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Model Based Monte Carlo Pricing Of Energy And Temperature Quanto Options
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Book Synopsis Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options by : Massimiliano Caporin
Download or read book Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options written by Massimiliano Caporin and published by . This book was released on 2014 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Weather derivatives have become very popular tools in weather risk management in recent years. One of the elements supporting their diffusion has been the increase in volatility observed on many energy markets. Among the several available contracts, Quanto options are now becoming very popular for a simple reason: they take into account the strong correlation between energy consumption and certain weather conditions, so enabling price and weather risk to be controlled at the same time. These products are more efficient and, in many cases, significantly cheaper than simpler plain vanilla options. Unfortunately, the specific features of energy and weather time series do not enable the use of analytical formulae based on the Black-Scholes pricing approach, nor other more advanced continuous time methods that extend the Black-Scholes approach, unless under strong and unrealistic assumptions. In this study, we propose a Monte Carlo pricing framework based on a bivariate time series model. Our approach takes into account the average and variance interdependence between temperature and energy price series. Furthermore, our approach includes other relevant empirical features, such as periodic patterns in average, variance, and correlations. The model structure enables a more appropriate pricing of Quanto options compared to traditional methods.
Book Synopsis Modeling and Pricing in Financial Markets for Weather Derivatives by : Fred Espen Benth
Download or read book Modeling and Pricing in Financial Markets for Weather Derivatives written by Fred Espen Benth and published by World Scientific. This book was released on 2013 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: Weather derivatives provide a tool for weather risk management, and the markets for these exotic financial products are gradually emerging in size and importance. This unique monograph presents a unified approach to the modeling and analysis of such weather derivatives, including financial contracts on temperature, wind and rain. Based on a deep statistical analysis of weather factors, sophisticated stochastic processes are introduced modeling the time and space dynamics. Applying ideas from the modern theory of mathematical finance, weather derivatives are priced, and questions of hedging analyzed. The treatise contains an in-depth analysis of typical weather contracts traded at the Chicago Mercantile Exchange (CME), including so-called CDD and HDD futures. The statistical analysis of weather variables are based on a large data set from Lithuania. The monograph includes the research done by the authors over the last decade on weather markets. Their work has gained considerable attention, and has been applied in many contexts.
Book Synopsis Economic Modeling Using Artificial Intelligence Methods by : Tshilidzi Marwala
Download or read book Economic Modeling Using Artificial Intelligence Methods written by Tshilidzi Marwala and published by Springer Science & Business Media. This book was released on 2013-04-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners.
Book Synopsis Monte Carlo Valuation of Energy Options by : Wen-Yu Liao
Download or read book Monte Carlo Valuation of Energy Options written by Wen-Yu Liao and published by . This book was released on 2008 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Issues in Energy Research and Application: 2013 Edition by :
Download or read book Issues in Energy Research and Application: 2013 Edition written by and published by ScholarlyEditions. This book was released on 2013-05-01 with total page 1186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Energy Research and Application / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Energy Economics. The editors have built Issues in Energy Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Energy Economics in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Energy Research and Application: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Book Synopsis Monte Carlo Methods by : Thomas B. Hall
Download or read book Monte Carlo Methods written by Thomas B. Hall and published by . This book was released on 2020 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this compilation, the authors first consider applying the Monte Carlo method to the general form of the heat equation that is used for analyzing conduction heat transfer. The Monte Carlo method is then extended to some convection heat transfer applications by representing the probabilistic interpretation of the energy equation to obtain the temperature profile.Following this, Monte Carlo Methods: History and Applications discusses the Monte Carlo methods needed for the estimation of the mean glandular dose in both digital mammography and digital breast tomosynthesis. Various breast anatomies are considered.The gradual development of the Monte Carlo method for solving problems of mathematical chemistry is considered. A comparison of various quantitative structure-property/activity relationships based on the Monte Carlo method is also presented.Lastly, the Monte Carlo technique is used to characterize the statistical distributions of received measurements in an electric energy power system, as well as to quantify the correlations among these variables. To check the numerical accuracy of the results, the point estimate algorithm is employed.
Book Synopsis A Guide to Monte Carlo Simulations in Statistical Physics by : David Landau
Download or read book A Guide to Monte Carlo Simulations in Statistical Physics written by David Landau and published by Cambridge University Press. This book was released on 2021-07-29 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
Book Synopsis Monte Carlo Methods in Statistical Physics by : Kurt Binder
Download or read book Monte Carlo Methods in Statistical Physics written by Kurt Binder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the seven years since this volume first appeared. there has been an enormous expansion of the range of problems to which Monte Carlo computer simulation methods have been applied. This fact has already led to the addition of a companion volume ("Applications of the Monte Carlo Method in Statistical Physics", Topics in Current Physics. Vol . 36), edited in 1984, to this book. But the field continues to develop further; rapid progress is being made with respect to the implementation of Monte Carlo algorithms, the construction of special-purpose computers dedicated to exe cute Monte Carlo programs, and new methods to analyze the "data" generated by these programs. Brief descriptions of these and other developments, together with numerous addi tional references, are included in a new chapter , "Recent Trends in Monte Carlo Simulations" , which has been written for this second edition. Typographical correc tions have been made and fuller references given where appropriate, but otherwise the layout and contents of the other chapters are left unchanged. Thus this book, together with its companion volume mentioned above, gives a fairly complete and up to-date review of the field. It is hoped that the reduced price of this paperback edition will make it accessible to a wide range of scientists and students in the fields to which it is relevant: theoretical phYSics and physical chemistry , con densed-matter physics and materials science, computational physics and applied mathematics, etc.
Book Synopsis A Guide to Monte Carlo Simulations in Statistical Physics by : David P. Landau
Download or read book A Guide to Monte Carlo Simulations in Statistical Physics written by David P. Landau and published by Cambridge University Press. This book was released on 2000-08-17 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, as well as in related fields, such as polymer science and lattice gauge theory. The authors give a succinct overview of simple sampling methods and develop the importance sampling method. In addition they introduce quantum Monte Carlo methods, aspects of simulations of growth phenomena and other systems far from equilibrium, and the Monte Carlo Renormalization Group approach to critical phenomena. The book includes many applications, examples, and current references, and exercises to help the reader.
Book Synopsis Monte Carlo Methods in Statistical Physics by : M. E. J. Newman
Download or read book Monte Carlo Methods in Statistical Physics written by M. E. J. Newman and published by Clarendon Press. This book was released on 1999-02-11 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the use of Monte Carlo computer simulation methods suitable for beginning graduate students and beyond. It is suitable for a course text for physics or chemistry departments or for self-teaching.
Book Synopsis Monte Carlo Simulation and Option Pricing by : Kalina P. Natcheva
Download or read book Monte Carlo Simulation and Option Pricing written by Kalina P. Natcheva and published by . This book was released on 2002 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Theory, Application, and Implementation of Monte Carlo Method in Science and Technology by : Pooneh Saidi Bidokhti
Download or read book Theory, Application, and Implementation of Monte Carlo Method in Science and Technology written by Pooneh Saidi Bidokhti and published by BoD – Books on Demand. This book was released on 2019-12-18 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo method is a numerical technique to model the probability of all possible outcomes in a process that cannot easily be predicted due to the interference of random variables. It is a technique used to understand the impact of risk, uncertainty, and ambiguity in forecasting models. However, this technique is complicated by the amount of computer time required to achieve sufficient precision in the simulations and evaluate their accuracy. This book discusses the general principles of the Monte Carlo method with an emphasis on techniques to decrease simulation time and increase accuracy.
Book Synopsis Monte Carlo Methods for American Option Pricing by : Alberto Barola
Download or read book Monte Carlo Methods for American Option Pricing written by Alberto Barola and published by LAP Lambert Academic Publishing. This book was released on 2014-05-21 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Monte Carlo approach has proved to be a valuable and flexible computational tool in modern finance. A number of Monte Carlo simulation-based methods have been developed within the past years to address the American option pricing problem. The aim of this book is to present and analyze three famous simulation algorithms for pricing American style derivatives: the stochastic tree; the stochastic mesh and the least squares method (LSM). The author first presents the mathematical descriptions underlying these numerical methods. Then the selected algorithms are tested on a common set of problems in order to assess the strengths and weaknesses of each approach as a function of the problem characteristics. The results are compared and discussed on the basis of estimates precision and computation time. Overall the simulation framework seems to work considerably well in valuing American style derivative securities. When multi-dimensional problems are considered, simulation based methods seem to be the best solution to estimate prices since the general numerical procedures of finite difference and binomial trees become impractical in these specific situations.
Book Synopsis Handbook in Monte Carlo Simulation by : Paolo Brandimarte
Download or read book Handbook in Monte Carlo Simulation written by Paolo Brandimarte and published by John Wiley & Sons. This book was released on 2014-06-20 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Book Synopsis Efficient Monte Carlo and Quasi-Monte Carlo Option Pricing Under the Variance-Gamma Model by :
Download or read book Efficient Monte Carlo and Quasi-Monte Carlo Option Pricing Under the Variance-Gamma Model written by and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop and study efficient Monte Carlo algorithms for pricing path-dependent options with the variance gamma model. The key ingredient is difference-of-gamma bridge sampling, based on the representation of a variance gamma process as the difference of two increasing gamma processes. For typical payoff structures, we obtain a pair of estimators (named low and high) with expectations that are (i) monotone along any such bridge sampler; (ii) contain the continuous-time price. These estimators provide pathwise bounds on unbiased estimators that would be more expensive to compute (infinitely expensive in some situations). By using these bounds together with extrapolation techniques, we obtain significant simulation efficiency improvements by work reduction. We then combine the gamma bridge sampling with randomized quasi-Monte Carlo to reduce the variance and thus improve the efficiency by another important factor. We illustrate the large efficiency improvements on numerical examples for Asian, lookback, and barrier options.
Book Synopsis A Monte Carlo Method for Pricing American Options by : Diego Garcia
Download or read book A Monte Carlo Method for Pricing American Options written by Diego Garcia and published by . This book was released on 1999 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis American-style Option Pricing and Improvement of Regression-based Monte Carlo Methods by Machine Learning Techniques by : Songyin Tang
Download or read book American-style Option Pricing and Improvement of Regression-based Monte Carlo Methods by Machine Learning Techniques written by Songyin Tang and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
