Decoherence Functional and Inhomogeneities in the Early Universe

We investigate the quantum to classical transition of small inhomogeneous fluctuations in the early Universe using the decoherence functional of Gell-Mann and Hartle. We study two types of coarse graining; one due to coarse graining the value of the scalar field and the other due to summing over an environment. We compare the results with a previous study using an environment and the off-diagonal rule proposed by Zurek. We show that the two methods give different results.Comment: 15 pages in plain te

Comparison of Field Theory Models of Interest Rates with Market Data

We calibrate and test various variants of field theory models of the interest rate with data from eurodollars futures. A model based on a simple psychological factor are seen to provide the best fit to the market. We make a model independent determination of the volatility function of the forward rates from market data.Comment: 9 figure

Entropy and Uncertainty of Squeezed Quantum Open Systems

We define the entropy S and uncertainty function of a squeezed system interacting with a thermal bath, and study how they change in time by following the evolution of the reduced density matrix in the influence functional formalism. As examples, we calculate the entropy of two exactly solvable squeezed systems: an inverted harmonic oscillator and a scalar field mode evolving in an inflationary universe. For the inverted oscillator with weak coupling to the bath, at both high and low temperatures, $S\to r$, where r is the squeeze parameter. In the de Sitter case, at high temperatures, $S\to (1-c)r$ where $c = \gamma_0/H$, $\gamma_0$ being the coupling to the bath and H the Hubble constant. These three cases confirm previous results based on more ad hoc prescriptions for calculating entropy. But at low temperatures, the de Sitter entropy $S\to (1/2-c)r$ is noticeably different. This result obtained from a more rigorous approach, shows that factors usually ignored by the conventional approaches, i.e., the nature of the environment and the coupling strength betwen the system and the environment, are important

Option Pricing from Wavelet-Filtered Financial Series

We perform wavelet decomposition of high frequency financial time series into large and small time scale components. Taking the FTSE100 index as a case study, and working with the Haar basis, it turns out that the small scale component defined by most ($\simeq$ 99.6%) of the wavelet coefficients can be neglected for the purpose of option premium evaluation. The relevance of the hugely compressed information provided by low-pass wavelet-filtering is related to the fact that the non-gaussian statistical structure of the original financial time series is essentially preserved for expiration times which are larger than just one trading day.Comment: 4 pages, 1 figur