Pricing and hedging short sterling options using artificial neural networks

This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging Short Sterling options. Using high frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging Short Sterling options positions using Short Sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model.

Representativity error for temperature and humidity using the Met Office high-resolution model

The observation-error covariance matrix used in data assimilation contains contributions from instrument errors, representativity errors and errors introduced by the approximated observation operator. Forward model errors arise when the observation operator does not correctly model the observations or when observations can resolve spatial scales that the model cannot. Previous work to estimate the observation-error covariance matrix for particular observing instruments has shown that it contains signifcant correlations. In particular, correlations for humidity data are more significant than those for temperature. However it is not known what proportion of these correlations can be attributed to the representativity errors. In this article we apply an existing method for calculating representativity error, previously applied to an idealised system, to NWP data. We calculate horizontal errors of representativity for temperature and humidity using data from the Met Office high-resolution UK variable resolution model. Our results show that errors of representativity are correlated and more significant for specific humidity than temperature. We also find that representativity error varies with height. This suggests that the assimilation scheme may be improved if these errors are explicitly included in a data assimilation scheme. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.

Fator estocástico de desconto: as cotas de variância, métricas de distância e suas extensões

The concept of stochastic discount factor pervades the Modern Theory of Asset Pricing. Initially, such object allows unattached pricing models to be discussed under the same terms. However, Hansen and Jagannathan have shown there is worthy information to be brought forth from such powerful concept which undelies asset pricing models. From security market data sets, one is able to explore the behavior of such random variable, determining a useful variance bound. Furthermore, through that instrument, they explore one pitfall on modern asset pricing: model misspecification. Those major contributions, alongside with some of its extensions, are thoroughly investigated in this exposition.

Pricing the option adjust spread of Brazilian Eurobonds

This paper presents results of a pricing system to compute the option adjusted spread ("DAS") of Eurobonds issued by Brazilian firms. The system computes the "DAS" over US treasury rates taktng imo account the embedded options present on these bonds. These options can be calls ("callable bond"), puts ("putable bond") or combinations ("callable and putable bond"). The pricing model takes into account the evolution of the term structure along time, is compatible with the observable market term structure and is able to compute risk measures such as duration and convexity, and pricing and hedging of options on these bonds. Examples show the ejJects of the embedded options on the spread and risk measures as well as the ejJects on the spread due to variations on the volatility parameters ofthe short rate.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Asset Pricing with Heterogeneous Agents, Incomplete Markets and Trading Constraints

The consumption capital asset pricing model is the standard economic model used to capture stock market behavior. However, empirical tests have pointed out to its inability to account quantitatively for the high average rate of return and volatility of stocks over time for plausible parameter values. Recent research has suggested that the consumption of stockholders is more strongly correlated with the performance of the stock market than the consumption of non-stockholders. We model two types of agents, non-stockholders with standard preferences and stock holders with preferences that incorporate elements of the prospect theory developed by Kahneman and Tversky (1979). In addition to consumption, stockholders consider fluctuations in their financial wealth explicitly when making decisions. Data from the Panel Study of Income Dynamics are used to calibrate the labor income processes of the two types of agents. Each agent faces idiosyncratic shocks to his labor income as well as aggregate shocks to the per-share dividend but markets are incomplete and agents cannot hedge consumption risks completely. In addition, consumers face both borrowing and short-sale constraints. Our results show that in equilibrium, agents hold different portfolios. Our model is able to generate a time-varying risk premium of about 5.5% while maintaining a low risk free rate, thus suggesting a plausible explanation for the equity premium puzzle reported by Mehra and Prescott (1985).

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

Equity pricing in the mining sector: evidence from NYSE and LSE

The study examines the Capital Asset Pricing Model (CAPM) for the mining sector using weekly stock returns from 27 companies traded on the New York Stock Exchange (NYSE) or on the London Stock Exchange (LSE) for the period of December 2008 to December 2010. The results support the use of the CAPM for the allocation of risk to companies. Most companies involved in precious metals (particularly gold), which have a beta value less than unity (Table 1), have been actuated as shelter values during the financial crisis. Values of R2 do not shown very explanatory power of fitted models (R2 < 70 %). Estimated coefficients beta are not sufficient to determine the expected returns on securities but the results of the tests conducted on sample data for the period analysed do not appear to clearly reject the CAPM

A model for turbulent combustion simulation of large scale hydrogen explosions

El agotamiento, la ausencia o, simplemente, la incertidumbre sobre la cantidad de las reservas de combustibles fósiles se añaden a la variabilidad de los precios y a la creciente inestabilidad en la cadena de aprovisionamiento para crear fuertes incentivos para el desarrollo de fuentes y vectores energéticos alternativos. El atractivo de hidrógeno como vector energético es muy alto en un contexto que abarca, además, fuertes inquietudes por parte de la población sobre la contaminación y las emisiones de gases de efecto invernadero. Debido a su excelente impacto ambiental, la aceptación pública del nuevo vector energético dependería, a priori, del control de los riesgos asociados su manipulación y almacenamiento. Entre estos, la existencia de un innegable riesgo de explosión aparece como el principal inconveniente de este combustible alternativo. Esta tesis investiga la modelización numérica de explosiones en grandes volúmenes, centrándose en la simulación de la combustión turbulenta en grandes dominios de cálculo en los que la resolución que es alcanzable está fuertemente limitada. En la introducción, se aborda una descripción general de los procesos de explosión. Se concluye que las restricciones en la resolución de los cálculos hacen necesario el modelado de los procesos de turbulencia y de combustión. Posteriormente, se realiza una revisión crítica de las metodologías disponibles tanto para turbulencia como para combustión, que se lleva a cabo señalando las fortalezas, deficiencias e idoneidad de cada una de las metodologías. Como conclusión de esta investigación, se obtiene que la única estrategia viable para el modelado de la combustión, teniendo en cuenta las limitaciones existentes, es la utilización de una expresión que describa la velocidad de combustión turbulenta en función de distintos parámetros. Este tipo de modelos se denominan Modelos de velocidad de llama turbulenta y permiten cerrar una ecuación de balance para la variable de progreso de combustión. Como conclusión también se ha obtenido, que la solución más adecuada para la simulación de la turbulencia es la utilización de diferentes metodologías para la simulación de la turbulencia, LES o RANS, en función de la geometría y de las restricciones en la resolución de cada problema particular. Sobre la base de estos hallazgos, el crea de un modelo de combustión en el marco de los modelos de velocidad de la llama turbulenta. La metodología propuesta es capaz de superar las deficiencias existentes en los modelos disponibles para aquellos problemas en los que se precisa realizar cálculos con una resolución moderada o baja. Particularmente, el modelo utiliza un algoritmo heurístico para impedir el crecimiento del espesor de la llama, una deficiencia que lastraba el célebre modelo de Zimont. Bajo este enfoque, el énfasis del análisis se centra en la determinación de la velocidad de combustión, tanto laminar como turbulenta. La velocidad de combustión laminar se determina a través de una nueva formulación capaz de tener en cuenta la influencia simultánea en la velocidad de combustión laminar de la relación de equivalencia, la temperatura, la presión y la dilución con vapor de agua. La formulación obtenida es válida para un dominio de temperaturas, presiones y dilución con vapor de agua más extenso de cualquiera de las formulaciones previamente disponibles. Por otra parte, el cálculo de la velocidad de combustión turbulenta puede ser abordado mediante el uso de correlaciones que permiten el la determinación de esta magnitud en función de distintos parámetros. Con el objetivo de seleccionar la formulación más adecuada, se ha realizado una comparación entre los resultados obtenidos con diversas expresiones y los resultados obtenidos en los experimentos. Se concluye que la ecuación debida a Schmidt es la más adecuada teniendo en cuenta las condiciones del estudio. A continuación, se analiza la importancia de las inestabilidades de la llama en la propagación de los frentes de combustión. Su relevancia resulta significativa para mezclas pobres en combustible en las que la intensidad de la turbulencia permanece moderada. Estas condiciones son importantes dado que son habituales en los accidentes que ocurren en las centrales nucleares. Por ello, se lleva a cabo la creación de un modelo que permita estimar el efecto de las inestabilidades, y en concreto de la inestabilidad acústica-paramétrica, en la velocidad de propagación de llama. El modelado incluye la derivación matemática de la formulación heurística de Bauwebs et al. para el cálculo de la incremento de la velocidad de combustión debido a las inestabilidades de la llama, así como el análisis de la estabilidad de las llamas con respecto a una perturbación cíclica. Por último, los resultados se combinan para concluir el modelado de la inestabilidad acústica-paramétrica. Tras finalizar esta fase, la investigación se centro en la aplicación del modelo desarrollado en varios problemas de importancia para la seguridad industrial y el posterior análisis de los resultados y la comparación de los mismos con los datos experimentales correspondientes. Concretamente, se abordo la simulación de explosiones en túneles y en contenedores, con y sin gradiente de concentración y ventilación. Como resultados generales, se logra validar el modelo confirmando su idoneidad para estos problemas. Como última tarea, se ha realizado un analisis en profundidad de la catástrofe de Fukushima-Daiichi. El objetivo del análisis es determinar la cantidad de hidrógeno que explotó en el reactor número uno, en contraste con los otros estudios sobre el tema que se han centrado en la determinación de la cantidad de hidrógeno generado durante el accidente. Como resultado de la investigación, se determinó que la cantidad más probable de hidrogeno que fue consumida durante la explosión fue de 130 kg. Es un hecho notable el que la combustión de una relativamente pequeña cantidad de hidrogeno pueda causar un daño tan significativo. Esta es una muestra de la importancia de este tipo de investigaciones. Las ramas de la industria para las que el modelo desarrollado será de interés abarca la totalidad de la futura economía de hidrógeno (pilas de combustible, vehículos, almacenamiento energético, etc) con un impacto especial en los sectores del transporte y la energía nuclear, tanto para las tecnologías de fisión y fusión. ABSTRACT The exhaustion, absolute absence or simply the uncertainty on the amount of the reserves of fossil fuels sources added to the variability of their prices and the increasing instability and difficulties on the supply chain are strong incentives for the development of alternative energy sources and carriers. The attractiveness of hydrogen in a context that additionally comprehends concerns on pollution and emissions is very high. Due to its excellent environmental impact, the public acceptance of the new energetic vector will depend on the risk associated to its handling and storage. Fromthese, the danger of a severe explosion appears as the major drawback of this alternative fuel. This thesis investigates the numerical modeling of large scale explosions, focusing on the simulation of turbulent combustion in large domains where the resolution achievable is forcefully limited. In the introduction, a general description of explosion process is undertaken. It is concluded that the restrictions of resolution makes necessary the modeling of the turbulence and combustion processes. Subsequently, a critical review of the available methodologies for both turbulence and combustion is carried out pointing out their strengths and deficiencies. As a conclusion of this investigation, it appears clear that the only viable methodology for combustion modeling is the utilization of an expression for the turbulent burning velocity to close a balance equation for the combustion progress variable, a model of the Turbulent flame velocity kind. Also, that depending on the particular resolution restriction of each problem and on its geometry the utilization of different simulation methodologies, LES or RANS, is the most adequate solution for modeling the turbulence. Based on these findings, the candidate undertakes the creation of a combustion model in the framework of turbulent flame speed methodology which is able to overcome the deficiencies of the available ones for low resolution problems. Particularly, the model utilizes a heuristic algorithm to maintain the thickness of the flame brush under control, a serious deficiency of the Zimont model. Under the approach utilized by the candidate, the emphasis of the analysis lays on the accurate determination of the burning velocity, both laminar and turbulent. On one side, the laminar burning velocity is determined through a newly developed correlation which is able to describe the simultaneous influence of the equivalence ratio, temperature, steam dilution and pressure on the laminar burning velocity. The formulation obtained is valid for a larger domain of temperature, steam dilution and pressure than any of the previously available formulations. On the other side, a certain number of turbulent burning velocity correlations are available in the literature. For the selection of the most suitable, they have been compared with experiments and ranked, with the outcome that the formulation due to Schmidt was the most adequate for the conditions studied. Subsequently, the role of the flame instabilities on the development of explosions is assessed. Their significance appears to be of importance for lean mixtures in which the turbulence intensity remains moderate. These are important conditions which are typical for accidents on Nuclear Power Plants. Therefore, the creation of a model to account for the instabilities, and concretely, the acoustic parametric instability is undertaken. This encloses the mathematical derivation of the heuristic formulation of Bauwebs et al. for the calculation of the burning velocity enhancement due to flame instabilities as well as the analysis of the stability of flames with respect to a cyclic velocity perturbation. The results are combined to build a model of the acoustic-parametric instability. The following task in this research has been to apply the model developed to several problems significant for the industrial safety and the subsequent analysis of the results and comparison with the corresponding experimental data was performed. As a part of such task simulations of explosions in a tunnel and explosions in large containers, with and without gradient of concentration and venting have been carried out. As a general outcome, the validation of the model is achieved, confirming its suitability for the problems addressed. As a last and final undertaking, a thorough study of the Fukushima-Daiichi catastrophe has been carried out. The analysis performed aims at the determination of the amount of hydrogen participating on the explosion that happened in the reactor one, in contrast with other analysis centered on the amount of hydrogen generated during the accident. As an outcome of the research, it was determined that the most probable amount of hydrogen exploding during the catastrophe was 130 kg. It is remarkable that the combustion of such a small quantity of material can cause tremendous damage. This is an indication of the importance of these types of investigations. The industrial branches that can benefit from the applications of the model developed in this thesis include the whole future hydrogen economy, as well as nuclear safety both in fusion and fission technology.

Forecasting stock returns using model-selection criteria

This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

Quantifying the effects of temperature and concentration on variable-density flow in numerical modeling of groundwater systems: Implications for predictive uncertainty and data collection

Groundwater systems of different densities are often mathematically modeled to understand and predict environmental behavior such as seawater intrusion or submarine groundwater discharge. Additional data collection may be justified if it will cost-effectively aid in reducing the uncertainty of a model's prediction. The collection of salinity, as well as, temperature data could aid in reducing predictive uncertainty in a variable-density model. However, before numerical models can be created, rigorous testing of the modeling code needs to be completed. This research documents the benchmark testing of a new modeling code, SEAWAT Version 4. The benchmark problems include various combinations of density-dependent flow resulting from variations in concentration and temperature. The verified code, SEAWAT, was then applied to two different hydrological analyses to explore the capacity of a variable-density model to guide data collection. ^ The first analysis tested a linear method to guide data collection by quantifying the contribution of different data types and locations toward reducing predictive uncertainty in a nonlinear variable-density flow and transport model. The relative contributions of temperature and concentration measurements, at different locations within a simulated carbonate platform, for predicting movement of the saltwater interface were assessed. Results from the method showed that concentration data had greater worth than temperature data in reducing predictive uncertainty in this case. Results also indicated that a linear method could be used to quantify data worth in a nonlinear model. ^ The second hydrological analysis utilized a model to identify the transient response of the salinity, temperature, age, and amount of submarine groundwater discharge to changes in tidal ocean stage, seasonal temperature variations, and different types of geology. The model was compared to multiple kinds of data to (1) calibrate and verify the model, and (2) explore the potential for the model to be used to guide the collection of data using techniques such as electromagnetic resistivity, thermal imagery, and seepage meters. Results indicated that the model can be used to give insight to submarine groundwater discharge and be used to guide data collection. ^

Personality and performance: Assessing the mediating role of mental model formation in the personality-performance relationship

Personality has long been linked to performance. Evolutions in this relationship have brought forward new questions regarding the true nature of how personality impacts performance. Both direct and indirect relationships have been proven significant. This study further investigated potential indirect relationships by including a mediating variable, mental model formation, in the personality-performance relationship. Undergraduate students were assessed in a 6-week period, Time 1 - Time 2 experiment. Conceptualizations of personality included measures of the Big 5 model and Self-efficacy, with performance measured by content quiz and overall course scores. Findings showed that the Big 5 personality traits, extraversion and agreeableness, positively and significantly impacted commonality with the instructor's mental model. However, commonality with the instructor's mental model did not impact performance. In comparison, commonality with an expert mental model positively and significantly impacted performance for both the content quiz and overall course score. Furthermore, similarity with an expert mental model positively and significantly impacted overall course performance. Hypothesized full mediation of mental model formation for the personality-performance relationship was not supported due to a lack of direct effect relationships required for mediation. However, a revised conceptualization of results emerged. Findings from the current study point to the novel and unique role mental models play in the personality-performance relationship. While personality traits do impact mental model formation, accuracy in the mental models formed is critical to performance.

Incorporating variable peak -to -daily ratios in the equilibrium traffic assignment procedure of the Florida Standard Urban Transportation Modeling Structure (FSUTMS)

The standard highway assignment model in the Florida Standard Urban Transportation Modeling Structure (FSUTMS) is based on the equilibrium traffic assignment method. This method involves running several iterations of all-or-nothing capacity-restraint assignment with an adjustment of travel time to reflect delays encountered in the associated iteration. The iterative link time adjustment process is accomplished through the Bureau of Public Roads (BPR) volume-delay equation. Since FSUTMS' traffic assignment procedure outputs daily volumes, and the input capacities are given in hourly volumes, it is necessary to convert the hourly capacities to their daily equivalents when computing the volume-to-capacity ratios used in the BPR function. The conversion is accomplished by dividing the hourly capacity by a factor called the peak-to-daily ratio, or referred to as CONFAC in FSUTMS. The ratio is computed as the highest hourly volume of a day divided by the corresponding total daily volume. ^ While several studies have indicated that CONFAC is a decreasing function of the level of congestion, a constant value is used for each facility type in the current version of FSUTMS. This ignores the different congestion level associated with each roadway and is believed to be one of the culprits of traffic assignment errors. Traffic counts data from across the state of Florida were used to calibrate CONFACs as a function of a congestion measure using the weighted least squares method. The calibrated functions were then implemented in FSUTMS through a procedure that takes advantage of the iterative nature of FSUTMS' equilibrium assignment method. ^ The assignment results based on constant and variable CONFACs were then compared against the ground counts for three selected networks. It was found that the accuracy from the two assignments was not significantly different, that the hypothesized improvement in assignment results from the variable CONFAC model was not empirically evident. It was recognized that many other factors beyond the scope and control of this study could contribute to this finding. It was recommended that further studies focus on the use of the variable CONFAC model with recalibrated parameters for the BPR function and/or with other forms of volume-delay functions. ^

Three dimensional circulation of water with variable wind in the Caspian Sea

This research is based on a numerical model for forecasting the three-dimensional behavior of (sea) water motion due to the effect of a variable wind velocity. The results obtained are then analyzed and compared with observation. This model is based on the equations that overcome the current and distribution of temperature by applying the method of finite difference with assuming Δx, Δy as constant and Δz, variable. The model is based on the momentum equation, continuity equation and thermodynamic energy equation and tension at the surface and middle layers and bottom stress. The horizontal and vertical eddy viscosity and thermal diffusivity coefficients we used in accordance with that of the Bennet on Outario Lake (1977). Considering the Caspian Sea dimension in numerical model the Coriolis parameter used with β effects and the approximation Boussines have been used. For the program controlling some simple experiment with boundary condition similar to that of the Caspian Sea have been done. For modeling the Caspian Sea the grid of the field was done as follows: At horizontal surface grid size is 10×10km extension and at vertical in 10 layers with varying thickness from surface to bed respectively as: 5, 10, 20, 3, 50, 100, 150, 200, 25, 500 and higher. The data of wind as velocity، direction and temperature of water related to 15th September 1995 at 6،12 and 18 o’clock were obtained from synoptic station at the Caspian Sea shore and the research marine of Haji Alief. The information concerning shore wind was measured and by the method of SPM (shore protection manual) was transferred to far shore winds through interpolation and by use of inverse square distance of position distribution of the wind velocity at the Caspian surface field was obtained. The model has been evaluated according to the reports and observations. Through studying the position of the current in different layers، the velocity in the cross section in the northern، southern and the middle layers، will be discussed. The results reveal the presence of the circulation cells in the three above mentioned areas. The circulation with depth is reduced too. The results obtained through the numerical solution of the temperature equation have been compared with the observation. The temperature change in different layers in cross section illustrates the relative accordance of the model mentioned.