Banking sector development and interest rate volatility in emerging economies

Over the last decades, macroeconomic stability is said to be one of the major concerns of emerging economies. Financial sector as a core of macroeconomic stability has been under close consideration of policy makers. The relationship between interest rate uncertainty and banking sector development as one of the most important indicators of financial sector development, especially for emerging economies, has not received enough attention in the literature. Perhaps this article is the most comprehensive study that investigates the relationship between interest rate uncertainty and banking sector development for a large group of emerging economies. To do this, the short-run and long-run models using a bounds testing approach to cointegration for 12 emerging economies over the period 1980–2011 have been developed. Estimated results from all models indicate that interest rate uncertainty has significant effect on banking sector development in both short-run and long-run phenomena in the majority of countries. The findings indicate that the link between interest rate uncertainty and banking sector development in each country depends on each country’s specific structure.     

An investigation of the effects of exchange rate volatility on exports in East Asia

This study investigates the effects of the exchange rate volatility on the export flows of Indonesia, Malaysia, Republic of Korea, Singapore, Thailand, and the Philippines during 1974–2011. Towards this goal a trade weighted real effective (rather than the bilateral) exchange rate and three different measures of volatility, i.e. obtained from an ARCH model, a GARCH model and a moving-average standard deviation measure are used in this study. Specifically, the export flows between six Asian countries and the rest of the world are investigated rather than focusing on trade with only one country. Our findings reveal that the exchange rate volatility has a significant impact on export flows in the short run as well as in the long run for all the countries in the sample. The impact in the long run is predominantly negative with the exception of Singapore, but in the short run the impact varies across countries. Moreover, our results are robust to the alternative measures of volatility used and most of the findings in the long run and short run are also robust to the crisis period.     

Nominal and real volatility as determinants of FDI

This article examines the role of country-specific sources of output and interest rate or exchange rate volatility in driving Foreign Direct Investment (FDI) activities. Building on a dataset with bilateral FDI flows among 24 Organization for Economic Co-operation and Development (OECD) economies over the period 1985–2007, we find that nominal and real volatility strongly deter foreign investments. Output and exchange rate volatility matter in particular for the decision whether to invest in a foreign country in the first place. Interest rate volatility mainly influences the amount of foreign investments.     

Exchange rate volatility and US commodity trade with the rest of the world

Exchange rate volatility is argued to affect the trade flows negatively and positively. Indeed, empirical studies that have addressed the issue have supported both effects. These studies have used aggregate trade flows data either between one country and the rest of the world or between two countries at the bilateral level. Studies that have disaggregated trade data by industry are rare. Thus, we extend the literature by looking at the experiences of 66 American industries that trade with the rest of the world using monthly data. In most cases, trade flows are not affected by GARCH‐based volatility of the real effective exchange rate of the dollar.     

Inflation and inflation volatility in Thailand

Quarterly data for Thailand are used in this article for the period 1965q3–2013q4 to investigate both the relationship between inflation and inflation volatility, and the impact of inflation volatility on economic growth. Inflation volatility is estimated by deploying the generalized autoregressive conditional heteroscedastic (GARCH) technique. A Granger causality test is then conducted to examine the causality between inflation and inflation volatility. The empirical results obtained are consistent with a number of theoretical propositions. First, the results are consistent with the Friedman–Ball proposition, which states that a rise in inflation raises inflation volatility. Second, there is evidence supporting the Holland proposition that inflation volatility lowers the rate of inflation. This is consistent with the view that central banks attempt to stabilize inflation with the rise in inflation volatility. Third, empirical results obtained by asymmetric GARCH models suggest that inflation shocks have an asymmetric impact on inflation volatility (i.e. a positive inflation shock has a larger impact on inflation volatility – as measured by the logarithm of the conditional variance of inflation – than a negative inflation shock). Fourth, inflation volatility has an adverse impact on economic growth. Finally, given the fixed/pegged or managed float exchange rate system, US inflation has been found to have a positive impact on inflation and its volatility in Thailand. This article discusses the implications of empirical findings on the design and enactment of monetary policy for price stability in Thailand.     

Financial market spillovers in transition economies

This paper examines financial market comovements across European transition economies and compares their experience to that of other regions. Correlations in monthly indices of exchange market pressures can partly be explained by direct trade linkages, but not by measures of other fundamentals. Higher-frequency data during three crisis periods reveals the presence of structural breaks in the relationship between exchange-, but not stock markets. While the reaction of markets during the Asian and Czech crises is muted, the pattern of high-frequency spillovers during the Russian crisis looks very similar to that observed in other regions during turbulent times. With greater financial market integration, the financial markets of the more advanced transition economies can be expected to behave more and more like their Asian and Latin American counterparts.     

Impacts of derivative markets on spot market volatility and their persistence

In this article, we investigate the impacts of futures and options markets on the volatility of the underlying market. Unlike earlier studies, the focus is on their persistence over time. Tests on the Hang Seng index yield several interesting results that often contrast with previous findings. Empirical results suggest that the quality of new information generated by derivative trading determines the impacts on the spot market volatility. The futures market provides new, material information reducing spot market volatility. The Options market, on the other hand, generates noisy information and distorts price, which is followed by an increase in volatility and a decrease in its sensitivity to price change. While the impact of futures persists, that of options mostly disappears as the market matures. Our conjecture is that the futures market is mainly driven by informed, experienced participants, while the options market attracts new, inexperienced investors.     

The information content of implied volatility in developed versus developing FX markets

This article predicts the daily movement of monthly foreign exchange (FX) rate volatility using a linear combination of a time-series model and implied volatilities from options. The focus is on analysing the FX volatilities in three developing economies (the Brazilian real (BRL), the Indian rupee (INR) and the Russian ruble (RUB)) against the US dollar (USD). The empirical exercise utilizes two time-series models, mixed data sampling (MIDAS) and GARCH. The analysis indicates that for both developed and developing economies the predictive power of MIDAS and that of GARCH is comparable. Further on in this article, we will ascertain whether the relationship between realized and implied volatility is fundamentally different in the case of developing economies from that among developed economies. Thus, we compare the pairs USD/BRL, USD/INR and USD/RUB against EURO/USD and USD/Japanese yen to determine the information content and predictive power of implied volatilities. Plots of the MIDAS coefficients show that the volatility is more persistent in developing economies than in developed economies.     

Exploring GDP growth volatility spillovers across countries

This study takes a portfolio approach to investigate GDP growth volatility spillovers among 120 countries of the world during the 1960–2017 period. Based on the ratios of growth rate to standard deviation, we rank these countries in pools of high-, midsize-, and low-income growth. Using a spillover index that is based on variance decompositions under a vector autoregressive framework, we analyze the sources of growth volatility dynamics in the world in terms of volatility proportions from and to others. We find that high-income growth countries are net transmitters, while low-income growth countries are net recipients of growth volatility. We also find that it takes several years for low-income growth countries to absorb growth shocks of global nature. Overall, our analyses illustrate the importance of partnership in risk sharing as it is related to portfolio strategies and risk management.     

Altered bank and exchange volatility

This paper examines the behaviour of the Czech crown's exchange rate when pegged to a currency basket. The peg is supposed to limit the overall instability of the currency. The GARCH(1,1) model with a dummy variable for the volatility response is used to account for a change in the width of the fluctuation band. The results of this paper show that volatility of the exchange rate decreased after a much wider fluctuation band was introduced to limit movements of the currency basket index.     

Examining the relationship between stock return volatility and trading volume: new evidence from an emerging economy

Using daily stock return data for individual stocks from an emerging economy, this article examines the relationship between return volatility and trading volume under the theoretical postulate of the mixture of distributions hypothesis. The results suggest that the contemporaneous trading volume as a proxy for latent information arrival to the market did not contribute to the removal of significant ARCH or Generalized Autoregressive Conditional Heteroscedasticity effects that are found in stocks at the first stage of the investigation. The same holds for the lagged volume except for one case. This, perhaps, suggests that the trading volume (contemporaneous or lagged) is not adequately conveying information to induce traders’ views of the desirability of trade and, therefore, points to the need for searching for other micro and macro variables to be used as potential proxy for information arrival to the stock market of the emerging economy.     

Long memory in the volatility of China stock returns

In this paper, we empirically examine the volatility process of China's stock market returns using daily and weekly Shanghai and Shenzhen stock indices during January 1990 to August 2008. To investigate the property of the process, we used the FIGARCH (fractionally integrated GARCH) model including GARCH and IGARCH processes as special cases. Since the FIGARCH model allows fractional integration order, it can detect hyperbolically decaying volatility processes which cannot be explained by previous models with integer integration order. Our results show that the Shanghai and Shenzhen stock indices exhibit long-term dependencies. The long memory properties of the Shanghai and Shenzhen stock markets do not seem to be spuriously induced without exception.     

Regulatory reform in telecommunications in Central and Eastern Europe

In this paper we discuss public policy towards the telecommunications sector in Central and Eastern Europe (CEE), focusing primarily on the need to ensure adequate capital investment. The analysis falls into two main parts: the regulation of monopoly, and policy on liberalization. Concerning regulation, we discuss how policy credibility is likely to be a problem in the region, and how reputational considerations, the design of regulatory institutions, and methods of price control can help to ameliorate this problem. Concerning liberalization, we consider the effects of potential competition on investment incentives, and construct a simple model to analyse the different effects of liberalization and regulatory risk on investment. Some preliminary policy conclusions are drawn, and we argue that in the CEE region – in contrast to more well developed countries – a reasonable case can be made for allowing a temporary period of monopoly for basic services.     

Calibration of implied volatility for the exchange rate for the Chinese Yuan from its derivatives

Revised implied volatility curves and surfaces for the Chinese Yuan (CNY) exchange rate are obtained from market quotations for CNY non-deliverable options by solving an inverse problem of foreign exchange option pricing, which is calculated using a regularization approach in an optimal control framework. To take account of the market expectation for the CNY exchange rate, a stochastic adjusted factor is applied that follows a Vasicek model with parameters fitted from market quotations for CNY non-deliverable forwards. A well-posed numerical scheme is implemented.     

Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong Stock Connect

This study investigates the impact of the recently introduced Shanghai-Hong Kong Stock Connect. Using high frequency data and dynamic forecasting techniques, we find that the new Stock Connect does contribute to the increasing importance of the Chinese mainland stock market and economic activity. A weak and unstable cointegration relationship is found after this event. Additionally, the Stock Connect has also increased the conditional variance of both stock markets. We observe a leading role of the Shanghai stock market to the Hong Kong stock market in terms of both mean and volatility spillover effects after the Stock Connect. Our study indicates that the opening up of stock markets in China could enhance the leading power, influence the risk level and improve the market efficiency of the Chinese mainland stock market, since the volatility spillover effect from Shanghai to Hong Kong is strengthened. Besides, our results have important policy implications, especially on how policy makers should deal with the increased market interconnectedness and for portfolio managers in choosing potential hedging instruments. The success of Shanghai-Hong Kong Stock Connect provides valuable operational experience for the forthcoming Shenzhen-Hong Kong Stock Connect which could further improve the market efficiency in China.     

Modelling the dynamics of Bitcoin and Litecoin: GARCH versus stochastic volatility models

We examine and compare a large number of generalized autoregressive conditional heteroskedastic (GARCH) and stochastic volatility (SV) models using series of Bitcoin and Litecoin price returns to assess the model fit for dynamics of these cryptocurrency price returns series. The various models examined include the standard GARCH(1,1) and SV with an AR(1) log-volatility process, as well as more flexible models with jumps, volatility in mean, leverage effects, t-distributed and moving average innovations. We report that the best model for Bitcoin is SV-t while it is GARCH-t for Litecoin. Overall, the t-class of models performs better than other classes for both cryptocurrencies. For Bitcoin, the SV models consistently outperform the GARCH models and the same holds true for Litecoin in most cases. Finally, the comparison of GARCH models with GARCH-GJR models reveals that the leverage effect is not significant for cryptocurrencies, suggesting that these do not behave like stock prices.     

基于GARCH模型族的上海房价分析

本文以房价历史信息、利率、汇率作为自变量来分析1995年11月至2006年9月上海房价的变化,并采用GARCH模型族来分析上海房价的波动性。计量结果表明：房价历史信息能部分解释当期房价的变化;利率对房价具有显著的负影响;汇率对房价的影响为正;房价变化存在不对称效应,降息对房价的冲击大于加息引起的冲击。宏观调控政策效果分析结果显示：2005年3月—2005年5月出台的宏观调控政策在短期内对上海房价的上涨有抑制作用。     

S&P 500 volatility,volatility regimes,and economic uncertainty

We assess the relationship between regime-dependent volatility in S&P 500, economic policy uncertainty, the S&P 500 bull and bear sentiment spread (bb_sp), as well as the Chicago Board Options Exchange's VIX over the period 2000–2018. Our findings from two-covariate GARCH–MIDAS (GM) methodology, regime switching Markov Chain, and quantile regressions suggest that the association of realized volatility and sentiment varies across high- and low-volatility regimes and depends on investors’ sensitivity toward incidents of market uncertainties under these regimes. The findings suggest that these indicators may not be useful in volatility forecasting, especially under high-volatility regimes.     

Asymmetric volatility spillovers between the U.K. regional worker flows and vacancies

This article investigates volatility spillovers between the U.K. regional job finding, job separation and vacancy rates. Employing a large Bayesian logistic smooth transition vector autoregression model, we find high volatility spillovers between the U.K. regional labour markets. Analyses of net spillovers show that, in general, shocks to job separation rates tend to spread into job finding and vacancy rates, while vacancy rates are usually at the receiving end of shocks transmitted from the job separations and job findings. To shed further light on the shock propagation mechanism, we also look into more detailed matters such as the differences in spillovers between regions within the same regime, and that of the same region but in different regimes.     

Volatility spillovers to the emerging financial markets during taper talk and actual tapering

On 22 May 2013, Fed chairman, Ben Bernanke surprised markets by indicating to the media that the US Fed may taper its quantitative easing programme. This set out financial volatility across the globe over the next several months that spilled over to the financial markets of emerging market economies (EMEs). It prompted many EME central banks to take varied policy actions. Looking into this widely known event, this article presents formal empirical evidence establishing that (i) conditional volatility during taper talk exceeded that during actual tapering and (ii) volatility spillovers took place ‘contemporaneously’ from the US markets to the key EMEs during this period. The results suggest importance of careful communications by advanced economy central banks and the possibility of establishing ‘rules of the monetary game’. They also suggest that in the absence of international policy coordination to contain spillovers, EME central banks should build adequate buffers and reinforce financial stability ahead of the reversal of the global interest rate cycle.