Tsinghua-PKU-Stanford Conference in Quantitative Finance

Tsinghua-PKU-Stanford
Conference in Quantitative Finance
May 15-16, 2015
Beijing, China
Sponsors:
Tsinghua University
Peking University
Stanford University
Organizers:
School of Economics and Management, Tsinghua University
Department of Mathematical Sciences, Tsinghua University
Contents
Scientific Committee .............................................................................................. 1
Organizers.............................................................................................................. 1
Conference Program .............................................................................................. 2
Speakers ................................................................................................................ 5
Rong Chen, Rutgers University ................................................................................................................. 5
Tze Leung Lai, Stanford University ............................................................................................................ 5
Chenxu Li, Peking University ..................................................................................................................... 6
Zongxia Liang, Tsinghua University ........................................................................................................... 7
Robert L. Kimmel, National University of Singapore ................................................................................ 7
Denis Kochedykov, J.P. Morgan ................................................................................................................ 8
Jian Sun, Morgan Stanley .......................................................................................................................... 9
Yintian Wang, Tsinghua University ......................................................................................................... 10
Haipeng Xing, State University of New York at Stony Brook .................................................................. 10
Qi Wang, China Financial Futures Exchange ........................................................................................... 11
Lan Wu, Peking University ...................................................................................................................... 11
Jianming Xia, China Academy of Science ................................................................................................ 12
Linfeng You, ICBC Credit Suisse Asset Management .............................................................................. 13
Joey Zhang, Derivative China .................................................................................................................. 13
Tao Zou, Peking University...................................................................................................................... 14
Frank Yulin Feng, Tsinghua University .................................................................................................... 14
Zhijian He, Tsinghua University ............................................................................................................... 15
Local Contacts ...................................................................................................... 16
Emergency Contacts ............................................................................................ 16
Scientific Committee
Tze Leung Lai
Stanford University
Chenxu Li
Peking University
Michael R. Powers
Tsinghua University
Xiaoqun Wang
Tsinghua University
Lan Wu
Peking University
Haipeng Xing
State University of New York at Stony Brook
Yingzi Zhu
Tsinghua University
Organizers
School of Economics and Management, Tsinghua University
Department of Mathematical Sciences, Tsinghua University
1
Conference Program
Academic Forum (Friday, May 15, 2015)
08:00-09:00
Registration
09:00-09:10
Opening Ceremony
Session 1
Chair: Michael R. Powers (Tsinghua University)
09:10-09:40
Speaker: Yintian Wang* and Yingzi Zhu (Tsinghua University)
Title: Chinese Warrant Bubble: A Fundamental Analysis
09:40-10:10
Speaker: Haipeng Xing (State University of New York at Stony
Brook)
Title: Predictive Effect of Economic and Market Variations on
Structural Breaks in Credit Rating Dynamics
10:10-10:40
Speaker: Lan Wu (Peking University)
Title: Empirical Analysis of Risk-free Interest Rates in Chinese
Financial System
10:40-11:00
Group photo and tea break
11:00-11:30
Speaker: Frank Yulin Feng* and Michael R. Powers (Tsinghua
University)
Title: Microinsurance without Underwriting: An Application of
Risk-Revealing Contract Design
11:30-12:00
Speaker: Songxi Chen and Tao Zou* (Peking University)
Title: Determining the Number of Factors in Affine Term
Structure Models
2
12:00-12:30
Speaker: Zhijian He* and Xiaoqun Wang (Tsinghua University)
Title: Smoothing and Dimension Reduction in Quasi-Monte
Carlo for Pricing and Hedging of Financial Derivatives
12:30-14:00
Lunch
Session 2
Chair: Xiaoqun Wang (Tsinghua University)
14:00-14:30
Speaker: Jianming Xia (China Academy of Science)
Title: Comonotonic Convex Preferences
14:30-15:00
Speaker: Chenxu Li (Peking University)
Title: Econometric Analysis of Continuous-time Models: a
Closed-form Expansion approach
15:00-15:30
Speaker: Zongxia Liang (Tsinghua University)
Title: Optimal Management of DC Pension Plan under Loss
Aversion and Value-at-Risk Constraints
15:30-16:00
Tea break
Session 3
Chair: Chenxu Li (Peking University)
16:00-17:30
Speaker: Rong Chen* (Rutgers University) and Tze Leung Lai*
(Stanford University)
Title: Mini-course on Particle Filters and their Applications in
Finance and Economics
3
Industrial Forum (Saturday, May 16, 2015)
Session 1
Chair: Michael R. Powers (Tsinghua University)
09:00-10:30 Speaker: Denis Kochedykov (J.P. Morgan)
Title: Mini-course on State-space Modeling and Financial
Applications
10:30-11:00 Group photo and tea break
11:00-11:35 Speaker: Robert L. Kimmel (National University of Singapore)
Title: New Methods for Evaluation of Asset Pricing Models
11:35-12:10 Qi Wang (China Financial Futures Exchange)
Title: The Development of China’s Stock Index Options Markets
12:10-14:00 Lunch
Session 2
Chair: Tze Leung Lai (Stanford University)
14:00-15:30 Speaker: Jian Sun (Morgan Stanley)
Title: Mini-course on Options Theory and Trading
15:30-15:50 Tea break
15:50-16:25 Speaker: Joey Zhang (Derivative China)
Title: Chinese derivatives market outlook
16:30-17:10 Speaker: Linfeng You (ICBC Credit Suisse Asset Management)
Title: Effective Quantitative Strategies for A-share Market
4
Speakers
Rong Chen, Rutgers University
Bio: Dr. Rong Chen is a Professor of Statistics at the Department of Statistics and
Biostatistics, Rutgers University. Dr. Chen received his B.S. (1985) in Mathematics
from Peking University, and Ph.D. (1990) in Statistics from Carnegie Mellon
University. He was Assistant/Associate Professor at Texas A&M University (19901999) and Professor at University of Illinois at Chicago (1999-2007) before he joined
Rutgers University in 2007. He also served as a program director in the Division of
Mathematical Sciences at National Science Foundation from 2005 to 2007. Dr. Chen
is an expert in nonlinear/nonparametric time series analysis, Monte Carlo methods
statistical and statistical applications. He is an elected fellow of American Statistical
Association, elected fellow of Institute of Mathematical Statistics and an elected
member of International Statistics Institute. He is currently serving as Joint-Editor
for Journal of Business & Economic Statistics, a leading statistics and econometrics
journal. He has also served as an Associate Editor for several other leading
statistical journals.
Tze Leung Lai, Stanford University
Bio: Tze Leung Lai is Professor of Statistics in the School of Humanities and Sciences,
and by courtesy, of Health Research and Policy in the School of Medicine and of the
Institute of Computational and Mathematical Engineering in the Engineering
School of Stanford University. He is also Director of Financial Mathematics Program
and the Financial and Risk Modelling Institute at Stanford, and Co-director of the
Biostatistics Core of the Cancer Institute and the Center of Innovative Design at the
School of Medicine. He received his B.A. (First Class Honours) in Mathematics from
Columbia University, where he stayed on the faculty until he moved to Stanford
University in 1987. He won the Committee of Presidents of Statistical Societies
Award in 1983 and the Abraham Wald Prize in Sequential Analysis in 2005. He is an
elected member of Academia Sinica, where he has been an Advisory Committee
member of the Institute of Statistical Science since 1992. He is also an Advisory
Committee member of the Department of Statistics and Actuarial Science and of
the Institute for Mathematical Research at HKU, and of the Statistics Center at
Peking University and the Mathematical Sciences Center at Tsinghua University. He
has published nine books, 275 papers, and has supervised sixty PhD students.
5
Title: Mini-course on Particle Filters and their Applications in Finance and
Economics
Abstract: This mini-course gives an introduction to the recent breakthroughs in the
long-standing problem of adaptive filtering and prediction in nonlinear state-space
(and more general hidden Markov) models with unknown parameters, using
efficient sequential Monte Carlo methods that are commonly called "particle
filters" in the engineering and econometrics literature. Such introduction paves the
way for the mini-course by Denis Kochedykov in Saturday's Industrial Forum on the
applications of state-space modeling with time series data in financial markets.
Chenxu Li, Peking University
Bio: Chenxu Li is now an Assistant Professor of Business Statistics and Econometrics
at the Guanghua School of Management, Peking University. He received a
bachelor's degree from the University of Science and Technology of China in 2004
and a Ph.D. degree from Columbia University in 2010, both in mathematics and
applied mathematics. His primary research interests include financial engineering
and financial econometrics, stochastic modeling and applied probability. His
scholarly research has appeared in a number of prestigious academic journals,
including the Annals of Statistics, Mathematics of Operations Research, and
Mathematical Finance. He teaches Mathematical Methods in Finance, Stochastic
Analysis and Applications, Econometrics, Statistical Analysis for Business and
Management Research, etc.
Title: Econometric Analysis of Continuous-time Models: a Closed-form Expansion
approach
Abstract: Continuous-time models are widely applied in financial economics in, e.g.,
analyzing financial time series, asset pricing, portfolio and asset management, and
risk-management. A key issue for successful theoretical and empirical study is to
have reliable and efficient methods for calculating some useful quantities, e.g.,
likelihood functions (transition density) and option prices. However, after the
Black-Scholes-Merton (1973), models have become sophisticated by including
various features, e.g., stochastic volatility and jumps. Trade-off must be be made
between analytical tractability and empirical capability. Models encounter
challenges in their efficient implementation. We propose a method of closed-form
expansion for analyzing continuous-time models.
6
Zongxia Liang, Tsinghua University
Bio: Zongxia Liang is now a Professor of Department of Mathematical Sciences,
Tsinghua University. He received MSc (1991) and PhD (1996) degrees from Xi'an
Jiaotong University and China Academy of Science. His current research interests
include insurance mathematics and insurance economics (such as dividend,
reinsurance, portfolio selection, pricing and hedging in insurance products,
pensions systems, risk and credit risk theory), actuarial Science, life and non-life
insurance, mathematical finance and mathematical economics, stochastic control
and optimization in insurance and finance, stochastic dynamic programming.,
probability theory and stochastic analysis. His scholarly research has appeared in
academic journals: Insurance: Mathematics and Economics, Ann.Inst.H.Poincare
Probab. Statist, Journal of Functional Analysis, and Stochastic Processes and Their
Applications.
Title: Optimal Management of DC Pension Plan under Loss Aversion and Value-atRisk Constraints
Abstract: In this talk we study the risk management in a defined contribution (DC)
pension plan. The financial market consists of cash, bond and stock. The interest
rate in our model is assumed to follow an Orstein-Uhlenbeck process while the
contribution rate follows a geometric Brownian Motion. Thus, the pension
manager has to hedge the risks of interest rate, stock and contribution rate.
Different from most works in DC pension plan, the pension manger has to obtain
the optimal allocations under loss aversion and Value-at-Risk (VaR) constraints. The
loss aversion pension manager is sensitive to losses while the VaR pension manager
has to ensure the quality of wealth at retirement. Since these problems are not
standard concave optimization problems, martingale method is applied to derive
the optimal investment strategies. Explicit solutions are obtained under these two
optimization criterions. Moreover, sensitivity analysis is presented in the end to
show the economic behaviors under these two criterions.
Robert L. Kimmel, National University of Singapore
Bio: Robert L. Kimmel is an Associate Professor at the NUS Business School, and
the Deputy Director of Research at the Risk Management Institute, at the National
University of Singapore. He received his PhD in finance from the University of
Chicago Graduate School of Business. Before joining NUS, Prof. Kimmel was at
7
Princeton University, Ohio State University, and EDHEC Business School. His
research focuses on the econometrics of continuous-time models for asset prices,
and on methods for estimation and testing of linear factor models of asset returns.
Title: New Methods for Evaluation of Asset Pricing Models
Abstract: A very common method for testing asset pricing models uses statistical
hypothesis testing to evaluate the null, that the model prices all assets correctly.
Recent literature has shown that this commonly used method has difficulties when
applied to models with macroeconomic explanatory factors. Such factors often have
low correlation with asset returns, resulting in poor estimation of their spanning
portfolios, the risk premia associated with the factors, and other relevant quantities.
Because these quantities are estimated very poorly, it is difficult to reject the null
hypothesis of correct model specification, even in extreme cases when the model
does not have any explanatory power at all in population. The apparent performance
of an asset pricing model can therefore be improved simply by adding noise,
uncorrelated with asset returns, to the explanatory factors. We examine alternate
methods for evaluating asset pricing models, which avoid this problem. For many
practical applications, it may be preferable to use a model which can be rejected by
traditional testing methods, if the estimated degree of misspecification is small, than
a model which is not rejected, because its degree of misspecification is poorly
estimated.
Denis Kochedykov, J.P. Morgan
Bio: Dr. Denis Kochedykov is a member of J.P.Morgan Quantitative Research Beijing
Center; main focus of his research is quantitative trading, algo-trading and
electronic execution models. Prior to this he worked with Linear Quantitative
Research group in J.P. Morgan Hong-Kong contributing to the establishment of JPM
electronic trading solutions in APAC. Before that he worked as a team lead and
adviser for the leading data-mining company in Moscow. Denis received 2 Master
degrees in Applied Math and Nuclear Physics from Moscow State University and
Far East State University and PhD in Machine Learning Theory from Russian
Academy of Sciences.
Title: Mini-course on State-space Modeling and Financial Applications
Abstract: State-space modeling of dynamic processes is a flexible and powerful
methodology. It allows constructing dynamical models from interpretable
8
components, easily incorporating expert knowledge about the structure of the
process and then applying a general and computationally effective estimation
methodology to the constructed model. It naturally handles some problems that
one often encounters in practice - modeling regime shifts, handling missing data,
aggregated data, multiple and irregular time-scales, blending of observations
related to the same system from multiple sources and of multiple types.
In this talk I will 1. Briefly introduce general state-space framework; 2. Describe
estimation of hidden state in the linear Gaussian case - the celebrated Kalman Filter;
3. Describe several practical applications including high-frequency intraday marketmaking, calibrating stoch-vol derivatives prices in the case of unreliable market
with low liquidity, modeling dynamics of derivatives prices term-structure, highfrequency arbitrage; 4. Show the relation of state-space with other statistical
techniques like ARIMA, regression, etc and 5. Show how to handle with state-space
framework the practical modeling problems mentioned above.
Jian Sun, Morgan Stanley
Bio: Dr. Jian Sun is an Executive Director in Morgan Stanley’s Fixed Income and
Commodities Division, where he is responsible for quantitative modeling, pricing
and trading of structured products and derivatives in fixed income and
commodities. Before joining Morgan Stanley, Dr. Sun was a Senior Vice President
at XE Capital, where he helped manage over one billion US dollars in assets. Prior
to XE Capital, he was a Vice President at BNP Paribas’ hedge fund unit, formerly
Zurich Capital Markets, a wholly owned funds and fund of funds. Dr. Sun is the
author of the book Financial Derivative Pricing Modeling, published in 2007 and coauthor of the book Credit Derivatives: Theory and Practice, published in 2010. Dr.
Sun earned a BS from Beijing University and a PhD from the University of Chicago.
Title: Mini-course on Options Theory and Trading
Abstract: In this short lecture, we will talk about how to model the implied volatility
surfaces for equity and some fixed income options. Modeling the implied volatility
surfaces was always a challenge in the option pricing theory and in practice.
Hectically there has been many models to explain the volatility skew. In this note
we will provide a brand new approach based on the paper published by Jian Sun
and Peter Carr. Empirical work suggests that the model fits the market very well.
9
Unlike previous models of stochastic implied volatility, the current model has no
implications for the dynamics of instantaneous volatility.
Yintian Wang, Tsinghua University
Bio: WANG Yintian is an assistant professor in finance area at School of Economic
and Management. Professor Wang’s research focuses on Option pricing, Credit
derivatives, Econometric modeling, Risk management. Her papers have been
published in a range of scholarly journals, which include: Journal of Financial
Economics, Journal of Business and Economic Statistics, and Journal of Financial
Research. Prof. Wang received the Gold Award of Stock Risk Management Research
Awards on the European Financial Management Association Meeting which was
held in Madrid, Spain in 2006. She was awarded the First Prize for scientific research
of Tsinghua University in 2008.
Title: Chinese Warrant Bubble: A Fundamental Analysis
Abstract: Based on a rational option pricing framework that incorporates shortselling and margin trading constraints in the underlying stock market, we present
evidence that the Chinese warrant prices, which are unanimously attributed as
bubbles in previous literature, can be explained by the new option pricing model.
Based on the new model, we develop a warrant price deviation measure to quantify
the unobserved demand for short-selling or margin trading due to underlying stock
market constraints. We then empirically show that the warrant price deviation is
mainly driven by the underlying stock valuation and trading volume, controlling for
variables determined by all other trading motivations proposed in the literature.
We conclude that the Chinese warrant market is better characterized by derivatives
helping to complete the market rather than a pure bubble detached from
underlying asset.
Haipeng Xing, State University of New York at Stony Brook
Bio: Haipeng Xing is now an associate professor of applied maths and statistics at
the State University of New York at Stony Brook. He received a bachelor degree in
maths from Nankai University in 1998, and a MPhil degree in maths from Hong
Kong University of Science and Technology. He then received a MS and a PhD
degree in financial maths and statistics, respectively, from Stanford University in
2005. He taught at Columbia University during 2005-2007, then he moved to Stony
10
Brook in 2008 and was tenured in 2012. He also served as a consultant in the Office
of Chief Economist at the World Bank during 2010-2012. His research interests
include financial econometrics, change-point problems, and macroeconometrics,
development economics.
Title: Predictive Effect of Economic and Market Variations on Structural Breaks in
Credit Rating Dynamics
Abstract: Recent studies have shown that firms’ credit rating transition process is
not stationary and may have structural breaks. To study the predictability of
structural breaks, we develop a predictive model for latent structural breaks in
firms’ rating transition dynamics, using historical records of (high-dimensional)
economic and market fundamentals. As a large number of economic and market
variables are sometimes involved in the study, we also introduce an inference
procedure that select and estimate important economic factors at the same time
from the high-dimensional factor space. Based on an empirical study using the U.S.
firms' credit rating transition records and the history of economic and market
variations from 1986 to 2013, we demonstrate that not all structural breaks are
black-swan events and some of them can be estimated and predicted up to certain
extent.
Qi Wang, China Financial Futures Exchange
Bio: Mr. Qi Wang is the head of Options Product Development Team at China
Financial Futures Exchange. Prior to this position Mr. Wang was senior analyst in
derivatives trading and risk management at Capital Market of Bank of Nova Scotia
in Canada. Mr. Wang is CFA and FRM. Mr. Wang obtained an MBA degree from
McMaster University.
Title: The Development of China’s Stock Index Options Markets
Abstract: First, the speaker will discuss recent development of China’s options
market. Then he will explain the contract design of CSI 300 stock index options and
logic behind the design. Also, he will talk about mock trading of CSI 300 stock index
option, which has operated for almost 2 years.
Lan Wu, Peking University
11
Bio: Lan WU is a professor and director of Department of Financial Mathematics of
School of Mathematical Sciences, Peking University. She received a bachelor's
degree in 1984 and a Ph.D. degree in 1999, both from PKU in mathematics and
mathematical statistics. Her current research interests include financial
mathematics and actuarial sciences, financial data modeling and risk capital theory.
She has published some scholarly research papers on academic journals and been
in charge of many projects from the industrial, including a stress testing of
commercial banks and the solvency regulation of insurance companies. She
teaches Financial Statistics, Risk Theory and Financial Economics, etc.
Title: Empirical Analysis of Risk-free Interest Rates in Chinese Financial System
Abstract: Since the China government began to issue the process of market-based
interest rate reform, the risk-free interest rates are the crucial factors and variables
for the central bank, commercial banks, fixed income markets and the insurance
industry. However, there is not a consistent observation and models for the riskfree interest rate in Chinese financial system. We suggest to consider the risk-free
rate feasible (term structure) from two aspects: one is grow out of the central bank
monetary policy tools, which is a by-products of the transform of monetary policy
from central bank to the major commercial banks or financial institutions. The
second is that the risk-free interest rate is endogenous through an emerging and
developing market of funds and fixed income securities of Chinese financial system.
Based on the above observation of the risk-free interest rate of China's financial
system, we propose to use the following two methodologies for empirical analysis
of the risk-free interest rate term structure: 1. pure statistical modeling of a
dynamic term structure model (DTSM), describe the basic statistical structure from
the data directly. 2. Combining the macro and monetary policy factors in the DTSM,
driven by the different modeling goals.
Jianming Xia, China Academy of Science
Bio: Jianming Xia is now a Professor of Mathematical Finance at Academy of
Mathematics and Systems Science, Chinese Academy of Sciences. He is also the
director of the Key Lab of Random Complex Structures and Data Science, Chinese
Academy of Science. He received BSc (1994), MSc (1997), and PhD (2000) degrees
from E ast China Normal University. His primary research interests include portfolio
selection, asset pricing and decision theory under uncertainty. His scholarly
12
research has appeared in academic journals such as Mathematical Finance, Finance
and Stochastic, and SIAM Journal on Control and Optimization.
Title: Comonotonic Convex Preferences
Abstract: In this paper we develop a set of axioms for preferences under
uncertainty which leads to a representation result unifying the Choquet expected
utility preferences of Schmeidler (1989) and the uncertainty averse preferences of
Cerreia-Vioglio et al (2011). The maxmin Choquet expected utility, as a special case
of the representation, can accommodate both of the 50:51 and reflection examples
of Machina (2009).
Linfeng You, ICBC Credit Suisse Asset Management
Bio: 游凛峰博士毕业于美国斯坦福大学统计系，在工银瑞信担任工银全球基金、全球精选基金、
基本面量化策略股票基金，以及混合型绝对收益基金的基金经理。先后在 Merrill Lynch Investment
Managers 担任美林集中基金和美林保本基金基金经理，Fore Research & Management 担任 Fore
Equity Market Neutral 组合基金经理，Jasper Asset Management 担任 Jasper Gemini Fund 基金基金
经理。
Title: Effective Quantitative Strategies for A-share Market
Joey Zhang, Derivative China
Bio: Joey Zhang 章友, Chairman& CIO of Derivatives China, a start-up hedge fund
registered in Shenzhen, specialized in derivatives trading and arbitrage. He
previously worked in Goldman Sachs (Asia) as Executive Director, in charge of AsiaPacific single stock derivatives trading. Joey has also been consulting new
derivatives product development for various exchanges. Joey graduated from
Tsinghua University with Bachelor degree, during his study in Tsinghua, he was
Chairman of Tsinghua Finance Association and Chief Editor of SEM Express.
Title: Chinese derivatives market outlook
Abstract: In the short presentation, we will start with how derivative business
operates on the trading floor, how traders hedge risk, how they make money, and
then move on to the current status of Chinese derivatives market development,
the outlook of the market, and how should students prepare for the upcoming
derivatives market boom.
13
Tao Zou, Peking University
Bio: 2016 Ph.D. Candidate of the Department of Business Statistics and
Econometrics, Guanghua School of Management, Peking University.
Title: Determining the Number of Factors in Affine Term Structure Models
Abstract: Affine term structure models are a wide range of interest rate models
and have been used to describe the dynamic of bond prices in finance. We consider
determining the number of the unobservable state variables in the affine term
structure models, which is an unresolved issue in the literatures of multi-factor
modeling. We propose some penalty criteria and show that the number of factors
can be consistently estimated. It is also found that our proposed method is very
helpful to find whether the observed bond prices do or do not have pricing errors,
which is required in the affine model estimation. Simulation experiments are
conducted to confirm the theoretical properties of the selection consistency. We
also analyze the affine term structure models employing the data of U.S. Treasury
bond prices.
Frank Yulin Feng, Tsinghua University
Bio: Frank Yulin Feng is a Ph.D. candidate in School of Economics and Management,
Tsinghua University. His research interests include micro-insurance, insurance
mathematics, and financial econometrics.
Title: Microinsurance without Underwriting: An Application of Risk-Revealing
Contract Design
Abstract: Microinsurance products, like other forms of microfinance, are designed
primarily to address the needs of low-income individuals and households in the
developing world. Given the small premium volumes and slight profit margins of
microinsurance, insurers generally cannot sustain the high marketing, underwriting,
and claim-settlement costs associated with conventional products. In the present
work, we propose a practical method of reducing problems of adverse selection
when selling micro health insurance without underwriting. Essentially, insurers can
force policyholders to reveal their individual risk levels by offering a sliding scale of
insurance benefits (calibrated by policy limits, deductibles, or coinsurance) priced
to ensure separating equilibrium.
14
Zhijian He, Tsinghua University
Bio: 2015 Ph.D. Candidate of the Department of Mathematical Sciences, Tsinghua
University. His research interests are Monte Carlo and quasi-Monte Carlo with
applications in Computational Finance and Statistics.
Title: Smoothing and Dimension Reduction in Quasi-Monte Carlo for Pricing and
Hedging of Financial Derivatives.
Abstract: Discontinuities and high dimensionality are common in the pricing and
hedging of financial derivatives. They may significantly deteriorate the
performance of QMC methods. Methods have been developed to deal with either
discontinuities or high dimensionality. This paper develops a method that handles
these difficulties simultaneously. For this purpose, a smoothing method is
proposed to remove the discontinuities for a typical kind of functions arising from
finance. To make the smoothing method applicable for more general functions, a
path generation method is designed for generating sample paths. The new path
generation method has an additional advantage to reduce the effective dimension.
Numerical results show that the proposed method can lead to dramatic variance
reduction for pricing exotic options and calculating Greeks.
15
Local Contacts
If you need our help during the conference, please do not hesitate
to contact the following conference organization assistants. We
wish you a fruitful exchange of ideas, along with a pleasant stay in
Beijing!
Zhijian He (何志坚): 152-0127-0850
Yulin Feng (冯玉林): 152-1058-0354
Sarah Zhang (张艳芳): 159-0127-5795
Emergency Contacts
Emergency Medical Center (急救中心): 120
清华大学校医院急诊：010-62782185
清华大学治安派出所：010-62782001
16