We extend the double-well potential process to a three-parameter version in order to model intraday price dynamics, with a focus on the intraday momentum and reversal. The proposed process has a parsimonious form of three parameters controlling momentum, reversal, and volatility respectively. By...

We show that updates to macroeconomic expectations among professional forecasters exhibit an offsetting pattern where increases in current-quarter predictions lead to decreases in three quarter ahead predictions. We further document evidence of individual overreaction at the quarterly frequency...

We experimentally investigate how price expectations are formed in a large asset market where subjects' only task is to forecast the future price of a risky asset. The realized prices depend on these expectations. We observe small (6 participants) and large markets (about 100 participants). In...

We propose an extension of the class of rational expectations bubbles (REBs) to the more general rational beliefs setting of Kurz (1994a,b). In a potentially non-stationary but stationarizable environment, it is possible to hold more than one (small-r) “rational” expectation. When rational...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

In our article is shown that no matter how good is the organization of the enterprises in stock market, sooner or later some financial and organizational difficulties will appear. Hence, the idea of assigning the analytical form of the logistic law based on selected financial data, enabling the...

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to ensure robustness and correct the downward bias of RS measure with an additive term. Moreover scaling factors are provided for different interquantile ranges to ensure unbiasedness....

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...