Mathematics and Financial Economics Editor-In-Chief: Elyès Jouini, CEREMADE, Université Paris-Dauphine, Paris, France; [email protected]

Total Page:16

File Type:pdf, Size:1020Kb

Mathematics and Financial Economics Editor-In-Chief: Elyès Jouini, CEREMADE, Université Paris-Dauphine, Paris, France; Jouini@Ceremade.Dauphine.Fr ABCD springer.com 2nd Announcement and Call for Papers Mathematics and Financial Economics Editor-in-Chief: Elyès Jouini, CEREMADE, Université Paris-Dauphine, Paris, France; [email protected] New from Springer 1st issue in July 2007 NEW JOURNAL Submit your manuscript online springer.com Mathematics and Financial Economics In the last twenty years mathematical finance approach. When quantitative methods useful to has developed independently from economic economists are developed by mathematicians theory, and largely as a branch of probability and published in mathematical journals, they theory and stochastic analysis. This has led to often remain unknown and confined to a very important developments e.g. in asset pricing specific readership. More generally, there is a theory, and interest-rate modeling. need for bridges between these disciplines. This direction of research however can be The aim of this new journal is to reconcile these viewed as somewhat removed from real- two approaches and to provide the bridging world considerations and increasingly many links between mathematics, economics and academics in the field agree over the necessity finance. Typical areas of interest include of returning to foundational economic issues. foundational issues in asset pricing, financial Mainstream finance on the other hand has markets equilibrium, insurance models, port- often considered interesting economic folio management, quantitative risk manage- problems, but finance journals typically pay ment, intertemporal economics, uncertainty less attention to the high-level quantitative and information in finance models. ISSN 1862-9679 (Print) ISSN 1862-9660 (Electronic) 4 issues per Year Co-Editors: NJ, USA Abel Cadenillas, University of Alberta, Jaksa Cvitanić, California Institute of Edmonton AB, Canada Technology, Pasadena, CA, USA Pierre Collin-Dufresne, University of California, NEW Rose-Anne Dana, CEREMADE, Université Berkeley, CA, USA JOURNAL Paris-Dauphine, Paris, France Bernard Cornet, Université Paris I, France and Advisory Board: University of Kansas, USA Domenico Cuoco, The Wharton School, George Constantinides, Graduate School of University of Pennsylvania, PA, USA From the contents Business, University of Chicago, IL, USA Hans Föllmer, Humboldt University, Berlin, Darrell Duffie, Graduate School of Business, Germany of the first issue: Stanford University, CA USA Michael F. Gallmeyer, Mays Business School, 1. Optimal derivatives design for Bernard Dumas, INSEAD, Fontainebleau, France Texas A & M University, College Station, TX, USA mean-variance agents under Ivar Ekeland, University of British Columbia, Christian Gollier, GREMAQ, Université de adverse selection Guillaume Vancouver BC, Canada Toulouse I, France Carlier, Ivar Ekeland and Roger Guesnerie, Collège de France, Paris, Thorsten Hens, Zurich University, Switzerland Nizar Touzi France Leonid Kogan, Sloan School of Management, 2. Optimal Compensation Pierre-Louis Lions, Université Paris-Dauphine, MIT, Cambridge, MA, USA with Adverse Selection and Paris, France Ali Lazrak, University of British Columbia, Dynamic Actions, Jakša Andreu Mas Colell, Universidad Pompeu Fabra, Vancouver, BC, Canada Cvitanić and Jianfeng Zhang Barcelona, Spain Michael Magill, University of Southern 3. The consumption-based Jean-Charles Rochet, Université des Sciences California, Los Angeles, CA, USA determinants of the term Sociales, Toulouse, France Walter Schachermayer, University of structure of discount rates, José Scheinkman, Princeton University, Technology, Vienna, Austria Christian Gollier NJ, USA Costis Skiadas, Kellogg School of Management, 4. The equity risk premium Evanston, IL, USA and the riskfree rate in an Editorial Board: Nizar Touzi, CREST, Malakoff, France economy with borrowing Kerry Back, Mays Business School, Texas Dimitry Vayanos, LSE, London, UK constraints, Leonid Kogan, A & M University, College Station, TX, USA Akira Yamazaki, Hitotsubashi University, Igor Makarov and Raman Suleyman Basak, London Business School, UK Tokyo, Japan Uppal Markus K. Brunnermeier, Princeton University, Fernando Zapatero, USC, Los Angeles, USA Easy Ways to Order (for the Americas) Write: Springer Order Department, PO Box 2485, Secaucus, NJ 07096-2485, USA Call: (toll free) 1-800-SPRINGER Fax: (201)348-4505 Email: [email protected] or (for outside the Americas) Write: Springer Distribution Center GmbH, Haberstrasse 7, 69126 Heidelberg, Germany Call: +49 (0) 6221-345-4303 Fax: +49 (0) 6221-345-4229 Email: [email protected] Q8588 http://www.springer.com/journal/11579.
Recommended publications
  • Mathematical Finance
    Mathematical Finance 6.1I nterest and Effective Rates In this section, you will learn about various ways to solve simple and compound interest problems related to bank accounts and calculate the effective rate of interest. Upon completion you will be able to: • Apply the simple interest formula to various financial scenarios. • Apply the continuously compounded interest formula to various financial scenarios. • State the difference between simple interest and compound interest. • Use technology to solve compound interest problems, not involving continuously compound interest. • Compute the effective rate of interest, using technology when possible. • Compare multiple accounts using the effective rates of interest/effective annual yields. Working with Simple Interest It costs money to borrow money. The rent one pays for the use of money is called interest. The amount of money that is being borrowed or loaned is called the principal or present value. Interest, in its simplest form, is called simple interest and is paid only on the original amount borrowed. When the money is loaned out, the person who borrows the money generally pays a fixed rate of interest on the principal for the time period the money is kept. Although the interest rate is often specified for a year, annual percentage rate, it may be specified for a week, a month, or a quarter, etc. When a person pays back the money owed, they pay back the original amount borrowed plus the interest earned on the loan, which is called the accumulated amount or future value. Definition Simple interest is the interest that is paid only on the principal, and is given by I = Prt where, I = Interest earned or paid P = Present value or Principal r = Annual percentage rate (APR) changed to a decimal* t = Number of years* *The units of time for r and t must be the same.
    [Show full text]
  • Math 581/Econ 673: Mathematical Finance
    Math 581/Econ 673: Mathematical Finance This course is ideal for students who want a rigorous introduction to finance. The course covers the following fundamental topics in finance: the time value of money, portfolio theory, capital market theory, security price modeling, and financial derivatives. We shall dissect financial models by isolating their central assumptions and conceptual building blocks, showing rigorously how their gov- erning equations and relations are derived, and weighing critically their strengths and weaknesses. Prerequisites: The mathematical prerequisites are Math 212 (or 222), Math 221, and Math 230 (or 340) or consent of instructor. The course assumes no prior back- ground in finance. Assignments: assignments are team based. Grading: homework is 70% and the individual in-class project is 30%. The date, time, and location of the individual project will be given during the first week of classes. The project is mandatory; missing it is analogous to missing a final exam. Text: A. O. Petters and X. Dong, An Introduction to Mathematical Finance with Appli- cations (Springer, New York, 2016) The text will be allowed as a reference during the individual project. The following books are not required and may serve as supplements: - M. Capi´nski and T. Zastawniak, Mathematics for Finance (Springer, London, 2003) - J. Hull, Options, Futures, and Other Derivatives (Pearson Prentice Hall, Upper Saddle River, 2015) - R. McDonald, Derivative Markets, Second Edition (Addison-Wesley, Boston, 2006) - S. Roman, Introduction to the Mathematics of Finance (Springer, New York, 2004) - S. Ross, An Elementary Introduction to Mathematical Finance, Third Edition (Cambrige U. Press, Cambridge, 2011) - P. Wilmott, S.
    [Show full text]
  • The Law and Economics of Hedge Funds: Financial Innovation and Investor Protection Houman B
    digitalcommons.nyls.edu Faculty Scholarship Articles & Chapters 2009 The Law and Economics of Hedge Funds: Financial Innovation and Investor Protection Houman B. Shadab New York Law School Follow this and additional works at: http://digitalcommons.nyls.edu/fac_articles_chapters Part of the Banking and Finance Law Commons, and the Insurance Law Commons Recommended Citation 6 Berkeley Bus. L.J. 240 (2009) This Article is brought to you for free and open access by the Faculty Scholarship at DigitalCommons@NYLS. It has been accepted for inclusion in Articles & Chapters by an authorized administrator of DigitalCommons@NYLS. The Law and Economics of Hedge Funds: Financial Innovation and Investor Protection Houman B. Shadab t Abstract: A persistent theme underlying contemporary debates about financial regulation is how to protect investors from the growing complexity of financial markets, new risks, and other changes brought about by financial innovation. Increasingly relevant to this debate are the leading innovators of complex investment strategies known as hedge funds. A hedge fund is a private investment company that is not subject to the full range of restrictions on investment activities and disclosure obligations imposed by federal securities laws, that compensates management in part with a fee based on annual profits, and typically engages in the active trading offinancial instruments. Hedge funds engage in financial innovation by pursuing novel investment strategies that lower market risk (beta) and may increase returns attributable to manager skill (alpha). Despite the funds' unique costs and risk properties, their historical performance suggests that the ultimate result of hedge fund innovation is to help investors reduce economic losses during market downturns.
    [Show full text]
  • From Big Data to Econophysics and Its Use to Explain Complex Phenomena
    Journal of Risk and Financial Management Review From Big Data to Econophysics and Its Use to Explain Complex Phenomena Paulo Ferreira 1,2,3,* , Éder J.A.L. Pereira 4,5 and Hernane B.B. Pereira 4,6 1 VALORIZA—Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal 2 Department of Economic Sciences and Organizations, Instituto Politécnico de Portalegre, 7300-555 Portalegre, Portugal 3 Centro de Estudos e Formação Avançada em Gestão e Economia, Instituto de Investigação e Formação Avançada, Universidade de Évora, Largo dos Colegiais 2, 7000 Évora, Portugal 4 Programa de Modelagem Computacional, SENAI Cimatec, Av. Orlando Gomes 1845, 41 650-010 Salvador, BA, Brazil; [email protected] (É.J.A.L.P.); [email protected] (H.B.B.P.) 5 Instituto Federal do Maranhão, 65075-441 São Luís-MA, Brazil 6 Universidade do Estado da Bahia, 41 150-000 Salvador, BA, Brazil * Correspondence: [email protected] Received: 5 June 2020; Accepted: 10 July 2020; Published: 13 July 2020 Abstract: Big data has become a very frequent research topic, due to the increase in data availability. In this introductory paper, we make the linkage between the use of big data and Econophysics, a research field which uses a large amount of data and deals with complex systems. Different approaches such as power laws and complex networks are discussed, as possible frameworks to analyze complex phenomena that could be studied using Econophysics and resorting to big data. Keywords: big data; complexity; networks; stock markets; power laws 1. Introduction Big data has become a very popular expression in recent years, related to the advance of technology which allows, on the one hand, the recovery of a great amount of data, and on the other hand, the analysis of that data, benefiting from the increasing computational capacity of devices.
    [Show full text]
  • An Introduction to Financial Econometrics
    An introduction to financial econometrics Jianqing Fan Department of Operation Research and Financial Engineering Princeton University Princeton, NJ 08544 November 14, 2004 What is the financial econometrics? This simple question does not have a simple answer. The boundary of such an interdisciplinary area is always moot and any attempt to give a formal definition is unlikely to be successful. Broadly speaking, financial econometrics is to study quantitative problems arising from finance. It uses sta- tistical techniques and economic theory to address a variety of problems from finance. These include building financial models, estimation and inferences of financial models, volatility estimation, risk management, testing financial economics theory, capital asset pricing, derivative pricing, portfolio allocation, risk-adjusted returns, simulating financial systems, hedging strategies, among others. Technological invention and trade globalization have brought us into a new era of financial markets. Over the last three decades, enormous number of new financial products have been created to meet customers’ demands. For example, to reduce the impact of the fluctuations of currency exchange rates on a firm’s finance, which makes its profit more predictable and competitive, a multinational corporation may decide to buy the options on the future of foreign exchanges; to reduce the risk of price fluctuations of a commodity (e.g. lumbers, corns, soybeans), a farmer may enter into the future contracts of the commodity; to reduce the risk of weather exposures, amuse parks (too hot or too cold reduces the number of visitors) and energy companies may decide to purchase the financial derivatives based on the temperature. An important milestone is that in the year 1973, the world’s first options exchange opened in Chicago.
    [Show full text]
  • Challenges in Macro-Finance Modeling
    Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. Challenges in Macro-Finance Modeling Don Kim 2008-06 NOTE: Staff working papers in the Finance and Economics Discussion Series (FEDS) are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by other members of the research staff or the Board of Governors. References in publications to the Finance and Economics Discussion Series (other than acknowledgement) should be cleared with the author(s) to protect the tentative character of these papers. CHALLENGES IN MACRO-FINANCE MODELING DON H. KIM∗ Abstract. This paper discusses various challenges in the specification and implemen- tation of “macro-finance” models in which macroeconomic variables and term structure variables are modeled together in a no-arbitrage framework. I classify macro-finance models into pure latent-factor models (“internal basis models”) and models which have observed macroeconomic variables as state variables (“external basis models”), and examine the underlying assumptions behind these models. Particular attention is paid to the issue of unspanned short-run fluctuations in macro variables and their poten- tially adverse effect on the specification of external basis models. I also discuss the challenge of addressing features like structural breaks and time-varying inflation uncer- tainty. Empirical difficulties in the estimation and evaluation of macro-finance models are also discussed in detail. 1. introduction In recent years there has been much interest in developing “macro-finance models”, in which yields on nominal bonds are jointly modeled with one or more macroeconomic variables within a no-arbitrage framework.
    [Show full text]
  • Careers in Quantitative Finance by Steven E
    Careers in Quantitative Finance by Steven E. Shreve1 August 2018 1 What is Quantitative Finance? Quantitative finance as a discipline emerged in the 1980s. It is also called financial engineering, financial mathematics, mathematical finance, or, as we call it at Carnegie Mellon, computational finance. It uses the tools of mathematics, statistics, and computer science to solve problems in finance. Computational methods have become an indispensable part of the finance in- dustry. Originally, mathematical modeling played the dominant role in com- putational finance. Although this continues to be important, in recent years data science and machine learning have become more prominent. Persons working in the finance industry using mathematics, statistics and computer science have come to be known as quants. Initially relegated to peripheral roles in finance firms, quants have now taken center stage. No longer do traders make decisions based solely on instinct. Top traders rely on sophisticated mathematical models, together with analysis of the current economic and financial landscape, to guide their actions. Instead of sitting in front of monitors \following the market" and making split-second decisions, traders write algorithms that make these split- second decisions for them. Banks are eager to hire \quantitative traders" who know or are prepared to learn this craft. While trading may be the highest profile activity within financial firms, it is not the only critical function of these firms, nor is it the only place where quants can find intellectually stimulating and rewarding careers. I present below an overview of the finance industry, emphasizing areas in which quantitative skills play a role.
    [Show full text]
  • Financial Mathematics
    Financial Mathematics Alec Kercheval (Chair, Florida State University) Ronnie Sircar (Princeton University) Jim Sochacki (James Madison University) Tim Sullivan (Economics, Towson University) Introduction Financial Mathematics developed in the mid-1980s as research mathematicians became interested in problems, largely involving stochastic control, that had until then been studied primarily by economists. The subject grew slowly at first and then more rapidly from the mid- 1990s through to today as mathematicians with backgrounds first in probability and control, then partial differential equations and numerical analysis, got into it and discovered new issues and challenges. A society of mostly mathematicians and some economists, the Bachelier Finance Society, began in 1997 and holds biannual world congresses. The Society for Industrial and Applied Mathematics (SIAM) started an Activity Group in Financial Mathematics & Engineering in 2002; it now has about 800 members. The 4th SIAM conference in this area was held jointly with its annual meeting in Minneapolis in 2013, and attracted over 300 participants to the Financial Mathematics meeting. In 2009 the SIAM Journal on Financial Mathematics was launched and it has been very successful gauged by numbers of submissions. Student interest grew enormously over the same period, fueled partly by the growing financial services sector of modern economies. This growth created a demand first for quantitatively trained PhDs (typically physicists); it then fostered the creation of a large number of Master’s programs around the world, especially in Europe and in the U.S. At a number of institutions undergraduate programs have developed and become quite popular, either as majors or tracks within a mathematics major, or as joint degrees with Business or Economics.
    [Show full text]
  • Mathematical Finance MS and Ph.D. Course Requirements
    Mathematical Finance M.S. and Ph.D. Course requirements Master of Science with a Specialization in Mathematical Finance The full-time program of study for the M.S. degree specializing in Mathematical Finance focuses on building a solid foundation in applied mathematics, uncovers models used in financial applications, and teaches computational tools for developing solutions. The M.S. degree consists of 36 hours of graduate work including 3 hours of credit for a departmental report or 6 hours of credit for the master’s thesis. Up to 3 hours of graduate work are permitted in other areas such as mathematics, statistics, business, economics, finance or fields as approved by the graduate advisor. M.S. students share core courses with beginning Ph.D. students. To enter the program of study leading to a Master of Science Degree specializing in Mathematical Finance, the applicant must meet the requirements of the Graduate School and of the Department of Mathematics and Statistics. The degree requirements are as follows. A. Completion of the following required courses. A.1 FIN 5328 - Options and Futures A.2 STAT 5328 - Mathematical Statistics I A.3 STAT 5329 - Mathematical Statistics II A.4 MATH 5399 (Special Topics) - Applied Time Series A.5 MATH 6351 - Quantitative Methods with Applications to Financial Data A.6 MATH 6353 - Stochastic Calculus with Applications to Financial Derivatives B. Completion of any two courses from the following elective list. B.1 STAT 5371 - Regression Analysis B.2 STAT 5386 - Statistical Computation and Simulation B.3
    [Show full text]
  • Course Information Sheet for Entry in 2018-19 Msc in Law and Finance
    24/10/2017 MSc in Law and Finance | University of Oxford Course Information Sheet for entry in 2018-19 MSc in Law and Finance About the course The MSc in Law and Finance is taught jointly by the Law Faculty and the Saïd Business School. It will provide you with an advanced interdisciplinary understanding of economic and nancial concepts and their application to legal topics. The MSc combines a highly analytic academic core with tailor-made practical applications derived from collaboration with professional and regulatory organisations. There are two core nance courses, Finance and First Principles of Financial Economics, a core interdisciplinary course, Law and Economics of Corporate Transactions, and one or more elective courses in law. There are also pre-sessional courses in maths and nancial reporting. In addition to these core MLF courses, students selecting the Law Stream will take two law electives from a tailored list of about 10 law courses that are available to students on the Bachelor of Civil Law (BCL). The list of law electives comprises courses that are business law-oriented and thus are intended to complement both each other and the MLF course as a whole. In taking these electives, you will be joined by students taking the Law Faculty's other taught graduate courses, the BCL and the Magister Juris (MJur). MLF students can also select the Finance Stream. If you select this option, you will take only one law elective. In lieu of the second law elective, you will take a mandatory nance course, Corporate Valuation, in the second term and one nance elective in the third term.
    [Show full text]
  • Econophysics: a Brief Review of Historical Development, Present Status and Future Trends
    1 Econophysics: A Brief Review of Historical Development, Present Status and Future Trends. B.G.Sharma Sadhana Agrawal Department of Physics and Computer Science, Department of Physics Govt. Science College Raipur. (India) NIT Raipur. (India) [email protected] [email protected] Malti Sharma WQ-1, Govt. Science College Raipur. (India) [email protected] D.P.Bisen SOS in Physics, Pt. Ravishankar Shukla University Raipur. (India) [email protected] Ravi Sharma Devendra Nagar Girls College Raipur. (India) [email protected] Abstract: The conventional economic 1. Introduction: approaches explore very little about the dynamics of the economic systems. Since such How is the stock market like the cosmos systems consist of a large number of agents or like the nucleus of an atom? To a interacting nonlinearly they exhibit the conservative physicist, or to an economist, properties of a complex system. Therefore the the question sounds like a joke. It is no tools of statistical physics and nonlinear laughing matter, however, for dynamics has been proved to be very useful Econophysicists seeking to plant their flag in the underlying dynamics of the system. In the field of economics. In the past few years, this paper we introduce the concept of the these trespassers have borrowed ideas from multidisciplinary field of econophysics, a quantum mechanics, string theory, and other neologism that denotes the activities of accomplishments of physics in an attempt to Physicists who are working on economic explore the divine undiscovered laws of problems to test a variety of new conceptual finance. They are already tallying what they approaches deriving from the physical science say are important gains.
    [Show full text]
  • University of Pennsylvania the Wharton School FNCE
    University of Pennsylvania The Wharton School FNCE 911: Foundations for Financial Economics Prof. Jessica A. Wachter Fall 2019 Office: SH-DH 2459 Classes: Wednesday 1:30{4:30 Email: [email protected] Office hours: Wednesday 4:30{5:30 Course Description The objective of this course is to undertake a rigorous study of the theoretical foun- dations of modern financial economics. The course will cover the central themes of modern finance including individual investment decisions under uncertainty, stochas- tic dominance, mean-variance theory, capital market equilibrium and asset valuation, arbitrage pricing theory, option pricing and the potential application of these themes. Upon completion of this course, students should acquire a clear understanding of the major theoretical results concerning individuals' consumption and portfolio decisions under uncertainty and their implications for the valuations of securities. Prerequisites The prerequisites for this course are graduate level microeconomics (Economics 681 or Economics 701), matrix algebra, and calculus. The microeconomics courses may be taken concurrently. Course Material • The website for this course can be accessed through Canvas: https://canvas.upenn.edu. On this website you can find lecture notes, sample problems, announcements. • All readings are optional, but may be helpful. The textbook is C.F. Huang and R. Litzenberger, 1988, Foundations for Financial Economics, Prentice Hall. 1 On the syllabus, readings from the textbook are prefaced by HL. This textbook is out of print. You can find the chapters on the course website. • Following each topic, there is a list of recommended articles which can also be found on the website. Other reading Some excellent texts that cover material related to this course are: • K.
    [Show full text]