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Table 12 Monthly Regression with Business-cycle Related Variables Controlled

From: Timing the market: the economic value of price extremes

PML t F

BM t

BM t+1

PML t F

DE t

DE t+1

PML t F

DF Y t

DFY t+1

PML t F

DP t

DP t+1

0.136***

    

0.133***

0.247*

 

0.137***

0.168

 

0.135***

31.118

 

0.135***

0.118

 

0.127***

19.746***

-19.627***

0.134***

-0.262

0.436

0.130***

6.632

27.265

0.153***

17.205***

-17.207***

PML t F

DY t

DY t+1

PML t F

EP t

EP+1

P ML t F

INFL t

INFL t+1

P ML t F

LT R t

LTR t+1

0.139***

0.115

 

0.136***

0.035

 

0.138***

-8.621

 

0.153***

5.133***

 

0.135***

-0.007

0.123

0.100***

8.748***

-8.811***

0.139***

-9.618

1.608

0.144***

4.969***

2.983**

PML t F

LT Y t

LTY t+1

PML t F

NTIS t

NTIS t+1

PML t F

SVAR t

SVAR t+1

PML t F

T BL t

TBL t+1

0.134***

1.642

 

0.136***

-4.308**

 

0.112***

19.485**

 

0.133***

1.173

 

0.123***

43.153***

-41.711***

0.130***

18.680*

-23.424**

0.118***

25.238**

-13.071

0.134***

37.059***

-36.196***

PML t F

TMS t

TMS t+1

   

0.136***

0.722

    

0.142***

-16.999*

18.533**

   
  1. Note. Our benchmark model is PMGFt+1=C+PMLtFt+1, where PMGF and PMLF are filtered observations. Filtered observations are used to alleviate the contamination of autocorrelations in PMG and PML. Regression with business-cycle related variables controlled is presented as follows,
  2. \( {\displaystyle \begin{array}{l}{{PMG^F}_t}_{+1}=C+\alpha {PML_t}^F+{\upbeta}_1{M}_t+{\upvarepsilon}_{\mathrm{t}+1,}\\ {}{{PMG_t}^F}_{+1}=C+{PML_t}^F+{\upbeta}_1{M}_t+{\upbeta}_2{M}_{t+1}+{\upvarepsilon}_{\mathrm{t}+1},\end{array}} \)
  3. where Mt represents business-cycle related variable. The constant C is not reported in the table for space-saving. ***, **, * mean respectively significance at the level of 1%, 5% and 10%