forked from tevgeniou/BuybacksIssuers
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathfilter_bbissuers_data.R
More file actions
335 lines (296 loc) · 18.3 KB
/
Copy pathfilter_bbissuers_data.R
File metadata and controls
335 lines (296 loc) · 18.3 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
# Copyright 2015, INSEAD
# by T. Evgeniou, Enric Junque de Fortuny, Nick Nassuphis, Theo Vermaelen
# Dual licensed under the MIT or GPL Version 2 licenses.
##########################################################################################
##########################################################################################
# Filter the data used for the paper
##########################################################################################
##########################################################################################
##########################################################################################
# Remove events for which we have missing values (for the main missing values)
##########################################################################################
to_remove = which(
# just in alphabetic order not to forget any
is.na(BUYBACK_DATA$BEME_used) |
is.na(BUYBACK_DATA$Performance_used) |
is.na(BUYBACK_DATA$Size_used) |
is.na(BUYBACK_DATA$DATASET$CRSP$pre_vol_Score) |
is.na(BUYBACK_DATA$DATASET$CRSP$IVOL_score) |
is.na(BUYBACK_DATA$DATASET$CRSP$Rsq_score) |
is.na(BUYBACK_DATA$DATASET$CRSP$Market.Cap)
)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
BUYBACK_DATA$BEME_used <- BUYBACK_DATA$BEME_used[-to_remove]
BUYBACK_DATA$Performance_used <- BUYBACK_DATA$Performance_used[-to_remove]
BUYBACK_DATA$Size_used <- BUYBACK_DATA$Size_used[-to_remove]
BUYBACK_DATA$Valuation_Index <- BUYBACK_DATA$Valuation_Index[-to_remove]
BUYBACK_DATA$DATASET$returns_by_event_monthly <- BUYBACK_DATA$DATASET$returns_by_event_monthly[,-to_remove]
BUYBACK_DATA$DATASET$SDC <- BUYBACK_DATA$DATASET$SDC[-to_remove,]
for(field in ls(BUYBACK_DATA$DATASET$CRSP)) BUYBACK_DATA$DATASET$CRSP[[field]] <- BUYBACK_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(BUYBACK_DATA$DATASET$ibes))
for (field in ls(BUYBACK_DATA$DATASET$ibes[[field1]]))
BUYBACK_DATA$DATASET$ibes[[field1]][[field]]<- BUYBACK_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
BUYBACK_DATA$cleanupMissingSomeValues = length(to_remove)
to_remove = which(
# just in alphabetic order not to forget any
is.na(ISSUERS_DATA$BEME_used) |
is.na(ISSUERS_DATA$Performance_used) |
is.na(ISSUERS_DATA$Size_used) |
is.na(ISSUERS_DATA$DATASET$CRSP$pre_vol_Score) |
is.na(ISSUERS_DATA$DATASET$CRSP$IVOL_score) |
is.na(ISSUERS_DATA$DATASET$CRSP$Rsq_score) |
is.na(ISSUERS_DATA$DATASET$CRSP$Market.Cap)
)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
ISSUERS_DATA$BEME_used <- ISSUERS_DATA$BEME_used[-to_remove]
ISSUERS_DATA$Performance_used <- ISSUERS_DATA$Performance_used[-to_remove]
ISSUERS_DATA$Size_used <- ISSUERS_DATA$Size_used[-to_remove]
ISSUERS_DATA$Valuation_Index <- ISSUERS_DATA$Valuation_Index[-to_remove]
ISSUERS_DATA$DATASET$returns_by_event_monthly <- ISSUERS_DATA$DATASET$returns_by_event_monthly[,-to_remove]
ISSUERS_DATA$DATASET$SDC <- ISSUERS_DATA$DATASET$SDC[-to_remove,]
for(field in ls(ISSUERS_DATA$DATASET$CRSP)) ISSUERS_DATA$DATASET$CRSP[[field]] <- ISSUERS_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(ISSUERS_DATA$DATASET$ibes))
for (field in ls(ISSUERS_DATA$DATASET$ibes[[field1]]))
ISSUERS_DATA$DATASET$ibes[[field1]][[field]]<- ISSUERS_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
ISSUERS_DATA$cleanupMissingSomeValues = length(to_remove)
############################################################################################################
if (remove_missing_permnosV2){
# Buybacks first
to_remove = which(is.na(BUYBACK_DATA$DATASET$SDC$permnoV2))
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
BUYBACK_DATA$BEME_used <- BUYBACK_DATA$BEME_used[-to_remove]
BUYBACK_DATA$Performance_used <- BUYBACK_DATA$Performance_used[-to_remove]
BUYBACK_DATA$Size_used <- BUYBACK_DATA$Size_used[-to_remove]
BUYBACK_DATA$Valuation_Index <- BUYBACK_DATA$Valuation_Index[-to_remove]
BUYBACK_DATA$DATASET$returns_by_event_monthly <- BUYBACK_DATA$DATASET$returns_by_event_monthly[,-to_remove]
BUYBACK_DATA$DATASET$SDC <- BUYBACK_DATA$DATASET$SDC[-to_remove,]
for(field in ls(BUYBACK_DATA$DATASET$CRSP)) BUYBACK_DATA$DATASET$CRSP[[field]] <- BUYBACK_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(BUYBACK_DATA$DATASET$ibes))
for (field in ls(BUYBACK_DATA$DATASET$ibes[[field1]]))
BUYBACK_DATA$DATASET$ibes[[field1]][[field]]<- BUYBACK_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
BUYBACK_DATA$cleanupNoPermno = BUYBACK_DATA$cleanupNoPermno + length(to_remove)
# Issuers now
to_remove = which(is.na(ISSUERS_DATA$DATASET$SDC$permnoV2))
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
ISSUERS_DATA$BEME_used <- ISSUERS_DATA$BEME_used[-to_remove]
ISSUERS_DATA$Performance_used <- ISSUERS_DATA$Performance_used[-to_remove]
ISSUERS_DATA$Size_used <- ISSUERS_DATA$Size_used[-to_remove]
ISSUERS_DATA$Valuation_Index <- ISSUERS_DATA$Valuation_Index[-to_remove]
ISSUERS_DATA$DATASET$returns_by_event_monthly <- ISSUERS_DATA$DATASET$returns_by_event_monthly[,-to_remove]
ISSUERS_DATA$DATASET$SDC <- ISSUERS_DATA$DATASET$SDC[-to_remove,]
for(field in ls(ISSUERS_DATA$DATASET$CRSP)) ISSUERS_DATA$DATASET$CRSP[[field]] <- ISSUERS_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(ISSUERS_DATA$DATASET$ibes))
for (field in ls(ISSUERS_DATA$DATASET$ibes[[field1]]))
ISSUERS_DATA$DATASET$ibes[[field1]][[field]]<- ISSUERS_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
ISSUERS_DATA$cleanupNoPermno = ISSUERS_DATA$cleanupNoPermno + length(to_remove)
rm("to_remove")
}
##########################################################################################
# Project specific filters now
# Note the use of the CRSP list instead of the SDC list for data like closing prices, market cap, etc (unlike earlier version)
# Buybacks first
events = BUYBACK_DATA$DATASET
No_filter = rep(T,length(events$SDC$Event.Date))
Basic_filter = No_filter # !is.na(events$SDC$ME_quantile) & !is.na(events$SDC$BEME_quantile)
Period_filter <- (as.Date(events$SDC$Event.Date) >= First) & (as.Date(events$SDC$Event.Date) <= Last)
#Penny_stock_filter = ifelse(events$SDC$Event.Date < "1995-01-01", scrub(events$SDC$Closing.Price) >= penny_stock_price_old, scrub(events$SDC$Closing.Price) >= penny_stock_price_recent)
Penny_stock_filter = ifelse(events$SDC$Event.Date < "1995-01-01", scrub(events$CRSP$closing.price) >= penny_stock_price_old, scrub(events$CRSP$closing.price) >= penny_stock_price_recent)
# REMOVE FINANCIALS AND UTILITIES: We leave them for now so we can use them as needed. This decision is made in bb_issuers_new.R
#Industry_filter = events$SDC$Industry %in% INDUSTRY_USED
Industry_filter = 1
US_only = (events$SDC$Currency %in% good_currencies)
major_markets_only = sapply(events$SDC$Stock.Exchange, function(i) sum(str_split(i, "\\+")[[1]] %in% major_markets)>0)
#BUYBACK SPECIFIC NOW:
Technique_filter = events$SDC$Tech..nique.Code %in% BB_allowed_techniques # OP, OPNG, and ""
TOTAL_FILTER_basic = No_filter & Basic_filter & Period_filter & Penny_stock_filter & Industry_filter & US_only & major_markets_only & Technique_filter
#Market_cap_filter = (scrub(events$SDC$Market.Cap) >= MIN_SIZE) & (scrub(events$SDC$Market.Cap) <= MAX_SIZE)
Market_cap_filter = (scrub(events$CRSP$Market.Cap) >= MIN_SIZE) & (scrub(events$CRSP$Market.Cap) <= MAX_SIZE)
#Leverage_filter = (scrub(events$SDC$lt/events$SDC$at) > 0.5)*(!is.na(events$SDC$lt/events$SDC$at))
EventSize_filter = (events$SDC$Event.Size >= MIN_EVENT_SIZE) & (events$SDC$Event.Size <= MAX_EVENT_SIZE)
TOTAL_FILTER_complex = Market_cap_filter & EventSize_filter
### remove
TOTAL_FILTER = TOTAL_FILTER_basic & TOTAL_FILTER_complex
BIZ_initial_data = length(TOTAL_FILTER)
to_remove = which(!TOTAL_FILTER)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
BUYBACK_DATA$BEME_used <- BUYBACK_DATA$BEME_used[-to_remove]
BUYBACK_DATA$Performance_used <- BUYBACK_DATA$Performance_used[-to_remove]
BUYBACK_DATA$Size_used <- BUYBACK_DATA$Size_used[-to_remove]
BUYBACK_DATA$Valuation_Index <- BUYBACK_DATA$Valuation_Index[-to_remove]
BUYBACK_DATA$DATASET$returns_by_event_monthly <- BUYBACK_DATA$DATASET$returns_by_event_monthly[,-to_remove]
BUYBACK_DATA$DATASET$SDC <- BUYBACK_DATA$DATASET$SDC[-to_remove,]
for(field in ls(BUYBACK_DATA$DATASET$CRSP)) BUYBACK_DATA$DATASET$CRSP[[field]] <- BUYBACK_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(BUYBACK_DATA$DATASET$ibes))
for (field in ls(BUYBACK_DATA$DATASET$ibes[[field1]]))
BUYBACK_DATA$DATASET$ibes[[field1]][[field]]<- BUYBACK_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
### Keep track
cleanup = list()
cleanup$initial_data <- BIZ_initial_data
cleanup$total_removed = length(to_remove)
cleanup$Basic_filter <- sum(!Basic_filter)
cleanup$Period_filter <- sum(!Period_filter)
cleanup$Penny_stock_filter <- sum(!Penny_stock_filter)
cleanup$Industry_filter <- sum(!Industry_filter)
cleanup$US_only <- sum(!US_only)
cleanup$BIZ_allowed_techniques <- sum(!Technique_filter)
cleanup$major_markets_only <- sum(!major_markets_only)
cleanup$Market_cap_filter <- sum(!Market_cap_filter)
cleanup$EventSize_filter <- sum(!EventSize_filter)
BUYBACK_DATA$cleanupBIZ = cleanup
# Issuers now
events = ISSUERS_DATA$DATASET
No_filter = rep(T,length(events$SDC$Event.Date))
Basic_filter = No_filter # !is.na(events$SDC$ME_quantile) & !is.na(events$SDC$BEME_quantile)
Period_filter <- (as.Date(events$SDC$Event.Date) >= First) & (as.Date(events$SDC$Event.Date) <= Last)
#Penny_stock_filter = ifelse(events$SDC$Event.Date < "1995-01-01", scrub(events$SDC$Closing.Price) >= penny_stock_price_old, scrub(events$SDC$Closing.Price) >= penny_stock_price_recent)
Penny_stock_filter = ifelse(events$SDC$Event.Date < "1995-01-01", scrub(events$CRSP$closing.price) >= penny_stock_price_old, scrub(events$CRSP$closing.price) >= penny_stock_price_recent)
# REMOVE FINANCIALS AND UTILITIES
# REMOVE FINANCIALS AND UTILITIES: We leave them for now so we can use them as needed. This decision is made in bb_issuers_new.R
#Industry_filter = events$SDC$Industry %in% INDUSTRY_USED
Industry_filter = 1
US_only = (events$SDC$Currency %in% good_currencies)
major_markets_only = sapply(events$SDC$Stock.Exchange, function(i) sum(str_split(i, "\\+")[[1]] %in% major_markets)>0)
#ISSUERS SPECIFIC NOW:
Technique_filter = events$SDC$Offering.Technique %in% ISS_allowed_techniques
TOTAL_FILTER_basic = No_filter & Basic_filter & Period_filter & Penny_stock_filter & Industry_filter & US_only & major_markets_only & Technique_filter
#Market_cap_filter = (scrub(events$SDC$Market.Cap) >= MIN_SIZE) & (scrub(events$SDC$Market.Cap) <= MAX_SIZE)
Market_cap_filter = (scrub(events$CRSP$Market.Cap) >= MIN_SIZE) & (scrub(events$CRSP$Market.Cap) <= MAX_SIZE)
#Leverage_filter = (scrub(events$SDC$lt/events$SDC$at) > 0.5)*(!is.na(events$SDC$lt/events$SDC$at))
EventSize_filter = (events$SDC$Event.Size >= MIN_EVENT_SIZE) & (events$SDC$Event.Size <= MAX_EVENT_SIZE)
TOTAL_FILTER_complex = Market_cap_filter & EventSize_filter
### remove
TOTAL_FILTER = TOTAL_FILTER_basic & TOTAL_FILTER_complex
BIZ_initial_data = length(TOTAL_FILTER)
to_remove = which(!TOTAL_FILTER)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
ISSUERS_DATA$BEME_used <- ISSUERS_DATA$BEME_used[-to_remove]
ISSUERS_DATA$Performance_used <- ISSUERS_DATA$Performance_used[-to_remove]
ISSUERS_DATA$Size_used <- ISSUERS_DATA$Size_used[-to_remove]
ISSUERS_DATA$Valuation_Index <- ISSUERS_DATA$Valuation_Index[-to_remove]
ISSUERS_DATA$DATASET$returns_by_event_monthly <- ISSUERS_DATA$DATASET$returns_by_event_monthly[,-to_remove]
ISSUERS_DATA$DATASET$SDC <- ISSUERS_DATA$DATASET$SDC[-to_remove,]
for(field in ls(ISSUERS_DATA$DATASET$CRSP)) ISSUERS_DATA$DATASET$CRSP[[field]] <- ISSUERS_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(ISSUERS_DATA$DATASET$ibes))
for (field in ls(ISSUERS_DATA$DATASET$ibes[[field1]]))
ISSUERS_DATA$DATASET$ibes[[field1]][[field]]<- ISSUERS_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
### Keep track
cleanup = list()
cleanup$initial_data <- BIZ_initial_data
cleanup$total_removed = length(to_remove)
cleanup$Basic_filter <- sum(!Basic_filter)
cleanup$Period_filter <- sum(!Period_filter)
cleanup$Penny_stock_filter <- sum(!Penny_stock_filter)
cleanup$Industry_filter <- sum(!Industry_filter)
cleanup$US_only <- sum(!US_only)
cleanup$BIZ_allowed_techniques <- sum(!Technique_filter)
cleanup$major_markets_only <- sum(!major_markets_only)
cleanup$Market_cap_filter <- sum(!Market_cap_filter)
cleanup$EventSize_filter <- sum(!EventSize_filter)
ISSUERS_DATA$cleanupBIZ = cleanup
###### Check time order of events
ordered_events = sort(as.numeric(BUYBACK_DATA$DATASET$SDC$Event.Date),index.return = T)$ix
if (length(unique(diff(ordered_events)))!=1)
stop("The time order was messed up somewhere for buybacks")
rm("ordered_events")
ordered_events = sort(as.numeric(ISSUERS_DATA$DATASET$SDC$Event.Date),index.return = T)$ix
if (length(unique(diff(ordered_events)))!=1)
stop("The time order was messed up somewhere for issuers")
rm("ordered_events")
############################################################################################################
############################################################################################################
# remove_financials_utilities is defined in the Paper_global_parameters.R file... default is 1
if (remove_financials_utilities){
# Buybacks first
Industry_filter = BUYBACK_DATA$DATASET$SDC$Industry %in% INDUSTRY_USED
to_remove = which(!Industry_filter)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
BUYBACK_DATA$BEME_used <- BUYBACK_DATA$BEME_used[-to_remove]
BUYBACK_DATA$Performance_used <- BUYBACK_DATA$Performance_used[-to_remove]
BUYBACK_DATA$Size_used <- BUYBACK_DATA$Size_used[-to_remove]
BUYBACK_DATA$Valuation_Index <- BUYBACK_DATA$Valuation_Index[-to_remove]
BUYBACK_DATA$DATASET$returns_by_event_monthly <- BUYBACK_DATA$DATASET$returns_by_event_monthly[,-to_remove]
BUYBACK_DATA$DATASET$SDC <- BUYBACK_DATA$DATASET$SDC[-to_remove,]
for(field in ls(BUYBACK_DATA$DATASET$CRSP)) BUYBACK_DATA$DATASET$CRSP[[field]] <- BUYBACK_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(BUYBACK_DATA$DATASET$ibes))
for (field in ls(BUYBACK_DATA$DATASET$ibes[[field1]]))
BUYBACK_DATA$DATASET$ibes[[field1]][[field]]<- BUYBACK_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
BUYBACK_DATA$cleanupBIZ$Industry_filter = sum(!Industry_filter)
# Issuers now
Industry_filter = ISSUERS_DATA$DATASET$SDC$Industry %in% INDUSTRY_USED
to_remove = which(!Industry_filter)
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
ISSUERS_DATA$BEME_used <- ISSUERS_DATA$BEME_used[-to_remove]
ISSUERS_DATA$Performance_used <- ISSUERS_DATA$Performance_used[-to_remove]
ISSUERS_DATA$Size_used <- ISSUERS_DATA$Size_used[-to_remove]
ISSUERS_DATA$Valuation_Index <- ISSUERS_DATA$Valuation_Index[-to_remove]
ISSUERS_DATA$DATASET$returns_by_event_monthly <- ISSUERS_DATA$DATASET$returns_by_event_monthly[,-to_remove]
ISSUERS_DATA$DATASET$SDC <- ISSUERS_DATA$DATASET$SDC[-to_remove,]
for(field in ls(ISSUERS_DATA$DATASET$CRSP)) ISSUERS_DATA$DATASET$CRSP[[field]] <- ISSUERS_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(ISSUERS_DATA$DATASET$ibes))
for (field in ls(ISSUERS_DATA$DATASET$ibes[[field1]]))
ISSUERS_DATA$DATASET$ibes[[field1]][[field]]<- ISSUERS_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
ISSUERS_DATA$cleanupBIZ$Industry_filter = sum(!Industry_filter)
rm("to_remove")
}
############################################################################################################
if (remove_CRSP_minor_markets){
# Buybacks first
to_remove = which(!(BUYBACK_DATA$DATASET$CRSP$exchange %in% major_markets_crsp))
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
BUYBACK_DATA$BEME_used <- BUYBACK_DATA$BEME_used[-to_remove]
BUYBACK_DATA$Performance_used <- BUYBACK_DATA$Performance_used[-to_remove]
BUYBACK_DATA$Size_used <- BUYBACK_DATA$Size_used[-to_remove]
BUYBACK_DATA$Valuation_Index <- BUYBACK_DATA$Valuation_Index[-to_remove]
BUYBACK_DATA$DATASET$returns_by_event_monthly <- BUYBACK_DATA$DATASET$returns_by_event_monthly[,-to_remove]
BUYBACK_DATA$DATASET$SDC <- BUYBACK_DATA$DATASET$SDC[-to_remove,]
for(field in ls(BUYBACK_DATA$DATASET$CRSP)) BUYBACK_DATA$DATASET$CRSP[[field]] <- BUYBACK_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(BUYBACK_DATA$DATASET$ibes))
for (field in ls(BUYBACK_DATA$DATASET$ibes[[field1]]))
BUYBACK_DATA$DATASET$ibes[[field1]][[field]]<- BUYBACK_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
BUYBACK_DATA$cleanupBIZ$major_markets_only = BUYBACK_DATA$cleanupBIZ$major_markets_only + length(to_remove)
# Issuers now
to_remove = which(!(ISSUERS_DATA$DATASET$CRSP$exchange %in% major_markets_crsp))
if (length(to_remove) > 0){
# just in alphabetic order not to forget any
ISSUERS_DATA$BEME_used <- ISSUERS_DATA$BEME_used[-to_remove]
ISSUERS_DATA$Performance_used <- ISSUERS_DATA$Performance_used[-to_remove]
ISSUERS_DATA$Size_used <- ISSUERS_DATA$Size_used[-to_remove]
ISSUERS_DATA$Valuation_Index <- ISSUERS_DATA$Valuation_Index[-to_remove]
ISSUERS_DATA$DATASET$returns_by_event_monthly <- ISSUERS_DATA$DATASET$returns_by_event_monthly[,-to_remove]
ISSUERS_DATA$DATASET$SDC <- ISSUERS_DATA$DATASET$SDC[-to_remove,]
for(field in ls(ISSUERS_DATA$DATASET$CRSP)) ISSUERS_DATA$DATASET$CRSP[[field]] <- ISSUERS_DATA$DATASET$CRSP[[field]][-to_remove]
for(field1 in ls(ISSUERS_DATA$DATASET$ibes))
for (field in ls(ISSUERS_DATA$DATASET$ibes[[field1]]))
ISSUERS_DATA$DATASET$ibes[[field1]][[field]]<- ISSUERS_DATA$DATASET$ibes[[field1]][[field]][-to_remove]
rm("field","field1")
}
ISSUERS_DATA$cleanupBIZ$major_markets_only = ISSUERS_DATA$cleanupBIZ$major_markets_only + length(to_remove)
rm("to_remove")
}