Exchange Rate Exposure of Sectoral Returns and Volatilities: Evidence from Japanese Industrial Sectors

Most studies of exchange rate exposure of stock returns do not address three relevant aspects simultaneously. They are, namely: sensitivity of stock returns to exchange rate changes; sensitivity of volatility of stock returns to volatility of changes in foreign exchange market; and the correlation between volatilities of stock returns and exchange rate changes. In this paper, we employ a bivariate GJR-GARCH model to examine all such aspects of exchange rate exposure of sectoral indexes in Japanese industries. Based on a sample data of fourteen sectors, we find significant evidence of exposed returns and its asymmetric conditional volatility of exchange rate exposure. In addition, returns in many sectors are correlated with those of exchange rate changes. We also find support for the “averaged-out exposure and asymmetries” argument. Our findings have direct implications for practitioners in formulating investment decisions and currency hedging strategies.exchange rate exposure; asymmetric volatility spillovers; GARCH-type models; conditional correlation

Time-Varying Currency Betas: Evidence from Developed and Emerging Markets

This paper examines the conditional time-varying currency betas from five developed markets and four emerging markets. A trivariate BEKK-GARCH-in-mean model is used to estimate the timevarying conditional variance and covariance of returns of stock index, the world market portfolio and changes in bilateral exchange rate between the US dollar and the local currency of each country. It is found that currency betas are more volatile than those of the world market betas. Currency betas in emerging markets are more volatile than those in developed markets. Moreover, we find evidence of long-memory in currency betas. The usefulness of time-varying currency betas are illustrated by two applications.time-varying currency betas; multivariate GARCH-M models; international CAPM; fractionally integrated processes; stochastic dominance

Volatility Dynamics in Foreign Exchange Rates: Further Evidence from the Malaysian Ringgit and Singapore Dollar

Singapore dollar are analyzed in this paper. Our approach can simultaneously capture the empirical regularities of persistent and asymmetric effects in volatility and timevarying correlations of financial time series. Consistent with the results of Tse and Tsui (1997), there is only some weak support for asymmetric volatility in the case of the Malaysian ringgit when the two currencies are measured against the US dollar. However, there is strong evidence that depreciation shocks have a greater impact on future volatility levels compared with appreciation shocks of the same magnitude when both currencies measured against the yen. Moreover, evidence of time-varying correlation is highly significant when both currencies are measured against the yen. Regardless of the choice of the numeraire currency and the volatility models, shocks to exchange rate volatility are found to be significantly persistent.Constant correlations; Exchange rate volatility; Fractional integration; Long memory; Bivariate asymmetric GARCH; Varying correlations

A Multivariate GARCH Model with Time-Varying correlations

In this paper we propose a new multivariate GARCH model with time- varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the MLE of the varying- correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.BEKK model, constant correlation, Monte Carlo method, multivariate GARCH model, maximum likelihood estimate, varying correlation

Medical Savings Accounts in Singapore: How much is adequate?

While many studies have examined the cost-containment aspect of Medical savings accounts (MSA), few have investigated the adequacy of MSA to finance the health care expenditure. This paper estimates the present value of lifetime healthcare expenses (PVHE) of the Singaporean male and female elderly upon retirement at age 62. The estimation involves calibrating the stream of future healthcare expenditure; stochastic forecasting of cohort survival probabilities; and discounting the projected lifetime healthcare expenditure. Estimated values of the PVHE under various scenarios are used to assess the adequacy of the government-decreed minimum saving to be maintained in the MSA.medical savings accounts, present value of lifetime health care expense, cohort survival probabilities

A Multivariate GARCH Model with Time-Varying Correlations

In this paper we propose a new multivariate GARCH model with time-varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we manage to construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the QMLE of the varying-correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.

Monetizing Housing Equity to Generate Retirement Incomes

The public housing program and the unique way of financing housing through the mandatory savings system in Singapore have created a class of homeowners. This paper compares the instruments available to different flat owners to monetize their assets, including the Lease Buyback Scheme (LBS), subletting, downsizing and reverse mortgage. We estimate the present value of retirement incomes derived from these options by incorporating the survival probability which is forecasted using the Lee-Carter demographic model. We compare the monthly payouts that can be unlocked and discuss the tradeoffs of adequate retirement with the elderly preference for leaving a bequest and ageing in place. Our results show that LBS is the most attractive option. It allows the elderly to age-inplace while generating a steady stream of monthly drawdown and possibility of leaving a bequest. Subletting releases housing equity while retaining the asset. This helps the elderly to fulfill their bequest motive. Reverse mortgage is the least attractive option, yielding the lowest retirement income due to high loading factors.

Measuring Asymmetry and Persistence in Conditional Volatility in Real Output: Evidence from Three East Asian Tigers Using a Multivariate GARCH approach

We search for evidence of conditional volatility in the quarterly real GDP growth rates of three East Asian tigers: Singapore, Hong Kong and Taiwan. The widely accepted exponential GARCH-type model is used to capture the existence of asymmetric volatility and the potential structural break points in the volatility. We find evidence of asymmetry and persistence in the volatility of GDP growth rates. It is noted that the identified structural breakpoints of volatility correspond reasonably well to the historical economic and political events in these economies. Policy implications are discussed.East Asia, Real Output, GARCH, structural changes, asymmetric volatility

East Asian financial crisis revisited: What does a copula tell?

We construct a regime-switching model of copulas to capture observed asymmetric dependence in daily changes of exchange rates in five selected East Asian economies during the 1997 financial crisis era. In particular, we investigate the effects of the financial crisis on asymmetric dependence in exchange rates returns and assess the asymmetric relationships between five currencies, including the Singapore Dollar, Japanese Yen, South Korea Won, Thailand Baht and Indonesia Rupiah. Various time-varying copula models will also be applied to examine the possible structural breaks. The results confirm significant changes at the dependence level, tail behaviour and asymmetry structures between returns of all permuted pairs from the five currencies before and after the crisis. In comparison with other methods, it is found that the copular approach has more explanatory power than the existing ones in identifying structure breaks

Modeling the Conditional Heteroscedasticity and Leverage Effect in the Chinese Stock Markets

The Chinese stock market has experienced an astonishing growth and unprecedented development since its inception in the early 1990s, emerged to be the world\u27s second-largest by market value by the end of 2009. The Chinese stock market is also one of the most volatile markets, which has been called by many observers a “casino”. In the recent years there are several far-reaching events that have reshaped the Chinese stock markets. The most notable events include the “dot-com bubble” in 2000, China’s non-tradable shares reform in 2005 and the global financial crisis in 2008. It is noted that the “dot-com bubble” has caused the Chinese stock markets a sharp oscillation since 2000. With a short-lived bull, the Chinese stock markets experienced a nearly five years long bear market until June 2005 when the reform of non-tradable shares was implemented, which increased the liquidity and brought the markets back to a long-term bull run. Since the US sub-prime mortgage crisis the Chinese stock markets have shown extreme instability and severe volatility, which has become the major concern to the policy-makers and investors. Many existing studies have revealed that the financial time series data exhibit linear dependence in volatility, which indicates the presence of heteroskedasticity, implying the existence of volatility clustering. Although direct generalizations from the univariate GARCH models are straightforward, their applications are limited by practical issues associated with cumbersome computation and strong restrictions on parameters to guarantee positive definiteness of variance matrixes. This study intends to examine the presence of heteroskedasticity and the leverage effect in the two Chinese stock markets, and to capture the dynamics of conditional correlation between returns of China’s stock markets and those of the U.S. in a bivariate VCMGARCH framework. The results show that that the leverage effect is significant in both Shanghai and Shenzhen markets during the sample period in 2000-2008, and the conditional correlation between mainland China’s and the U.S. stock markets is quite low and highly volatile. The results indicate that that uncertainty derived from time-varying relationship between Shanghai and the U.S. stock markets is more significant than that between Shenzhen and the U.S. stock markets. In addition, the Chinese stock markets are found to be highly regimes persistent, thereby reducing potential benefits induced by actively trading. These findings have important implication for investors seeking opportunity of portfolio diversification