Model Risk for European-Style Stock Index Options

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning     

Pricing and hedging derivative securities with neural networks:Bayesian regularization, early stopping, and bagging

We study the effectiveness of cross validation, Bayesian regularization, early stopping, and bagging to mitigate overfitting and improving generalization for pricing and hedging derivative securities with daily S&P 500 index daily call options from January 1988 to December 1993. Our results indicate that Bayesian regularization can generate significantly smaller pricing and delta-hedging errors than the baseline neural-network (NN) model and the Black-Scholes model for some years. While early stopping does not affect the pricing errors, it significantly reduces the hedging error (HE) in four of the six years we investigated. Although computationally most demanding, bagging seems to provide the most accurate pricing and delta hedging. Furthermore, the standard deviation of the MSPE of bagging is far less than that of the baseline model in all six years, and the standard deviation of the average HE of bagging is far less than that of the baseline model in five out of six years. We conclude that they be used at least in cases when no appropriate hints are available.     

Species distribution,molecular characteristics and vancomycin resistance gene profiles of Enterococcus sp. isolates from farmhouse cheeses in western Turkey

Species distribution, virulence traits and vancomycin resistance gene profiles of Enterococcus isolated from 43 home‐made artisan cheese samples collected from open markets, located in Aydin region of Turkey, were investigated. Of the 129 isolates, 95 were identified as Enterococcus sp.; Enterococcus faecium being the most prevalent species (82.1%), followed by Enterococcus faecalis (13.6%) and Enterococcus durans (1.0%). None of the enterococci were harbouring vanA or vanC, while seven isolates (7.3%) were shown to harbour vanB gene by multiplex PCR. gelE (49.4%) being the most prevalent virulence factor was followed by asa1 (27.3%), esp (22.1%), cylA (4.2%) and hyl (3.1%).     

Option Pricing With Modular Neural Networks

This paper investigates a nonparametric modular neural network (MNN) model to price the S&P-500 European call options. The modules are based on time to maturity and moneyness of the options. The option price function of interest is homogeneous of degree one with respect to the underlying index price and the strike price. When compared to an array of parametric and nonparametric models, the MNN method consistently exerts superior out-of-sample pricing performance. We conclude that modularity improves the generalization properties of standard feedforward neural network option pricing models (with and without the homogeneity hint).     

Mesophase AR pitch derived carbon foam: Effect of temperature, pressure and pressure release time

For the carbon foam production, mesophase pitch pellets are heated up in a reactor in an aluminum mold to specified pressures and finally pressure released to obtain green carbon foam samples. The green foams were then stabilized and carbonized. The effects of various temperatures, pressures and pressure release times on production of carbons foams are investigated. The samples are subjected to SEM, mechanical testing, mercury porosimetry analysis and bulk density determination for characterization. For the processing temperatures of 553, 556, 566 and 573 K, the densities of the foams produced were 380, 390, 410 and 560 kg/m³ respectively. The compressive strengths of the respective samples were increased from 1.47, to 3.31 MPa for the lowest and highest temperatures. The processing pressures were 3.8, 5.8, 6.8 and 7.8 MPa. The bulk density and the compressive strength of the carbon foams produced were changed from 500 to 580 kg/m³, and 1.87 to 3.52 MPa for the lowest and highest pressures respectively. Pressure release times of 5 s, 80 s, 160 s and 600 s are used to produce different carbon foam samples. The densities and the comprehensive strengths measured for the highest and lowest pressure release times changed from 560 to 240 kg/m³ and 3.31 to 2.16 MPa respectively. The pore size distribution of all of the products changed between 0.052×10^-6m and 120×10^-6m. Increase in temperature and pressure increased the bulk density and compressive strength of the carbon foams. The mercury porosimetry results show % porosity increase with increasing temperature and pressure. On the other hand, increase in pressure release time decreased the bulk density, compressive strength of the carbon foam.     

New production process for insulation blocks composed of EPS and lightweight concrete containing pumice aggregate

This study introduces a new production method for production of the insulation blocks made of pumice aggregate, lightweight concrete and expanded polystyrene foam (EPS). Products produced via this method were analyzed for compliance with the Turkish standards institution (TS EN) standards. A single-line lightweight masonry block with 200?mm?×?400?mm?×?200?mm dimension (width?×?length?×?height) was produced to produce an insulation block by using circular saw block cutting machine for the first time. Physical and thermal properties of the all-in aggregate pumice used in lightweight aggregate were determined and the all-in aggregate pumice was subjected to sieve analysis. After the production, insulation blocks were subjected to some analysis according to pre-set standards to determine their usability as masonry unit. After the curing period (28?days), it was found that the highest value of deviation from the plane was 0.150?mm; deviation of the flanges from plain parallelism was 0.40?mm; dry density was 562?kg/m³; compressive strength value was 2.99?N/mm²; water absorption coefficient by capillaries was 20.63?g/mm²sn^0.5; sound absorption value of the masonry unit was 60 (dB); thermal conductivity coefficient was 0.33?W/mK; initial shear strength value was 0.471?N/mm² and plaster-holding capacity was considerably high. When compared to other construction elements, thermal conductivity and masonry unit weight of the insulation block and masonry costs were found to be lower.     

Characterization of acidic pumice and determination of its electrokinetic properties in water

In this study some characterization tests of acidic pumice were performed using various techniques such as Mercury Intrusion Porosimetry (MIP), Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD), Thermal Analysis (DTA–TG), FTIR and its electrokinetic properties in water such as zeta potential (ZP), isoelectrical point (IEP), indifferent, specifically adsorbing and potential determining ions were determined. The results showed that (i) pore dimensions of the irregular or oval and fibrous cavities of the pumice varied between 0.05 μm and 2 mm depending on its particle size and these cavities usually did not intersect each other; (ii) as the pumice particle size decreases, both total pore volume and total pore surface area significantly decrease as well; (iii) pumice maintained its thermal stability approximately up to 900 °C; (iv) pumice had a negative surface charge between pH 1.8 and 11.4; and (v) Cl^?, Br^? SO₄^2?, Na⁺, Al(OH)₂⁺ and Ca²⁺ ions were indifferent, C₁₆H₃₃(CH₃)₃N⁺, Al³⁺ and Al(OH)²⁺ cations were specifically adsorbing and, H⁺ and OH^? ions were potential determining ions for acidic pumice.     

Applications of glaze and decor on dimensioned andesites used in construction sector

This report presents initial results of the development process of a new product using andesites obtained from Afyon/Iscehisar region as an alternative to traditional ceramic wall and floor tiles used in construction sector. The series of characterization tests were conducted on andesite samples. Then, the samples were applied glaze for trial purposes. Analysis indicated that the andesite samples consisted of sanidine, mica and pyroxene minerals and its apparent porosity, density, water absorption and compressive strength values were 15.75%, 2610 g/cm³, 7.43% and 40.7 MPa, respectively. In heat microscope measurements, maximum sintering was recorded at 1138 °C. Linear expansion coefficient (α) of the andesite at 400 °C was 3.26 × 10^?6 K^?1. Firing performed by using the prepared glaze recipe at approximately 1160 °C produced good results in terms of body-glaze harmony. In addition, different decorative surface finishes to be used in indoor and outdoor spaces were obtained via under glaze decorative technique.