Recent Interesting Publications

Management Quality, Financial and Investment Policies, and Asymmetric Information

Thomas J. Chemmanur, Imants Paeglis, Karen Simonyan

Journal of Financial and Quantitative Analysis

doi:10.1017/S0022109009990299 Published online by Cambridge University Press 10 Sep 2009

Link: http://www2.bc.edu/~chemmanu/paper/JFQA2007.pdf

Comment: the asymmetric information is an interesting topic.



Does Futures Price Volatility Differ Across Delivery Horizon?

Berna Karali, Jeffrey H. Dorfman , Walter N. Thurman

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1456555

Comments: The applications of Bayesian estimator would be interesting to quants.


Resolving Macroeconomic Uncertainty in Stock and Bond Markets

Beber, Alessandro, and Michael W. Brandt, Review of Finance 13, 2009, 1-45. Lead article.

Link: http://faculty.fuqua.duke.edu/~mbrandt/papers/published/econderivs.pdf

Comments: a nice paper that links macroeconomics and microeconomics and inspires/gives the ideas accounting for the jumps.


Agent-Based Approach to Option Pricing Anomalies

Kyoko Suzuki, Tetsuya Shimokawa, and Tadanobu Misawa

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL. 13, NO. 5, OCTOBER 2009, pp:959-972

Comments: a paper that delivers the idea of modeling human decision behavior using evolutionary computation.


What the Market Watched: Bloomberg News Stories and Bank Returns as the Financial Crisis Unfolded

Robin L. Lumsdaine

Link:http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1482019

Comments: a paper about information retrieval from the news, which is a good direction. 


Hard-To-Value Stocks, Behavioral Biases, and Informed Trading

Alok Kumar

Journal of Financial and Quantitative Analysis, Oct 2009

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=903820

Comments: Study the decision behavior for trading


On the Volatility and Comovement of U.S. Financial Markets Around Macroeconomic News Announcements

Menachem Brenner, Paolo Pasquariello and Marti Subrahmanyam

Journal of Financial and Quantitative Analysis, Oct 2009

Link: http://webuser.bus.umich.edu/ppasquar/fed.pdf

Comments: another paper about linking microeconomics and macroeconomics using information retrieval approach


Nonparametric Estimation of the Short Rate Diffusion Process from a Panel of Yields

Abdoul G. Sam and George J. Jiang

Journal of Financial and Quantitative Analysis, Oct 2009

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=890982

Comments: Nonparametric or nonparametric statistics methods are promising.


The value of combining the information content of analyst recommendations and target prices

Joshua Huang, G. Mujtaba Mian, and Srinivasan Sankaraguruswamy

Journal of Financial Markets, Volume 12, Issue 4, November 2009, Pages 754-777

Comments: another paper about information retrieval for stock trading.


Extreme return–volume dependence in East-Asian stock markets: A copula approach

Cathy Ninga,  and Tony S. Wirjantob

Finance Research Letters, Volume 6, Issue 4, December 2009, Pages 202-209

Comments: This paper indicates when you trade in east-Asian markets, you should pay careful attention to the size of volume. 


The Relative Informational Efficiency of Stocks and Bonds: An Intraday Analysis

Chris Downing, Shane Underwood and Yuhang Xing

Journal of Financial and Quantitative Analysis (2009), 44:1081-1102 

Link: http://www.ruf.rice.edu/~yxing/bondinfoeff.pdf

Comments: an interesting paper about informational inefficiency and information transparency in the corporate bond market and stock market. Another point in this paper worthy attention is that  evidence of the return relation can be the indicative of the activities of informed traders in the market.


Risk Management Research Report - Fall 2009

Robert W. Kolb 


Comments: The first introduced paper is quite interesting. Driven by the desire to gamble in human personality, favoring lottery-type stocks leads to investment underperformance.


The Relationship between the Volatility of Returns and the Number of Jumps in Financial Markets
Álvaro Cartea and Dimitrios Karyampas


Comments: A very nice paper presents many interesting findings. The role of jumps is explained well in affecting the volatility. Detection and Forecasts of the average number of jumps are also investigated. The Levy jump process is worth exact understanding. A nice tutorial can be found on http://www.stochastik.uni-freiburg.de/~eberlein/papers/JumpTypeLevyProcesses.pdf . A reference in this paper is also worth reading, Lee and Hannig, Detecting jumps from Levy jump diffusion process, working paper


Review of Discrete and Continuous Processes in Finance: Theory and Applications
Attilio Meucci 


Comments: A nice review of stochastic processes in finance.


Option Pricing with Piecewise-Constant Parameters, Discrete Jumps and Regime-Switching

Jianwei Zhu 


Comments: a paper treats the stochastic model parameters time-variant to account for regime-change. The idea is pretty like approaches of adaptively learning/updating models, but of less flexibility and may be practical. 


Multivariate GARCH Models with Correlation Clustering

Mike K. P. So and Iris W.H. Yip 


Comments: A paper explores a cluster patterns to cluster the parameters of the multivariate Garch models. Methods based on DP (Dirichlet Process) or LPP (Local Partition Process) clustering seem more beautiful.


Consumption Risk-Sharing in Social Networks

Attila Ambrus, Markus M. Mobius and Adam Szeidl 


Comments: Good idea about applying social network to risk sharing in insurance. 


Conference: Computational Intelligence for Our Financial Crisis


Comments: Nice summaries of CI/AI application directions. About how Computational Intelligence can be used to make better decisions in this uncertain environment. It can be applied in many areas of interest such as: Financial Decision Analysis, Business Rules Management, Cognitive and Human Behavioral Modeling, Semantic Technologies and Data Interoperability, Data Mining and Data Analysis, Social Network Marketing, and Risk Management.


Who dares wins: Opportunities await traders who embrace new technologies
Comments: Peter van Kleef, principal, Lakeview Capital Market Services, has nice points about the future of automated trading in this article. I agree that machine-readable news (in my mind, it is the information extraction/retrieval (IR) from news, announcements, etc) and social networking will be the next promising technologies for A.I. Trading. Information type analysis (ITA) is also critical as well as traditional technical analysis (TA) and fundamental analysis (FA). 


Wall St. Computers Read the News, and Trade on It
Comments: This is a good practice using text information retrieval (IR) techniques. More IR approaches, like audio, video IR, will be applied, as is mentioned in the article. Again, it will be a good direction.

Also, recall the paper titled with "What the Market Watched: Bloomberg News Stories and Bank Returns as the Financial Crisis Unfolded" which is listed above. Some great ideas started from academia. So stay in touch with them! 

Keywords: information retrieval (IR), news


Do Bond Rating Changes Affect Information Risk of Stock Trading?
Authors: Yan He, Junbo Wang,  and K.C. John Wei
Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=966691&rec=1&srcabs=977979 Also, in Journal of Empirical Finance, Volume 18, Issue 1, January 2011, Pages 103-116.
Comments: This paper studied effects of changes in firm’s bond rating on the information asymmetry of its stock trading and other measures of information risk and thus presents a cross-asset approach.

Keywords: cross-asset approach, bond rate, stock trading


Combining Technical Analysis and Support Vector Machine for Stock Trading
Authors: Pittipol Kantavat, Boonserm Kijsirikul
Link: http://doi.ieeecomputersociety.org/10.1109/HIS.2008.76 in 2008 Eighth International Conference on Hybrid Intelligent Systems
Comments: Although only some preliminary results are presented in this paper, it is still a nice trial of combining technical analysis with machine learning approaches like SVM.

Keywords: technical analysis, SVM, stock trend
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