period ahead; in the Volatility treatment, we also elicit subjective confidence intervals of forecasts, which we take as a … measure of perceived volatility. The realized asset price is derived from a Walrasian market equilibrium equation with non …-linear feedback from individual forecasts. Our experimental markets exhibit high volatility, fat tails and other properties typical of …

, with technical analysts conditioning their forecastingrule upon deviations from a benchmark fundamental. Volatility …

equilibrium exists and the agents' optimal trading strategies are constant. Affine processes, and the theory of information … are obtained and applied to numerically analyze the impact of the agents' risk aversion on the implied volatility of …

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean …(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable … Stochastic Volatility (SV)model. However, efficient Monte Carlo simulationmethods for SV models have been developed to overcome …

-variance analysis of alternative investments has been hampered by the lack of a systematic treatment of volatility in these markets … underlying volatility. For example, in art markets, auction houses often give price guarantees to the seller that resemble put … the price index, allowing to treat the volatility parameter as the object of interest. The model can be estimated using …

on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new … directions. First, the realized variance is a much better estimate of the latent volatility than the sum of the weighted daily … squared returns. As such it is better suited for comparing the out-of-sample performances of competing volatility models …

achieve similar volatility than fully deregulated labor markets. Flexibility at the margin produces a gap in separation costs … de labor market volatility. This increased volatility is partially reverted when limitations in the duration and number … explain the similar volatility observed in many regulated OECD labor markets with flexibility at the margin vis-à-vis the …

Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components … forecasts which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo …

forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo … linear compared to optimal forecasts is small. Extending the number of volatility components beyond what is feasible with MLE …