18,839 research outputs found

    The Role of Non-Parity Fundamentals in Exchange Rate Determination: Australia and the Asia Pacific Region

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    This paper extends the literature by looking at the contribution of non-parity variables after extracting the impact of parity variables on exchange rates of Australia and the Asia Pacific countries. Exchange rates are examined using high- and low-frequency multi-country panel time series data for a group of trade-related nations in the Asia Pacific, including Japan. Our findings suggest that exchange rate is affected by growth rate, and trade and capital flows: other less significant variables include sovereign debt; balance of payments; money supply; and trade openness. It also confirms that interest rate has significant effect on exchange rates while price effect is not significant in short run regressions. These key findings are robust across different time intervals, thus showing new findings on the exchange rate dynamics consistent with theories.

    Bayesian Analysis of the Stochastic Conditional Duration Model

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    A Bayesian Markov Chain Monte Carlo methodology is developed for estimating the stochastic conditional duration model. The conditional mean of durations between trades is modelled as a latent stochastic process, with the conditional distribution of durations having positive support. The sampling scheme employed is a hybrid of the Gibbs and Metropolis Hastings algorithms, with the latent vector sampled in blocks. The suggested approach is shown to be preferable to the quasi-maximum likelihood approach, and its mixing speed faster than that of an alternative single-move algorithm. The methodology is illustrated with an application to Australian intraday stock market data.Transaction data, Latent factor model, Non-Gaussian state space model, Kalman filter and simulation smoother.

    Theory of Combined Photoassociation and Feshbach Resonances in a Bose-Einstein Condensate

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    We model combined photoassociation and Feshbach resonances in a Bose-Einstein condensate, where the shared dissociation continuum allows for quantum interference in losses from the condensate, as well as a dispersive-like shift of resonance. A simple analytical model, based on the limit of weakly bound molecules, agrees well with numerical experiments that explicitly include dissociation to noncondensate modes. For a resonant laser and an off-resonant magnetic field, constructive interference enables saturation of the photoassociation rate at user-friendly intensities, at a value set by the interparticle distance. This rate limit is larger for smaller condensate densities and, near the Feshbach resonance, approaches the rate limit for magnetoassociation alone. Also, we find agreement with the unitary limit--set by the condensate size--only for a limited range of near-resonant magnetic fields. Finally, for a resonant magnetic field and an off-resonant laser, magnetoassociation displays similar quantum interference and a dispersive-like shift. Unlike photoassociation, interference and the fieldshift in resonant magnetoassociation is tunable with both laser intensity and detuning. Also, the dispersive-like shift of the Feshbach resonance depends on the size of the Feshbach molecule, and is a signature of non-universal physics in a strongly interacting system.Comment: 10 pages, 5 figures, 82 reference

    Inhibition of Intestinal Thiamin Transport in Rat Model of Sepsis.

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    ObjectivesThiamin deficiency is highly prevalent in patients with sepsis, but the mechanism by which sepsis induces thiamin deficiency is unknown. This study aimed to determine the influence of various severity of sepsis on carrier-mediated intestinal thiamin uptake, level of expressions of thiamin transporters (thiamin transporter-1 and thiamin transporter-2), and mitochondrial thiamin pyrophosphate transporter.DesignRandomized controlled study.SettingResearch laboratory at a Veterans Affairs Medical Center.SubjectsTwenty-four Sprague-Dawley rats were randomized into controls, mild, moderate, and severe sepsis with equal number of animals in each group.InterventionsSepsis was induced by cecal ligation and puncture with the cecum ligated below the cecal valve at 25%, 50%, and 75% of cecal length, defined as severe, moderate, and mild sepsis, respectively. Control animals underwent laparotomy only.Measurements and main resultsAfter 2 days of induced sepsis, carrier-mediated intestinal thiamin uptake was measured using [H]thiamin. Expressions of thiamin transporter-1, thiamin transporter-2, and mitochondrial thiamin pyrophosphate transporter proteins and messenger RNA were measured. Proinflammatory cytokines (interleukin-1β and interleukin-6) and adenosine triphosphate were also measured. Sepsis inhibited [H]thiamin uptake, and the inhibition was a function of sepsis severity. Both cell membrane thiamin transporters and mitochondrial thiamin pyrophosphate transporter expression levels were suppressed; also levels of adenosine triphosphate in the intestine of animals with moderate and severe sepsis were significantly lower than that of sham-operated controls.ConclusionsFor the first time, we demonstrated that sepsis inhibited carrier-mediated intestinal thiamin uptake as a function of sepsis severity, suppressed thiamin transporters and mitochondrial thiamin pyrophosphate transporter, leading to adenosine triphosphate depletion

    Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices: Application of a Bivariate Kalman Filter

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    In this paper Bayesian methods are applied to a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Posterior densities for all model parameters, latent volatilities and the market price of volatility risk are produced via a hybrid Markov Chain Monte Carlo sampling algorithm. Candidate draws for the unobserved volatilities are obtained by applying the Kalman filter and smoother to a linearization of a state-space representation of the model. The method is illustrated using the Heston (1993) stochastic volatility model applied to Australian News Corporation spot and option price data. Alternative models nested in the Heston framework are ranked via Bayes Factors and via fit, predictive and hedging performance.Option Pricing; Volatility Risk; Markov Chain Monte Carlo; Nonlinear State Space Model; Kalman Filter and Smoother.

    Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models

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    The impact of parameterisation on the simulation efficiency of Bayesian Markov chain Monte Carlo (MCMC) algorithms for two non-Gaussian state space models is examined. Specifically, focus is given to particular forms of the stochastic conditional duration (SCD) model and the stochastic volatility (SV) model, with four alternative parameterisations of each model considered. A controlled experiment using simulated data reveals that relationships exist between the simulation efficiency of the MCMC sampler, the magnitudes of the population parameters and the particular parameterisation of the state space model. Results of an empirical analysis of two separate transaction data sets for the SCD model, as well as equity and exchange rate data sets for the SV model, are also reported. Both the simulation and empirical results reveal that substantial gains in simulation efficiency can be obtained from simple reparameterisations of both types of non-Gaussian state space models.Bayesian methodology, stochastic volatility, durations, non-centred in location, non-centred in scale, inefficiency factors.

    Implicit Bayesian Inference Using Option Prices

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    A Bayesian approach to option pricing is presented, in which posterior inference about the underlying returns process is conducted implicitly via observed option prices. A range of models allowing for conditional leptokurtosis, skewness and time-varying volatility in returns are considered, with posterior parameter distributions and model probabilities backed out from the option prices. Models are ranked according to several criteria, including out-of-sample fit, predictive and hedging performance. The methodology accommodates heteroscedasticity and autocorrelation in the option pricing errors, as well as regime shifts across contract groups. The method is applied to intraday option price data on the S&P500 stock index for 1995. Whilst the results provide support for models which accommodate leptokurtosis, no one model dominates according to all criteria considered.Bayesian Option Pricing; Leptokurtosis; Skewness; GARCH Option Pricing; Option Price Prediction; Hedging Errors.
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