Changes and additions are sprinkled throughout. Among the significant new features are: • Markov-chain simulation (Sections 1. 3, 2. 6, 3. 6, 4. 3, 5. 4. 5, and 5. 5); • gradient estimation (Sections 1. 6, 2. 5, and 4. 9); • better handling of asynchronous observations (Sections 3. 3 and 3. 6); • radically updated treatment of indirect estimation (Section 3. 3); • new section on standardized time series (Section 3. 8); • better way to generate random integers (Section 6. 7. 1) and fractions (Appendix L, program UNIFL); • thirty-seven new problems plus improvements of old problems. Helpful comments by Peter Glynn, Barry Nelson, Lee Schruben, and Pierre Trudeau stimulated several changes. Our new random integer routine extends ideas of Aarni Perko. Our new random fraction routine implements Pierre L'Ecuyer's recommended composite generator and provides seeds to produce disjoint streams. We thank Springer-Verlag and its late editor, Walter Kaufmann-Bilhler, for inviting us to update the book for its second edition. Working with them has been a pleasure. Denise St-Michel again contributed invaluable text-editing assistance. Preface to the First Edition Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences.
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.
In the spring of 1917 the Arras offensive was begun to break the stalemate of the Western Front by piercing the formidable German defences of the Hindenburg Line. The village of Bullecourt lay at the southern end of the battle front, and the fighting there over a period of six weeks from 11 April until late May 1917, epitomised the awful trench warfare of World War I. In Bullecourt 1917, Paul Kendall tells the stories of the fierce battles fought by three British and three Australian divisions in an attempt to aid Allenby’s Third Army break out from Arras. Approximately 10,000 Australian and 7,000 British soldiers died, many of whom were listed as missing and have no known grave. The battle caused much consternation due to the failure of British tanks in supporting Australian infantry on 11 April, but despite the lack of tank and artillery support the Australian infantry valiantly fought their way into the German trenches. It took a further six weeks for British and Australian infantry to capture the village. This book tells the story of this bitter battle and pays tribute to the men who took part. Crucially, Paul Kendall has contacted as many of the surviving relatives of the combatants as he could, to gain new insight into those terrible events on the Hindenburg Line.
The energy mix is changing, and renewable energy is growing in importance. If you were born before 1989, you lived in a U.S. where there was no electricity generated from either wind or solar power and very little from geothermal and biomass. Now, in 2018, the combined generation from wind and solar has surpassed hydroelectricity. Fourteen states now generate more than 10% of their electricity from wind and three generate more than 30%. And bioethanol, produced from corn grain, now makes up 10% of the U.S. gasoline market. Changes have also occurred in the nonrenewable energy mix. Coal, which was responsible for 53% of the U.S. electricity generation in 1998 is now only 28%, as natural gas has taken the leadership role, surpassing coal in 2015 as the primary energy for producing electricity. Similarly, the world did not see any electricity generation from wind until 1985 and none from solar until 1989. Now solar plus wind generate 7% of the worldwide electricity. The worldwide demand for all energy types is also increasing rapidly, as energy usage has increased 84% over the last twenty years. This book makes a systematic comparison of twelve different energy types to help understand the driving forces for this changing energy mix. Twelve common criteria are used to provide tools to make these comparisons, such as proven reserves, the levelized cost for each energy type, energy balances, environmental issues, and the energy footprint. Proven reserves are also projected for each renewable energy type"--
Since around the turn of the millennium there has been a general acceptance that one of the more practical improvements one may make in the light of the shortfalls of the classical Black-Scholes model is to replace the underlying source of randomness, a Brownian motion, by a Lévy process. Working with Lévy processes allows one to capture desirable distributional characteristics in the stock returns. In addition, recent work on Lévy processes has led to the understanding of many probabilistic and analytical properties, which make the processes attractive as mathematical tools. At the same time, exotic derivatives are gaining increasing importance as financial instruments and are traded nowadays in large quantities in OTC markets. The current volume is a compendium of chapters, each of which consists of discursive review and recent research on the topic of exotic option pricing and advanced Lévy markets, written by leading scientists in this field. In recent years, Lévy processes have leapt to the fore as a tractable mechanism for modeling asset returns. Exotic option values are especially sensitive to an accurate portrayal of these dynamics. This comprehensive volume provides a valuable service for financial researchers everywhere by assembling key contributions from the world's leading researchers in the field. Peter Carr, Head of Quantitative Finance, Bloomberg LP. This book provides a front-row seat to the hottest new field in modern finance: options pricing in turbulent markets. The old models have failed, as many a professional investor can sadly attest. So many of the brightest minds in mathematical finance across the globe are now in search of new, more accurate models. Here, in one volume, is a comprehensive selection of this cutting-edge research. Richard L. Hudson, former Managing Editor of The Wall Street Journal Europe, and co-author with Benoit B. Mandelbrot of The (Mis)Behaviour of Markets: A Fractal View of Risk, Ruin and Reward
This totally new and much needed work on the County’s flora – published in association with the Hampshire and Isle of Wight Wildlife Trust – is the first comprehensive study for nearly a century. Excluding the Isle of Wight, it contains over 1750 species of vascular plants including some non-indigenous speces as well as subspecies, varieties and hybrids. In addition, condensed accounts of the lichens (590 taxa) and bryophytes (459 taxa) – groups in which the county is particularly rich – have been contributed by Francis Rose with Ken Sandell and Alan Crundwell respectively. As in Townsend’s Flora of Hampshire (1884), there are introductory chapters on Structure and Geology; Climate; Habitats; and an up-to-date Comparison of Hampshire’s Flora with some other southern Counties (including the Isle of Wight) – all by Francis Rose. There are also chapters on Conservation of the Flora (with a complete list of nature reserves) by Peter Brough and Paul Bowman; Some earlier Workers on the Hampshire Flora by David Allen; and Botanical Recording by Paul Bowman. The Flora ends with an extensive Bibliography and References and a fully comprehensive Index. The principal authors are all experienced Hampshire botanists with an intimate knowledge of its flora.
Changes and additions are sprinkled throughout. Among the significant new features are: • Markov-chain simulation (Sections 1. 3, 2. 6, 3. 6, 4. 3, 5. 4. 5, and 5. 5); • gradient estimation (Sections 1. 6, 2. 5, and 4. 9); • better handling of asynchronous observations (Sections 3. 3 and 3. 6); • radically updated treatment of indirect estimation (Section 3. 3); • new section on standardized time series (Section 3. 8); • better way to generate random integers (Section 6. 7. 1) and fractions (Appendix L, program UNIFL); • thirty-seven new problems plus improvements of old problems. Helpful comments by Peter Glynn, Barry Nelson, Lee Schruben, and Pierre Trudeau stimulated several changes. Our new random integer routine extends ideas of Aarni Perko. Our new random fraction routine implements Pierre L'Ecuyer's recommended composite generator and provides seeds to produce disjoint streams. We thank Springer-Verlag and its late editor, Walter Kaufmann-Bilhler, for inviting us to update the book for its second edition. Working with them has been a pleasure. Denise St-Michel again contributed invaluable text-editing assistance. Preface to the First Edition Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.