Exchange rate volatility across financial crises

This paper studies the impact of global financial turmoil on the exchange rate policies in emerging countries. Spillovers from advanced financial markets to currencies in emerging countries are likely to be exacerbated during crisis periods. To test this hypothesis, we assess the exchange rate policies by currencies’ volatility and investigate their relationship to a global financial stress indicator, measured by the volatility on global markets. We introduce the possibility of nonlinearities by running smooth transition regressions over a sample of 21 emerging countries from January 1994 to September 2009. The results confirm that exchange rate volatility does increase more than proportionally with the global financial stress, for most countries in the sample. We also evidence regional contagion effects spreading from one emerging currency to other currencies in the neighboring area.     

Exchange rate dynamics under alternative optimal interest rate rules

We explore the role of interest rate policy in the exchange rate determination process. Specifically, we derive exchange rate equations from interest rate rules that are theoretically optimal under a few alternative settings. The exchange rate equation depends on its underlying interest rule and its performance could vary across evaluation criteria and sample periods. The exchange rate equation implied by the interest rate rule that allows for interest rate and inflation inertia under commitment offers some encouraging results — exchange rate changes “calibrated” from the equation have a positive and significant correlation with actual data, and offer good direction of change prediction. Our exercise also demonstrates the role of the foreign exchange risk premium in determining exchange rates and the difficulty of explaining exchange rate variability using only policy based fundamentals.     

Covered interest rate parity in emerging markets

This paper finds that while covered interest rate parity holds for large and small triple A rated economies, it holds for emerging markets only for a three-month maturity. For a five-year horizon the size and frequency of violations lead to the conclusion that covered interest rate parity does not hold for longer maturities for Brazil, Chile, Russia and South Korea. Overall this paper finds that aspects of credit risk are the source of violations in CIRP in the long-term capital markets rather than transactions costs or the size of the economy.     

On the determinants of credit rationing: Firm-level evidence from transition countries

Using survey data for firms from Eastern European transition economies we investigate the determinants of credit rationing. Our rationing definition incorporates firms whose loan application was rejected, but also ‘discouraged’ potential borrowers. We employ a bivariate probit with censoring, approach that accounts for the underlying selectivity since rationed firms are a subset of those without a loan. We include firm-specific attributes related to the alleviation of informational asymmetries, and therefore expected to affect credit rationing. We find that credit rationing depends on firm size, profitability, sales growth, ownership type, legal status, sectoral heterogeneity and the country-specific level of domestic credit.     

Why do central banks intervene?

Intervention by central banks, in terms of buying and selling foreign currency, has been a major activity in recent years. This paper investigates the motivations for such policy and the evidence for its effectiveness. We use high quality daily data on the dollar amounts of intervention by the central banks of the US and Germany. We also use information on agreed G7 target levels for the $/DM and $/Yen nominal exchange rates. Daily, nominal dollar exchange rate returns are well described as a Martingale-GARCH process, and we find little evidence that the different types of intervention have had much effect on the conditional mean of exchange rate returns. There is some evidence that intervention is associated with slight increases in the volatility of exchange rate returns. While little evidence is found for the effectiveness of intervention, the motivations are more clear. In particular, from the application of probit analysis we find that the probability of intervention is determined by the magnitude of the deviation of the nominal exchange rate from the agreed target level and, to a lesser extent, by the current volatility of exchange rates.     

Modelling the term structure of interest rates: An efficient nonparametric approach

We propose a new approach for estimating the coefficients of the term structure equation by means of the volatility of the interest rates and the slope of the yield curve. One advantage of this approach consists in the fact that the drift and the market price of risk are jointly estimated and need not be individually specified. We then generate trajectories in a test problem to investigate the finite properties of this approach. Our simulation results show that this new approach outperforms the classic nonparametric models in the literature. Finally, an application to USA Treasury Bill data is also illustrated.     

Conditional beta pricing models: A nonparametric approach

We propose a two-stage procedure to estimate conditional beta pricing models that allows for flexibility in the dynamics of asset betas and market prices of risk (MPR). First, conditional betas are estimated nonparametrically for each asset and period using the time-series of previous data. Then, time-varying MPR are estimated from the cross-section of returns and betas. We prove the consistency and asymptotic normality of the estimators. We also perform Monte Carlo simulations for the conditional version of the three-factor model of Fama and French (1993) and show that nonparametrically estimated betas outperform rolling betas under different specifications of beta dynamics. Using return data on the 25 size and book-to-market sorted portfolios, we find that the nonparametric procedure produces a better fit of the three-factor model to the data, less biased estimates of MPR and lower pricing errors than the Fama–MacBeth procedure with betas estimated under several alternative parametric specifications.     

Volatility and covariation of financial assets: A high-frequency analysis

Using high frequency data for the price dynamics of equities we measure the impact that market microstructure noise has on estimates of the: (i) volatility of returns; and (ii) variance–covariance matrix of n assets. We propose a Kalman-filter-based methodology that allows us to deconstruct price series into the true efficient price and the microstructure noise. This approach allows us to employ volatility estimators that achieve very low Root Mean Squared Errors (RMSEs) compared to other estimators that have been proposed to deal with market microstructure noise at high frequencies. Furthermore, this price series decomposition allows us to estimate the variance covariance matrix of n assets in a more efficient way than the methods so far proposed in the literature. We illustrate our results by calculating how microstructure noise affects portfolio decisions and calculations of the equity beta in a CAPM setting.     

Alternative models for hedging yield curve risk: An empirical comparison

We test alternative models of yield curve risk by hedging US Treasury bond portfolios through note/bond futures. We show that traditional implementations of models based on principal component analysis, duration vectors and key rate duration lead to high exposure to model errors and to sizable transaction costs, thus lowering the hedging quality. Also, this quality randomly varies from one model and hedging problem to the other. We show that accounting for the variance of modeling errors substantially reduces both hedging errors and transaction costs for all considered models. Additionally, it leads to much more stable weights in the hedging portfolios and – as a result – to more homogeneous hedging quality. On this basis, error-adjusted principal component analysis is found to systematically and significantly outperform alternative models.     

The random-walk behavior of the Euro exchange rate

We use Generalized Andrews–Ploberger (GAP) tests to examine the random-walk behavior of 17 OECD countries’ euro exchange rates at daily frequencies. The GAP tests reject the hypothesis of random-walk behavior less often than do traditional tests. Moreover, the random-walk hypothesis cannot be rejected for the euro’s exchange rate against most of the major currencies. We also use the generalized Box–Pierce tests to produce evidence that corroborates the above findings. Finally, and in contrast to the traditional tests, the GAP tests produce results that are consistent during the great moderation and the recent global financial crisis periods.     

Estimating the credibility of an exchange rate target zone

Recent breakthroughs in the theory of exchange rate target zones have not been followed by similar contributions on the empirical side. The drift adjustment method of evaluating the credibility of a target zone has become common practice. However, the estimates of the expected rate of depreciation inside the band do not model knowledge of the band in the agents' information set. In this paper, a rational expectations limited-dependent variable method to estimate the expected rate of depreciation is used to remedy this weakness. In the case of the franc-mark target zone with daily data covering a 4-year period, we show that expected rates of devaluation of the order of 2.5% were still present in the early 1990s. Their reappearance in the autumn of 1992 may thus not be surprising.     

Stock market volatility and the crash of 1987: evidence from six emerging markets

This paper studies volatility, risk premia and the persistence of volatility in six emerging stock markets before and after the 1987 stock market crash. The empirical investigation is conducted by means of the GARCH in the mean model (GARCH-M) and monthly data from Argentina, Greece, India, Mexico, Thailand, and Zimbabwe between January of 1976 and August of 1994. Results indicate changes in the ARCH parameter, risk premia and persistence of volatility before and after the 1987 crash. But these noted changes are not uniform and depend upon the individual markets. Factors other than the 1987 crash may also be responsible for the changes.     

Central bank intervention and the volatility of foreign exchange rates: evidence from the options market

This paper tests the effects of central bank intervention on the ex ante volatility of $/DM and $/yen exchange rates between 1985 and 1991. In contrast to previous research which employed GARCH estimates of conditional volatility, we estimate ex ante volatility using the implied volatilities of currency option prices. We also control for the effects of other macroeconomic announcements. We find little support for the hypothesis that central bank intervention decreases expected exchange rate volatility. Instead, central bank intervention is generally associated with a positive change in ex ante exchange rate volatility, or with no change.     

Marriage and other risky assets: A portfolio approach

We study the joint impact of gender and marital status on financial investments by testing the hypothesis that marriage represents – in a portfolio framework – a sort of safe asset and that this attribute may change over time. We show that married individuals have a higher propensity to invest in risky assets than single ones, that this marital status gap is stronger for women and that, for women only, it evolves and declines at the end of the sample period. Next we explore a number of possible explanations of the observed gender differences by controlling for background factors that capture the evolution of family and society. We find that both the higher female marital status gap and its time variability vanish for those women who are employed. Our empirical investigation is based on a dataset drawn from the 1993–2006 Bank of Italy Survey of Household Income and Wealth.     

Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions

Financial returns typically display heavy tails and some degree of skewness, and conditional variance models with these features often outperform more limited models. The difference in performance may be especially important in estimating quantities that depend on tail features, including risk measures such as the expected shortfall. Here, using recent generalizations of the asymmetric Student-t and exponential power distributions to allow separate parameters to control skewness and the thickness of each tail, we fit daily financial return volatility and forecast expected shortfall for the S&P 500 index and a number of individual company stocks; the generalized distributions are used for the standardized innovations in a nonlinear, asymmetric GARCH-type model. The results provide evidence for the usefulness of the general distributions in improving fit and prediction of downside market risk of financial assets. Constrained versions, corresponding with distributions used in the previous literature, are also estimated in order to provide a comparison of the performance of different conditional distributions.     

The liquidity effect for open market operations

The liquidity effect is the negative relationship between the supply of federal funds and the overnight federal funds rate. Deviations of the federal funds rate from its target can be interpreted as demand innovations for federal funds. Permanent adjustments to demand are modeled as an unobserved component and estimated using the Kalman filter to identify liquidity effects. The demand-based approach for identifying the liquidity effect contrasts previous work which concentrates on errors forecasting the supply of federal funds. This paper finds a liquidity effect several times larger than that from previous studies, indicating the market for federal funds is less liquid than previously thought. The effect of a $1 billion increase in open market operations over a 1-week period is a decrease of the federal funds rate by about 12 basis points.     

Fast approximations of bond option prices under CKLS models

A new computational method for approximating prices of zero-coupon bonds and bond option prices under general Chan–Karolyi–Longstaff–Schwartz models is proposed. The pricing partial differential equations are discretized using second-order finite difference approximations and an exponential time integration scheme combined with best rational approximations based on the Carathéodory–Fejér procedure is employed for solving the resulting semi-discrete equations. The algorithm has a linear computational complexity and provides accurate bond and European bond option prices. We give several numerical results which illustrate the computational efficiency of the algorithm and uniform second-order convergence rates for the computed bond and bond option prices.     

Explaining exchange rate volatility: an empirical analysis of ‘the holy trinity’ of monetary independence, fixed exchange rates, and capital mobility

This paper uses a panel of data from twenty-two countries between 1967 and 1992 to explain exchange rate volatility, focusing on potential tradeoffs between fixed exchange rates, independent monetary policy, and capital mobility. I use monetary models to parameterize monetary divergence and factor analysis to measure capital mobility. Exchange rate volatility is loosely linked to both monetary divergence and the degree of capital mobility. Interestingly, exchange rate volatility is significantly correlated with the width of the explicitly declared exchange rate band, even after taking monetary divergence and capital mobility into account.     

Housing, consumption and monetary policy: How different are the US and the euro area?

This paper provides a systematic empirical analysis of the role of the housing market in the macroeconomy in the US and the euro area. First, it establishes some stylised facts concerning key variables in the housing market on the two sides of the Atlantic, such as real house prices, residential investment and mortgage debt. It then presents evidence from Structural Vector Autoregressions (SVAR) by focusing on the effects of monetary policy, credit supply and housing demand shocks on the housing market and the broader economy. The analysis shows that similarities outweigh differences as far as the housing market is concerned. The empirical evidence suggests a stronger role for housing in the transmission of monetary policy shocks in the US. The evidence is less clear-cut for housing demand shocks. Finally, credit supply shocks seem to matter more in the euro area.