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The Fed Policy Decisions and Implied Volatility

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					               THE FED’S POLICY DECISIONS AND IMPLIED VOLATILITY



                                        Sami Vähämaa*, Janne Äijö**
                                  Department of Accounting and Finance
                                        University of Vaasa, Finland



                                               March 18, 2010

                                                  Abstract

    This paper examines how the Fed’s monetary policy decisions affect the implied volatility of the
    S&P 500 index. The results show that option-implied stock market uncertainty is significantly
    affected by monetary policy decisions. In particular, we find that stock market volatility generally
    decreases after the FOMC meetings. However, our results also indicate that stock market uncertainty
    may increase after positive target rate surprises. We further document that the policy decisions made
    in unscheduled FOMC meetings exert a stronger influence on volatility. Finally, our findings
    demonstrate that the impact of policy decisions on implied volatility is more pronounced during
    periods of expansive monetary policy.

    JEL classification: E44, E52, E58, G10, G13

    Keywords: Monetary policy decisions, stock market uncertainty, implied volatility




*
  Professor of Accounting and Finance. Address: University of Vaasa, Department of Accounting and Finance, P.O.
Box 700, FI-65101 Vaasa, Finland; Tel. +358 6 324 8197; E-mail address: sami@uwasa.fi
**
   Corresponding author. Professor of Accounting and Finance. Address: University of Vaasa, Department of
Accounting and Finance, P.O. Box 700, FI-65101 Vaasa, Finland; Tel. +358 6 324 8276; E-mail address:
jja@uwasa.fi
                                                     1


INTRODUCTION


      Monetary policy decisions of central banks are often associated with large stock price movements.

Bernanke and Kuttner (2005), for instance, document that an unexpected 25 basis points cut in the target

rate of the Federal Reserve typically increases stock prices in the U.S. by around one percent. Similar

findings on strong stock market reactions to monetary policy decisions are recently reported e.g. in

Ehrmann and Fratzscher (2004, 2009), Wang, Yang and Wu (2006), Chen (2007), Basistha and Kurov

(2008), Bohl, Siklos and Sondermann (2008), Ioannidis and Kontonikas (2008), Kholodilin, Montagnoli,

Napolitano and Siliversotvs (2009), Wongswan (2009), and Kurov (2010). While the effects of monetary

policy actions on stock prices have been examined extensively in the prior literature, considerably less

attention has been given to the effects of monetary policy on stock market volatility. Thus, in this paper,

we aim to contribute to the literature by examining the effects of the Federal Reserve’s monetary policy

decisions on the implied volatility of the S&P 500 index.

      Previously, the effects of monetary policy decisions on stock market volatility have been studied in

Lobo (2002), Bomfim (2003), Nikkinen and Sahlström (2004), Chen and Clements (2007), Farka (2009),

Andersson (2010), and Chuliá, Martens and van Dijk (2010). Lobo (2002) and Bomfim (2003) apply

GARCH modelling to ascertain the impact of monetary policy on stock market volatility, and document a

significant increase in volatility on the days of monetary policy announcements. Farka (2009), Andersson

(2010) and Chuliá et al. (2010) use intraday data to examine volatility dynamics around monetary policy

meetings. Consistent with Lobo (2002) and Bomfim (2003), these studies report large increases in stock

market volatility in the immediate aftermath of monetary policy decisions. Farka (2009) and Chuliá et al.

(2010) further show that the increase in volatility is substantially larger during recessions and expansive

monetary policy cycles than during periods of restrictive policy.

      Most related to the our paper, Nikkinen and Sahlström (2004) and Chen and Clements (2007) focus

on the behaviour of implied volatility indices around the Federal Open Market Committee (FOMC)
                                                      2


meetings, and document systematic decreases in implied volatility on the FOMC meeting days. In contrast

to studies based on realized volatility, Nikkinen and Sahlström (2004) and Chen and Clements (2007)

exclude unscheduled monetary policy decisions, and moreover, ignore the potential surprise components

of the policy announcements.

      In this paper, we extend the analysis of Nikkinen and Sahlström (2004) and Chen and Clements

(2007) in three main respects. First, we use fed funds futures contracts to extract surprises in monetary

policy decisions, and are thereby able to assess the impact of monetary policy shocks on stock market

uncertainty. Second, given that the policy decisions made in scheduled and unscheduled FOMC meetings

are likely to affect market uncertainty somewhat differently, we differentiate between scheduled and

unscheduled policy actions in our empirical analysis. Third, recent empirical evidence suggests that the

reaction of stock markets to monetary policy is asymmetric and may depend on the monetary policy cycle

and macroeconomic conditions (see e.g., Chen, 2007; Basistha and Kurov, 2008; Farka, 2009; Chuliá et

al., 2010; Kurov, 2010). Therefore, we attempt to extend the literature by examining the potential cyclical

variation in the effects of policy decisions on option-implied stock market volatility.

      Our empirical findings demonstrate that stock market uncertainty is significantly affected by

monetary policy decisions. Consistent with Nikkinen and Sahlström (2004) and Chen and Clements

(2007), we find that implied stock market volatility generally decreases after FOMC meetings. However,

our results also indicate a positive relationship between monetary policy surprises and implied volatility,

thereby suggesting that positive target rate surprises, i.e. larger than expected rate increases and smaller

than expected rate cuts, may actually increase stock market uncertainty. Furthermore, our findings

demonstrate that target rate decisions made in unscheduled FOMC meetings have a stronger effect on

implied volatility. Finally, consistent with Farka (2009) among others, we document that the impact of

monetary policy decisions on stock market volatility is more pronounced during periods of expansive

monetary policy.
                                                     3


DATA


      The data used in our empirical analysis consist of (i) the VIX implied volatility index, (ii) the

monetary policy decisions of the Federal Reserve, and (iii) federal funds futures prices. The sample period

spans from January 3, 1994 through December 31, 2007. This sample includes 120 FOMC meetings and a

total number of 53 changes in the federal funds target rate. Following Bernanke and Kuttner (2005),

Basistha and Kurov (2008), and Kurov (2010), we exclude the monetary policy decision made in the

immediate aftermath of the terrorist attacks on September 17, 2001.

      We measure stock market uncertainty with the VIX implied volatility index. VIX index is calculated

from S&P 500 index options by the Chicago Board Options Exchange (CBOE). The volatility index is

constructed from short-term out-of-the money call and put options and represents the expected volatility

of the S&P 500 index over the next 30 days (for details, see e.g. Chicago Board Options Exchange, 2009;

Whaley, 2009). VIX index has been widely used in prior literature to measure uncertainty in stock markets

(see e.g., Connolly, Stivers and Sun, 2005; Bialkowski, Gottschalk and Wisniewski, 2008).

      We use federal funds futures contracts to extract surprises in monetary policy decisions of the

Federal Reserve. Previous studies have shown that federal funds futures rates provide an efficient measure

of expectations regarding the Fed’s monetary policy decisions (see e.g., Krueger and Kuttner, 1996;

Söderström, 2001). In this paper, we apply the approach proposed in Kuttner (2001) and Bernanke and

Kuttner (2005) to measure monetary policy surprises. Thus, the surprise component of the federal funds

target rate decision is based on the daily changes in the implied target rate of the current-month fed funds

futures contract:


       itu 
                 D
                Dd
                       
                    f t 0  f t 01
                                                                                                       (1)


where itu is the unexpected component of the announcement,  is the first difference operator, f t 0 is the

current-month futures rate at the end of the FOMC day d and D is the number of days in the month. This
                                                     4


approach to measure monetary policy surprises has been recently used e.g. in Bomfirm (2003), Wang et

al. (2006), Basistha and Kurov (2008) and Chuliá et al. (2010).



      (Insert Table 1 about here.)


      Table 1 reports descriptive statistics of the sample. As can be seen from the table, the sample

includes 112 scheduled FOMC meetings and 7 unscheduled meetings. The monetary policy decisions of

the Federal Reserve have generally been well anticipated by investors, as the mean (median) monetary

policy surprise is only -1.88 (-1.00) basis points. Not surprisingly, the unscheduled FOMC meetings are

associated with much larger policy surprises, with a mean (median) surprise estimate of -22.75 (-29.25)

basis points. Regarding the VIX index, Table 1 shows that implied volatility of the S&P 500 index has, on

average, been about 19.4 %, and varied between 6.7 % and 45.7 % over the sample period.



RESULTS


Monetary Policy Decisions and Stock Market Uncertainty



     To examine the impact of the Fed’s monetary policy decisions on stock market uncertainty, we

regress the daily changes in implied volatility index on alternative monetary policy variables:

          t     FOMCt    t                                                                    (2)

where  t denotes implied volatility (the VIX index) at time t, Δ is the first difference operator and FOMCt

is defined as one of the following monetary policy variables: (i) a meeting dummy that takes the value of

one on the FOMC meeting days, (ii) monetary policy surprise variable defined based on Equation (1), (iii)

scheduled surprise variable that identifies policy surprises in scheduled FOMC meetings, (iv) unscheduled

surprise variable that identifies policy surprises in unscheduled FOMC meetings. In addition, we also
                                                       5


estimate a fifth regression specification in which the monetary policy surprise variable is divided into

positive and negative surprises.

     Throughout the regressions, we use White’s heteroskedasticity consistent covariance matrix

estimator. The Ljung-Box statistic indicates significant serial correlation in the residuals of the

regressions, and hence, AR(p) terms are added to the models. Moreover, since Engle’s LM test indicates

significant serial correlation in the squared residuals of the regressions, we also fit a GARCH(1,1)

structure.



      (Insert Table 2 about here.)


     Table 2 reports the regression results for the impact of monetary policy decisions on implied

volatility. In Model (1), daily changes in the VIX index are regressed on the FOMC meeting dummy.

Thus, in essence, this model provides a re-examination of the findings documented in Nikkinen and

Sahlström and Chen and Clements (2007). Consistent with the previous studies, our results indicate that

implied volatility decreases on the FOMC meeting days, as the potential policy-induced uncertainty is

resolved by the market participants. Nevertheless, it should be noted that the approach based on the

FOMC dummy variable ignores the actual policy decisions made in the meetings. Therefore, we next

extend the analysis by taking into account the surprise components of policy decisions.

     In Model (2), we regress implied volatility changes on monetary policy surprises. As discussed

above, the Fed’s policy surprises are extracted from the fed fund futures contracts. The estimates of this

regression show that surprises in monetary policy are positively associated with stock market uncertainty.

Thus, our results indicate that positive target rate surprises (i.e., larger than expected target rate increases

and smaller than expected rate cuts) increase option-implied stock market uncertainty, while negative

surprises (i.e., smaller than expected target rate increases and larger than expected rate cuts) typically lead

to a decrease in implied volatility. Positive (negative) surprises are obviously bad (good) news for the
                                                      6


stock market, and thereby our findings are broadly consistent with the prior literature showing that bad

news increase implied volatility (see e.g, Nofsinger and Prucyk, 2003).

     In order to ascertain whether the policy surprises in scheduled and unscheduled FOMC meetings

have a different impact on stock market uncertainty, we next regress implied volatility changes separately

on the scheduled and unscheduled policy surprises (Models 3 and 4, respectively). Again, the estimated

coefficients for both surprise variables are positive, and thereby suggest that monetary policy surprises are

positively associated with stock market uncertainty. Nevertheless, our results indicate that the policy

decisions made in the unscheduled FOMC meetings exert a much stronger influence on implied volatility.

     Finally, given that positive and negative policy surprises may potentially have an asymmetric effect

on stock market uncertainty, we regress implied volatility changes on positive and absolute negative

surprises (Model 5). As can be noted from Table 2, the estimated coefficient for the absolute negative

surprise variable is negative, while the coefficient for the positive surprise variable is statistically

insignificant. Thus, our findings suggest that stock market uncertainty decreases after good monetary

policy news (i.e., smaller than expected target rate increases and larger than expected rate cuts).



Does Monetary Policy Cycle Matter?



     So far, we have assumed that the impact of monetary policy decision on implied volatility is

symmetric across monetary policy cycles, that is, the effects of policy decisions are the same during

restrictive and expansive periods. However, the results recently reported in Chen (2007), Basistha and

Kurov (2008), Farka (2009), Chuliá et al. (2010), and Kurov (2010) suggest that the reaction of stock

markets to monetary policy decisions may vary under different policy cycles and macroecomic conditions.

Thus, to examine whether the Fed’s monetary policy decisions affect implied volatility differently during

restrictive and expansive monetary policy periods, we estimate the following model:

                                    
     t    1 FOMCtRES   2 FOMCtEXP   t                                                         (3)
                                                      7



where  t denotes implied volatility, Δ is the first difference operator and FOMCtRES and

FOMCtEXP denote monetary policy decision variables in restrictive and expansive monetary policy cycles,

respectively, and the alternative policy variables used in the regression are as defined in Equation (2).

Again, we remove the serial correlation in the residuals and squared residuals by adding AR(p) and

GARCH (1,1) terms into the models.



      (Insert Table 3 about here.)


     Table 3 reports the regression results for the effects of monetary policy decisions on implied

volatility under different monetary policy cycles. In Model (6), daily changes in the VIX index are

regressed on the restrictive and expansive FOMC meeting dummies. Our estimates indicate that the

previously documented decrease in implied volatility on the FOMC meeting days (see Table 2) can be

attributed solely to the FOMC meetings in an expansive monetary policy cycle. This result extends the

findings on the FOMC day effects reported in the prior literature (see Nikkinen and Sahlström, 2004;

Chen and Clements, 2007).

     Model (7) is applied to examine the impact of monetary policy surprises on implied volatility in

different policy cycles. As can be noted from Table 3, the coefficient estimate for the policy surprise in

expansive cycle is positive, thereby indicating that smaller (larger) than expected interest rate cuts increase

(decrease) stock market uncertainty. The estimated coefficient for the restrictive surprise variable is

insignificant. Therefore, consistent with Model (6), the results suggest that the effect of policy decisions

on implied volatility is larger during periods of expansive monetary policy. These results are broadly

consistent with e.g. Chen (2007), Basistha and Kurov (2008), Farka (2009), and Kurov (2010), and thus,

provide further evidence to suggest that stock markets are more strongly influenced by monetary policy

decisions under adverse economic conditions.
                                                       8


     In Models (8) and (9), we examine how implied volatility is affected by scheduled and unscheduled

monetary policy surprises in expansive and restrictive policy cycles. In general, the results again show that

unscheduled policy surprises have a larger impact on implied volatility than scheduled surprises. In fact,

the estimated coefficient for scheduled surprise in restrictive policy cycle is statistically insignificant, and

the coefficient for the scheduled surprise in expansive policy cycle is positive and significant at the 10 %

level. In contrast, the coefficients for the unscheduled surprises both in restrictive and expansive monetary

policy cycles are statistically highly significant. Thus, regardless of the monetary policy cycle, our results

indicate that positive (negative) target rate surprises in unscheduled FOMC meetings increase (decrease)

stock market uncertainty.

     Finally, in Model (10), implied volatility changes are regressed on positive and absolute negative

surprises in expansive and restrictive policy cycles. The estimates of Model (10) show that negative

surprises in expansive policy cycle (i.e., higher than expected target rate cuts) reduce stock market

uncertainty. This finding further demonstrates that the effects of monetary policy decisions on implied

volatility are more pronounced during periods of expansive monetary policy.



CONCLUSIONS


     This paper focuses on the impact of monetary policy decisions on stock market uncertainty. In

particular, we examine how the Fed’s policy decisions affect the implied volatility of the S&P 500 index.

We use fed funds futures contracts to extract surprises in monetary policy decisions, and assess the effects

of monetary policy shocks on implied volatility. Furthermore, we also examine whether the policy

surprises in scheduled and unscheduled FOMC meetings affect stock market uncertainty differently.

Finally, we attempt to extend the literature by examining the potential cyclical variation in the effects of

policy decisions on option-implied stock market volatility.
                                                    9


      The empirical findings reported in this paper demonstrate that stock market uncertainty is

significantly affected by monetary policy decisions. Consistent with the prior literature, we find that

implied stock market volatility generally tends to decrease after FOMC meetings. However, our results

also indicate a positive relationship between monetary policy surprises and implied volatility, thereby

suggesting that positive target rate surprises may increase stock market uncertainty. Furthermore, our

findings suggest that target rate decisions made in unscheduled FOMC meetings have a stronger effect on

implied volatility than scheduled policy decisions. Finally, we document that the impact of monetary

policy decisions on implied volatility depends on the prevailing monetary policy stance, as the market

reaction to policy surprises is more pronounced during periods of expansive policy.
                                                      10


BIBLIOGRAPHY


Andersson, M., (2010). Using intraday data to gauge financial market responses to Fed and ECB monetary

      policy decisions. International Journal of Central Banking, forthcoming.

Basistha, A., & Kurov, A. (2008). Macroeconomic cycle and the stock market’s reaction to monetary

      policy. Journal of Banking and Finance 32, 2606-2616.

Bernanke, B., & Kuttner, K. (2005). What explains the stock market’s reaction to Federal Reserve policy?

      Journal of Finance 60, 1221-1257.

Białkowski, J., Gottschalk, K., & Wisniewski, T. (2008). Stock market volatility around national elections.

      Journal of Banking and Finance 32, 1941-1953.

Bohl, M., Siklos, P., & Sondermann, D. (2008). European stock markets and the ECB`s monetary policy

      surprises. International Finance 11, 117-130.

Bomfim, A., (2003). Pre-announcement effects, news effects, and volatility: Monetary policy and the

      stock market. Journal of Banking and Finance 27, 133-151.

Chen, S. (2007). Does monetary policy have asymmetric effects on stock returns? Journal of Money,

      Credit and Banking 39, 667-688.

Chen, E.-T., & Clements, A. (2007). S&P 500 implied volatility and monetary policy announcements.

      Finance Research Letters 4, 227-232.

Chicago Board Options Exchange (2009). The CBOE Volatility Index – VIX. Chicago: Chicago Board

      Options Exchange.

Chuliá, H., Martens, M., & van Dijk, D. (2010). Asymmetrical effects of federal funds target rate changes

      on S&P100 stock returns volatilities and correlations. Journal of Banking and Finance, forthcoming.

Connolly, R., Stivers, C., & Sun, L. (2005). Stock market uncertainty and stock-bond relation. Journal of

      Financial and Quantitative Analysis, 40 161-194.

Ehrmann, M., & Fratzscher, M. (2004). Taking stock: Monetary policy transmission to equity markets.

      Journal of Money, Credit and Banking 36, 719-737.
                                                    11


Ehrmann, M., & Fratzscher, M. (2009). Global financial transmission of monetary policy shocks. Oxford

      Bulletin of Economics and Statistics 71, 739-759.

Farka, M. (2009). The effect of monetary policy shocks on stock prices accounting for endogeneity and

      omitted variable biases. Review of Financial Economics 18, 47-55.

Ioannidis, C., & Kontonikas, A. (2008). The impact of monetary policy on stock prices. Journal of Policy

     Modeling 30, 33-53.

Kholodilin, K., Montagnoli, A., Napolitano, O., & Siliversotvs, B. (2009). Assessing the impact of the

     ECB’s monetary policy on the stock markets: A sectoral view. Economics Letters, forthcoming.

Krueger, J. & Kuttner, K. (1996). The Fed funds futures rate as a predictor of Federal Reserve policy.

      Journal of Futures Markets, 16, 865-879.

Kurov, A. (2010). Investor sentiment and the stock market’s reaction to monetary policy. Journal of

     Banking and Finance 34, 139-149.

Kuttner, K. (2001). Monetary policy surprises and interest rates: Evidence from the fed funds futures

     markets. Journal of Monetary Economics 47, 523-544.

Lobo, B. (2002). Interest rate surprises and stock prices. The Financial Review 37. 73-92.

Nikkinen, J., & Sahlström, P. (2004). Impact of Federal Open Market Committee’s meetings and

     scheduled macroeconomic news on stock market uncertainty. International Review of Financial

     Analysis 13, 1-12.

Nofsinger, J., & Prucyk, B. (2003). Option volume and volatility response to scheduled economic news

      releases. Journal of Futures Markets, 23, 315-345.

Söderström, U. (2001). Predicting monetary policy with federal funds futures prices. Journal of Futures

      Markets, 21, 377-391.

Wang, T., Yang, J., & Wu, J. (2006). Central bank communications and equity ETFs. Journal of Futures

      Markets, 26, 959-995.

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Wongswan, J. (2009). The response of global equity indexes to U.S. monetary policy announcements.

      Journal of International Money and Finance 28, 344-365.
                                       12


                         Table 1. Descriptive statistics.


                       No. of
                        Obs.       Mean      Median         St. Dev.     Min    Max
FOMC                     119
Scheduled FOMC           112
Unscheduled FOMC            7
Surprise                  75       -1.88       -1.00           9.55    -42.50   14.50
Scheduled Surprise        71       -0.71       -1.00           6.77    -19.40   14.50
Unscheduled Surprise        4     -22.75      -29.25          23.86    -42.50   10.00
VIX                     3651       19.42       18.64           9.89      6.65   45.74
                                                      13


                       Table 2. Monetary policy decisions and implied volatility.

The reported results are based on the following regression specification:
 t     FOMCt    t
where  t denotes implied volatility (the VIX index) at time t, Δ is the first difference operator, and
FOMCt is defined as one of the following monetary policy variables: (i) FOMC meeting dummy, (ii)
surprise (based on fed funds futures contracts), (iii) scheduled surprise, (iv) unscheduled surprise, (v)
positive surprise, and (vi) absolute negative surprise. Serial correlation in the residuals and in the squared
residuals is removed by adding AR(1) and GARCH (1,1) terms into the models. The reported t-statistics
(in parentheses) are based on heteroskedasticity consistent standard errors. ***, **, and * denote significance
at the 0.01, 0.05, and 0.10 levels, respectively.

                         Model (1)    Model (2)     Model (3)               Model (4)        Model (5)
Constant                     0.000        0.000         0.000                   0.000            0.000
                            (0.61)      (-0.24)       (-0.31)                 (-0.23)          (-0.07)
Meeting                    -0.023 ***
                           (-3.84)
Surprise                                  0.003 ***
                                         (2.92)
Scheduled Surp.                                         0.003 *
                                                       (1.77)
Unscheduled Surp.                                                                0.003 ***
                                                                                 (3.28)
Pos. Surp.                                                                                         0.001
                                                                                                  (0.34)
Abs. Neg. Surp.                                                                                  -0.004 ***
                                                                                                 (-3.76)

Adjusted R2                   0.010            0.010            0.007            0.006            0.010
F-stat.                       8.462 ***        8.266 ***        6.318 ***        5.521 ***        7.390 ***
                                                       14


               Table 3. Monetary policy decisions, policy cycles, and implied volatility.

The reported results are based on the following regression specification:
                                 
 t    1 FOMCtRES   2 FOMCtEXP   t     
where  t denotes implied volatility (the VIX index) at time t, Δ is the first difference operator, and
FOMCtRES and FOMCtEXP denote monetary policy decision variables in restrictive and expansive
monetary policy cycles, respectively. The alternative monetary policy variables used in the regressions
are: (i) FOMC meeting dummy, (ii) surprise (based on fed funds futures contracts), (iii) scheduled
surprise, (iv) unscheduled surprise, (v) positive surprise, and (vi) absolute negative surprise. Serial
correlation in the residuals and in the squared residuals is removed by adding AR(1) and GARCH (1,1)
terms into the models. The reported t-statistics (in parentheses) are based on heteroskedasticity consistent
standard errors. ***, **, and * denote significance at the 0.01, 0.05, and 0.10 levels, respectively.

                         Model (1)    Model (2)     Model (3)                 Model (4)         Model (5)
Constant                     0.000        0.000         0.000                     0.000             0.000
                            (0.23)      (-0.29)       (-0.35)                   (-0.27)           (-0.14)
MeetingRES                 -0.012
                           (-0.83)
MeetingEXP                 -0.034 ***
                           (-3.68)
SurpriseRES                               0.003
                                         (0.86)
SurpriseEXP                               0.003 ***
                                         (3.39)
Scheduled SurpRES                                       0.003
                                                       (0.78)
Scheduled SurpEXP                                       0.003 *
                                                       (1.80)
Unscheduled SurpRES                                                                0.007 ***
                                                                                  (34.76)
Unscheduled SurpEXP                                                                 0.003 ***
                                                                                   (3.22)
                                                15


                                      Table 3. Continued.


                    Model (1)       Model (2)        Model (3)       Model (4)       Model (5)
            RES
Pos. Surp                                                                                0.003
                                                                                        (0.56)
Pos. SurpEXP                                                                           -0.001
                                                                                       (-0.95)
Abs. Neg. SurpRES                                                                      -0.004
                                                                                       (-1.44)
Abs. Neg. SurpEXP                                                                      -0.003 ***
                                                                                       (-3.28)
Adjusted R2             0.008           0.009            0.007           0.006          0.009
F-stat.                 5.873 ***       6.664 ***        5.112 ***       4.698 ***      5.352 ***

				
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