1. Macroeconomic News Announcement Effects on Stocks Allison Keane

2. Motivation Determine if there exists a relationship between news announcements and stock returns News announcements occur before market opens – need appropriate measure of return  Need appropriate measure of standardization

3. Equations Returns  R 1000 = log(P 1000,t+1 ) - log(P close,t ) Announcements (data taken from Yahoo Finance)  S kt = (A kt – E kt ) / σ k  Have to standardize because of units Realized Variance  RV = Σr 2 (calculated using five minute log returns)  DRV t = √ RV t-1  WRV t = √((1/5)*(RV t-1 + RV t-2 + RV t-3 + RV t-4 +RV t-5 ))

4. Equations Standarizing R  Standardize R since S is standardized  R t /DRV t  R t /WRV t  R t /MRV t Regressions  R t /WRV t = β k S k,t + ε t

5. Different standardizations of R

6. Stocks Focused on four stock from S&P100  Begin with different industries Procter & Gamble (PG) Kraft (KFT) American International Group (AIG) Ford (F)  Later expand to see if similarities among industries Avon Product Inc.(AVP) Hartford Financial Group(HIG) Allstate Corp. (ALL) Colgate-Palmolive(CL)  Data sets include one minute price data from 2002 - 2007

7. Announcements Produce Price Index (PPI) Consumer Price Index (CPI) Durable Goods (D) Industrial Production (I) Retail Sales (R) Average Work Week (AWW) Unemployment Rate (UR) Hourly Earnings (HE) Nonfarm Payrolls (NP) Capacity Utilization (CU) Business Inventories (BI) Personal Income (PI) All announcements occur before market opens Any days announcements did not occur or data was not available are disregarded

8. Regression I: Test Different Standardizations Attempt to determine which standardization value for R was best  None, DRV, WRV, MRV Took the 10:00 return from four primary stocks standardized four different ways  Regressed each standardized R against each announcement individually  R 1000 / DRV t = β k S k,t + ε t  192 different regressions

9. Regression I Results Average R 2 values Found P-values very different for different combinations Could have small p-values for PG and KFT, but AIG and F would have high values Not very many significant coefficients for any standardization Examined highest R 2 values but no consistent pattern Looked at averages and used the best standardization based on the average Significant Betas

10. Regression II: Test Different Return Values Question: Which return should be used as overnight return measure?  Want to account more market adjustment Assume market will adjust quickly  Test 9:35, 9:40, 9:45, 9:50; 9:55, 10:00, 10:10, 10:20, 10:30, 10:40, 10:50, 11:00, 11:10, 11:20, 11:30, 12:30, 3:00 Use later times, 12:30 and 3:00 to show the announcement has had an effect by then  Standardize each return by WRV based on previous regression results R 1000 = log(P 1000,t+1 ) - log(P close,t ) R 1000 /WRV = β k S k,t + ε t  Do this regression for each return measure for PG only against each announcement individually  214 regressions

11. Regression II Results P-values varied depending on the announcement - Some announcements had very high p-values for all returns, some had smaller values - General trend – smaller p-values in morning relative to those in the afternoon -There was not one consistent return with the lowest P-value -Most lowest p-values occurred between 9:35 and 10:00 and only one past 11:00 -Focused on returns between 9:35 and 10:00 and used 10:00 because had lowest average R2 Difficulty: the coefficients would change sign - When regressed against HE, the first two returns had pos coefficients and the rest were negative - Occasionally, just one coefficient would change sign

12. Regression III: Multivariate Regressions Real Activity R t = β k (NP) t + β k (R) t + β k (I) t + β k (CU) t + β k (PI) t + ε t Prices R t = β k (CPI) t + β k (PPI) t + ε t Investment R t = β k (BI) t + β k (D) t + ε t Employment R t = β k (NP) t + β k (HE) t + β k (AWW) t + β k (UR) t + ε t

13. Regression III: Results Regress (F-stats) Newey - West Was hoping to see PG, AVP, CL to have similar significant regressions and AIG, HIG, ALL have similarities F-test for all announcement on PG becomes insignificant if take out BI

14. Extensions Perform regressions on individual stocks for ALL, AVP, CL, HIG Add more stocks from similar industries and S&P500 data In process of determining if response varies with sign Β k = β 0 + β 1k,t S k,t if S<0 = β 2 + β 3k,t S k,t if S>0