Page 6 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.75, # 2, 2018, pp. 4-16

II. RESEARCH METHODOLOGY

We define the absolute percent change in NASDAQ Composite Index as

= | − −1 × 100| (1)

−1

where t can be either month or day depending on whether we are looking at the daily
monthly percentage change or the daily percentage change. The mean absolute
percentage change (MAPC) then is simply the mean of the absolute percentage
̅
changes, which we can denote as .

For the first study, our data consists of the percentage changes in the monthly closing
values of the Nasdaq Composite Index from February 1971 until December 2017. The
NASDAQ Composite Index is market value weighted. It may seem that analysis of
month effect will be affected by the omission of dividends. Lakonishok and Smidt
(1988) find that this omission does not seem to affect their results with respect to
month effect. Hence, we do not include the dividends. For the second study we find
the MAPC for a month by averaging the on daily percentage changes.

In addition to analyzing the data for the entire period (February 1971 to December
2017), we divide the entire period into the following sub-periods to gain deeper insight
into the performance of NASDAQ Composite Index:

 1971 to 1992: a rather stable period;

 1993 to 2002: period characterized by run-up in stock prices created by dot.com
bubble, and subsequent bust;

 2003 to 2017: the post Sep 11, 2001 world, the Great Recession, and the longest
period of economic expansion following that.

We hope to show that the month effect is sensitive to the time period under study.

We first look at the statistical descriptives for the period February 1971 to December
2017. We present distribution of the absolute monthly percentage changes and test the
distribution for normality through the Jarque-Bera statistic. This widely used statistics
is based on the values of skewness and kurtosis of sample data. For large n, with

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