The current volume presents four chapters touching on some of the most important and modern areas of research in Mathematical Finance: asset price bubbles (by Philip Protter); energy markets (by Fred Espen Benth); investment under transaction costs (by Paolo Guasoni and Johannes Muhle-Karbe); and numerical methods for solving stochastic equations (by Dan Crisan, K. Manolarakis and C. Nee).The Paris-Princeton Lecture Notes on Mathematical Finance, of which this is the fifth volume, publish cutting-edge research in self-contained, expository articles from renowned specialists. The aim is to produce a series of articles that can serve as an introductory reference source for research in the field.

The book gives a systematical presentation of stochastic approximation methods for discrete time Markov price processes. Advanced methods combining backward recurrence algorithms for computing of option rewards and general results on convergence of stochastic space skeleton and tree approximations for option rewards are applied to a variety of models of multivariate modulated Markov price processes. The principal novelty of presented results is based on consideration of multivariate modulated Markov price processes and general pay-off functions, which can depend not only on price but also an additional stochastic modulating index component, and use of minimal conditions of smoothness for transition probabilities and pay-off functions, compactness conditions for log-price processes and rate of growth conditions for pay-off functions. The volume presents results on structural studies of optimal stopping domains, Monte Carlo based approximation reward algorithms, and convergence of American-type options for autoregressive and continuous time models, as well as results of the corresponding experimental studies.

This work, now in a thoroughly revised second edition, presents the economic foundations of financial markets theory from a mathematically rigorous standpoint and offers a self-contained critical discussion based on empirical results. It is the only textbook on the subject to include more than two hundred exercises, with detailed solutions to selected exercises. Financial Markets Theory covers classical asset pricing theory in great detail, including utility theory, equilibrium theory, portfolio selection, mean-variance portfolio theory, CAPM, CCAPM, APT, and the Modigliani-Miller theorem. Starting from an analysis of the empirical evidence on the theory, the authors provide a discussion of the relevant literature, pointing out the main advances in classical asset pricing theory and the new approaches designed to address asset pricing puzzles and open problems (e.g., behavioral finance). Later chapters in the book contain more advanced material, including on the role of information in financial markets, non-classical preferences, noise traders and market microstructure. This textbook is aimed at graduate students in mathematical finance and financial economics, but also serves as a useful reference for practitioners working in insurance, banking, investment funds and financial consultancy. Introducing necessary tools from microeconomic theory, this book is highly accessible and completely self-contained. Advance praise for the second edition: "Financial Markets Theory is comprehensive, rigorous, and yet highly accessible. With their second edition, Barucci and Fontana have set an even higher standard!"Darrell Duffie, Dean Witter Distinguished Professor of Finance, Graduate School of Business, Stanford University "This comprehensive book is a great self-contained source for studying most major theoretical aspects of financial economics. What makes the book particularly useful is that it provides a lot of intuition, detailed discussions of empirical implications, a very thorough survey of the related literature, and many completely solved exercises. The second edition covers more ground and provides many more proofs, and it will be a handy addition to the library of every student or researcher in the field."Jaksa Cvitanic, Richard N. Merkin Professor of Mathematical Finance, Caltech "The second edition of Financial Markets Theory by Barucci and Fontana is a superb achievement that knits together all aspects of modern finance theory, including financial markets microstructure, in a consistent and self-contained framework. Many exercises, together with their detailed solutions, make this book indispensable for serious students in finance."Michel Crouhy, Head of Research and Development, NATIXIS

This Gedenkschrift for Peter Carr, our dear friend and colleague who suddenly left us on March 1, 2022, was organized to honor the life and lasting contributions of Peter to Quantitative Finance. A group of Peter's co-authors and professional friends contributed chapters for this Gedenkschrift shortly after his passing. The papers were received by September 15, 2022 and some were presented at the Peter Carr Gedenkschrift Conference held at the Robert H Smith School of Business on November 11, 2022. The contributed papers cover a wide range of topics corresponding to the vast range of Peter's interests. Each paper represents new research results in recognition of Peter's scholarly activities. The book serves as an important marker for the research knowledge existing at the time of the Gedenkschrift's publication on a number of topics within quantitative finance. It reflects the diverse interactions between mathematics and finance and illustrates, for those interested, the breadth and depth of this development. The book also presents a collection of tributes to Peter from family and friends including those made at his Memorial Service on March 19, 2022. The result is hopefully a more complete testament to a personal and professional life well lived, and unexpectedly cut short.

Articles from many of the main contributors to recent progress in stochastic analysis are included in this volume, which provides a snapshot of the current state of the area and its ongoing developments. It constitutes the proceedings of the conference on "Stochastic Analysis and Applications" held at the University of Oxford and the Oxford-Man Institute during 23-27 September, 2013. The conference honored the 60th birthday of Professor Terry Lyons FLSW FRSE FRS, Wallis Professor of Mathematics, University of Oxford. Terry Lyons is one of the leaders in the field of stochastic analysis. His introduction of the notion of rough paths has revolutionized the field, both in theory and in practice. Stochastic Analysis is the branch of mathematics that deals with the analysis of dynamical systems affected by noise. It emerged as a core area of mathematics in the late 20th century and has subsequently developed into an important theory with a wide range of powerful and novel tools, and with impressive applications within and beyond mathematics. Many systems are profoundly affected by stochastic fluctuations and it is not surprising that the array of applications of Stochastic Analysis is vast and touches on many aspects of life. The present volume is intended for researchers and Ph.D. students in stochastic analysis and its applications, stochastic optimization and financial mathematics, as well as financial engineers and quantitative analysts.

Solve the DVA/FVA Overlap Issue and Effectively Manage Portfolio Credit Risk Counterparty Risk and Funding: A Tale of Two Puzzles explains how to study risk embedded in financial transactions between the bank and its counterparty. The authors provide an analytical basis for the quantitative methodology of dynamic valuation, mitigation, and hedging of bilateral counterparty risk on over-the-counter (OTC) derivative contracts under funding constraints. They explore credit, debt, funding, liquidity, and rating valuation adjustment (CVA, DVA, FVA, LVA, and RVA) as well as replacement cost (RC), wrong-way risk, multiple funding curves, and collateral. The first part of the book assesses today’s financial landscape, including the current multi-curve reality of financial markets. In mathematical but model-free terms, the second part describes all the basic elements of the pricing and hedging framework. Taking a more practical slant, the third part introduces a reduced-form modeling approach in which the risk of default of the two parties only shows up through their default intensities. The fourth part addresses counterparty risk on credit derivatives through dynamic copula models. In the fifth part, the authors present a credit migrations model that allows you to account for rating-dependent credit support annex (CSA) clauses. They also touch on nonlinear FVA computations in credit portfolio models. The final part covers classical tools from stochastic analysis and gives a brief introduction to the theory of Markov copulas. The credit crisis and ongoing European sovereign debt crisis have shown the importance of the proper assessment and management of counterparty risk. This book focuses on the interaction and possible overlap between DVA and FVA terms. It also explores the particularly challenging issue of counterparty risk in portfolio credit modeling. Primarily for researchers and graduate students in financial mathematics, the book is also suitable for financial quants, managers in banks, CVA desks, and members of supervisory bodies.

'Overall, the book provides an interesting and useful synthesis of the authors’ research on the predictions of stock market crashes. The book can be recommended to anyone interested in the Bond Stock Earnings Yield Differential model, and similar methods to predict crashes.'Quantitative FinanceThis book presents studies of stock market crashes big and small that occur from bubbles bursting or other reasons. By a bubble we mean that prices are rising just because they are rising and that prices exceed fundamental values. A bubble can be a large rise in prices followed by a steep fall. The focus is on determining if a bubble actually exists, on models to predict stock market declines in bubble-like markets and exit strategies from these bubble-like markets. We list historical great bubbles of various markets over hundreds of years.We present four models that have been successful in predicting large stock market declines of ten percent plus that average about minus twenty-five percent. The bond stock earnings yield difference model was based on the 1987 US crash where the S&P 500 futures fell 29% in one day. The model is based on earnings yields relative to interest rates. When interest rates become too high relative to earnings, there almost always is a decline in four to twelve months. The initial out of sample test was on the Japanese stock market from 1948-88. There all twelve danger signals produced correct decline signals. But there were eight other ten percent plus declines that occurred for other reasons. Then the model called the 1990 Japan huge -56% decline. We show various later applications of the model to US stock declines such as in 2000 and 2007 and to the Chinese stock market. We also compare the model with high price earnings decline predictions over a sixty year period in the US. We show that over twenty year periods that have high returns they all start with low price earnings ratios and end with high ratios. High price earnings models have predictive value and the BSEYD models predict even better. Other large decline prediction models are call option prices exceeding put prices, Warren Buffett's value of the stock market to the value of the economy adjusted using BSEYD ideas and the value of Sotheby's stock. Investors expect more declines than actually occur. We present research on the positive effects of FOMC meetings and small cap dominance with Democratic Presidents. Marty Zweig was a wall street legend while he was alive. We discuss his methods for stock market predictability using momentum and FED actions. These helped him become the leading analyst and we show that his ideas still give useful predictions in 2016-2017. We study small declines in the five to fifteen percent range that are either not expected or are expected but when is not clear. For these we present methods to deal with these situations.The last four January-February 2016, Brexit, Trump and French elections are analzyed using simple volatility-S&P 500 graphs. Another very important issue is can you exit bubble-like markets at favorable prices. We use a stopping rule model that gives very good exit results. This is applied successfully to Apple computer stock in 2012, the Nasdaq 100 in 2000, the Japanese stock and golf course membership prices, the US stock market in 1929 and 1987 and other markets. We also show how to incorporate predictive models into stochastic investment models.