نوسانات نرخ ارز روزانه: اخبار و اثرات فصلی

This paper examines how the calendar seasonality in terms of intraday New Taiwan dollar/U.S. dollar (NTD/USD) exchange rate volatility is impacted by public news arrivals and the unexpected volume shocks. Incorporating counts of Taiwan and the U.S news releases, unexpected volume of trading, and explicit time-of-day seasonality into the framework of GARCH model, we find that the pronounced periodicity of intraday volatility can be partly captured by the augmented model, whereas the spikes of volatility at the market closing and at the opening of the afternoon trading session are not successfully explained by time-of-day factors, public news, unexpected volume of trading, and lagged squared return innovations.

The market volatility is related to information releases (Ross, 1989). The use of high-frequency intraday data allows us to examine the link between the variation of intraday volatility and information arrivals during a day. However, to interpret the impact of intraday information arrivals on the volatility, we have to adjust for intraday volatility seasonality to avoid compounded results. The seasonality of volatility has been found in intradaily and intraweekly returns in the foreign exchange (FX) markets, stock markets, and other exchange traded instruments. A typically U-shaped pattern is often observed in intraday volatility,1 even a doubly U-shaped pattern is found in exchanges where the daily trading schemes are interrupted by a lunch break (e.g., Andersen, Bollerslev, and Cai, 2000; Gau, 2005; Gau & Hua, 2004; Ito & Lin, 1992; Tang & Lui, 2002). The substantial periodic clustering variation in intraday returns is often explained by the arrival of information. Mitchell and Mulherin (1994) apply daily counts of news reported by Dow Jones on the Broadtape to investigate the link between news arrivals and stock prices. Their results indicate a significant relation between information arrivals and trading volumes, but only a weak link between news counts and stock returns. Berry and Howe (1994) employ the numbers of news headlines crossing the Reuters news screen as the proxy of information arrivals and find a positive relation between news arrivals and trading volume but an insignificant relation with stock return volatility. Moreover, they find that public information arrives seasonally, and it exhibits a distinctively inverted U-shaped pattern across trading days. Low and Muthuswamy (1996), Melvin and Yin (2000), and Chang and Taylor (2003) use the numbers of news reported in Reuters News pages as the information proxy and discuss the link between public information arrivals and exchange rate volatility. As argued in Andersen and Bollerslev (1998), Ederington and Lee (2001) also point out the inappropriate use of the traditional ARCH-GARCH (i.e., Autoregressive Conditional Heteroskedastic and Generalized Autoregressive Conditional Heteroskedastic; see Bollerslev, 1986; Engle, 1982) models for estimating the intraday periodicity and persistence in the volatility of high-frequency returns. Ederington and Lee (2001) observe that the typically U-shaped pattern of intraday volatility completely disappears after controlling for effects of scheduled macroeconomic announcements. By contrast, Andersen and Bollerslev (1998) and Han, Kling, and Sell (1999) find that public news arrivals cannot explain the intraday periodicity fully, implying that there are some other important factors that affect the periodicity of intraday volatility. On the other hand, the dealers’ liquidity demand and private information could influence the exchange rate volatility as well. As discussed in Flood (1994) and Lyons, 1995, Lyons, 1996 and Lyons, 2001, the hot-potato hypothesis or inventory-control hypothesis implies that dealers in the FX market tend to pass undesired positions along to another, thus giving rise to temporary misallocations of currency inventories. Moreover, as argued in Lyons (2001), order flow is an ideal variable to measure dealers’ belief or uncommon-knowledge information. However, due to the unavailability of inventory and order flow data for the New Taiwan dollar/U.S. dollar (NTD/USD) exchange rate, we utilize the unexpected volume of trading as a proxy variable that corresponds to the combined effects of inventory adjustments and uncommon-knowledge information. As new information flows into the market, the expected volume changes in response to common-knowledge information and the unexpected volume reflects the disagreement or uncommon-knowledge information among dealers. If the dealers adjust trading volumes just for inventory control, the trading volume will change even when no new information flows into the FX market and the expected volume remains unchanged. The discrepancy between the actual volume and expected volume of trading therefore can work as a proxy variable for the combined effects of inventory control and private information. However, to handle the intraday seasonality in high-frequency return volatility, some researchers deseasonalize or filter out the seasonality in the data before analyzing the time-varying and persistent intraday volatility. This two-stage approach is taken by, for example, Andersen and Bollerslev (1998) (with the flexible Fourier transformation), and Taylor and Xu (1997) (with the set of multiplicative factors). The other approach is a one-stage procedure that incorporates the periodicity and volatility persistence at the same time. For example, Ederington and Lee (2001) employ dummy variables indicating announcements and time-of-day within the GARCH framework. Bollerslev and Ghysels (1996), Gau and Hua (2004) and Gau (2005) use the periodic GARCH model to capture the repetitive seasonal variations in the volatility by allowing state-dependent ARCH coefficients in the equation of conditional variance. In this paper, we examine the seasonality in the volatility of intraday NTD/USD exchange rate and study factors that influence for the periodicity in terms of intraday volatility. Different from the two-stage approach that uses deseasonalized return to study the impact of news arrivals, as in Melvin and Yin (2000) and Chang and Taylor (2003), we apply a one-stage approach that incorporates the ARCH, news effects, unexpected volume innovations, and time-of-day seasonality simultaneously, as in Ederington and Lee (2001). However, Ederington and Lee only discuss the effect of scheduled announcements releases on the intraday volatility of foreign exchange rate, ignoring the influences of inventory control and uncommon-knowledge information on the intraday volatility. In this paper, we consider both effects of public information and unexpected volume that is linked to inventory control and non-public information, allowing for seasonality and autocorrelation in the intraday volatility. To capture the seasonal and time-varying intraday volatility, we estimate 15-min NTD/USD exchange rate volatility within the framework of the GARCH model.2 Different from the finding of Ederington and Lee (2001) that the U-shaped patterns completely disappear after controlling for the scheduled announcement effects, we find that the arrivals of public information and unexpected volume of trading can only explain for the increased volatility at the market opening, but not for the spike of volatility at the market closing. This suggests another possible factors other than macroeconomic news announcements, uncommon-knowledge information and inventory control reflected in the unexpected volume of trading. A possible source attributing to the intraday variation of exchange rate is the intervention from the central bank. Chang and Taylor (1998) and Dominguez, 1998 and Dominguez, 2003 show that interventions from central banks generally increase the exchange rate volatility. Nevertheless, the central bank in Taiwan does not reveal any data about the FX intervention. The only available information is the news reports on the next day after the central bank explicitly bought or sold USD in the Taipei FX market. To investigate the impacts of central bank intervention operations on the daily volatility of the NTD/USD exchange rate, we calculate the realized volatility by the sum of 15-min deseasonalized squared-changes (Andersen, Bollerslev, Diebold, & Labys, 2003). The estimation results, based on the binary indicator variable of the central bank intervention operations reported in the newspapers, show that the central bank intervention has a positive and significant effect on the daily NTD/USD realized volatility. The remainder of this paper is organized as follows. Section 2 introduces the trading of the Taipei FX market and documents the intraday periodicity in absolute changes and trading volumes of NTD/USD. Section 3 presents specifications of the GARCH model that simultaneously consider explicit time-of-day factors, numbers of news headlines related to Taiwan and the U.S. reported on the Bloomberg Headline News screen, and unexpected volume of trading. Section 4 explains the estimation results and explores to what extent the periodicity in the intraday NTD/USD volatility is captured by the model proposed in this paper. Section 5 concludes.

By comparing with other simpler models with alone information sets, we find that the simultaneous GARCH model, that incorporates explicit time-of-day seasonality factors, lagged squared return innovations, counts of news related to the U.S. and Taiwan, and unexpected volume innovations, performs best in capturing the time-varying dynamics of the intraday NTD/USD exchange rate volatility. However, after the news effects and response to the unexpected volume shocks are controlled for, the two subdued but still significant spikes of volatility at the market closing and at the opening of the afternoon trading session are still observed. This indicates that some other factors like, for example, the central bank intervention operations, may have significant influence on the intraday NTD/USD volatility. We separate news events into categories by countries and find that both counts of news related to the U.S. and Taiwan, respectively, have significant and positive impacts on the intraday NTD/USD volatility. Although the total news count measures some less relevant reports, it is the most comprehensive news variable available. The results of estimation show that the quantitative impact of the count of news related to the U.S. is larger than that related to Taiwan. There is an interesting question of the NTD/USD exchange rate volatility related to central bank intervention operations in the Taipei FX market. Although the intraday intervention data are not available from the central bank, we collect the daily news reports about the central bank intervention operations and examine the impact of central bank intervention based on the daily realized volatility. The results indicate that the central bank intervention operations in the Taipei FX market have a significantly positive influence on the daily NTD/USD realized volatility.