[PDF] Improved Lower Bounds Of Call Options Written On Defaultable Assets eBook
Improved Lower Bounds Of Call Options Written On Defaultable Assets Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Improved Lower Bounds Of Call Options Written On Defaultable Assets book. This book definitely worth reading, it is an incredibly well-written.
This paper provides an improved model-independent lower bound of European call options written on defaultable assets. Based on static arbitrage arguments, improved lower bounds are established, which also depend on the probability of option implied default. The results are also extended to dividend paying stocks. Moreover, our findings imply that it is never optimal to exercise certain American call options. Finally, we discuss the implications of our results for constructing an arbitrage-free volatility surface and extracting risk-neutral densities from option prices.
In this paper, we derive closed-form, interpolation-based expressions for European call options written on defaultable assets. Our results are based on the work of Henderson at al. (2007), who derive formulas that incorporate standard static no-arbitrage restrictions, and Orosi (2014) who establishes an improved lower bound for European call options written on defaultable assets. Although, in general, the models are incapable of representing the entire call option surface because of the low number of parameters, we demonstrate their applicability to extract important quantities from quoted options. In particular, the probability of default, the size of a default barrier, and the recovery rate can be inferred from the model.
Based on the result of Orosi (2014), we derive an improved lower bound for European-style put options written on defaultable assets. Furthermore, we establish two additional no-arbitrage conditions, one for European-style puts and one for calls, which are tighter than the ones commonly reported in current literature. All of our results are based on static arbitrage arguments and have important implications for constructing arbitrage-free call or put option surfaces. In particular, we point out that the commonly stated conditions required for a call option surface are not always sufficient to generate an arbitrage-free call option surface.
In this article, we develop new upper and lower bounds on American option prices which improve the bounds by Broadie and Detemple. The main idea is the consideration of doubly capped call options which have two cap prices. We present a new option price approximation based on the two upper bounds. On average, our upper bound extrapolation (named UBE) has an average accuracy better than a 1,000 time-step binomial tree with a computation speed comparable to a 100 time-step binomial tree. We also provide a new method of approximating the optimal exercise boundaries of American options.
This book illustrates the application of the economic concept of stochastic dominance to option markets and presents an alternative option pricing paradigm to the prevailing no arbitrage simultaneous equilibrium in the frictionless underlying and option markets. This new methodology was developed primarily by the author, working independently or jointly with other co-authors, over the course of more than thirty years. Among others, it yields the fundamental Black-Scholes-Merton option value when markets are complete, presents a new approach to the pricing of rare event risk, and uncovers option mispricing that leads to tradeable strategies in the presence of transaction costs. In the latter case it shows how a utility-maximizing investor trading in the market and a riskless bond, subject to proportional transaction costs, can increase his/her expected utility by overlaying a zero-net-cost portfolio of options bought at their ask price and written at their bid price, irrespective of the specific form of the utility function. The book contains a unified presentation of these methods and results, making it a highly readable supplement for educators and sophisticated professionals working in the popular field of option pricing. It also features a foreword by George Constantinides, the Leo Melamed Professor of Finance at the Booth School of Business, University of Chicago, USA, who was a co-author in several parts of the book.
Risk neutral densities recovered from option prices can be used to infer market participantsņ expectations of future stock returns and are a vital tool for pricing illiquid exotic options. Although there is a broad literature on the subject, most studies do not address the likelihood of default. To fill this gap, in this paper we develop a novel method to retrieve the risk neutral probability density function from call options written on a defaultable asset. The primary advantage of the method is that default probabilities inferred by the model can be analytically expressed and, if available, can be incorporated as an input in a ፟lexible, robust and easily implementable manner.
Over the last 20 years hedge funds and derivatives have fluctuated in reputational terms; they have been blamed for the global financial crisis and been praised for the provision of liquidity in troubled times. Both topics are rather under-researched due to a combination of data and secrecy issues. This book is a collection of papers celebrating 20 years of the Journal of Derivatives and Hedge Funds (JDHF). The 18 papers included in this volume represent a small sample of influential papers included during the life of the Journal, representing industry-orientated research in these areas. With a Preface from co-editor of the journal Stephen Satchell, the first part of the collection focuses on hedge funds and the second on markets, prices and products.
This second edition, now featuring new material, focuses on the valuation principles that are common to most derivative securities. A wide range of financial derivatives commonly traded in the equity and fixed income markets are analysed, emphasising aspects of pricing, hedging and practical usage. This second edition features additional emphasis on the discussion of Ito calculus and Girsanovs Theorem, and the risk-neutral measure and equivalent martingale pricing approach. A new chapter on credit risk models and pricing of credit derivatives has been added. Up-to-date research results are provided by many useful exercises.
Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.