What is patell Z?
[4] Patell or Standardized Residual Test (Abbr.: Patell Z) The Patell test is a widely used test statistic in event studies. In the first step, Patell (1976, 1979) suggested to standardize each ARi by the forecast-error-corrected standard deviation before calculating the test statistic.
What is meant by abnormal rate of return?
Abnormal rate of return or ‘alpha’ is the return generated by a given stock or portfolio over a period of time which is higher than the return generated by its benchmark or the expected rate of return. It is a measure of performance on a risk-adjusted basis.
What does event study measure?
An event study, or event-history analysis, examines the impact of an event on the financial performance of a security, such as company stock. An event study analyzes the effect of a specific event on a company by looking at the associated impact on the company’s stock.
How to calculate t-test in event studies?
I have also read MacKinley (1997) popular paper for event studies but it seems to use when calculating the t-test- the number of observations (CAR) and not the number of days in the event window. Thank you in advance for your valuable help. ΣΑR is the sum of abnormal returns, i.e. CAR. Also, N is the number of days in the event window.
Is the t statistic the same as the s statistic?
I cannot calculate t-statistic in the same way I calculated cumulative abnormal return (CARs) for 6 and 12 days because I cannot calculate standard deviation. S.E. refers to the standard deviations of ARs during the event window which is different from my estimation window for normal returns.
How is abnormal return calculated in event studies?
In this code, abnormal return is calculated only for the event_window. Later when they calculate abnormal return sd, it only uses the values from the event window. As far as I understand from the literature, it should be using the values from the estimation window.
How is the t value of a t test calculated?
A t-test measures the difference in group means divided by the pooled standard error of the two group means. In this way, it calculates a number (the t-value) illustrating the magnitude of the difference between the two group means being compared, and estimates the likelihood that this difference exists purely by chance (p-value).