Intraday periodicity, calendar and announcement effects in Euro exchange rate volatility

This paper provides an analysis of intraday volatility using 5-min returns for Euro-Dollar, Euro-Sterling and Euro-Yen exchange rates, and therefore a new market setting. This includes a comparison of the performance of the Fourier flexible form (FFF) intraday volatility filter with an alternative cubic spline approach in the modelling of high frequency exchange rate volatility. Analysis of various potential calendar effects and seasonal chronological changes reveals that although such effects cause deviations from the average intraday volatility pattern, these intraday timing effects are in many cases only marginally statistically significant and are insignificant in economic terms. Results for the cubic spline approach imply that significant macroeconomic announcement effects are larger and far more quickly absorbed into exchange rates than is suggested by the FFF model, and underscores the advantage of the cubic spline in permitting the periodicity in intraday volatility to be more closely identified. Further analysis of macroeconomic announcement effects on volatility by country of origin (including the US, Eurozone, UK, Germany, France and Japan) reveals that the predominant reactions occur in response to US macroeconomic news, but that Eurozone, German and UK announcements also cause significant volatility reactions. Furthermore, Eurozone announcements are found to impact significantly upon volatility in the pre-announcement period.     

Intraday volatility and periodicity in the Malaysian stock returns

Many empirical studies using high-frequency intraday data from a variety of markets indicate that PGARCH models give superior return volatility forecasts than those produced from standard GARCH models. This paper investigates into modelling approaches of four versions of PGARCH models of high-frequency data of Bursa Malaysia, in particular where the intraday volatility of double U-shaped pattern. It is examined through half-hourly dummy variables, quarterly-hourly dummy variables, Fourier Functional Form (FFF) based variables and spline-based variables. The non-periodic GARCH models, i.e., GARCH, EGARCH and TARCH are used for comparison of performance of best fit. The analysis show that among the four versions of PGARCH models, the half-dummy and the spline-based versions perform the best. EGARCH produced consistently superior results to other GARCH specifications.     

Intraday jumps and US macroeconomic news announcements

This paper applies recent non-parametric intraday jump detection procedures to investigate the presence and importance of intraday jumps in US futures markets. More importantly, the paper investigates the extent to which statistically significant intraday jumps are associated with US macroeconomic news announcements. Jumps are prevalent, large and contribute heavily to total daily price variation. Approximately one third of jumps correspond to US macroeconomic news announcements, with pure announcement effects causing large increases in the absolute sizes of jumps and the informational surprise of the announcement explaining large proportions of the jumps. The statistical and economic significance of news-related jumps is confirmed by results that show higher volatility persistence, predictability of lower frequency returns, larger effects on microstructure variables, jump clustering and co-jumps from these jumps versus non-news-related jumps, although there are some interesting variations across asset classes.     

Spanish Treasury bond market liquidity and volatility pre- and post-European Monetary Union

Spain enacted a number of important debt management initiatives in 1997 to prepare its Treasury bond market for European Monetary Union. We interpret the impacts of these changes through shifts in a bond liquidity “life cycle” function. Furthermore, we highlight the importance of expected average future liquidity in explaining Spanish bond liquidity premiums. We also uncover pricing biases that support the Spanish Treasury’s tactical decision to target high-coupon, premium bonds in its pre-EMU debt exchanges. Finally, we show that EMU has been associated with both a decrease in bond yield volatility and an increase in pricing efficiency.     

Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation

We study two methods of adjusting for intraday periodicity of high-frequency financial data: the well-known Duration Adjustment (DA) method and the recently proposed Time Transformation (TT) method (Wu (2012)). We examine the effects of these adjustments on the estimation of intraday volatility using the Autoregressive Conditional Duration-Integrated Conditional Variance (ACD-ICV) method of Tse and Yang (2012). We find that daily volatility estimates are not sensitive to intraday periodicity adjustment. However, intraday volatility is found to have a weaker U-shaped volatility smile and a biased trough if intraday periodicity adjustment is not applied. In addition, adjustment taking account of trades with zero duration (multiple trades at the same time stamp) results in deeper intraday volatility smile.     

Intraday and interday volatility in the Japanese stock market

This paper characterizes the volatility in the Japanese stock market based on a 4-year sample of 5-min Nikkei 225 returns from 1994 through 1997. The intradaily volatility exhibits a doubly U-shaped pattern associated with the opening and closing of the separate morning and afternoon trading sessions on the Tokyo Stock Exchange. This feature is consistent with market microstructure theories that emphasize the role of private and asymmetric information in the price formation process. Meanwhile, readily identifiable Japanese macroeconomic news announcements explain little of the day-to-day variation in the volatility, confirming previous findings for US equity markets. Furthermore, by appropriately filtering out the strong intradaily periodic pattern, the high-frequency returns reveal the existence of important long-memory interdaily volatility dependencies. This supports recent results stressing the importance of exploiting high-frequency intraday asset prices in the study of long-run volatility properties of asset returns.     

Exchange rate volatility,macroeconomic announcements and the choice of intraday periodicity filtering method

Filtering out the intraday periodicity of volatility is crucial for using high frequency data in econometric analysis. This paper studies the effects of filtering on statistical inference as regards the impact of news on exchange rate volatility. The properties of different methods are studied using a five-minute frequency EUR/USD data set and simulated returns. The simulation results suggest that all the methods tend to produce downward-biased estimates of news coefficients, some more biased than others. The study supports the Flexible Fourier Form method as the best for seasonality filtering.     

Information shares in the US Treasury market

This paper highlights the previously neglected role of the futures markets in US Treasury price discovery. The estimates of 5- and 10-year GovPX spot market information shares typically fail to reach 50% from 1999 on. The GovPX information shares for the 2-year contract are higher than those of the 5- and 10-year maturities but also decline after 1998. Relative bid-ask spreads, number of trades, and realized volatility are statistically significant and explain up to 21% of daily information shares. In roughly 1/4 of cases when public information is released, the futures market gains information share, but macroeconomic announcements rarely explain information shares independently of liquidity.     

Intraday asymmetric liquidity and asymmetric volatility in FTSE-100 futures market

In this study, we use both quote and trade data for the FTSE-100 futures for 2001–2004 in order to examine asymmetric volatility in the context of extreme sells. We define extreme sells as ask quotes that involve large percentages of total depth, selling orders executed at prices much closer to bids than to asking prices, and consecutive sell-initiated trades. Sell trades tend to demand higher liquidity than buys, while extreme trading conditions demand more liquidity than non-extreme ones. In extreme sells, liquidity demand surpasses supply. We show that asymmetric liquidity (quote demand vs. supply) better explains the asymmetric volatility observed in high-frequency data than trade information does. Ask-depth share plays a dominant role in asymmetric volatility, while order flow (sell-initiated volume share) makes a far smaller contribution.     

Information transmission and causality in the Italian Treasury bond market

We examine causality and efficiency in the Italian T-bond market, where cash trades take place on the domestic Mercato Telematico dei Titoli di Stato, while futures trading is based on the London International Financial Futures Exchange. We find evidence that causality in prices runs in both directions, and that the cash lead is almost comparable in size and extension to the futures lead. We then try to assess whether the cash market is weak-form efficient with respect to LIFFE prices. Using a simple trading rule with a variety of time and price filters, we conclude that the observed lead cannot be exploited to make a profit after transaction costs.     

Stochastic volatility,power laws and long memory

Benoit B Mandelbrot comments on the paper by Blake LeBaron, on page 621 of this issue, by tracing the merits and pitfalls of power-law scaling models from antiquity to the present.     

US macroeconomic surprises and the emerging-market sovereign CDS market

Our primary aim is to examine whether US macroeconomic surprises affect the slope of the term structure of ‘sovereign credit default swap’ (SCDS) spreads in emerging markets. Our empirical results show that positive (negative) US macroeconomic surprises are likely to reduce (increase) the term structure slope of SCDS spreads in emerging countries. We find that the slope values in emerging markets are positively related to future market returns over 1- and 2-day horizons. Our results provide general support for the future informational role played by SCDS spreads for the national stock market within emerging markets.     

Bank size, market concentration, and bank earnings volatility in the US

We examine whether bank earnings volatility depends on bank size and the degree of concentration in the banking sector. Using quarterly data for non-investment banks in the United States for the period 2004Q1-2009Q4 and controlling for the quality of management, leverage, and diversification, we find that bank size reduces return volatility. The negative impact of bank size on bank earnings volatility decreases (in absolute terms) with market concentration. We also find that larger banks located in concentrated markets have experienced higher volatility during the recent financial crisis.     

Dealer behavior in the specials market for US Treasury securities

We assess dealer behavior in the specials market for US Treasury securities by comparing dealer participation in the Federal Reserve's securities loan auctions with prices in the private market. Dealer behavior is generally consistent with the law of one price and apparent violations can largely be explained by institutional differences between the private market and the Fed's program. However, for auctions that are effectively noncompetitive, dealers regularly pass up true arbitrage opportunities and frequently overpay to borrow securities. Dealers apparently do not realize that certain auctions are noncompetitive, even though the information needed to discern this fact is publicly available in advance.     

Cojumping: Evidence from the US Treasury bond and futures markets

The basis between spot and future prices will be affected by jump behavior in each asset price, challenging intraday hedging strategies. Using formal cojumping tests this paper considers the cojumping behavior of spot and futures prices in high frequency US Treasury data. Cojumping occurs most frequently at shorter maturities and higher sampling frequencies. We find that the probability of cojumping is altered by the presence of an anticipated macroeconomic news announcement. The probability of cojumping is particularly affected by news surprises in non-farm payrolls, CPI, GDP and retail sales. However, the two cojumping tests are also more likely to provide contradictory results in the presence of surprises in non-farm payrolls. On these occasions the market does not clearly signal its short term pricing behavior.     

The pricing of volatility risk in the US equity market

We analyze whether the pricing of volatility risk depends on the asset pricing framework applied in the tests, the specified volatility proxies, and the portfolio sorts used for spanning the asset universe. For this purpose, we compare the results using a macroeconomic and fundamental based asset pricing model using three proxies of volatility and uncertainty, using size/value sorted and industry sector portfolios. Our results reveal that the marginal pricing effect of the VIX volatility factor is strong and statistically significant throughout the models and specifications, while the effect of an EGARCH-based volatility factor is mixed, mostly smaller but with the correct sign. In most cases, the EGARCH factor does not impair the pricing effect of the VIX. The portfolio sorts have a substantial impact on the volatility premiums in both model frameworks. The size of the volatility risk premium is more uniform across the models if the industry sector portfolio sort is used. Finally, the size/value portfolio sort generates larger volatility risk premiums for both models.     

Oil price shocks and volatility spillovers in the Nigerian sovereign bond market

This paper investigates volatility spillover in the Nigerian sovereign bond market arising from oil price shocks, using Vector Autoregressive Moving Average ‐ Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (VARMA‐AGARCH) model. The paper covers the period March 22, 2011 to April 14, 2016 and makes use of the daily data of the Nigerian Sovereign Bond, Brent oil and West Texas Intermediate (WTI), respectively. We endogenously and sequentially detect structural break points using the test of Bai and Perron (2003) framework. In order to accurately estimate the model, we modify it by incorporating the break points into the VARMA‐AGARCH model, a process which if ignored would lead to model misspecification. The results obtained demonstrate a significant cross‐market volatility transmission between oil and sovereign bond market with ample sensitivity to structural breaks. The study also computes optimum weight portfolio and hedge ratio both with and without structural breaks and results equally indicate sensitivity to structural breaks.     

U.S. and Japanese macroeconomic news and stock market volatility in Asia-Pacific

I use a new comprehensive dataset to analyze the impact of ten U.S. and six Japanese macroeconomic announcements on stock market volatility in Japan, Hong Kong, South-Korea and Australia. A GARCH model that allows for multiplicative announcement effects and asymmetries is employed. Overnight conditional variances are significantly higher on announcement days and significantly lower on days before and after announcements, especially for U.S. news. The impact of announcements on implied volatilities, in contrast, is much weaker. Out-of-sample trading strategies that systematically buy delta-neutral straddles on announcement days generate statistically significant profits, but these disappear after transaction costs are taken into account.     

The US financial crisis,market volatility,credit risk and stock returns in the Americas

We employ the multivariate DCC-GARCH model to identify contagion from the USA to the largest developed and emerging markets in the Americas during the US financial crisis. We analyze the dynamic conditional correlations between stock market returns, changes in the general economy’s credit risk represented by the TED spread, and changes in the US market volatility represented by the CBOE Volatility Index^® (VIX). Our sample includes daily closing prices from January 1, 2002 to December 31, 2015, for the USA and stock markets in Argentina, Brazil, Canada, Chile, Colombia, Mexico, and Peru. We first identify that increases in VIX have a negative intertemporal and contemporaneous relationship with most of the stock returns, and these relationships increase significantly during the US financial crisis. We then find evidence of significant increases in contemporaneous conditional correlations between changes in the TED spread and stock returns. Increases in conditional correlations during the financial crisis are associated with financial contagion from the USA to the Americas. Our findings have policy implications and are of interest to practitioners since they illustrate that during periods of financial distress, US stock volatility and weakening credit market conditions could promote financial contagion to the Americas.