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Macroeconomic News Announcement Effects on Stocks

Macroeconomic News Announcement Effects on Stocks. Allison Keane. 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.

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Macroeconomic News Announcement Effects on Stocks

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  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 • R1000 = log(P1000,t+1) - log(Pclose,t ) • Announcements (data taken from Yahoo Finance) • Skt = (Akt – Ekt ) / σk • Have to standardize because of units • Realized Variance • RV = Σr2 (calculated using five minute log returns) • DRVt = √ RVt-1 • WRVt = √((1/5)*(RVt-1 + RVt-2 + RVt-3 + RVt-4 +RVt-5))

  4. Equations • Standarizing R • Standardize R since S is standardized • Rt/DRVt • Rt/WRVt • Rt/MRVt • Regressions • Rt/WRVt = βkSk,t + εt

  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. 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 Announcements

  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 • R1000/ DRVt = βkSk,t + εt • 192 different regressions

  9. Regression I Results • 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 Significant Betas Average R2 values • Examined highest R2 values but no consistent pattern • Looked at averages and used the best standardization based on the average

  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 • R1000 = log(P1000,t+1) - log(Pclose,t ) • R1000/WRV = βkSk,t + εt • 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 Rt = βk(NP) t + βk(R) t + βk(I) t + βk(CU) t + βk(PI) t + εt • Prices Rt = βk(CPI) t + βk(PPI) t + εt • Investment Rt = βk(BI) t + βk(D) t + εt • Employment Rt = βk(NP) t + βk(HE) t + βk(AWW) t + βk(UR) t + εt

  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 Βk = β0+ β1k,t Sk,t if S<0 = β2+ β3k,t Sk,t if S>0

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