《金融物理学》主要内容：金融市场是“行为复杂性”中最令人迷醉的例子，它是真实世界中的复杂系统，其演化方式由众多交易者的决策结果所决定，交易者们都试图在这场巨大的全局“博弈”中赢利。《金融物理学》从当今最流行的学科——复杂性和复杂系统中吸取了最新的概念，来说明如下几方面的问题：金融市场的行为如何；为什么金融市场要以这样的方式运行；如果知道金融市场的这些行为，为了将金融风险减小到最低程度，我们能够做些什么。在有关金融市场动力学的几个似乎无伤大雅的假设基础上，人们建立起来了标准的金融理论。《金融物理学》将会说明在解决重要的实际问题时，这些假设会给出令人误解的答案。这些实际问题包括降低金融风险、预测金融危机和股市暴跌之类的极端事件以及对衍生产品进行定价等。

《金融衍生品建模:基于Matlab、C++和Excel工具》主要讲述重要的衍生品定价模型，并运用Matlab、C++和Excel对包括信用衍生品（如信用违约掉期和信用关联记录）、债务抵押债券（CDO）、住房抵押贷款支持证券（MBS）、资产支持证券（ABS）、互换、固定收益证券，以及日渐重要的天气、电力、能源衍生品等进行建模.《金融衍生品建模:基于Matlab、C++和Excel工具》提供了Matlab和C++的示例代码，这些代码都可以更改和扩展，以满足实际需要读者将从衍生品模型的数据、理论和代码执行上获益。 《金融衍生品建模:基于Matlab、C++和Excel工具》适合作为统计、金融数学、经济管理等相关专业的教材，也可供对金融衍生品建模感兴趣的读者参考。

《当代经济学系列丛书.当代经济学教学参考书系·金融学原理》从金融的基本功能出发，构造了一个有别于传统货币银行学的金融学新体系。《当代经济学系列丛书.当代经济学教学参考书系·金融学原理》立足于中国的实践，以通俗易懂的语言，深入浅出地阐述了金融学的基本原理，具有综合性、实践性、可读性和前沿性等几方面的突出特点，对推动中国金融学的发展作出了有益的尝试。自2003年初版以来，《当代经济学系列丛书.当代经济学教学参考书系·金融学原理》已经修订三次，本次是第四次修订。书中的相关数据均更新至2009年年末，同时，作者还对部分案例、专栏和思考题进行了修订。《当代经济学系列丛书.当代经济学教学参考书系·金融学原理》是大学本科学生、在职研究生班学员，金融从业人员以及想了想和掌握金融知识的一般读者学习金融学的理想的入门级教材。

《统计与金融》内容涉及金融学与统计学的诸多内容，与一般偏重于单纯介绍理论知识和模型的著作不同，它把统计模型和金融模型联系在一起，寓统计学知识于金融学之中，并且用各种软件做出了完美的应用程序。《统计与金融》的主要特点是： 运用金融中的例子，阐明概率与统计的主要原理。 帮助读者理解以经验为依据的研究方法在金融和运筹学中是如何运用的。 介绍了新的统计方法，例如时间序列、GARCH模型、再抽样以及非参数回归。 提供了一些运用MATLAB和SAS软件包的例子。

近年来，金融数学的发展离不开随机微积分，而《量子金融(英文版)》提供了一种完全独立于该方法的新方法，将量子力学和量子场论中的数学公式和概念运用到期货理论和利率模型中，重点讲述路径积分。相应的得到了不少新的预期结果。《量子金融(英文版)》主要介绍了金融基本概念：金融基础；衍生证券；有限自由度系统：哈密顿体系和股票期货；路径积分和股票期货；随机利率模型的哈密顿体系和路径积分；利率模型的量子场论：利率远期合约的量子场论；经验利率远期合约和场论模型；国债衍生品场论；利率远期合约和场论哈密顿体系结论。

《金融计量学:基于SAS的金融实证研究》介绍了古典线性模型及其扩展、一元和多元时间序列模型以及GARCH模型、面板数据模型、事件研究法与组合价差法、利率期限结构和期权定价等金融计量的主要理论方法及其软件实现。 《金融计量学:基于SAS的金融实证研究》目的 ——《金融计量学:基于SAS的金融实证研究》将金融学、计量经济学和统计学的知识有机结合在一起，试图帮助金融专业学生以及研究人员快速有效地将理论、方法和数据结合起来，尽快进入金融研究的领域。 《金融计量学:基于SAS的金融实证研究》宗旨 ——提供运用金融计量学来进行金融实证研究的方法，帮助研究者较快地使用已有的数学工具和计算机工具来验证自己的思想与观点。 《金融计量学:基于SAS的金融实证研究》特色 ——每个部分附有相应案例。 ——SAS程序及数据与正文配套。读者可以登录“北京大学出版社主页一下载专区一课件下载”免费下载；也可登录作者个人主页http：／／hoomepage．fLJdan．edu．cn／～songiun／下载，并与作者进行交流。 ——教师用ppt。请教师填写书后“教师反馈及课件申请表”来函索取，我们将免费提供。

“[Taleb is] Wall Street’s principal dissident. . . . [Fooled By Randomness] is to conventional Wall Street wisdom approximately what Martin Luther’s ninety-nine theses were to the Catholic Church.” – Malcolm Gladwell, The New Yorker Finally in paperback, the word-of-mouth sensation that will change the way you think about the markets and the world.This book is about luck: more precisely how we perceive luck in our personal and professional experiences. Set against the backdrop of the most conspicuous forum in which luck is mistaken for skill–the world of business– Fooled by Randomness is an irreverent, iconoclastic, eye-opening, and endlessly entertaining exploration of one of the least understood forces in all of our lives.

在线阅读本书 Praise for The Volatility Surface "I′m thrilled by the appearance of Jim Gatheral′s new book The Volatility Surface. The literature on stochastic volatility is vast, but difficult to penetrate and use. Gatheral′s book, by contrast, is accessible and practical. It successfully charts a middle ground between specific examples and general models––achieving remarkable clarity without giving up sophistication, depth, or breadth." ––Robert V. Kohn, Professor of Mathematics and Chair, Mathematical Finance Committee, Courant Institute of Mathematical Sciences, New York University "Concise yet comprehensive, equally attentive to both theory and phenomena, this book provides an unsurpassed account of the peculiarities of the implied volatility surface, its consequences for pricing and hedging, and the theories that struggle to explain it." ––Emanuel Derman, author of My Life as a Quant "Jim Gatheral is the wiliest practitioner in the business. This very fine book is an outgrowth of the lecture notes prepared for one of the most popular classes at NYU′s esteemed Courant Institute. The topics covered are at the forefront of research in mathematical finance and the author′s treatment of them is simply the best available in this form." ––Peter Carr, PhD, head of Quantitative Financial Research, Bloomberg LP Director of the Masters Program in Mathematical Finance, New York University "Jim Gatheral is an acknowledged master of advanced modeling for derivatives. In The Volatility Surface he reveals the secrets of dealing with the most important but most elusive of financial quantities, volatility." ––Paul Wilmott, author and mathematician "As a teacher in the field of mathematical finance, I welcome Jim Gatheral′s book as a significant development. Written by a Wall Street practitioner with extensive market and teaching experience, The Volatility Surface gives students access to a level of knowledge on derivatives which was not previously available. I strongly recommend it." ––Marco Avellaneda, Director, Division of Mathematical Finance Courant Institute, New York University "Jim Gatheral could not have written a better book." ––Bruno Dupire, winner of the 2006 Wilmott Cutting Edge Research Award Quantitative Research, Bloomberg LP

This introductory text provides a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice. M. Joshi covers the strengths and weaknesses of such models as stochastic volatility, jump diffusion, and variance gamma, as well as the Black-Scholes. Examples and exercises, with answers, as well as computer projects, challenge the mind and encourage learning how to become a good quantitative analyst.

《金融工程学》（第2版）重实践而不重理论，全书侧重于金融工程学的思想方法和应用实例，而不拘泥于数学推导和求解过程。全书基本上是将作者自己充分理解并在实践中印证的理论，按照一个新的框架写成的。主要内容包括金融市场、资产定价、金融工具、债券、期权等八章内容。全书并配合有许多生动的案例，也是作者这些年来仔细收录的，相信对读者会有所启发。

An invaluable resource for quantitative analysts who need to run models that assist in option pricing and risk management. This concise, practical hands on guide to Monte Carlo simulation introduces standard and advanced methods to the increasing complexity of derivatives portfolios. Ranging from pricing more complex derivatives, such as American and Asian options, to measuring Value at Risk, or modelling complex market dynamics, simulation is the only method general enough to capture the complexity and Monte Carlo simulation is the best pricing and risk management method available. The book is packed with numerous examples using real world data and is supplied with a CD to aid in the use of the examples.

内容简介 l 金融市场是否确实可以用数学模型来解释？全球顶级金融专家特里亚纳用一长串强有力的证据证明了市场不能够被各种等式所驯服。因为那些标新立异、不合法规的人类行为支配着市场，出乎意料且难以想象的骇人事件则塑造了市场，所以使用历史数据来指导未来市场的方式并不可靠。 l 获得诺贝尔经济学奖的布莱克-斯科尔斯-默顿（BSM）模型无视黑天鹅事件的可能，无法预料到危险的产生，是造成金融灾难的罪魁祸首，我们还要继续迷信它们吗？鼓吹量化金融市场的学者们在象牙塔内坐井观天，以看似合理的数学公式对衍生产品交易员们的选择指手画脚，这些脱离了实践的理论有何资格获得实践者的信任？ l 市场不需要教授，市场需要“胖东尼”——重视实效、不受理论与教条奴役的金融业内人士。特里亚纳强烈呼吁用常识性方法取代基于数学的决策模型，并且呼吁让那些有实战经验而不是仅仅拥有学术理论的人们行使金融权利。 l 适合金融界人士、管理人员与投资者。 编辑推荐 l 畅销书《黑天鹅》、《反脆弱》作者纳西姆·塔勒布最为推崇的作品。他认为帕布罗· 特里亚纳是以一种清晰的思路、可嘉的勇气和无私奉献的精神为真相服务的。这本书非常难得，它揭露了模型的副作用及其带来的危害，并无所畏惧地指出我们应该前进的方向。这本书会让读者变得更加聪明，也会使我们的世界变得更加美好、更加安全并且更具风险意识。 l 从1987年的股市“黑色星期一”到美国长期资本管理公司的危机，特里亚纳用丰富的事例和强有力的论述抨击了金融市场中对量化模型的盲目追捧。“模型对，市场错”的信条无疑本末倒置，他强调，数学公式不可能归纳、预言和掌控市场的脉动。 l 本书对近几年来困扰模型的问题以及获得大量资金支持的定量技术所存在的问题进行了一次全面的解读。要是银行家们几年前就能留意这些信息，那么，今天我们也就不必面临那么多的混乱了。 l 湛庐文化出品

《精通Excel金融建模:公司金融应用指南(第2版)》作者根据自己近20年的建模经验，为读者介绍了如何方便地利用微软的Excel建立用途各异的金融分析模型。书中内容分为两部分。第一部分介绍了开发金融模型的一般流程、模型特性及技术要求和基础模型。第二部分则具体介绍了绩效分析模型、现金流模型、预测模型、差异分析模型、盈亏平衡点分析模型、投资组合分析模型、资本成本模型、债券模型、投资分析和风险分析模型、折旧模型、租赁模型、公司价值评估模型、最优化模型，以及决策树模型、风险管理模型和数据函数与数据分析模型。 《精通Excel金融建模:公司金融应用指南(第2版)》不仅能为高等院校金融、财会、投资等专业的师生提供极具价值的专业核心技能训练指导，同样能为相关领域的从业人员提供切实的帮助。 海报：

Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems and constructing an index fund, using techniques such as nonlinear optimization models, quadratic programming formulations and integer programming models respectively. The book is based on Master's courses in financial engineering and comes with worked examples, exercises and case studies. It will be welcomed by applied mathematicians, operational researchers and others who work in mathematical and computational finance and who are seeking a text for self-learning or for use with courses.

金融计算教程：MATLAB金融工具箱的应用，ISBN：9787302157885，作者：张树德 编著

Written by leading market risk academic, Professor Carol Alexander, Quantitative Methods in Finance forms part one of the Market Risk Analysis four volume set. Starting from the basics, this book helps readers to take the first step towards becoming a properly qualified financial risk manager and asset manager, roles that are currently in huge demand. Accessible to intelligent readers with a moderate understanding of mathematics at high school level or to anyone with a university degree in mathematics, physics or engineering, no prior knowledge of finance is necessary. Instead the emphasis is on understanding ideas rather than on mathematical rigour, meaning that this book offers a fast-track introduction to financial analysis for readers with some quantitative background, highlighting those areas of mathematics that are particularly relevant to solving problems in financial risk management and asset management. Unique to this book is a focus on both continuous and discrete time finance so that Quantitative Methods in Finance is not only about the application of mathematics to finance; it also explains, in very pedagogical terms, how the continuous time and discrete time finance disciplines meet, providing a comprehensive, highly accessible guide which will provide readers with the tools to start applying their knowledge immediately. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Principal component analysis of European equity indices; Calibration of Student t distribution by maximum likelihood; Orthogonal regression and estimation of equity factor models; Simulations of geometric Brownian motion, and of correlated Student t variables; Pricing European and American options with binomial trees, and European options with the Black-Scholes-Merton formula; Cubic spline fitting of yields curves and implied volatilities; Solution of Markowitz problem with no short sales and other constraints; Calculation of risk adjusted performance metrics including generalised Sharpe ratio, omega and kappa indices.