns over Chinese influence relate mainly to increased volatility of stock market indices and government bond yields, and downward pressure on the share prices of individual firms that are heavily exposed to Chinese markets. However, the overall effects appear to be minor or insignificant. The implications of these results are that China's economic coercion (if any) may not be effective, and Australia's responses to Chinese influence and interference (if any) may generate insignificant costs. Finally, this study makes original and significant academic contributions to academia by providing a novel framework for exploring international relations. [ABSTRACT FROM AUTHOR]

Bitcoin is a virtual currency scheme that is characterised by a decentralised network and cryptographic transfer verification. It has attracted much public attention due to its innovative technology and its high currency exchange rate volatility. In this paper, Bitcoin's exchange rate movement from 2011 to 2018 and its relationship with the global financial markets are explored using an EGARCH framework. The results are as follows. First, fundamentals and Bitcoin-related specific events play a critical role in the formation of its exchange rate. Second, the impact on Bitcoin of regulation-related events indicates that market sentiment responds to market regulation statements. Third, news coverage is an essential factor in driving its volatility. Fourth, Bitcoin can be a hedge in times of low uncertainty in global financial markets and can also serve as a safe haven against high economic uncertainty worldwide, but with increasing global financial uncertainty, it is likely to move with the markets and therefore cannot serve as a hedge or safe haven against stock market crashes. Lastly, the positive effect of global expansionary monetary policy on Bitcoin's exchange rate is marginal enough to rule out the involvement of central banks worldwide in the inflation of Bitcoin's exchange rate over the years, as may have been the case with many asset prices after the 2008 US financial crisis. [ABSTRACT FROM AUTHOR]

This paper develops and tests an intertemporal regime-switching asset pricing model characterized by heterogeneous agents that have different expectations about the persistence and volatility of bitcoin prices. The model is estimated using daily bitcoin price data from 2013 until 2020 whereby three types of agents are considered: mean–variance optimizers, speculators and fundamentalists, respectively. While mean–variance optimizers trade on the basis of conditional first and second moments of the return distribution, speculators engage in trend chasing and buy when prices are rising and sell when prices are declining. Fundamentalists trade on the basis of fundamental factors that can impact the value of bitcoin. The fractions of agents engaging in one strategy over another shows statistically substantial variation during high and low bitcoin price volatility regimes. Estimation results reveal the following. First, unlike in traditional asset classes, there is evidence of mean–variance optimizers. Second, there is evidence of speculators who engage in 'bandwagon behavior' and buy bitcoins during price appreciations and sell bitcoins during price declines. Finally, there is evidence of fundamentalists who trade bitcoins when fundamental factors deviate from their long-run trends. Remarkably, these fundamentalists exhibit contrarian-type behaviors during low price volatility regimes while behaving more like fundamental traders during high price volatility regimes. [ABSTRACT FROM AUTHOR]

This study analysed the impact of the volatility of the rupiah exchange rate on four main commodities exported from Indonesia to six member countries of the Organisation of the Islamic Cooperation (OIC) (Saudi Arabia, Malaysia, Pakistan, United Arab Emirates, Turkey, and Bangladesh). The study employed monthly data spanning from January 2007 to December 2019 and the EGARCH method to obtain exchange rate volatility, while the ARDL method was used to model both the short-run and long-run impact of exchange rate and its volatility on exports. In the short term, findings revealed that exchange rate volatility has a significant negative effect on five main commodity exports to OIC countries, whereas, in the long-term, volatility of the exchange rate negatively affects twelve main commodity exports to OIC countries. Our results further imply that most of Indonesia’s exporters to six OIC Member countries are risk-averse.

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Copyright of Boğaziçi Journal: Review of Social, Economic & Administrative Studies is the property of Bogazici University, Faculty of Economics & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Semestre Económico is the property of Sello Editorial de la Universidad de Medellin and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)