Summer School on Mathematical Methods in Finance and Economy, Hanoi, 06/2010

(unofficial anouncement)

Summer School on Mathematical Methods in Finance and Economy

31/May – 04/June/2010

Hanoi Center for Financial and Industrial Mathematics

Hanoi National University of Education

Targeted audience

Graduate students and researchers in finance, economics, and mathematics

People working in the financial industry (investment, insurance, …)

Programme

This School will consist of 4 main intensive minicourses (about 6 hours per course), computer sessions, and some research talks.

The four minicourses are:

Time Series Applied to Finance, by Anne Van Hems (Professor at Toulouse Business School)

Non-Parametric Models With Applications To Production Frontiers, by Michel Simoni (Research Director at INRA)

Scoring, by Christine Thomas-Agnan (Professor at Toulouse School of Economics)

Quantitative Portfolio Management, by Nguyen Tien Zung (Professor at Toulouse Institute of Mathematics, and Scientific Director of HCFIM)

Computer sessions will be animated by CNRS research engineer Thibault Laurent

Detailed description of the courses

Course: SCORING (Christine Thomas-Agnan)

Part I: Introduction

–       What is scoring ?

–       Background on linear regression models

–       Generalized linear regression models

Part II: Logistic regression

–       Fundamental assumption – Odds

–       Estimation and interpretation of coefficients

–        Tests

–       Goodness of fit: sensibility, specificity and ROC curves

Part III: Scorecard development

–       Data preparation (variable treatment)

–       Characteristic selection

–       Scorecard calibration

–       Reject inference

It is important for this course to already know the background on ordinary linear regression models

Bibliography:

1- Background on linear regression models: any book on that topic (you may tell me what you have and I can advice you then on what to read)

2- Generalized Linear regression

chapters 1 and 6 of Extending the linear model with R, J.J. Faraway, Chapman \& Hall/CRC, 2006.

chapter 7 of W.N. Venables and B.D.Ripley, Modern Applied Statistics with S, 2002, Springer.

chapter 1 and 2 of Generalized additive models, an introduction with R, S. Wood, Chapman \& Hall/CRC, 2006.

chapter 2 of L. Fahrmeir and G. Tutz, Multivariate statistical modelling based on generalized linear models, Springer series in statistics, 1994.

3- Logistic regression

J.M. Hilbe, Logistic regression models, CRC Press, Chapman and Hall, 2009.

D.W. Hosmer, S. Lemeshow, Applied logistic regression, second edition, Wiley, 2000.

4- Scorecard development

R. Anderson, The credit scoring toolkit, Oxford U.P., 2007.

Thomas, Edelman and Crook, Credit scoring and its applications, SIAM, 2002.

N. Siddiqi, Credit risk scorecards, Wiley, 2006.

——–

Course: Time series applied to Finance(Anne Vanhems)

The objective of this course is to gain a working knowledge of time series and forecasting methods as applied in economics, engineering and finance. The purpose is to study techniques for drawing inferences from time series. After an appropriate family of models has been chosen, it is then possible to estimate parameters, check for goodness of fit to the data, and possibly to use the fitted model to enhance our understanding of the mechanism generating the series.

After recalling some basic notions in statistics and modeling, we will present the main time series models: ARMA, SARIMA, ARCH, GARCH

Outline of the course:

1)      Introduction to Time-series Analysis and stochastic processes

2)      Stationnarity of a process and ARMA modeling

3)      Box-Jenkins methodology: identification, estimation and testing

4)      Times series in finance and conditional heteroscedastic models: ARCH and GARCH

It is important for this course to already know the background on linear regression models,  linear projection of Hilbert spaces,  maximum likelihood estimation and  standard testing hypothesis.

A few references:

–          P.J. Brockwell and R.A. Davis:” Introduction to Time series and forecasting”, Springer Texts in Statistics, Springer

–          J.D.  Hamilton: “Time series analysis” , Princeton University Press

–          C. Brooks: “Introductory econometrics for finance”, Cambridge University Press

–          C. Gouriéroux and J. Jasiak: “Financial econometrics : problems, models, methods », Princeton Series in Finance

—–

Course: Nonparametric Models with Applications to Production Frontiers
(Michel Simioni, Toulouse School of Economics, INRA-GREMAQ)
The approach of production frontiers is an effort to define empirically an envelopment of production data. This approach is based on the conventional microecomic theory paradigm, assuming that producers optimize by no wasting resources in a systematic way, i.e. producers operate somewhere on the boundary of their production possibility sets, namely the production frontier.  Empirical evidence shows that not all producers succeed in all circumstances. Hence, it is important to analyze the degree to which producers fail to optimize and the extent of departures from technical and economic efficiency. The aim of the course is thus to provide an overview of nonparametric methods used in production frontier estimation and efficiency measurement.
1.Production Frontiers and the Measurement of Efficiency
The economic model
A taxonomy of production frontier models
The nonparametric envelopment estimators:
Data Envelopment Analysis (DEA)
Free Disposal Hull (FDH)
2.Statistical Inference in Nonparametric Frontier Estimation
Statistical foundation
A summary of asymptotic results
Bootstrapping DEA and FDH Efficiency scores
3.Robust Nonparametric Frontier Estimators
A reformulation based on the probability of being dominated
Order-m partial frontiers
Order-α quantile-type frontiers
4.Explaining Efficiencies
The two-stage regression approach
Conditional efficiency measures
5.Conclusion
References:
Daraio, C., and L. Simar (2007), Advanced Robust and Nonparametric Methods in Efficiency Analysis, Springer, New-York.
Fried, H.O., Lovell, C.A.Knox, and S.S. Schmidt (2008), The Measurement of Productive Efficiency and Productivity Growth, Oxford University Press, Oxford.
Software:
Wilson, P. (2008), “FEAR 1.0: A Software Package for Frontier Efficiency Analysis with R,” Socio-Economic Planning Sciences 42, 247-254.
See http://www.clemson.edu/economcs/faculty/wilson/Software/FEAR/fear.html

——

Course: QUANTITATIVE PORTFOLIO MANAGEMENT

This course will be an overview of modern theories of porfolio management, with some applications to investing in stock markets in Vietnam.

1. Measures of risk and return

– Risk/return relationship

– Expected vs. actual return

– Variance and volatility

– Downside risk

– Value at risk

2. Pricing theories

– CAPM

– APT

– Other models

3. Portfolio theories

– Constraints and objectives

– Markowitz, Black-Litterman, etc.

– Dynamic asset allocation

4. Numerical optimization methods

– Linear and quadratic programming

– Monte-Carlo

– Heuristic optimization

– Robust optimization

5. Applications to Vietnamese stock market

– Explanatory factors

– Index tracking

– Asset allocation

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6 comments to Summer School on Mathematical Methods in Finance and Economy, Hanoi, 06/2010

  • Vinh MonsterID Icon Vinh

    Professeur, j’aimerais savoir òu je peux trouver des infos officiellement et comment pour s’incrire ce cours ?

    Merci,

  • admin MonsterID Icon admin

    Thank you for your interest. Official announcement and contact information in VN will be available in a week.

  • Phi Ha MonsterID Icon Phi Ha

    Chú Dũng ơi ch cháu hỏi

    1. Hanoi National University of Education có phải là Đại học Sư phạm Hà nội, chỗ thầy Thái không?

    2. Đối với sinh viên đã xong năm thứ 3 Đại học (đã học Probability and Convex Opti.) thì có đi nghe được không hay quá tầm?

    3. Có gì liên quan đến Numerical Analysis không?

    Cháu cám ơn chú.

  • admin MonsterID Icon admin

    @Phi Ha

    1. đúng thế
    2. SV cũng có thể nghe, chắc sẽ hiểu được phần nào
    3. Có một số thực hành trên máy tính, phần đó có liên quan
    đến một số numerical methods cho stats & finance

  • Linh MonsterID Icon Linh

    Bác Zung cho hỏi nếu muốn tham gia các course này thì có phải đăng ký không? Nếu có thì đăng ký ở đâu? Có lệ phí gì không? Cảm ơn bác.

  • admin MonsterID Icon admin

    Linh có thể đăng ký tại ĐHSPHN (hỏi ở khoa toán chắc mọi người sẽ chỉ cho)

    Nếu có trục trặc gì thì báo cho tôi

    Về mặt lệ phí, phía VN sẽ quyết định.

    Việc tổ chức một school khá là tốn kém, tính trên đầu học viên chắc phải lên đến vài trăm USD/người. Tuy tất nhiên
    có trợ cấp (cả từ phía Pháp khá nhiều), nhưng có lẽ vẫn phải thu phí để trang trải thêm cho chi phí, và để
    cho mọi người có ý thức về sự tốn kém của giáo dục. Phải nộp tiền mới được dự, thì sẽ “quí” hơn, nghiêm túc
    hơn, là đi học “chùa”. Ai “con nhà nghèo” không thể có khả năng nộp lệ phí, mà rất muốn đến dự, có thể
    xin miễn lệ phí, nếu thấy hợp lý chắc sẽ được chấp nhận.

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