上财朱杰金融计量经济学9_2_EventStudy
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JZ (SUFE) Financial Econometrics 11/2012 7 / 12
Savor (JFE, 2012)
Create two zero-investment portfolios for no-information and information based price shocks, long losers and short winners. We expect the former portfolio to enjoy a positive abnormal return and the latter to su¤er a negative abnormal return. Run the following regression: 0 Rport,t = αport + βport Xt + uport,t , where Xt contains MKTt , SMBt , HMLt , and UMDt . The null: H0 : αport = 0. See results in Table 6.
JZ (SUFE) Financial Econometrics 11/2012 5 / 12
Savor (JFE, 2012)
Next step: examine which factors determine post-event returns. ARm,n = α + βAR0 + γ0 X + u, where X is a set of explanatory variables, including log size (log(ME )), log book-to-market ratio (log(BE /ME )), return over the previous 12 months (mom), and trading volume (vol). See results in Table 4. An alternative regression: ARm,n = α + βAR0 + γ(AR0 un) + δ0 X + ε(AR0 vol ) + u,
JZ (SUFE)
Financial Econometrics
11/2012
8 / 12
Savor (JFE, 2012)
Analyst report content. One interpretation of the results is that investors underreact to new …rm-speci…c fundamental information and overreact to other shocks. If this explanation is correct, the content of analyst reports should matter. We can run the following regression ARm,n = α + βAR0 + γagree (AR0 Results are given in Table 12. agree ) + γdis (AR0
JZ (SUFE) Financial Econometrics 11/2012 3 / 12
Savor (JFE, 2012)
The full sample is devided o 4 subsamples based on the direction of price change and on whether an analyst report was released around the price event. Price movement accompanied by an analyst report if: at least one is published during ( 1, 1). The 4 subsamples are: 1. Reported negative sample (17, 566 observations) 2. Unreported negative sample (52, 666 observations) 3. Reported positive sample (17, 056 observations) 4. Unreported positive sample (79, 182 observations). See summary statistics in Table 1 and Table 2.
disagree ) + δ0 X +
JZ (SUFE)
Financial Econometrics
11/2012
9 / 12
Exercises (From CLM, chapter 4)
1. Show that when using the market model to measure the abnormal returns, the sample abnormal returns from the following equation are asymptotically independent as the length of the estimation window L1 increases to in…nity. bi = Ri ε Xi bi . θ (1)
JZ (SUFE) Financial Econometrics 11/2012 2 / 12
Savor (JFE, 2012)
Data: Sample: Stocks covered by sell-side analysts and experienced large price changes. I/B/E/S Recommendations database provide data on analyst coverage. CRSP provides data on daily stock returns, …rm size, and trading volume. Annual accounting data are from CRSP/Compustat merged database. Each recommendation is classi…ed as: upgrade/downgrade/reiterations/initialization. Stocks are included only if at least …ve recommendations issued over the past 12 months. The sample starts in 1995 and ends in 2009. Final sample observations: 166, 470.
JZ (SUFE)
Financial Econometrics
11/2012
4 / 12
Savor (JFE, 2012)
Methodology: Large Price changes: any …rm-date observation where the absolute value of abnormal return from the 4-factor model over 10%:
Financial Econometrics
ZHU Jie
Shanghai University of Finance and Economics
November 2012
JZ (SUFE)
Financial Econometrics
11/2012
1 / 12
Savor (JFE, 2012)
Stock returns after major price shocks: the impact of information. The paper investigates whether information has any e¤ect on large price changes. Analyst reports are used as a proxy for information. Main …ndings: 1. Price events accompanied by information are followed by drift. 2. Price events without information result in reversals. 3. This is due to investors underreact to news about fundamentals and overreact to other shocks. 4. Information-based price changes are more strongly correlated with future earnings surprises than no-information ones. 5. The ratio of no-information to information-based price shocks is strongly correlated with aggregate implied volatility and also forecasts momentum returns.
where un is 1 if no report and 0 otherwise. See results in Table 5.
JZ (SUFE) Financial Econometrics 11/2012 6 / 12
Savor (JFE, 2012)
The regressions show that presence of information a¤ects post-event returns: Price shocks unaccompanied by information are followed by signi…cant reversals. Portfolio analysis con…rms the anomaly leads to a pro…table trading strategy. Each of the stocks in the full sample is assigned to one of four portfolios: 1. Negative no-information 2. Negative information 3. Positive no-information 4. Positive information At any point of time, these portfolios are made up of all stocks that experienced the required price event over the previous N trading days.
jARi ,t j = jRit
where R it is calculated from R it Rft
R it j,
= α + βi ,m (Rmt Rft ) + βi ,smb SMBt + βi ,hml HMLt + βi ,umd UMDt + uit
The Estimate window: 255 trading day-period starting 31 trading days before the event day. See summary statistics in Table 3. The ARm,n statistics con…rm that post-event returns are driven by information.
JZ (SUFE)
Financial Econometrics
11/2012
Savor (JFE, 2012)
Create two zero-investment portfolios for no-information and information based price shocks, long losers and short winners. We expect the former portfolio to enjoy a positive abnormal return and the latter to su¤er a negative abnormal return. Run the following regression: 0 Rport,t = αport + βport Xt + uport,t , where Xt contains MKTt , SMBt , HMLt , and UMDt . The null: H0 : αport = 0. See results in Table 6.
JZ (SUFE) Financial Econometrics 11/2012 5 / 12
Savor (JFE, 2012)
Next step: examine which factors determine post-event returns. ARm,n = α + βAR0 + γ0 X + u, where X is a set of explanatory variables, including log size (log(ME )), log book-to-market ratio (log(BE /ME )), return over the previous 12 months (mom), and trading volume (vol). See results in Table 4. An alternative regression: ARm,n = α + βAR0 + γ(AR0 un) + δ0 X + ε(AR0 vol ) + u,
JZ (SUFE)
Financial Econometrics
11/2012
8 / 12
Savor (JFE, 2012)
Analyst report content. One interpretation of the results is that investors underreact to new …rm-speci…c fundamental information and overreact to other shocks. If this explanation is correct, the content of analyst reports should matter. We can run the following regression ARm,n = α + βAR0 + γagree (AR0 Results are given in Table 12. agree ) + γdis (AR0
JZ (SUFE) Financial Econometrics 11/2012 3 / 12
Savor (JFE, 2012)
The full sample is devided o 4 subsamples based on the direction of price change and on whether an analyst report was released around the price event. Price movement accompanied by an analyst report if: at least one is published during ( 1, 1). The 4 subsamples are: 1. Reported negative sample (17, 566 observations) 2. Unreported negative sample (52, 666 observations) 3. Reported positive sample (17, 056 observations) 4. Unreported positive sample (79, 182 observations). See summary statistics in Table 1 and Table 2.
disagree ) + δ0 X +
JZ (SUFE)
Financial Econometrics
11/2012
9 / 12
Exercises (From CLM, chapter 4)
1. Show that when using the market model to measure the abnormal returns, the sample abnormal returns from the following equation are asymptotically independent as the length of the estimation window L1 increases to in…nity. bi = Ri ε Xi bi . θ (1)
JZ (SUFE) Financial Econometrics 11/2012 2 / 12
Savor (JFE, 2012)
Data: Sample: Stocks covered by sell-side analysts and experienced large price changes. I/B/E/S Recommendations database provide data on analyst coverage. CRSP provides data on daily stock returns, …rm size, and trading volume. Annual accounting data are from CRSP/Compustat merged database. Each recommendation is classi…ed as: upgrade/downgrade/reiterations/initialization. Stocks are included only if at least …ve recommendations issued over the past 12 months. The sample starts in 1995 and ends in 2009. Final sample observations: 166, 470.
JZ (SUFE)
Financial Econometrics
11/2012
4 / 12
Savor (JFE, 2012)
Methodology: Large Price changes: any …rm-date observation where the absolute value of abnormal return from the 4-factor model over 10%:
Financial Econometrics
ZHU Jie
Shanghai University of Finance and Economics
November 2012
JZ (SUFE)
Financial Econometrics
11/2012
1 / 12
Savor (JFE, 2012)
Stock returns after major price shocks: the impact of information. The paper investigates whether information has any e¤ect on large price changes. Analyst reports are used as a proxy for information. Main …ndings: 1. Price events accompanied by information are followed by drift. 2. Price events without information result in reversals. 3. This is due to investors underreact to news about fundamentals and overreact to other shocks. 4. Information-based price changes are more strongly correlated with future earnings surprises than no-information ones. 5. The ratio of no-information to information-based price shocks is strongly correlated with aggregate implied volatility and also forecasts momentum returns.
where un is 1 if no report and 0 otherwise. See results in Table 5.
JZ (SUFE) Financial Econometrics 11/2012 6 / 12
Savor (JFE, 2012)
The regressions show that presence of information a¤ects post-event returns: Price shocks unaccompanied by information are followed by signi…cant reversals. Portfolio analysis con…rms the anomaly leads to a pro…table trading strategy. Each of the stocks in the full sample is assigned to one of four portfolios: 1. Negative no-information 2. Negative information 3. Positive no-information 4. Positive information At any point of time, these portfolios are made up of all stocks that experienced the required price event over the previous N trading days.
jARi ,t j = jRit
where R it is calculated from R it Rft
R it j,
= α + βi ,m (Rmt Rft ) + βi ,smb SMBt + βi ,hml HMLt + βi ,umd UMDt + uit
The Estimate window: 255 trading day-period starting 31 trading days before the event day. See summary statistics in Table 3. The ARm,n statistics con…rm that post-event returns are driven by information.
JZ (SUFE)
Financial Econometrics
11/2012