Interest and exchange rate risk and stock returns: A multivariate GARCH-M modelling approach

In this paper we examine the sensitivity of stock returns to market, interest rate, and exchange rate risk in three financial sectors (Banking, Financial Services and Insurance) in 16 countries, including various European economies, the US and Japan. We also test for the presence of causality-in-mean and volatility spillovers. The econometric framework is a four-variate GARCH-in-mean model, which incorporates long-and short-term interest rates in turn. We find in most cases a positive effect of stock market returns on mean returns in each sector; by contrast, interest rates and exchange rates have a significant effect only in a few cases, respectively negative and without a clear sign pattern. As for the three types of risk, these are found to play a role in a minority of cases, with mixed signs. Finally, most cases of volatility spillovers occur from market return to sectoral returns in the insurance and banking sector in European economies, though there are also some instances of interest rate and exchange rate spillovers, both in Europe and the US

Liquidity risk, credit risk and the overnight interest rate spread: A stochastic volatility modelling approach

In this paper we model the volatility of the spread between the overnight interest rate and the central bank policy rate (the policy spread) for the euro area and the UK during the two main phases of the financial crisis that began in late 2007. During the crisis, the policy spread exhibited signs of volatility, owing to the breakdown in interbank market activity. The determinants of this volatility are assessed using Stochastic Volatility models to gauge the role played by liquidity risk, credit risk (financial and sovereign), and interest rate expectations. Our results suggest that liquidity risk is the main determinant of the volatility of the policy spread, but also that private bank credit risk has become more apparent in the post-Lehman collapse phase of the crisis for the euro area as financial CDS premia rose due to possible default fears. In addition, the ECB appears to have been more effective in addressing liquidity risk since the onset of the crisis, and this may be related to its greater direct access to a broader range of counterparties and its acceptance of a broader range of eligible collateral. The main implication is that, in crisis times, a sufficiently flexible operational framework for monetary policy implementation produces the most timely response to market tensions

Photometric measurements of simulated lunar surfaces Quarterly progress report, Jul. 1 - Sep. 30, 1965

Modified photometric analyzer and enlarged beam splitter for studying simulated lunar surfaces and opposition effect on moo

Photometric measurements of simulated lunar surfaces Quarterly progress report no. 2, 1 Oct. - 31 Dec. 1965

Spectral and suspended particle photometry and geometry of backscattering surfaces in study on photometric measurements of simulated lunar surface

Contemporaneous threshold autoregressive models: estimation, testing and forecasting

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finite-sample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen (1992) procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed. ; Earlier title: Contemporaneous threshold autoregressive models: estimation, forecasting and rational expectations applicationsRational expectations (Economic theory) ; Forecasting

The Actual Structure of eBay’s Feedback Mechanism and Early Evidence on the Effects of Recent Changes

eBay’s feedback mechanism is considered crucial to establishing and maintaining trust on the world’s largest trading platform. The effects of a user’s reputation on the probability of sale and on prices are at the center of a large number of studies. More recent theoretical work considers aspects of the mechanism itself. Yet, there is confusion amongst users about its exact institutional details, which also changed substantially in the last few months. An understanding of these details, and how the mechanism is perceived by users, is crucial for any assessment of the system. We provide a thorough description of the institutional setup of eBay’s feedback mechanism, including recent changes to it. Most importantly, buyers now have the possibility to leave additional, anonymous ratings on sellers on four different criteria. We discuss the implications of these changes and provide first descriptive evidence on their impact on rating behavior

Last Minute Feedback

Feedback mechanisms that allow partners to rate each other after a transaction are considered crucial for the success of anonymous internet trading platforms. We document an asymmetry in the feedback behavior on eBay, propose an explanation based on the micro structure of the feedback mechanism and the time when feedbacks are given, and support this explanation by findings from a large data set. Our analysis implies that the informational content of feedback records is likely to be low. The reason for this is that agents appear to leave feedbacks strategically. Negative feedbacks are given late, in the "last minute," or not given at all, most likely because of the fear of retaliative negative feedback. Conversely, positive feedbacks are given early in order to encourage reciprocation. Towards refining our insights into the observed pattern, we look separately at buyers and sellers, and relate the magnitude of the effects to the trading partners' experience

State-Dependent Threshold STAR Models

In this paper we consider extensions of smooth transition autoregressive (STAR) models to situations where the threshold is a time-varying function of variables that affect the separation of regimes of the time series under consideration. Our specification is motivated by the observation that unusually high/low values for an economic variable may sometimes be best thought of in relative terms. State-dependent logistic STAR and contemporaneous-threshold STAR models are introduced and discussed. These models are also used to investigate the dynamics of U.S. short-term interest rates, where the threshold is allowed to be a function of past output growth and inflation.Nonlinear autoregressive models; Smooth transition; Threshold; Interest rates.

Multivariate contemporaneous threshold autoregressive models

In this paper we propose a contemporaneous threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. The model is a multivariate generalization of the contemporaneous threshold autoregressive model introduced by Dueker et al. (2007). A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. The stability and distributional properties of the proposed model are investigated. The C-MSTAR model is also used to examine the relationship between US stock prices and interest rates.Time-series analysis ; Capital assets pricing model

Multivariate Contemporaneous-Threshold Autoregressive Models

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific innovation covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.Nonlinear autoregressive model; Smooth transition; Stability; Threshold.