Examining and Modeling the Dynamics of the Volatility Surface

The objective of this paper is to investigate and model the characteristics of the prevailing volatility smiles and surfaces on the DAX- and ESX-index options markets. Continuing on the trend of Implied Volatility Functions, the Standardized Log-Moneyness model is introduced and fitted to historical data. The model replaces the constant volatility parameter of the Black & Scholes pricing model with a matrix of volatilities with respect to moneyness and maturity and is tested out-of-sample. Considering the dynamics, the results show support for the hypotheses put forward in this study, implying that the smile increases in magnitude when maturity and ATM volatility decreases and that there is a negative/positive correlation between a change in the underlying asset/time to maturity and implied ATM volatility. Further, the Standardized Log-Moneyness model indicates an improvement to pricing accuracy compared to previous Implied Volatility Function models, however indicating that the parameters of the models are to be re-estimated continuously for the models to fully capture the changing dynamics of the volatility smiles.

Studies of Solids and Surfaces by Auger Electron Spectroscopy

Although the applications of Auger electron spectroscopy in surface analysis have by far outweighed its use as a tool to investigate electron states of solids and surfaces, there are a variety of situations where Auger spectroscopy provides unique information. Apart from the chemical shifts, Auger intensities are useful in determining the number of d-electron states in transition metal systems. Auger spectroscopy is a good probe to investigate the surface oxidation of metals. In addition to the intra-atomic Auger transitions, inter-atomic transitions observed in oxides and other systems reveal the nature of electron states of surfaces. Charge-transfer and hybridization effects in alloys are also usefully studied by Auger spectroscopy. Auger electron spectroscopy has not been a popular technique to investigate adsorption of molecules on surfaces, but the technique is useful to obtain fingerprints of surface species.

Study of solids and surfaces by photoacoustic spectroscopy

Photoacoustic spectroscopy has been employed to study the electronic spectra of a variety of solids. The systems studied include powders of intensely coloured dyes, amorphous chalcogenides and oxide gels besides polycrystalline samples of several oxide materials. Surface sensitivity of the technique has been examined by study of dye adsorption on oxide surfaces and determination of surface areas of active oxides. Acidic and basic sites on catalyst surfaces have also been estimated by this technique.

Photoacoustic spectroscopy of solids and surfaces

After briefly reviewing the theory and instrumentation, results from a variety of experiments carried out by the authors on the photoacoustic spectroscopy of solids and surfaces by employing an indigenous spectrometer are discussed in the light of the recent literature. Some of the important findings discussed are, phase angle spectroscopy, anomalous behaviour of monolayers, unusual frequency dependence in small cell volumes, spectra of a variety of solids including amorphous arsenic chalcogenides, photoacoustic detection of phase transitions and determination of surface areas and surface acidities of oxides. Recent developments such as piezoelectric photoacoustic spectroscopy, depth profiling and subsurface imaging are also presented.

Autorregresive conditional volatility, skewness and kurtosis

This paper proposes a GARCH-type model allowing for time-varying volatility, skewness and kurtosis. The model is estimated assuming a Gram-Charlier series expansion of the normal density function for the error term, which is easier to estimate than the non-central t distribution proposed by Harvey and Siddique (1999). Moreover, this approach accounts for time-varying skewness and kurtosis while the approach by Harvey and Siddique (1999) only accounts for nonnormal skewness. We apply this method to daily returns of a variety of stock indices and exchange rates. Our results indicate a significant presence of conditional skewness and kurtosis. It is also found that specifications allowing for time-varying skewness and kurtosis outperform specifications with constant third and fourth moments.

A Neural Theory of Visual Search: Recursive Attention to Segmentations and Surfaces

A neural theory is proposed in which visual search is accomplished by perceptual grouping and segregation, which occurs simultaneous across the visual field, and object recognition, which is restricted to a selected region of the field. The theory offers an alternative hypothesis to recently developed variations on Feature Integration Theory (Treisman, and Sato, 1991) and Guided Search Model (Wolfe, Cave, and Franzel, 1989). A neural architecture and search algorithm is specified that quantitatively explains a wide range of psychophysical search data (Wolfe, Cave, and Franzel, 1989; Cohen, and lvry, 1991; Mordkoff, Yantis, and Egeth, 1990; Treisman, and Sato, 1991).