Management Quality, Financial and Investment Policies, and Asymmetric InformationThomas 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 |