Jun
24
Master of Financial Engineering (MFE) degree has increasingly become a shortcut for people willing to work at a financial institution, especially to pursue a Quantitative finance related career. There are dozens of universities around the world providing with MFE program, for instance, Haas MFE, Columbia FE, and NYU are indisputably among the best. Sadly or not, only a few people have the chance to study at these top schools, how do you choose other program then? which factors will you give priority when applying? location, tuition, possibility to get financial aid, job placement?
Find MFE is a simple php+mysql page I wrote yesterday evening, the goal is to filter your ideal MFE program by the self-defined criteria, for example, you can say "I want to find a MFE program in United States, total tuition less than $40K, and with financial aid", the script will return the following MFE programs:
1.) Bentley College in Massachusetts
2.) Florida State University in Tallahassee
3.) Kent State University in Kent
4.) Princeton University in Princeton
5.) Purdue University in West Lafayette
6.) The University of Arizona in Arizona
7.) Vanderbilt University in Nashville
Clicking the link leads you to a page showing the more detailed introduction of this program, including length of study, size of class, program website, etc. (some content requires you to be able to get access to those sites like Youtube, Flickr and Twitter.)
I have no idea if people would find it useful or totally rubbish, it just tests the water, anyway. I fully understand the accuracy of the searching results depends largely on the information collected, please do help to improve it by rating the MFE program, adding a comment or leaving a message. Thank you. Advanced search like the job placement can be easily added technically, depending on your feedback.
Find your ideal MFE at http://www.mathfinance.cn/findMFE.php
Find MFE is a simple php+mysql page I wrote yesterday evening, the goal is to filter your ideal MFE program by the self-defined criteria, for example, you can say "I want to find a MFE program in United States, total tuition less than $40K, and with financial aid", the script will return the following MFE programs:
1.) Bentley College in Massachusetts
2.) Florida State University in Tallahassee
3.) Kent State University in Kent
4.) Princeton University in Princeton
5.) Purdue University in West Lafayette
6.) The University of Arizona in Arizona
7.) Vanderbilt University in Nashville
Clicking the link leads you to a page showing the more detailed introduction of this program, including length of study, size of class, program website, etc. (some content requires you to be able to get access to those sites like Youtube, Flickr and Twitter.)
I have no idea if people would find it useful or totally rubbish, it just tests the water, anyway. I fully understand the accuracy of the searching results depends largely on the information collected, please do help to improve it by rating the MFE program, adding a comment or leaving a message. Thank you. Advanced search like the job placement can be easily added technically, depending on your feedback.
Find your ideal MFE at http://www.mathfinance.cn/findMFE.php
Jun
23
This is the most up-to-date version of the switching regression procedures built by Simon van Norden and Robert Vigfusson with help from Jeff Gable. This Regime-Switching Model library lets you to estimate a general class of regime-switching models along the lines of those described in James Hamilton's textbook. Key features and limitations of the code include:
one independent variable only
two states only
arbitrary number of observed variables may be included to explain time-varying transition probablities or state-dependent means
external c-code, analytical gradients and combined maxlik()/EM algorithms for fast calculation
descriptive statistics, plots and White's model-misspecification tests
cascading estimation
separate, faster code for "simple switching" models (i.i.d. mixtures of regimes.)
learn more and download at http://www.hec.ca/pages/simon.van-norden/codepage.html and a Guide to the Bank of Canada Gauss Procedures at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=50565.
one independent variable only
two states only
arbitrary number of observed variables may be included to explain time-varying transition probablities or state-dependent means
external c-code, analytical gradients and combined maxlik()/EM algorithms for fast calculation
descriptive statistics, plots and White's model-misspecification tests
cascading estimation
separate, faster code for "simple switching" models (i.i.d. mixtures of regimes.)
learn more and download at http://www.hec.ca/pages/simon.van-norden/codepage.html and a Guide to the Bank of Canada Gauss Procedures at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=50565.
Jun
21
This weekend's review is about vault career guide, I bet many people have heard of it or even used it, I remember when I looked for a job before graduation, the two books I read often were Heard on the Street: Quantitative Questions from Wall Street Job Interviews
and Vault Career Guide to Investment Banking, 6th Edition
, both of which provide with clear explanation and insightful experience on how to look for a job and prepare interviews efficiently, expecially on investment banking industry.
Vault.com is the leading media company focused on careers. Job seekers, students and professionals have discovered that Vault is the Internet's ultimate destination for insider career and education information.
Vault publishes over 120 career guides and its web site, features thousands of company, university, industry and occupational profiles. Additionally, Vault provides salary surveys, articles on workplace topics, a network of message boards for professionals, and job-related video, blogs and research tools.
Here is an opportunity to sign up for free membership on Vault.com and get Career Guides for Free.
, enjoy!
and Vault Career Guide to Investment Banking, 6th Edition, both of which provide with clear explanation and insightful experience on how to look for a job and prepare interviews efficiently, expecially on investment banking industry.Vault.com is the leading media company focused on careers. Job seekers, students and professionals have discovered that Vault is the Internet's ultimate destination for insider career and education information.
Vault publishes over 120 career guides and its web site, features thousands of company, university, industry and occupational profiles. Additionally, Vault provides salary surveys, articles on workplace topics, a network of message boards for professionals, and job-related video, blogs and research tools.
Here is an opportunity to sign up for free membership on Vault.com and get Career Guides for Free.
Jun
18
Please allow me to share an interesting paper I came across this morning, Simulation-Based Estimation of Contingent-Claims Prices, the main point of this paper is to use Monte Carlo simulation, along with Maximum likelihood estimation (MLE), to reduce the biases caused by MLE method alone,
Download the paper and accompanying matlab code at http://www.mysmu.edu/faculty/yujun/research.html
Quotation
A new methodology is proposed to estimate theoretical prices of financial contingent claims whose values are dependent on some other underlying financial assets. In the literature, the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but is not necessarily the best method in finite samples.
This paper proposes a simulation-based method. When it is used in connection with ML, it can improve the finite-sample performance of the ML estimator while maintaining its good asymptotic properties. The method is implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond and bond option pricing
model. It is especially favored when the bias in ML is large due to strong persistence in the data or strong nonlinearity in pricing functions. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims when ML is biased. The bias reductions are sometimes accompanied by reductions in variance. Empirical applications to U.S. Treasury bills highlight the differences between the bond prices implied by the simulation-based approach and those delivered by ML. Some consequences for the statistical testing of contingent-claim pricing models are discussed.
This paper proposes a simulation-based method. When it is used in connection with ML, it can improve the finite-sample performance of the ML estimator while maintaining its good asymptotic properties. The method is implemented and evaluated here in the Black-Scholes option pricing model and in the Vasicek bond and bond option pricing
model. It is especially favored when the bias in ML is large due to strong persistence in the data or strong nonlinearity in pricing functions. Monte Carlo studies show that the proposed procedures achieve bias reductions over ML estimation in pricing contingent claims when ML is biased. The bias reductions are sometimes accompanied by reductions in variance. Empirical applications to U.S. Treasury bills highlight the differences between the bond prices implied by the simulation-based approach and those delivered by ML. Some consequences for the statistical testing of contingent-claim pricing models are discussed.
Download the paper and accompanying matlab code at http://www.mysmu.edu/faculty/yujun/research.html
Jun
15
I would like to take this opportunity to thank the author Thierry Roncalli for letting me know this great source.
QAM (Quantitative Asset Management) library:
QAM is the Gauss library which has been developped for the lecture notes on Quantitative Asset Management.
This library contains procedures:
for computing backtest (monthly rebalancing, currency hedging, strategy leveraging, fees managing, performance reporting, etc.).
for portfolio allocation (Black-Litterman, Markowitz, ERC, MDP, risk Bbdgeting, index sampling, 130/30, MSR, Sharpe style analysis, etc.).
for computing numerical algorithms (simplex set, Markov generator, quadrature rules, Fokker-Planck equation, etc.).
for derivatives pricing (dynamic delta hedging, Hedge fund replication, etc.).
for statistical methods (Artificial neural networks, copula, CSS, FLS, GMM, Huber, LAD, Logit, MARS, ML, NLS, PCA, Probit, Quantile regression, QP, Robust, Non-parametric Kernel regression, RBS, Tobit, factor models, etc.).
for time series analysis (arch, garch, vecm, spectral analysis, wavelets, etc.)
for strategy backtesting (covered call, bull-spread, carry trade, variance swaps, vix, long/short equity, absolute return strategy, trend-following strategy, etc.);
for stock screening (gini optimization, scoring methods, boosting, baging method, etc.)
for risk management (stop loss strategy, take profit strategy, concentration, etc.)
Please download the manual, library and lecture notes (in French only, unfortunately) at the author's webpage.
QAM (Quantitative Asset Management) library:
QAM is the Gauss library which has been developped for the lecture notes on Quantitative Asset Management.
This library contains procedures:
for computing backtest (monthly rebalancing, currency hedging, strategy leveraging, fees managing, performance reporting, etc.).
for portfolio allocation (Black-Litterman, Markowitz, ERC, MDP, risk Bbdgeting, index sampling, 130/30, MSR, Sharpe style analysis, etc.).
for computing numerical algorithms (simplex set, Markov generator, quadrature rules, Fokker-Planck equation, etc.).
for derivatives pricing (dynamic delta hedging, Hedge fund replication, etc.).
for statistical methods (Artificial neural networks, copula, CSS, FLS, GMM, Huber, LAD, Logit, MARS, ML, NLS, PCA, Probit, Quantile regression, QP, Robust, Non-parametric Kernel regression, RBS, Tobit, factor models, etc.).
for time series analysis (arch, garch, vecm, spectral analysis, wavelets, etc.)
for strategy backtesting (covered call, bull-spread, carry trade, variance swaps, vix, long/short equity, absolute return strategy, trend-following strategy, etc.);
for stock screening (gini optimization, scoring methods, boosting, baging method, etc.)
for risk management (stop loss strategy, take profit strategy, concentration, etc.)
Please download the manual, library and lecture notes (in French only, unfortunately) at the author's webpage.
