Disentangling the effect of jumps on systematic risk using a new estimator of integrated co-volatility

We propose a new threshold–pre-averaging realized estimator for the integrated co-volatility of two assets using non-synchronous observations with the simultaneous presence of microstructure noise and jumps. We derive a noise-robust Hayashi–Yoshida estimator that allows for very general structure of jumps in the underlying process. Based on the new estimator, different aspects and components of co-volatility are compared to examine the effect of jumps on systematic risk using tick-by-tick data from the Chinese stock market during 2009–2011. We find controlling for jumps contributes significantly to the beta estimation and common jumps mostly dominate the jump’s effect, but there is also evidence that idiosyncratic jumps may lead to significant deviation. We also find that not controlling for noise and jumps in previous realized beta estimations tend to considerably underestimate the systematic risk.     

Modelling and forecasting short-term interest rate volatility: A semiparametric approach

This paper employs a semiparametric procedure to estimate the diffusion process of short-term interest rates. The Monte Carlo study shows that the semiparametric approach produces more accurate volatility estimates than models that accommodate asymmetry, level effect and serial dependence in the conditional variance. Moreover, the semiparametric approach yields robust volatility estimates even if the short rate drift function and the underlying innovation distribution are misspecified. Empirical investigation with the U.S. three-month Treasury bill rates suggests that the semiparametric procedure produces superior in-sample and out-of-sample forecast of short rate changes volatility compared with the widely used single-factor diffusion models. This forecast improvement has implications for pricing interest rate derivatives.     

Term structure modelling with observable state variables

This paper proposes and implements a parsimonious three-factor model of the term structure whose dynamics is driven uniquely by observable state variables. This approach allows comparing alternative views on the way state variables – macroeconomic variables, in particular – influence the yield curve dynamics, avoids curse of dimensionality problems, and provides more reliable inference by using both the cross-sectional and the time series dimension of the data. I simulate the small-sample properties of the procedure and conduct in- and out-of-sample studies using a comprehensive set of US data. I show that even a parsimonious model where the level, slope and curvature factors of the term structure are driven by, respectively, inflation, monetary policy and economic activity consistently outperforms the (latent-variable) benchmark model in an out-of-sample study.     

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.     

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.     

On the relationship between exchange rates and equity returns: A new approach

This paper employs a new approach in order to investigate the underlying relationship between stock markets and exchange rates. Current approaches suggest that the relative equity market performance of two countries is linked to their exchange rate. In contrast, this study proposes an alternative approach where one global variable – global equity market returns – is believed to have an effect on exchange rates, with the relative interest rate level of a currency determining the sign of the relationship. Our empirical findings suggest that exchange rates and global stock market returns are strongly linked. The value of currencies with higher interest rates is positively related with global equity returns, whereas the value of currencies with lower interest rates is negatively related with global equity returns.     

Resolving the deposit dilemma: A new DEA bank efficiency model

One of the weaknesses of current bank efficiency models is a disagreement as to the role of deposits in the bank production process. Some models view deposits as an input, while others view them as an output. Such disparity of approaches results in inconsistent efficiency estimates. In this study we propose an alternative Data Envelopment Analysis (DEA) bank efficiency model that treats deposits as an intermediate product, thus emphasizing the dual role of deposits in the bank production process. Consequently, the effect of the amount of deposits on bank efficiency depends on the efficiency at both stages of the bank production process. The main advantage of our model is that it does not require a researcher to make a judgment call as to whether having more (production approach) or less (intermediation approach) deposits is “better” for bank efficiency. Our unified framework has the potential to produce more consistent efficiency estimates.     

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.     

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.     

Price discovery in currency markets

This paper examines the price discovery process in currency markets, basing its analysis on the pivotal distinction between the customer (end-user) market and the interdealer market. It first provides evidence that this price discovery process cannot be based on adverse selection between dealers and their customers, as postulated in standard models, because the spreads dealers quote to their customers are not positively related to a trade’s likely information content. The paper then highlights three factors familiar in the literature – fixed operating costs, market power, and strategic dealing – that may explain the cross-sectional variation in customers’ spreads. The paper finishes by proposing a price discovery process relevant to liquid two-tier markets and providing preliminary evidence that this process applies to currencies.     

Nonparametric estimation and testing of stochastic discount factor

This paper attempts to estimate stochastic discount factor (SDF) proxies nonparametrically using the conditional Hansen–Jagannathan distance. Nonparametric estimation can not only avoid misspecification when dealing with nonlinearity in the model but also provide more precise information about the local properties of the estimators. Empirical studies show that our method performs better than the alternative parametric polynomial models, and furthermore, we find that the return on aggregate wealth can sufficiently explain the SDF proxies when one deals with nonlinearity appropriately.     

Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union

Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.     

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.     

CAPM option pricing

This paper extends the option pricing equations of [Black and Scholes, 1973] , [Jarrow and Madan, 1997] and [Husmann and Stephan, 2007] . In particular, we show that the length of the individual planning horizon is a determinant of an option’s value. The derived pricing equations can be presented in terms of the Black and Scholes [1973. Journal of Political Economy 81, 637–654] option values which ensures an easy application in practice.     

A multi-country test of the Fisher model for stock returns

This article provides a test of the Fisher model, linking expected stock returns and inflation, based on international data. Since the Fisher model is ‘universal’ and calls for a slope of 1 in any country, we improve the testing power by conducting a joint test over eight countries. The pooling of data for several countries seems to reduce the small-sample bias. We test the Fisher model, using an instrumental variable approach, for holding-period horizons ranging from 1–12 months. The Fisher model is not rejected at any horizon: however, the magnitude of the slope coefficient lends stronger support at long horizons. This study using multi-country panel data provides evidence corroborating the finding of Boudoukh and Richardson (1993) that the Fisher model holds at long horizons (5 years), using 180 years of US data.     

Are incentives for earnings management reflected in the ERC: Large sample evidence

In this study, I examine the effect of exposure to earnings management (EM) incentives on the earnings response coefficient (ERC). Drawing from several anecdotes and normative arguments about the implications of managers' incentives for investor perception, I predict and test that exposure to EM incentives is negatively associated with the ERC. I find that ERC is reliably lower for firms with elevated exposure to EM incentives, holding constant the effects of actual EM and other factors that affect the returns–earnings relation. Furthermore, the effect of the incentive exposure on cash flows as well as on total accruals is reliably negative. These results are robust across alternative price– and returns–earnings specifications, and are insensitive to the inclusion of other measures of earnings quality. Additional analysis shows that the effect of such incentives on the ERC is more pronounced at higher levels of institutional stock ownership. However, a certain class of institutional owners – transient institutions – are less sensitive to the implications of such incentives for earnings quality.     

Money and economic activity revisited

Recent literature has concluded that money no longer plays a fundamental role in determining US economic activity, especially when post-1982 data are included in the analysis. We re-examine the issue using annual and quarterly data sets ranging back to the Civil War. Cointegration tests show that an equilibrium relationship holds between money and income in all data samples of 35 years or longer, but frequently fails to hold for many shorter samples. However, when the normal monetary lags are explicitly imposed, a cointegrating relationship is frequently captured, even in quite short samples. Examining the issue in a standard five-variable VAR model, we find that money is the most important variable in explaining real output for the full 1874–1993 as well as 1952–1993 periods, even allowing for interest rate effects. Finally, using monthly data over the troublesome 1983–1994 sample, we show that when appropriate adjustments are made to capture recent structural changes, such as the growing importance of the international economy on US output, money still Granger-causes economic activity.     

Volatility transmission in emerging European foreign exchange markets

This paper studies the dynamics of volatility transmission between Central European (CE) currencies and the EUR/USD foreign exchange using model-free estimates of daily exchange rate volatility based on intraday data. We formulate a flexible yet parsimonious parametric model in which the daily realized volatility of a given exchange rate depends both on its own lags as well as on the lagged realized volatilities of the other exchange rates. We find evidence of statistically significant intra-regional volatility spillovers among the CE foreign exchange markets. With the exception of the Czech and, prior to the recent turbulent economic events, Polish currencies, we find no significant spillovers running from the EUR/USD to the CE foreign exchange markets. To measure the overall magnitude and evolution of volatility transmission over time, we construct a dynamic version of the Diebold–Yilmaz volatility spillover index and show that volatility spillovers tend to increase in periods characterized by market uncertainty.     

Deposit insurance and subsidized recapitalizations

The 2007–2009 financial crisis saw a vast expansion in deposit insurance guarantees around the world and yet our understanding of the design and consequences of deposit insurance schemes is in its infancy. We provide a new rationale for the provision of deposit insurance. In our model the banking sector exhibits both adverse selection and moral hazard, which implies that the social benefits of bank monitoring must for incentive reasons be shared between depositors and banks. Consequently, socially too few deposits are made in equilibrium. Deposit insurance – or, equivalently, bank recapitalization – corrects this market failure. We find that deposit insurance should be funded not by banks or depositors but out of general taxation. The optimal level of deposit insurance varies inversely with the quality of the banking system. Hence, when the soundness of the financial sector is uncertain, governments should consider supporting deposit insurance schemes and undertaking subsidized recapitalizations.     

The role of trading intensity estimating the implicit bid–ask spread and determining transitory effects

In this paper, we investigate the information content of trading intensity applying the Madhavan, Richardson and Roomans (1997) structural model to express trading intensity as trading momentum in duration and volume. Using both transactions and intraday data from the Helsinki Stock Exchange Limit Order Bookmarket, we find that momentum in duration and volume enhances the information effect. We reach this conclusion based on the parametric effect determined by the sign and the magnitude of the coefficients associated with the trading intensity variables, the trading effect determined by the ratio of transitory effects to permanent effects, and the economic effect determined by the size of the implicit bid–ask spread. While we find that the implicit bid–ask spread and transitory effects are decreasing toward the end of the trading day in consistency with information models in the literature, there is a surge of trades at the market close, most probably due to information uncertainty at market opening in New York.