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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%