We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic Unit Root (GSTUR) model. This allows us to investigate the presence of a deterministic time trend in economic series, while allowing the degree of persistence to change over time. In particular...

This paper makes use of the novel Generalized Stochastic Unit Root (GSTUR) model, Bayesian model estimation and model comparison techniques to investigate the presence of a deterministic time trend in economic series. The model is specified to allow for changes in persistence over time, such as...

Betting exchanges allow punters to bet on a horse to lose a race. This, many argue, has opened up the sport to a new form of corruption, where races will be deliberately lost in order to profit from betting. We examine whether anecdotal evidence of the fixing of horses to lose - of which there...

Bayesian inference is developed and applied for an extended Nelson–Siegel term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson–Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. A Markov chain Monte Carlo (MCMC)...

Recent evidence suggests that the fastest algorithmic traders in financial markets profit at the expense of slower traders. One solution gaining traction is a `speed-bump', which introduces a delay between the time in which an order is submitted, and when it is processed. We conduct an impact...

Women are under-represented in many top jobs. We investigate whether biased beliefs about female ability – a form of ‘mistake-based discrimination’ – are partially responsible for this under-representation. We use more than 10 years of data on the performance of female jockeys in U.K....

Does speculative trade reduce mispricing - and help create efficient markets - or drive prices further from fundamentals? We analyse betting exchange trading, on 9,562 U.K. horse races in 2013 and 2014, to find out. Crucially, as each race is run, the fundamental value of bets is unambiguously...

A stationary bilinear (SB) model can be used to describe processes with a time-varying degree of persistence that depends on past shocks. An example of such a process is inflation. This study develops methods for Bayesian inference, model comparison, and forecasting in the SB model. Using...

We propose a Bayesian framework for nowcasting GDP growth in real time. Using vintage data on macroeconomic announcements we set up a state space system connecting latent GDP growth rates to agencies' releases of GDP and other economic indicators. We propose a Gibbs sampling scheme to filter out...

In this paper, we develop and apply Bayesian inference for an extended Nelson- Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...