Mark Kamstra Associate Professor of Finance Schulich School of Business On Sabbatical July 2009 - June 2010: Psychology Department, Stanford University Email: mkamstra -at- schulich -dot- yorku -dot- ca

CURRICULUM VITAE  (in PDF format)

RESEARCH

PUBLICATIONS

• R. Glen Donaldson, M. Kamstra and Lisa A. Kramer [forthcoming 2010] " Estimating the Ex Ante Equity Premium " Journal of Financial and Quantitative Analysis.
• M. Kamstra, Lisa A. Kramer and Maurice D. Levi [2009] " Is it the weather? Comment " Journal of Banking and Finance, 33, 578-582.
• M. Kamstra and L. Kramer [2009] Time Variation in the Market Return, Encyclopedia of Complexity and System Science, Bruce Mizrach (Ed.), Springer-Verlag.
• M. Kamstra and Moshe A. Milevsky [2005] " Waiting for Returns: Using Space-Time Duality to Calibrate Financial Diffusions " Quantitative Finance, 5 (3), June, 237-244, 2005.
• I. Garrett, M. Kamstra and L.A. Kramer [2005] " Winter Blues and Time Variation in the Price of Risk " Journal of Empirical Finance, 12, 291-316, 2005.
• R.G. Donaldson and M. Kamstra [2005] " Volatility Forecasts, Trading Volume and the ARCH vs Option-Implied Volatility Tradeoff " Journal of Financial Research, 27 (4), Winter, 519-538, 2005.
  See the bottom of this page for Supplemental Materials to accompany this paper.
• M. Kamstra, L.A. Kramer and M.D. Levi [2003] " Winter Blues: Seasonal Affective Disorder (SAD) and Stock Market Returns " American Economic Review, March, 93 (1), 324-343.
  See the bottom of this page for Supplemental Materials to accompany the "Winter Blues" paper.
• M. Kamstra,  L.A. Kramer and M.D. Levi. [2002] "Losing Sleep at the Market: The Daylight Saving Anomaly: Reply'' American Economic Review, September, 92 (4), 1257-1263.
• M. Kamstra, P. Kennedy and T.K. Suan. [2001] " Combining Bond Rating Forecasts Using Logit "  The Financial Review, 37 (2), May, 75-96.
• R.G. Donaldson  and M. Kamstra, [2001] " Estimating and Testing Fundamental Stock Prices: Evidence from Simulated Economies " Computer-Intensive Econometrics, ed. D. Giles, Statistics Textbooks & Monographs, Marcel Dekker: New York, forthcoming.
• M. Kamstra, L.A. Kramer and M. Levi, [2000] " Losing Sleep at the Market: The Daylight Saving Anomaly " American Economic Review, 90 (4), Sept., pp.1005-1011.
• M. Kamstra, [1999] "An Observation on Regression-Based Specification Tests" Communications in Statistics, Theory and Methods, 28 (6),  pp.1435-1446.
• R.G. Donaldson and M. Kamstra, [1999] "Neural Network Forecast Combining with Interaction Effects" Journal of the Franklin Institute, 336B (2)  pp.227-236.
• M. Kamstra and P. Kennedy, [1998] "Combining Qualitative Forecasts Using Logit" International Journal of Forecasting, 14,  pp.83-93.
• R.G. Donaldson and M. Kamstra, [1997] "An Artificial Neural Network - GARCH Model for International Stock Return Volatility" Journal of Empirical Finance, 4 (1),  pp. 17-46.
• P. Harrald and M. Kamstra, [1997] "Evolving Artificial Neural Networks to Combine Financial Forecasts"    IEEE Transactions on Evolutionary Computation, 1 (1), pp.40-52.
• R.G. Donaldson and M. Kamstra, [1996] "Using Dividend Forecasting Models to Reject Bubbles in Asset Prices: The Case of the Crash of 1929" Review of Financial Studies, 9,  pp.333-383.
• R.G. Donaldson and M. Kamstra, [1996] "Using Artificial Neural Networks to Combine Forecasts" Journal of Forecasting, 15,  pp.49-61.
• J. Hallman and M. Kamstra, [1989] "Combining Algorithms Based on Cointegrating Restrictions Together with Robust Estimation Techniques," Journal of Forecasting, 8,  pp.189-198.
• C.W.J. Granger, H. White and M. Kamstra, [1989] "Interval Forecasting: An Analysis Based on ARCH - Quantile Estimators," Journal of Econometrics, 40,  pp.87-96.

SCHOLARLY CONFERENCE PAPERS

• Together with R.G. Donaldson, [1996] "Neural Network Forecast Combining with Interaction Effects" Proceedings, Workshop on Foundations of Information/Decision Fusion, Washington, DC August 7-9, 1996.
• Together with R.G. Donaldson, [1996] "Artificial Neural Networks in Fundamental Asset Pricing and Volatility Forecasting" Proceedings, CIFO , Montreal, Quebec, September 16-18, 1996.

Some of My Working Papers and Work In Progress

• Opposing Seasonalities in Treasury versus Equity Returns, with Mark Kamstra and Maurice Levi. Under revision for resubmission to the Journal of Financial and Quantitative Analysis.
  • Supplemental materials are available to accompany this paper, including data on the Onset/Recovery variable used to test for an opposing effect of time-varying risk aversion on Treasury and equity returns.
• Seasonal Variation in Bid-Ask Spreads with Mark Kamstra and Ramon DeGennaro
  • Supplemental materials are available to accompany this paper, including data on the Incidence variable used to test for the effect of time-varying risk aversion on spreads.

Data and Supplemental Materials

•  Materials to accompany "Opposing Seasonalities in Treasury Versus Equity Returns":
Below I provide data for the Onset/Recovery variable defined in this paper. Use of the Onset/Recovery variable is recommended for settings where you expect seasonal risk aversion to lead to opposite signs on the dependent variable across the fall and winter periods. That is, it is appropriate for studying "flow" variables (as opposed to "stock" variables). For example, use of the Onset/Recovery variable is appropriate to use when considering security returns. (Daily equity returns are expected to be negative in the fall, as risk averse investors shun risky assets. Then daily equity returns are expected to be positive in the fall, as investors resume their former risky holdings. Similarly daily Treasury bond returns are expected to be positive in the fall and negative in winter.)
• The Onset/Recovery variable (OR) is available in raw text format in monthly or daily form.
• The Onset/Recovery variable (OR) is available as a SAS dataset in monthly or daily form.
• Note that in the daily data files, "Julian" refers to the day of the year (from 1 to 365, or 366 in leap years). For non-leap years, simply delete the 366th observation.
•  Materials to accompany "Seasonal Cycles in Bid-Ask Spreads":
Below I provide data for the Incidence variable defined in this paper. Use of the Incidence variable is recommended for settings where you expect seasonal risk aversion to lead to the same sign on the dependent variable across the fall and winter periods. That is, it is appropriate for studying "stock" variables (as opposed to "flow" variables). For example, use of the Incidence variable is appropriate for use when considering bid-ask spreads. When considering bid-ask spreads, one expects seasonal depression to lead to a spread between dealer bid and ask quotes that is wider during both the fall and winter seasons than during the rest of the year. As such, the Incidence variable, which has the same sign across the fall and winter periods, is appropriate.
• The Incidence variable is available in raw text format in monthly or daily form.
• The Incidence variable is available in SAS dataset format in monthly or daily form.
• Note that for the daily data, "Julian" refers to the day of the year (from 1 to 365, or 366 in leap years). For non-leap years, simply delete the 366th observation.
•  Materials to accompany "Winter Blues: A SAD Stock Market Cycle":
• Appendix containing sensitivity checks and a table of gains to various pro-SAD trading strategies
• If you are interested in estimating the effect of seasonal risk aversion on equity returns, I recommend that you use the Onset/Recovery variable we introduce in our "Opposing Seasonalities in Treasury Versus Equity Returns" paper instead of the obsolete sine wave and Fall dummy variable specification that we employed in our original "Winter Blues..." paper. It yields virtually indentical results without relying on an ad hoc dummy variable.
•  Materials to accompany "Volatility Forecasts, Trading Volume and the ARCH vs Option-Implied Volatility Tradeoff":
• Detailed supplement containing additional model estimation results.