Controlling for the market

However, one may suggest that a high or low return can arise if generally investors are buying or selling stocks on the day. The reason for that might be an economy-wide news piece. Therefore, to identify the abnormal company-related returns we also subtract S&P 500 index return from the stock return. Then we shall have a return of the company less the overall investors’ buying attitude – the adjusted company return .

This would make more sense as it removes market-wide news. Moreover, most of the sampled stocks exhibit appreciation during the sample period, which means that a negative return is less likely to happen than positive (or that the positive returns’ scale is larger), therefore even if a piece of news led to significant positive return for company A (say, 7%) it may only make its competitor to grow slower than usual (say, 0.2% instead of 1.2%). S&P 500 index itself grew by 44% during the sample period and if we subtract it from the company returns we may identify the “losers” and “winners” as well as “better than index”, or positive returns and “worse than index”, or negative returns. In the previous case, say the S&P rose by 2.5%, then company A performed (7-2.5)=4.5% better than the index, while its competitor performed (0.2-2.5)=-2.2% worse than the index. After subtraction it is easier to see whether a news article affected both the company A and its competitor.

Date	INITIAL RETURNS						ADJUSTED
	AGILENT TECHS.	TERADYNE	THERMO FISHER SCIENTIFIC		S&P 500		AGILENT TECHS.	TERADYNE	THERMO FISHER SCIENTIFIC
28/11/2011	0.039	0.036	0.026		2.88%		0.97%	0.73%	-0.26%
29/11/2011	-0.004	-0.002	0.011		0.22%		-0.62%	-0.47%	0.85%
30/11/2011	0.068	0.108	0.025		4.24%		2.60%	6.58%	-1.75%
01/12/2011	0.008	-0.007	-0.004		-0.19%		1.04%	-0.48%	-0.25%
02/12/2011	-0.028	-0.016	-0.011		-0.02%		-2.82%	-1.56%	-1.04%
05/12/2011	0.008	0.025	0.005		1.02%		-0.21%	1.45%	-0.51%
06/12/2011	-0.002	0.009	0.009		0.11%		-0.33%	0.78%	0.74%
07/12/2011	-0.009	0.001	-0.004		0.20%		-1.07%	-0.05%	-0.63%
08/12/2011	-0.063	-0.019	-0.037		-2.14%		-4.17%	0.29%	-1.53%
09/12/2011	0.026	0.054	0.008		1.67%		0.94%	3.71%	-0.90%
12/12/2011	-0.046	-0.029	-0.011		-1.50%		-3.13%	-1.37%	0.38%
13/12/2011	-0.017	-0.034	-0.01		-0.87%		-0.86%	-2.54%	-0.11%
14/12/2011	-0.007	-0.029	-0.021		-1.14%		0.48%	-1.77%	-0.98%
15/12/2011	0.016	-0.001	0.009		0.32%		1.24%	-0.40%	0.59%

Table 2 – Adjusting data for market returns

The “Adjusted” part of the table (table 2) represents companies’ daily returns less S&P return. On 28^th of November, 2011 all three companies showed to have exceptional returns. However, the S&P index itself showed a return of 2.88% on that day as well and therefore we may not conclude that all three stocks had positive news on that day. After the adjustments the companies show relative returns ranging from -0.26% to 0.97%, which are not that large. However, not all events are hidden with the adjustments. On 8^th of December, 2011 (table 4) we see that even after the subtraction of S&P’s return Agilent Technologies stock has a significant negative return of -4.7% and other outliers still remain.

However, comparing the adjusted returns themselves is not comfortable. Some returns are negative and some are positive. So I first take the square of the returns, and then find the outliers. Squaring the returns will magnify the heteroscedastic properties of the returns as well as make it easier to compare negative and positive returns.