Influence on Competitors – Regression

But our main question is whether significant news affects the competitors. In the previous regressions we had all the data, but now only significant news are analysed. Approximately 10% of the largest returns (both positive and negative) were chosen as “important” news (the number is equal to the number of outliers in the first tests). I regressed competitors’ returns on company A’s significant returns and controlled for the industry using S&P technology index.

- – denotes significant returns at time t for company A

- – is the constant term

- – is the return of the first (second) competitor at time t. If the company A has only 1 competitor, the second regression is not calculated.

- – is the industry return (return of the S&P index for technological companies only) at time t.

Proportion of the news’ effect on competitor(s)’ return

H₀: company A’s significant return does not negatively affect its competitors’ returns on the same day.

H_a: company A’s significant return negatively affects its competitors’ returns on the same day.

	Competitor 1	Competitor 2		Competitor 1	Competitor 2
	p-value		p-value		p-value		p-value
A	0.2451	0.0073	0.2866	0.0000	KLAC	0.3936	0.0000
AAPL	-0.7736	0.0000	-0.9780	0.0000	LLTC	0.6494	0.0000	0.6237	0.0000
ADI	0.8126	0.0000			LXK	0.1858	0.0134
ALTR	0.3693	0.0000			MSFT	-0.0485	0.1191	-0.0708	0.3635
AMAT	0.4154	0.0002			MXIM	0.2980	0.0000	0.3140	0.0001
AMD	0.0253	0.2442	0.0659	0.0284	NCR	-0.0117	0.8934	0.0427	0.1433
BRCM	0.1678	0.0009	0.1680	0.0076	NTAP	0.1025	0.3227	0.2772	0.0002
CIEN	0.0669	0.2331			QCOM	0.2036	0.0365
CSCO	0.2601	0.0071	0.1812	0.0250	QLGC	0.1453	0.0000	0.1446	0.0000
EMC	0.2499	0.0041	0.0566	0.5656	SANM	0.0458	0.1162
GOOG	0.4007	0.1035	0.1565	0.0146	TMO	0.2218	0.0006
HPQ	0.0345	0.4132			TXN	0.5289	0.0000
IBM	0.1999	0.1549	0.1266	0.2976	XLNX	0.9892	0.0000
INTC	0.3791	0.0840	0.0490	0.3629	XRX	0.1222	0.2233
					YHOO	0.3076	0.0226	0.0800	0.1349

Table 9 – Results || Estimated values of for competitors 1 and 2 P-value less than 0.1 denotes 90% significance level P-value less than 0.05 denotes 95% significance level P-value less than 0.01 denotes 99% significance level

This time the only significant results are shown by Apple. It has a dramatic opposite effect on its competitors. The results are also highly significant. NCR and Microsoft also show some opposite effect, but the results are insignificant and are very close to 0.

Discussion of the Results

Date: 2015-12-17; view: 634