Mispricing score for the individual stock using the characteristics in the Open Asset Pricing

Mispricing_Score.r

@@ -0,0 +1,114 @@
+##
+library(data.table)
+library(tidyverse)
+library(dtplry)
+library(magrittr)
+DT_CRSP <- fread("Data/CRSP.csv")
+## Standard Filter is applied to the DT_CRSP 
+DT_CRSP$Date = DT_CRSP$date %>% ceiling_date(., "m") %>% add(-1)
+DT_CRSP <- DT_CRSP %>% filter( SHRCD %in% c(10,11), EXCHCD %in% c(1,2,3)) %>% as_dt
+DT_CRSP$date <- NULL
+DT_CRSP$Date %<>% ymd()
+
+###### From OAPS 
+
+DT_Mom12 <- fread("Data/Misp/Mom12m.csv")
+DT_Share1Y <- fread("Data/Misp/ShareIss1Y.csv")
+DT_Accrual <- fread("Data/Misp/Accruals.csv")
+DT_NOA <- fread("Data/Misp/NOA.csv")
+DT_GP <- fread("Data/Misp/GP.csv")
+DT_Roa <- fread("Data/Misp/roaq.csv")
+DT_AG <- fread("Data/Misp/AssetGrowth.csv")
+DT_PPE <- fread("Data/Misp/InvestPPEInv.csv")
+DT_Comp <- fread("Data/Misp/CompEquIss.csv")
+DT_Failure <- fread("Data/FailureProbability.csv")
+
+################################
+DT_OAPS_CRSP <- DT_CRSP %>% select(PERMNO,Date,ALTPRC) %>% 
+  filter( abs(ALTPRC) > 5 ) %>% as_dt 
+###################
+DT_OAPS_CRSP <- DT_OAPS_CRSP %>% rename(permno = PERMNO) %>% 
+  left_join(DT_Mom12) %>% left_join(DT_Share1Y) %>%
+  left_join(DT_Accrual) %>% left_join(DT_NOA) %>%
+  left_join(DT_GP) %>%
+  left_join(DT_Roa) %>% left_join(DT_AG) %>%
+  left_join(DT_PPE) %>% left_join(DT_Comp) %>%
+  left_join(DT_Failure) %>% as_dt
+#
+DT_OAPS_CRSP$Date <- DT_OAPS_CRSP$yyyymm * 100 + 1
+DT_OAPS_CRSP$Date <- ymd(DT_OAPS_CRSP$Date)
+DT_OAPS_CRSP$Date <- ceiling_date(DT_OAPS_CRSP$Date ,"m") -1 
+
+DT_OAPS_CRSP %>% 
+  group_by(Date) %>% 
+  mutate( N_Roa = sum( (!is.na(roaq)) ) , 
+          N_ShareIss1Y = sum( (!is.na(ShareIss1Y))),
+          N_Mom12 = sum( (!is.na(Mom12m))),
+          N_GP = sum( (!is.na(GP))),
+          N_Accruals = sum( (!is.na(Accruals))), 
+          N_NOA = sum( (!is.na(NOA))),
+          N_Comp = sum( (!is.na(CompEquIss))),
+          N_Inv = sum( (!is.na(InvestPPEInv))),
+          N_Failure = sum( (!is.na(FailureProbability)))
+          ) %>% ungroup() %>% 
+  as_dt -> DT_OAPS_CRSP
+
+
+DT_OAPS_CRSP <- DT_OAPS_CRSP %>%
+  mutate( roaq = ifelse(N_Roa < 30 , roaq, NA), 
+          ShareIss1Y = ifelse(N_ShareIss1Y < 30 , ShareIss1Y, NA),
+          Mom12m = ifelse(N_Mom12 < 30 , Mom12m, NA),
+          GP = ifelse(N_GP < 30 , GP, NA),
+          Accruals = ifelse(N_Accruals < 30 , Accruals, NA),
+          NOA = ifelse(N_NOA < 30 , NOA, NA),
+          CompEquIss = ifelse(N_Comp < 30 , CompEquIss, NA),
+          InvestPPEInv = ifelse(N_Inv < 30 , InvestPPEInv, NA), 
+          FailureProbability = ifelse(N_Failure < 30 , FailureProbability, NA)
+        ) %>% 
+  as_dt 
+
+
+DT_OAPS_CRSP_MISP <- DT_OAPS_CRSP %>% 
+  select(-ALTPRC) %>%
+  group_by(Date) %>%
+  mutate( Anom1_Rank = percent_rank(Mom12m ) ,
+          Anom2_Rank = percent_rank(-ShareIss1Y) ,
+          Anom3_Rank = percent_rank(-Accruals) ,
+          Anom4_Rank = percent_rank(-NOA) ,
+          Anom5_Rank = percent_rank(GP) ,
+          Anom6_Rank = percent_rank(roaq) ,
+          Anom7_Rank = percent_rank(-AssetGrowth) ,
+          Anom8_Rank = percent_rank(-CompEquIss) ,
+          Anom9_Rank = percent_rank(-InvestPPEInv) ,
+          Anom10_Rank = percent_rank(FailureProbability)
+  ) %>% 
+  ungroup() %>% as_dt 
+
+DT_Misp_OAPS_New <- DT_OAPS_CRSP_MISP %>%
+  mutate(
+    valid_anomalies = (!is.na(Anom1_Rank)) +  (!is.na(Anom2_Rank)) + (!is.na(Anom3_Rank)) +
+      (!is.na(Anom4_Rank)) + (!is.na(Anom5_Rank)) + (!is.na(Anom6_Rank)) +
+      (!is.na(Anom7_Rank)) + (!is.na(Anom8_Rank)) + (!is.na(Anom9_Rank)) +
+      (!is.na(Anom10_Rank))   ,
+    Anom1_Rank_NA = ifelse(is.na(Anom1_Rank),0,Anom1_Rank),
+    Anom2_Rank_NA = ifelse(is.na(Anom2_Rank),0,Anom2_Rank),
+    Anom3_Rank_NA = ifelse(is.na(Anom3_Rank),0,Anom3_Rank),
+    Anom4_Rank_NA = ifelse(is.na(Anom4_Rank),0,Anom4_Rank),
+    Anom5_Rank_NA = ifelse(is.na(Anom5_Rank),0,Anom5_Rank),
+    Anom6_Rank_NA = ifelse(is.na(Anom6_Rank),0,Anom6_Rank),
+    Anom7_Rank_NA = ifelse(is.na(Anom7_Rank),0,Anom7_Rank),
+    Anom8_Rank_NA = ifelse(is.na(Anom8_Rank),0,Anom8_Rank),
+    Anom9_Rank_NA = ifelse(is.na(Anom9_Rank),0,Anom9_Rank),
+    Anom10_Rank_NA = ifelse(is.na(Anom10_Rank),0,Anom10_Rank),
+    MISP = ifelse(valid_anomalies >= 5 , 
+                  (Anom1_Rank_NA + Anom2_Rank_NA + Anom3_Rank_NA + Anom4_Rank_NA + 
+                     Anom5_Rank_NA + Anom6_Rank_NA + Anom7_Rank_NA + Anom8_Rank_NA + 
+                     Anom9_Rank_NA + Anom10_Rank_NA  ) / valid_anomalies , NA)
+  ) %>% select( PERMNO , Date , MISP) %>%
+ mutate( OAPS_MISP = 100 - 100 * MISP) %>% select(-MISP) %>% as_dt
+
+# Construct average rank for equity with at least 5 anomaly information
+
+
+
+