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Can the publication of annual financial reports become an opportunity for insider trading?

Suliga M.

Managerial Economics

2015

Vol. 16, no. 1

77--89

Illegal insider trading is a problem that involves most of financial markets. Unusual abnormal returns as well as increased trading volumes observed ahead of price sensitive information can be signals of this type of market abuse behavior. In this paper, I study the occurrence of insider trading on the Warsaw Stock Exchange. I verify if publications of annual financial reports of WIG issuers can be preceded by this phenomenon. The study includes reports from the period between 1 January, 2010, and 29 May, 2014. In order to define abnormal returns, I suit the GARCH process to daily returns and use event-study analysis. Potential insider trading behaviors are found with the use of two-day cumulative abnormal returns in a first step and with the use of daily abnormal returns afterwards. The publications that are marked with potential informed price movements are analyzed for the presence of extremely high abnormal trading volumes, which can be additional signals of market abuse.

The modified tempered stable distribution, GARCH models and option pricing

Kim Y. S., Rachev S. T., Chung D. M., Bianchi M. L.

Probability and Mathematical Statistics

2009

Vol. 29, Fasc. 1

91--117

We introduce a new variant of the tempered stable distribution, named the modified tempered stable (MTS) distribution and we develop a GARCH option pricing model with MTS innovations. This model allows the description of some stylized empirical facts observed in financial markets, such as volatility clustering, skewness, and heavy tails of stock returns. To demonstrate the advantages of the MTS-GARCH model, we present the results of the parameter estimation.

Dependence structure of stable R-GARCH processes

Nowicka-Zagrajek J., Weron A.

Probability and Mathematical Statistics

2001

Vol. 21, Fasc. 2

371--380

In this paper we investigate properties of R-GARCH processes with positive strictly stable innovations. We derive the unconditional distributions and analyze the dependence structure. This analysis is carried out by means of the measure of dependence - the codifference - which extends the behavior of the covariance function to situations where the covariance function is no longer defined. In the case of R-GARCH (1,1,0) process we determine the exact asymptotic behavior.