1,952 research outputs found

    Pricing stock options under stochastic volatility and interest rates with efficient method of moments estimation

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    While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the Black-Scholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to first estimate a multivariate SV model using the efficient method of moments (EMM) technique from observations of underlying state variables and then investigate the respective effect of stochastic interest rates, systematic volatility and idiosyncratic volatility on option prices. We compute option prices using reprojected underlying historical volatilities and implied stochastic volatility risk to gauge each model’s performance through direct comparison with observed market option prices. Our major empirical findings are summarized as follows. First, while theory predicts that the short-term interest rates are strongly related to the systematic volatility of the consumption process, our estimation results suggest that the short-term interest rate fails to be a good proxy of the systematic volatility factor; Second, while allowing for stochastic volatility can reduce the pricing errors and allowing for asymmetric volatility or leverage effect does help to explain the skewness of the volatility smile, allowing for stochastic interest rates has minimal impact on option prices in our case; Third, similar to Melino and Turnbull (1990), our empirical findings strongly suggest the existence of a non-zero risk premium for stochastic volatility of stock returns. Based on implied volatility risk, the SV models can largely reduce the option pricing errors, suggesting the importance of incorporating the information in the options market in pricing options; Finally, both the model diagnostics and option pricing errors in our study suggest that the Gaussian SV model is not sufficient in modeling short-term kurtosis of asset returns, a SV model with fatter-tailed noise or jump component may have better explanatory power.

    FE calculations on a three stage metal forming process of Sandvik Nanoflex

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    Sandvik NanoflexTM combines good corrosion resistance with high strength. This steel has good deformability in\ud austenitic conditions. It belongs to the group of metastable austenites, which means that during deformation a strain-induced\ud transformation into martensite takes place. After deformation, transformation continues as a result of internal stresses. Both\ud transformations are stress-state and temperature dependent. A constitutive model for this steel has been formulated, based\ud on the macroscopic material behaviour measured by inductive measurements. Both the stress-assisted and the strain-induced\ud transformation into martensite have been incorporated in this model. Path-dependent work hardening has also been taken\ud into account. This article describes how the model is implemented in an internal Philips FE code called CRYSTAL, which is\ud a dedicated robust and accurate finite element solver. The implementation is based on lookup tables in combination with\ud feed-forward neural networks. The radial return method is used to determine the material state during and after plastic\ud flow, however, it has been extended to cope with the stiff character of the partial differential equation that describes the\ud transformation behaviour

    Oriënterend onderzoek naar de oorzaak van het ontstaan van bastknobbels in laanbomen op de kwekerij

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    Bastknobbels op de stam van laanbomen komen niet alleen in het stedelijk groen voor, maar ook op de boomkwekerij in jongere bomen. In een consultancy opdracht is gekeken in hoeverre er een relatie kan worden gevonden met een infectie van fytoplasma’s. Dit is in 30 gevallen onderzocht bij Fagus, Fraxinus, Aesculus en Tilia met behulp van PCR technieken. Er konden geen fytoplasma’s worden aangetoond. De oorzaak van bastknobbels blijft vooralsnog onduidelij

    COST OF SEGREGATING NON-TRANSGENIC GRAINS AT COUNTRY ELEVATORS IN SOUTH DAKOTA

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    Genetically modified grains have rapidly become popular among producers across U.S. Some consumers, particularly in the EU, South Korea, and Japan, are unwilling to purchase products containing ingredients from genetically modified or transgenic crops. This paper develops a model to represent costs of segregating non-transgenic grains at country elevators and simulates these costs at representative elevators in South Dakota under alternative scenarios employing a case study approach. The overall cost of segregating non-transgenic grains under a zero rejection rate ranged from 1.5 to 21.7, 1.2 to 11.3, and 1.3 to 16.4 cents per bushel, for corn, soybeans, and wheat, respectively.Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

    Segregating Transgenic Grains:Results of a Survey Among Country Elevators in South Dakota

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    Using responses from a mail survey conducted among 203 South Dakota grain elevator managers in 2002, we analyzed the degree to which their elevators were prepared to segregate non-transgenic from commodity grains. Results showed four percent of the managers expected their own, and ten percent expected a competing elevator be dedicated to handling only non-transgenic or identity preserved grains within five years. Only four and one percent of the elevators handled non-transgenic corn and soybeans, respectively, and only one percent participated in identity preserved grains. One in five elevator managers in the state reported having tested corn for transgenic material, and none of the respondents conducted any genetic testing for soybeans in 2001. Further, 17 and two percent reported having buyers inquire about segregated non-transgenic or identity preserved corn, and such soybeans, respectively. Among those handling corn (soybeans), 29 (30) percent was familiar with the non-transgenic corn (soybean) market and 53 (58) percent was willing to participate in these markets at an average premium of 28 (37) cents per bushel. One in five elevators are able to participate in segregating non-transgenic and commodity grains without additional capital outlays. Thus, if a sizable demand for non-transgenic grains develops, the South Dakota grain handling industry appears ready to deal with it.transgenic, grain segregation, Agricultural Experiment Station

    SEGREGATING TRANSGENIC GRAINS: RESULTS OF A SURVEY AMONG COUNTRY ELEVATORS IN SOUTH DAKOTA

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    Using responses from a mail survey conducted among 203 South Dakota grain elevator managers in 2002, we analyzed the degree to which the elevators were prepared to segregate non-transgenic from commodity grains. Only 17 and two percent reported having buyers inquire about segregated non-transgenic or identity preserved corn, and such soybeans, respectively. Among those handling corn (soybeans), 53 (58) percent were willing to participate in non-transgenic corn (soybean) markets at an average premium of 28 (37) cents per bushel. It appears that one in five elevators are able to participate in segregating non-transgenic and commodity grains without additional capital outlays.Crop Production/Industries, Research and Development/Tech Change/Emerging Technologies,

    Adding Value to South Dakota Corn: Opportunities in Food Markets

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    Pricing stock options under stochastic volatility and interest rates with efficient method of moments estimation

    Get PDF
    While the stochastic volatility (SV) generalization has been shown to improve the explanatory power over the Black-Scholes model, empirical implications of SV models on option pricing have not yet been adequately tested. The purpose of this paper is to first estimate a multivariate SV model using the efficient method of moments (EMM) technique from observations of underlying state variables and then investigate the respective effect of stochastic interest rates, systematic volatility and idiosyncratic volatility on option prices. We compute option prices using reprojected underlying historical volatilities and implied stochastic volatility risk to gauge each model’s performance through direct comparison with observed market option prices. Our major empirical findings are summarized as follows. First, while theory predicts that the short-term interest rates are strongly related to the systematic volatility of the consumption process, our estimation results suggest that the short-term interest rate fails to be a good proxy of the systematic volatility factor; Second, while allowing for stochastic volatility can reduce the pricing errors and allowing for asymmetric volatility or leverage effect does help to explain the skewness of the volatility smile, allowing for stochastic interest rates has minimal impact on option prices in our case; Third, similar to Melino and Turnbull (1990), our empirical findings strongly suggest the existence of a non-zero risk premium for stochastic volatility of stock returns. Based on implied volatility risk, the SV models can largely reduce the option pricing errors, suggesting the importance of incorporating the information in the options market in pricing options; Finally, both the model diagnostics and option pricing errors in our study suggest that the Gaussian SV model is not sufficient in modeling short-term kurtosis of asset returns, a SV model with fatter-tailed noise or jump component may have better explanatory power

    Adding Value to South Dakota Corn: Opportunities in Pet Food Markets

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