Quarterly Publication of Multinational Finance Society • ISSN 1096-1879

The Scrutinized-firm Effect, Portfolio Rebalancing, Stock Return Seasonality, and the Pervasiveness of the January Effect in Canada
(Multinational Finance Journal, 2002, vol. 6, no. 1, pp. 1-27)

George Athanassakos
Wilfrid Laurier University, Canada,
and ALBA, Greece

This article examines whether seasonality is present in the excess returns of low risk Canadian firms in safe industries for a sample of firms that are highly scrutinized and visible and uses such tests as the foundation to empirically test competing explanations of stock market seasonality, namely, the tax-loss selling hypothesis and the gamesmanship hypothesis. The tests cover the period 1980 to 1998. For a sample of highly scrutinized and visible firms strong seasonality in excess returns is reported. However, the firms in our sample have unusually low excess returns in January and returns adjust upwards over the remainder of the year. The results hold even after we control for various risk differences among the stocks of our sample. Further, this article’s findings imply that the January effect is not as pervasive across risk classes and industry sectors as earlier studies using aggregate data have shown it to be. The disaggregated data of this study provide evidence in support of the gamesmanship hypothesis, but not the tax-loss selling hypothesis. Whenever a January effect is observed, the last quarter of the year tends to be weak for those companies in our sample that experienced a strong January. The opposite is true when a January effect is not evident, as the gamesmanship hypothesis would predict (JEL G14).

Keywords: firm visibility, gamesmanship hypothesis, January effect, portfolio rebalancing.

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Dissemination of Stock Recommendations and Small Investors: Who Benefits?
(Multinational Finance Journal, 2002, vol. 6, no. 1, pp. 29-42)

Bilgehan Yazici
ABN-AMRO Asset Management Turkey Istanbul, Turkey
Gülnur Muradoglu
Cass University Business School City of London, UK

The objective of this study is to examine whether published investment advice generates higher returns for investors. We investigate the impact of security recommendations in the financial press on common stock prices in Istanbul Stock Exchange. Recommendations of Investor Ali column of the weekly-published popular economics journal Moneymatik constitutes our sample. The column is designed to inform individual investors about company prospects and use them as the basis for its recommendations. The results show that the published investment advice in this column does not help small investors earn excess returns. On the contrary, it provides a valuable deal to its ‘preferred investors’, if any, in selecting the stocks. If one could front-run the column’s recommendations by five days he/she could earn more than 5% per week in excess of the index return. Compounded annually the excess return of a preferred investor could earn would be more than an amazing 1500% per annum (JEL G11, G12, G14, G15).

Keywords: excess returns, insider trading, investment advice, ISE, stocks.

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Nonlinear Noise Estimation in International Capital Markets
(Multinational Finance Journal, 2002, vol. 6, no. 1, pp. 43-63)

Costas Siriopoulos
University of Macedonia, Greece
Alexandros Leontitsis
University of Kent at Canterbury, U.K.

We analyzed six stock exchange markets through the nonlinear dynamics concept. We used daily data from the Toronto Stock Exchange, NYSE, London Stock Exchange, Hong Kong Stock Market, Tokyo Stock Exchange, and the Singapore Stock Exchange. The period studied is from January 1, 1988 to June 30, 1999. We performed Local Principal Components Analysis in order to estimate the dimension of each underlying attractor. Our main interest is the noise level estimation of each time series. The results indicate weak determinism and strong noise influence. The noise-to-signal ratio for almost all time series is above 50%. Noise is leptokurtic in the eastern stock markets, and mesokurtic in western ones. (JEL C22, G15).

Keywords: chaos theory, local principal components analysis, noise estimation, nonlinear dynamics.

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