• East Asian Economic Review
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• v.18 no.1
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• pp.3-27
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• 2014

This paper examines the effects of financial crises on the long memory volatility dependency of daily exchange returns focusing on the Asian crisis in 97-98 and the Global crisis in 08-09. By using the daily KRW-USD and JPY-USD exchange rates which have different trading regions and volumes, this paper first applies both the parametric FIGARCH model and the semi-parametric Local Whittle method to estimate the long memory volatility dependency of the daily returns and the temporally aggregated returns of the two exchange rates. Then it compares the effects of the two financial crises on the long memory volatility dependency of the daily returns. The estimation results reflect that the long memory volatility dependency of the KRW-USD is generally greater than that of the JPY-USD returns and the long memory dependency of the two returns appears to be invariant to temporal aggregation. And, the two financial crises appear to affect the volatility dynamics of all the returns by inducing greater long memory dependency in the volatility process of the exchange returns, but the degree of the effects of the two crises seems to be different on the exchange rates.

• East Asian Economic Review
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• v.20 no.3
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• pp.365-390
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• 2016

This paper quantitatively compares the intrinsic features of the daily USD-GBP exchange rates in two different periods, the 1920s and the 2010s, under the same freely floating exchange rate system. Even though the foreign exchange markets in the 1920s seem to be much less organized and developed than in the 2010s, this paper finds that both the long memory volatility property and the structural break appear to be the common intrigue features of the exchange rates in the two periods by using the FIGARCH model. In particular, the long memory volatility properties in the two periods are found to be upward biased and overstated because of the structural breaks in the exchange markets. Thus this paper applies the Adaptive-FIGARCH model to consider the long memory volatility property and the structural breaks jointly. The main finding is that the structural breaks in the exchange markets affect the long memory volatility property significantly in the two periods but the degree of the long memory volatility property in the 1920s is reduced more remarkably than in the 2010s after the structural breaks are accounted for; thus implying that the structural breaks in the foreign exchange markets in the 1920s seem to be more significant.

• International Commerce and Information Review
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• v.12 no.1
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• pp.99-121
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• 2010

This paper reviews the categories and properties of risk measures, analyzes the classes and structural equations of volatility forecasting models, and presents the practical methodologies and their expansion methods of estimating and forecasting the volatilities of exchange rates using Excel spreadsheet modeling. We apply the GARCH(1,1) model to the Korean won(KRW) denominated daily and monthly exchange rates of USD, JPY, EUR, GBP, CAD and CNY during the periods from January 4, 1998 to December 31, 2009, make the estimates of long-run variances in the returns of exchange rate calculated as the step-by-step change rate, and test the adequacy of estimated GARCH(1,1) model using the Box-Pierce-Ljung statistics Q and chi-square test-statistics. We demonstrate the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the monthly series except the semi-variance GARCH(1,1) applied to KRW/JPY100 rate. But we reject the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the daily series because of the very high Box-Pierce-Ljung statistics in the respective time lags resulting to the self-autocorrelation. In conclusion, the GARCH(1,1) model provides for the easy and helpful tools to forecast the exchange rate volatilities and may become the powerful methodology to overcome the application difficulties with the spreadsheet modeling.

• Journal of Korea Trade
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• v.23 no.2
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• pp.110-126
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• 2019

Purpose - This paper examines the recently realized continuous volatility and discrete jumps of US Dollar/Euro returns using the frequency of five minute returns spanning the period from February 2010 through February 2018with periodicity filters. Design/Methodology - This paper adopts the nonparametric estimation. The realized volatility and Realized Outlying Weighted variations show non-Gaussian, fat-tailed, and leptokurtic distributions. Some significant volatility jumps in returns occurred from 2010 through 2018, and the very exceptionally large and irregular jumps occurred around 2010-2011, after the EU financial crisis, and 2015-2016. The outliers occurred somewhat frequently around the years of 2015 and 2016. Originality/value - When we include periodicity filters of volatility such as MAD, Short Half Scale, and WSD, the five minute returns of US Dollar/Euro exchange rates have smaller daily jump probabilities by 20-30% than when we do not include the periodicity filters of volatility. Thus, when we consider the periodicity filters of volatility such as MAD, Short Half Scale, and WSD, the five minute returns of US Dollar/Euro have considerably smaller jump probabilities.

• International Area Studies Review
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• v.20 no.3
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• pp.123-144
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• 2016

This paper investigates the linkages between returns both in foreign exchange and stock markets, and uncertainties in two markets using daily data for the period of 16 July 2004 to 30 June 2014 in Nepalese economy. Four hypotheses are tested about how uncertainty influences the stock index and exchange rates. From the empirical results, a bivariate EGARCH-M model is the best to explain the volatility in the two markets. There is a negative relationship from the exchange rates return to stock price return. Empirical results do provide strong empirical confirmation that negative effect of stock index uncertainty and positive effect of exchange rates uncertainty on average stock index. GARCH-in-mean variables in AR modeling are significant and shows that there is positive effect of exchange rates uncertainty and negative effect of stock index uncertainty on average exchange rates. Stock index shocks have longer lived effects on uncertainty in the stock market than exchange rates shock have on uncertainly in the foreign exchange market. The effect of the last period's shock, volatility is more sensitive to its own lagged values.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1-10
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• 2021

This study examines the dynamic pattern of the exchange rate volatilities of the ASEAN-5 currencies from January 2006 to August 2020. The exchange rates applied in this study comprise bilateral and effective exchange rates in order to investigate the influence of the US dollar on the stability of the ASEAN-5 currencies. Since a volatility model employed in this study is a natural cubic spline volatility model, the Monte Carlo simulation is consequently conducted to determine an appropriate criterion to select a number of quantile knots for this model. The simulation results reveal that, among four candidate criteria, Generalized Cross-Validation is a suitable criterion for modeling the ASEAN-5 exchange rate volatilities. The estimated volatilities showed the inconstant dynamic patterns reflecting the uncertain exchange rate risk arising in international transactions. The bilateral exchange rate volatilities of the ASEAN-5 currencies to the US dollar are more variable than their corresponding effective exchange rate volatilities, indicating the influence of the US dollar on the stability of the ASEAN-5 currencies. The findings of this study suggest that the natural cubic spline volatility model with the quantile knots selected by Generalized Cross-Validation is practical and can be used to examine the dynamic patterns of the financial volatility.

• East Asian Economic Review
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• v.24 no.1
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• pp.61-87
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• 2020

Five diffusion models are estimated using three different foreign exchange rates to find an appropriate model for each. Daily spot exchange rates expressed as the prices of 1 euro, 1 British pound and 100 Japanese yen in US dollars, respectively denoted by USD/EUR, USD/GBP, and USD/100JPY, are used. The maximum likelihood estimation method is implemented after deriving an approximate log-transition density function (log-TDF) of the diffusion processes because the true log-TDF is unknown. Of the five models, the most general model is the best fit for the USD/GBP, and USD/100JPY exchange rates, but it is not the case for the case of USD/EUR. Although we could not find any evidence of the mean-reverting property for the USD/EUR exchange rate, the USD/GBP, and USD/100JPY exchange rates show the mean-reversion behavior. Interestingly, the volatility function of the USD/EUR exchange rate is increasing in the exchange rate while the volatility functions of the USD/GBP and USD/100Yen exchange rates have a U-shape. Our results reveal that more care has to be taken when determining a diffusion model for the exchange rate. The results also imply that we may have to use a more general diffusion model than those proposed in the literature when developing economic theories for the behavior of the exchange rate and pricing foreign currency options or derivatives.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.23-37
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• 2022

Purpose - The purpose of this paper is to analyze the dynamic factors of the daily FX implied volatility based on the fractional integration methods focusing on long memory feature and structural changes. Design/methodology/approach - This paper uses the daily FX implied volatility data of the EUR-USD and the JPY-USD exchange rates. For the fractional integration analysis, this paper first applies the basic ARFIMA-FIGARCH model and the Local Whittle method to explore the long memory feature in the implied volatility series. Then, this paper employs the Adaptive-ARFIMA-Adaptive-FIGARCH model with a flexible Fourier form to allow for the structural changes with the long memory feature in the implied volatility series. Findings - This paper finds statistical evidence of the long memory feature in the first two moments of the implied volatility series. And, this paper shows that the structural changes appear to be an important factor and that neglecting the structural changes may lead to an upward bias in the long memory feature of the implied volatility series. Research implications or Originality - The implied volatility has widely been believed to be the market's best forecast regarding the future volatility in FX markets, and modeling the evolution of the implied volatility is quite important as it has clear implications for the behavior of the exchange rates in FX markets. The Adaptive-ARFIMA-Adaptive-FIGARCH model could be an excellent description for the FX implied volatility series

• International Area Studies Review
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• v.21 no.1
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• pp.181-200
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• 2017

This study investigates the impact of exchange rate and exchange rate volatility on the stock prices of eight industries from 2006 to 2015. The first and second exchange rate exposure of these eight industries is estimated with respect to four different exchange rates, namely the US dollar, Japanese yen, European currency unit, and British pound. In exchange rate exposure, stock prices in foods-beverages, paper-wood, electricity-gas, and banks industries are negatively related to exchange rate, whereas stock prices in electrical-electronic equp. and transport-equp. industries are positively related to exchange rate as expected. However stock price in machinery industry is negatively related to exchange rate, which is opposite to the expectation. Negative relationship is found between stock price in chemicals industry and exchange rate. In exchange rate volatility exposure, stock price in paper-wood industry is found to be negatively related to exchange rate volatility. Stock price in banks industry is also negatively related to exchange rate volatility. This result is opposite as expected, because banks are supposed to get more revenue by issuing derivatives related to foreign exchange when exchange rate volatility increases.

• East Asian Economic Review
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• v.20 no.4
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• pp.469-491
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• 2016

In this paper, we estimate the exchange rate exposure, indicating the effect of exchange rate movements on firm values, for a sample of 1,400 firms in seven East Asian countries. The exposure estimates based on various exchange rate variables, return horizons and a control variable are compared. A key result from our analysis is that the long term effect of exchange rate movements on firm values is greater than the short term effect. And we find very similar results from using other exchange rate variables such as the U.S. dollar exchange rate, etc. Second, we add exchange rate volatility as a control variable and find that the extent of exposure is not much changed. Third, we examine the changes in exposure to exchange rate volatility with an increase in return horizon. Consequently the ratio of firms with significant exposures increases with the return horizons. Interestingly, the increase of exposure with the return horizons is faster for exposure to volatility than for exposure to exchange rate itself. Taken as a whole, our findings suggest that the socalled "exposure puzzle" may be a matter of the methodology used to measure exposure.