Exchange Market Volatility Research Articles

A Note on the Premiums and Discounts Embedded in VIX Futures Prices

This article illustrates the volatile nature of the premiums and discounts embedded in the prices of VIX (Chicago Board Options Exchange Market Volatility Index) futures contracts. The fact that the underlying VIX index cannot be traded leads VIX futures to be priced more on expectations of market participants than on a typical cost-of-carry relationship. As they near expiration, VIX futures, in the aggregate, tend to trade at an increased premium, when trading in contango, and at an increased discount, when trading in backwardation. In addition, the premium in these contracts tends to peak as the VIX index nears a low, and the discount in the contracts tends to bottom as the index nears a high.

Exchange Traded Funds and Market Volatility: The Case of S&P 500

This study investigates the relationship between the volatility of stock market indexes and the trading volumes of their Exchange Traded Funds (ETFs). Using both OLS and GARCH approaches we demonstrate that the contemporaneous trading volume of S&P 500 ETFs is a key determinant of S&P 500 volatility at both monthly and daily frequencies. Vector autoregressive estimation on the other hand suggests a two-way Granger causality between S&P 500 volatility and the trading of S&P 500 ETFs. A replication analysis of other market indexes and the corresponding ETFs tracking these indexes confirms that these findings are robust.

Has Quantitative Easing Affected the U.S. Treasury Auction Market?

A dataset of every U.S. Treasury auction from 2003 to 2012 investigates how Federal Reserve policy of quantitative easing (QE) affects the high-yield at Treasury auctions. Market structural factors known in advance (Federal funds rate, Standard and Poor’s, Chicago Board Option Exchange Market Volatility Index) are significant for the auction high-yield, but the relationships change with QE. The Federal-funds rate is less correlated to bills high-yield during QE. Before QE, equity market and risk channels have the same relationship to bond and bill high-yields. During QE, correlations tighten for bond high-yields, but drop dramatically for bills. Auction-specific bid-cover is more strongly negatively associated with bills high-yield during QE. indirect bidders (a proxy for foreign central banks) may put relatively more downward pressure on bond high-yields. The changes in these correlations could affect borrowing costs and Fed balance sheet exposure going forward.

Uncertainty, market structure, and liquidity

In this study we show that market uncertainty [measured by the Chicago Board Options Exchange Market Volatility Index (VIX)] exerts a large market-wide impact on liquidity, which gives rise to co-movements in individual asset liquidity. The effect of VIX on stock liquidity is greater than the combined effects of all other common determinants of stock liquidity. We show that the uncertainty elasticity of liquidity (UEL: percent change in liquidity given a 1% change in VIX) has increased around regulatory changes in the US markets that increased the role of public traders in liquidity provision, reduced the minimum allowable price variation, weakened the affirmative obligation of NASDAQ dealers, and abolished the specialist system on the NYSE.

The effectiveness of the combined use of VIX and Support Vector Machines on the prediction of S&P 500

The aim of this research is to analyse the effectiveness of the Chicago Board Options Exchange Market Volatility Index (VIX) when used with Support Vector Machines (SVMs) in order to forecast the weekly change in the S&P 500 index. The data provided cover the period between 3 January 2000 and 30 December 2011. A trading simulation is implemented so that statistical efficiency is complemented by measures of economic performance. The inputs retained are traditional technical trading rules commonly used in the analysis of equity markets such as Relative Strength Index, Moving Average Convergence Divergence, VIX and the daily return of the S&P 500. The SVM identifies the best situations in which to buy or sell in the market. The two outputs of the SVM are the movement of the market and the degree of set membership. The obtained results show that SVM using VIX produce better results than the Buy and Hold strategy or SVM without VIX. The influence of VIX in the trading system is particularly significant when bearish periods appear. Moreover, the SVM allows the reduction in the Maximum Drawdown and the annualised standard deviation.

Determinants of stock market comovements among US and emerging economies during the US financial crisis

By analyzing the dynamic conditional correlations (DCC) of the daily stock returns of 10 emerging economies in comparison with those of the US for the period of 2006–2010, we find different patterns of crisis spillover among 10 emerging economies. While a group of countries has three distinctive phases of crisis spillover (contagion, herding, and post-crisis adjustment), other groups show different phases of crisis spillover. It is also shown that increases in CDS spread and TED spread decrease conditional correlations while increases in foreign institutional investment, exchange market volatility, and the VIX index of the S&P 500 increase conditional correlations.

Transmission of Financial Stress Under Regime-Switching: Evidence from a MENA Country

A general consensus among studies focusing on the transmission of crises from advanced economies to emerging markets indicates that the extent of pass-through of financial stress is linked to the depth of financial linkages between advanced and emerging economies. Using the Financial Stress Index (FSI) database developed by Balakrishnan et al (2009), the present paper attempts to investigate the financial transmission from a particular advanced economy, namely the USA, to an emerging economy from MENA region, namely Egypt. The investigation of particular interactions between a single advanced economy’s financial component variables and the FSI of emerging economy within a regime-switching framework constitutes the major feature of this study that distinguish it from earlier works. Rather than ascribing the intensity of the index to some pre-set zero-one type of classification, the Markov switching approach allows the flexibility of an endogenously defined, thus data-dependent intensity. Monthly observations covering 2001.7-2009.10 periods are utilized in this study. Preliminary findings indicates that linearity of FSI series can be rejected in favor of the 2-regime Markov Switching framework. Among explanatory variables, the TED spread defined as the difference between US interbank rates and the yield on Treasury bills, the U.S stock market returns, U.S stock market volatility have all been found influential in driving up the Egyptian FSI. On the other hand, foreign exchange market volatility defined as month of month growth rate of USD turned out to be insignificant.

Hedging Against Unexpected Changes and Tail Risks in the Foreign Exchange Market Volatility

In this study, we propose a new approach to forecast exchange rate movements on a panel of two exchange rates quite vulnerable to financial contagion, the Brazilian Real and the Russian Ruble vis-a-vis the US Dollar. We investigate interrelationships during periods of excess volatility and reverse conditions across a range of asset classes, capturing symmetric and asymmetric tail dependences. Using the Joe-Clayton (SJC) copula we attain upper and lower tail dependences with symmetric relations during periods of increased volatility and asymmetric dependencies for the rest of the time period. Particularly, an aggressive increase in the Volatility Index and the stock market index lead to accelerated increases in the volatility levels in the foreign exchange market. Moreover, we observe positive relationships when a prompt increase in the S&P Goldman Sachs commodity index volatility provokes accelerated increases in the foreign exchange market volatility. Consequently, shocks in the foreign exchange market can be anticipated when risk managers and corporations adjust their risk levels accordingly, while asset managers and investors modify their strategic asset allocation considering spikes in volatility levels from these asset classes. JEL Classification: C53, C58, G11, G17.

Carry Trade and Liquidity Risk: Evidence from forward and Cross-Currency Swap Markets

This study empirically examines the effect of foreign exchange (FX) market liquidity risk and volatility on the excess returns of currency carry trades. In contrast to the existent literature, we construct an alternative proxy of liquidity risk - violations of no arbitrage bounds in the forward and currency swap markets. We also use volatility smile data to capture FX-market specific volatility. The sample data cover periods both before and after the Global Financial Crisis (GFC). Both proxies are significant in explaining the abnormal returns of carry trades, particularly after the GFC. Our findings provide substantial evidence that uncovered interest parity (UIP) puzzle can be resolved after controlling for liquidity risk and market volatility.

The relationship between stock market volatility and macroeconomic volatility: Evidence from Pakistan

This study is based on examining the relationship between stock exchange market volatility and macroeconomic variables volatility with respect to Pakistan. To measure this time series relationship for Pakistan exponential generalized autoregressive conditional heteroskedasticity (EGARCH) and lag-augmented vector autoregression (LA-VAR) models were used. It was found that there is a positive relationship of consumer price index (CPI) and foreign direct investment (FDI) with stock market; however, exchange rate (ER) and T-bill rate (TBR) are inversely related to stock market volatility. On the other hand, we found strong evidence that there is a bilateral relationship of FDI and ER with stock prices, while a unidirectional relationship was found between TBR and stock market prices, with the direction from stock prices to treasury bills interest rate. However, a significant causal relationship not found between CPI and stock prices. The analysis of this study reveals that the stock market of Pakistan is relatively less efficient as compared to US and other developed economies of the world. Key words: Pakistan, macroeconomic volatility, stock market volatility, exponential generalized autoregressive conditional heteroskedasticity (EGARCH), lag-augmented vector autoregression (LA-VAR) model.

Intertemporal relations between the market volatility index and stock index returns

We examine the intertemporal relationships between Chicago Board Options Exchange (CBOE) market volatility index (VIX) and returns of the S&P 100, 500 and 600 indexes among three subperiods during 1992–2011 to account for structural shifts in VIX and to investigate if the role of VIX as an investor fear gauge and indicator of portfolio insurance price has strengthened in periods of high market anxiety and turbulence. We find a strong negative contemporaneous relation between daily changes (innovations) in VIX and S&P 100, 500 and 600 returns. Our results suggest that the strength of contemporaneous VIX-returns relation depends on the mean and volatility regime of VIX, and that this relation is much stronger when VIX is both high and more volatile. In fact, during 2004–2011, the negative contemporaneous VIX-returns relation was the most dominating and the only significant relation. Our results also indicate a strong asymmetric relation between daily stock market returns and innovations in VIX, suggesting t...

Empirical Comparison of Alternative Implied Volatility Measures of the Forecasting Performance of Future Volatility*

Implied volatility from the Black and Scholes (Journal of Political Economy 81, 1973, p. 637) model has been empirically analyzed for the forecasting performance of future volatility and is well known to be biased. Based on the belief that implied volatility from option prices can best estimate future volatility, this study identifies the best way to derive implied volatility to overcome the forecast bias associated with the Black–Scholes model. For this, the following three models are considered: Heston’s model, which best addresses the problems associated with the Black–Scholes model for pricing and hedging options; Britten-Jones and Neuberger’s model-free implied volatility (MFIV), which eliminates the model-oriented bias; and VKOSPI, the Korean version of the Chicago Board Options Exchange Market Volatility Index. This study conducts a comparative analysis of implied volatilities from the Black–Scholes model, Heston’s model, the MFIV, and VKOSPI for their abilities to forecast future volatility. The results of the empirical analysis of the KOSPI 200 options market indicate that Heston’s model can eliminate most of the bias associated with the Black–Scholes model, whereas the MFIV and VKOSPI do not show any improvement in terms of forecasting performance.

The Relationship between Stock Market Volatility and Macroeconomic Volatility: Evidence from Pakistan

This study is based on examining the relationship between stock exchange market volatility and macroeconomic variables volatility with respect to Pakistan. To measure this time series relationship for Pakistan Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) and lag-augmented VAR (LA-VAR) models were used. It was found that there is a positive relationship of CPI and FDI with stock market; however ER and TBR are inversely related to sock market volatility. On the other hand we found strong evidence that there is a bilateral relationship of FDI and ER with stock prices, while a unidirectional relationship found between TBR and stock market prices, with the direction from stock prices to treasury bills interest rate. However a significant causal relationship not found between CPI and stock prices. The analysis of this study reveals that the stock market of Pakistan is relatively less efficient as compared to U.S and other developed economies of the world.

Improvement of the VaR Method for Foreign Exchange Risk Measurement Based on Macro Information Released

This paper, based on GARCH model, investigates the impact towards foreign exchange market of 13 kinds of macroeconomic information, and finds the released information of Sino-American monetary and retail trade has the biggest influence on foreign exchange market. As Chinese monetary policy, investment and consumer information, as well as American monetary policy and real estate information have been released, the market appears abnormal return rate; after Chinese currency and consumer information as well as American trade and consumer information have been released, the foreign exchange market volatility aggravates and continues. This paper attempts to use the GARCH model with macro information based on the VaR method to measure foreign exchange risk renewedly. Finally we find adding macro information into the model could increase the information of estimation which would improve the VaR measurement results.

MODELLING SOUTH AFRICAN CURRENCY CRISES AS STRUCTURAL CHANGES IN THE VOLATILITY OF THE RAND

AbstractThis study tests the theory that currency crises are associated with sudden large changes in the structure of foreign exchange market volatility. Due to increases in market uncertainty, crisis periods exhibit abnormally high levels of volatility. By studying short‐term changes in volatility dynamics, it is possible to identify the start and end dates of crisis periods with a high degree of precision. We use the iterative cumulative sum of squares algorithm to detect multiple shifts in the volatility of rand returns between January 1994 and March 2009. Dummy variables controlling for the detected shifts in variance are incorporated in a generalised autoregressive conditional heteroscedasticity modelling framework. The analysis indicates that previously identified crisis periods in the rand coincide with significant structural changes in market volatility.

Volatility Spillover Between the Stock Market and the Foreign Exchange Market in Pakistan

Our paper examines the volatility spillover between the stock market and the foreign exchange market in Pakistan. For long run relationship we use Engle Granger two step procedure and the volatility spillover is modelled through bivariate EGARCH method. The estimated results from cointegration analysis show that there is no long run relationship between the two markets. The results from the volatility modelling show that the behaviour of both the stock exchange and the foreign exchange markets are interlinked. The returns of one market are affected by the volatility of other market. Particularly the returns of the stock market are sensitive to the returns as well as the volatility of foreign exchange market. On the other hand returns in the foreign exchange market are mean reverting and they are affected by the volatility of stock market returns. There is strong relationship between the volatility of foreign exchange market and the volatility of returns in stock market.

Day of the week effect on foreign exchange market volatility: Evidence from Turkey

This paper assesses the day of the week effect of the daily depreciation of the Turkish lira (TL) against the US dollar (USD) and its volatility. The empirical evidence from Turkey presented here suggests that Thursdays are associated with higher and Mondays with lower depreciation rates compared to those of Wednesdays. Moreover, Mondays and Tuesdays are associated with higher volatility than Wednesdays.

Intraday volatility in the Taipei FX market

This paper characterizes the volatility in the Taipei foreign exchange (FX) market based on a 4-year sample of 15-minute NTD (New Taiwan dollar)/USD exchange rates from 1996 through 1999. To identify the pattern of intraday volatility in NTD/USD exchange rate changes, the impacts of scheduled macroeconomic news releases in Taiwan and the U.S. are considered. In this paper, the periodic GARCH (P-GARCH) model and the dummy variable approach are combined together to capture the more complicated periodic structure of the intraday volatility in the NTD/USD exchange rate changes. The estimation results suggest that the doubly U-shaped pattern in the Taipei FX market, associated with separate morning and afternoon sessions due to a 2-hour lunch break, can only be partly explained by the scheduled news announcements.

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Korean Abstract: 실현변동성(realized volatility)은 모형에 의존하지 않고 측정되며 관찰이 가능하다는 장점을 가진 변동성의 개념이다. 본 연구에서는 2분 간격으로 관찰되는 고빈도 자료를 이용하여 원/달러, 엔/달러, 유로/달러 환율의 실현변동성을 측정하고, 그 통계적 특성을 비교 분석하였다. 첫째, 다른 통화들과 마찬가지로 원/달러 환율의 실현변동성은 정규분포를 따르지 않으나, 로그를 취하면 정규분포의 형태로 접근하는 것으로 나타났다. 둘째, 평균적인 실현변동성에 있어서는 원/달러가 다른 두 국제통화에 비해 낮은 수준이지만, 그 변화폭은 실현변동성의 정의에 따라 다르게 나타났다. 셋째, 세 환율의 실현변동성은 양의 상관관계를 갖는 것으로 분석되었다. 넷째, 실현변동성은 장기기억(long memory) 특성을 갖는 것으로 보이는데, 다른 두 통화에 비해 외생적 충격의 효과가 오래 지속되는 것으로 분석되었다. English Abstract: China's Special Economic Zones (SEZs) have been entering a new development stage after China's entry into WTO. China has been developing ‘China's economic development model’, in which SEZs have ideally been combined with FDIs. China's SEZs concentrated in the east coastal region geographically, specialized in secondary industry, and put in practice many important favourable policies. China's SEZs also play an important role in regional development with the growth pole. At the time of entering the WTO, China's SEZs have been faced with new changes. This paper analyses this new change in China's SEZs, and considers the effect to Korea in the view of policy. In the past ten years, Korea has acquired a better development in the field of economic cooperation. The industrial structure of the two countries has become more and more closed. Especially, the FDI cooperation of the past ten years mostly concentrated on China's SEZs. From the view of country's spatial division, Korea needs to adjust FDI its strategy more diversely in investment regions and industries, and it needs more joint cooperation.

Foreign exchange market volatility in EU accession countries in the run-up to Euro adoption: weathering uncharted waters

The paper analyzes foreign exchange market volatility in four Central European EU accession countries in 2001–2003. By using a Markov regime-switching model, it identifies two regimes representing high- and low-volatility periods. The estimation results show not only that volatilities are different between the two regimes, but also that some of the cross-correlations differ. Notably, cross-correlations increase substantially for two pairs of currencies (the Hungarian forint–Polish zloty and the Czech koruna–Slovak koruna) in the high-volatility period. The paper concludes by discussing the policy implications of these findings.