0

I have an xts object with hourly prices, and want to look at price behavior after Non Farm Payrolls (NFP) economic releases. NFP take place on the first Friday of every month. So I want to create a subset with the prices for the first Friday of every month and the Monday after. To achieve that I looked at this question Get the 4th Wednesday of each November in R and put together the following code:

library(xts)        

DATSxts <- structure(c(1069.4, 1070.7, 1070.4, 1070.3, 1068.7, 1068.7, 1069.4, 1069.7, 1069.5, 1068.1, 1069.3, 1069.2, 1069.3, 1070.7, 1070.9, 1070.7, 1070.8, 1070.5, 1070.5, 1069.7, 1068.9, 1070.2, 1067.3, 1067.8, 1067.9, 1061.7, 1060.8, 1061.7, 1060.9, 1060.2, 1060.9, 1061, 1060.3, 1061.2, 1061.9, 1062, 1061.9, 1062.5, 1062.3, 1062.3, 1062, 1062.7, 1063, 1062, 1062.6, 1062.4, 1061.8, 1058.9, 1061.5, 1062.4, 1061.4, 1060.9, 1062, 1060.6, 1059.4, 1060.5, 1061.3, 1063.1, 1064.6, 1063.5, 1064.3, 1063.7, 1065.3, 1068.7, 1069.8, 1071.3, 1072.8, 1073.8, 1072.9, 1072.7, 1072.6, 1078.8, 1080.6, 1078.2, 1073.7, 1076.4, 1075.2, 1075.4, 1075.4, 1074.7, 1073.2, 1076, 1076.5, 1076.2, 1077.1, 1077.6, 1078.5, 1079.1, 1077, 1077, 1078.1, 1077.7, 1080, 1079.7, 1075.6, 1077.2, 1077.2, 1080, 1080, 1078.8, 1079, 1078.9, 1077.8, 1078, 1077.7, 1076.1, 1077, 1078.4, 1078.6, 1079.5, 1080.5, 1082.1, 1083.3, 1083.5, 1085.6, 1085.2, 1088.8, 1085.1, 1090.5, 1088, 1091.1, 1091.4, 1094.3, 1094.4, 1094.2, 1094.1, 1093.1, 1093.1, 1097.6, 1098.7, 1098.2, 1100.1, 
   1099.4, 1100.1, 1097.6, 1096.1, 1097, 1096.4, 1098.5, 1100.8, 1101.8, 1106.4, 1103.5, 1106.4, 1109.5, 1108.7, 1110.4, 1109.8, 1109.5, 1109.9, 1109.1, 1104.3, 1105.2, 1104.1, 1103.5, 1104, 1102.9, 1101.7, 1099.8, 1096.8, 1098.6, 1100, 1100.1, 1100, 1101.9, 1103.7, 1103.8, 1101.2, 1098.9, 1103.1, 1104.6, 1104.9, 1107.2, 1107.1, 1106.1, 1105.2, 1104.5, 1104.4, 1105.6, 1107.4, 1106.7, 1100.8, 1100, 1104.4, 1103.4, 1104, 1101.4, 1102, 1100, 1098.9, 1099.6, 1097.3, 1096.8, 1095.4, 1094.5, 1096.3, 1095.4, 1095.8, 1096, 1097.4, 1098.4, 1096.3, 1095, 1095.4, 1096.9, 1095.4, 1092.3, 1091.6, 1087.8, 1089, 1085.8, 1088.8, 1086.8, 1086.8, 1087.5, 1090.3, 1090, 1086.8, 1087.1, 1086.6, 1086.2, 1085, 1084.4, 1083.9, 1085.7, 1085.9, 1082.9, 1082.7, 1081.7, 1082.7, 1083.3, 1083.2, 1082.2, 1088.7, 1089.5, 1092.4, 1091.6, 1093, 1094.4, 1095.2, 1094.1, 1095.8, 1094.5, 1093.1, 1093.7, 1093.1, 1095.4, 1092.3, 1091.5, 1089.1, 1092.5, 1092.4, 1091.4, 1092.3, 1086.1, 1084.8, 1088.7, 1082.9, 1082.6, 1078.4, 1073.6, 1076.9, 1077.6, 1079.1, 1077.7, 1078.6, 1078.8, 1080.4, 1081.2, 1081.5, 1081.1, 1083.6, 1084.9, 1084.2, 1083.9, 1081.3, 1082.4, 1084.6, 1094.6, 1094.1, 1091.1, 1090.7, 1090.8, 1090.3, 1089.3, 1088.8, 1089.4, 1091, 1091.5, 1091.9, 1093.3, 1092.4, 1093.1, 1090.9, 1090.6, 1091, 1089.3, 1091.8, 1091.2, 1090.5, 1091, 1090.6, 1089.8, 1089.7, 1090.1, 1089.7, 1089.3, 1089.1, 1086.4, 1090.6, 1090.3, 1089, 1089.3, 1089.5, 1090.8, 1093.3, 1089.5, 1087.8, 1084.7, 1085.3, 1086.7, 1086.8, 1086.9, 1087.7, 1090.1, 1090.8, 1088.3, 1087.9, 1088.1, 1088.6, 1090.1, 1092.2, 1091.6, 1093.3, 1093.3, 1091.9, 1092.7, 1094.8, 1096.3, 1094.1, 1095.5, 1095.9, 1102.5, 1100.5, 1101.9, 1102.8, 1104.3, 1106.8, 1105.6, 1104.5, 1102.7, 1101.8, 1100.4, 1099.7, 1100.7, 1100.3, 1100.9, 1103, 1104.3, 1103.8, 1104.1, 1101.4, 1099.7, 1098.3, 1100.2, 1100.6, 1098.6, 1097.2, 1095.7, 1095.4, 1096, 1101.8, 1101.6, 1103.5, 1102.2, 1101.7, 1100.3, 1100.4, 1100.1, 1102.1, 1100.6, 1099.8, 1099.5, 1097.8, 1096.4, 1098.1, 1098.7, 1099.1, 1098.9, 1096.2, 1097.3, 1101.3, 1100, 1099, 1097, 1097.8, 1098.8, 1099, 1099.1, 1099.3, 1101.3, 1102.1, 1102.9, 1103.1, 1101.9, 1102.3, 1105.2, 1104.3, 1105.7, 1105.1, 1107.5, 1105.4, 1107.9, 1107.4, 1107.5, 1108.8, 1107, 1106.4, 1106.5, 1109.6, 1108.9, 1109.7, 1109.4, 1110.9, 1112.2, 1114.1, 1113.5, 1113.5, 1115.9, 1117.3, 1115.2, 1114.5, 1114.9, 1112.7, 1113.2, 1114.2, 1114.9, 1119.6, 1118.8, 1119.6, 1122.1, 1123.1, 1122.6, 1120.7, 1120.5, 1121.4, 1121.3, 1122, 1122.3, 1121, 1121.5, 1120.4, 1119, 1118.4, 1119.7, 1117.9, 1118.9, 1119.8, 1119.4, 1117.6, 1117.2, 1117.5, 1118.2, 1117.3, 1128.3, 1126.4, 1125.7, 1125.3, 1122.8, 1120.6, 1121, 1122.3, 1121.1, 1120.3, 1118, 1118.5, 1119.3, 1118.2, 1118.9, 1122.1, 1120.3, 1120.8, 1114, 1115.9, 1116.5, 1116.1, 1115.8, 1115.9, 1114.3, 1115.6, 1114.6, 1114.8, 1116.3, 1114.9, 1112.7, 1115.7, 1114.6, 1115.5, 1113.4, 1111.7, 1113.4, 1112.8, 1112.1, 1115.4, 1113.5, 1112.4, 1118, 1117, 1117.1, 1116.6, 1116.5, 1117.9, 1118.4, 1117.8, 1118.4, 1120.4, 1121.4, 1122.5, 1122.3, 1122.3, 1121.8, 1122.9, 1122, 1122, 1123, 1121.8, 1123.9, 1122.9, 1126.4, 1126.3, 1126.7, 1127.2, 1127.6, 1128.8, 1129.7, 1128.6, 1128.6, 1129.5, 1127.6, 1127.4, 1126.1, 1125.8, 1125.8, 1125.9, 1126.1, 1126.4, 1125.8, 1125.2, 1124.8, 1125.4, 1127.4, 1128.9, 1128.3, 1125, 1126.3, 1128, 1128.3, 1130.1, 1129.6, 1127.9, 1127.6, 1128.4, 1128.7, 1127.8, 1127.1, 1128.5, 1128.5, 1124.9, 1126.8, 1128.2, 1130.4, 1128.6, 1130.2, 1126.7, 1132.5, 1138.2, 1138.6, 1140, 1144.2, 1138.9, 1142.8, 1143, 1142.6, 1143.5, 1141.8, 1141.3, 1141.2, 1141.8, 1143.5, 1143.9, 1142.4, 1145.4, 1146.4, 1147.6, 1145.8, 1148.2, 1153.5, 1155.3, 1152.1, 1154.6, 1155.9, 1155.5, 1156.4, 1156.4, 1156, 1156, 1156.1, 1154.8, 1156.4, 1156.1, 1155.7, 1155.3, 1154.8, 1154.8, 1156.3, 1157.9, 1159.4, 1159.4, 1159, 1151.5, 1149.9, 1154, 1155.3, 1157.6, 1157.9, 1162.8, 1174.5, 1174.1, 1174.1, 1165.3, 1168.5, 1165.4, 1165.5, 1166.2, 1166.7, 1166.2, 1166.4, 1165.8, 1168.5, 1173.8, 1176.4, 1175.9, 1182.5, 1182.1, 1192.1, 1193.6, 1194.4, 1195.6, 1201, 1195.5, 1190.7, 1189.6, 1191.5, 
   1193.2, 1193.9, 1194, 1193.2, 1193.1, 1191.8, 1193.4, 1186.7, 1188.7, 1189.5, 1189.3, 1191.7, 1196.6, 1198.5, 1189.7, 1195.5, 1195.6, 1197.3, 1195.2, 1190.8, 1187.9, 1189.4, 1189.6, 1192.1, 1193.4, 1191.5, 1191.3, 1191.8, 1191.8, 1191.2, 1188, 1187, 1182.3, 1182.6, 1182.8, 1183.7, 1187.9, 1191, 1192.6, 1193.3, 1192.1, 1192.5, 1194, 1196.9, 1197.4, 1197.4, 1199, 1208.7, 1208.4, 1207, 1206.1, 1209.3, 1206.7, 1208.2, 1207.6, 1217.6, 1217.6, 1224.8, 1237.3, 1235.9, 1236, 1233, 1247.1, 1254.5, 1248.4, 1249.4, 1245, 1245.1, 1247, 1240.7, 1238.6, 1236.3, 1238.2, 1233.9, 1233.5, 1239.3, 1245, 1242.6, 1239.5, 1238.4, 1242.6, 1238, 1238.7, 1236, 1239.5, 1238.4, 1237.8, 1236.9, 1239.3, 1238.7, 1238.5, 1238.5, 1233.8, 1228.1, 1223.7, 1224.7, 1221, 1220.6, 1219.8, 1219.5, 1212.4, 1210.1, 1209.5, 1210.2, 1209.9, 1209.6, 1211.7, 1210, 1205.7, 1207.4, 1209.4, 1208.4, 1208.4, 1204.7, 1198.4, 1193.4, 1194.2, 1197.9, 1201.3, 1196.2, 1200, 1211, 1212, 1215.4, 1213.9, 1215.3, 1211.2, 1216.4, 1213, 1209.1, 1204.2, 1204.2, 1200.4, 1200.9, 1203.2, 1198.2, 1202.6, 1203.7, 1209.3, 1209.1, 1206.8, 1207.3, 1211.5, 1204.6, 1202.9, 1203, 1202.3, 1207, 1209.4, 1210.9, 1210.6, 1212.8, 1210.2, 1210.3, 1208.9, 1208.3, 1209, 1207.4, 1209.3, 1209.1, 1210.5, 1210.1, 1209.5, 1209.9, 1208.1, 1207.5, 1207.6, 1206.8, 1203.4, 1204.3, 1205.8, 1206.9, 1210.8, 1215.8, 1218.8, 1227.8, 1232.9, 1234.7, 1237.5, 1231.3, 1231.6, 1232.8, 1227.2, 1227.5, 1228.4, 1228, 1226.7, 1226.5, 1224.4, 1224.2, 1221.5, 1222.9, 1230.8, 1231.7, 1230.7, 1229.3, 1231.6, 1233, 1231.3, 1231.9, 1232.7, 1229.6, 1226.6, 1226.1, 1225.9, 1223.5, 1223.3, 1217.1, 1216.3, 1217, 1217.7, 1211, 1209.5, 1206.6, 1205.2, 1204, 1207.6, 1209.1, 1212.6, 1212.2, 1210.3, 1211.1, 1209.2, 1208.2, 1207.9, 1208.9, 1209.3, 1211.2, 1215.8, 1215.7, 1221.1, 1220.5, 1216.6, 1216.7, 1217.8, 1216.9, 1219.2, 1218.8, 1217.4, 1219.3, 1218.6, 1221.6, 1225.6, 1224.6, 1223.8, 1222.8, 1223.6, 1226.1, 1226, 1231.1, 1230, 1225.9, 1228, 1228.6, 1228.7, 1228.1, 1226, 1224.2, 1226.2, 1230.6, 1237.1, 1238, 1236.1, 1244.4, 1250.2, 1248.6, 1245.6, 1238.4, 1239.7, 1230.5, 1230.3, 1229.4, 1225, 1228.5, 1236.3, 1233.3, 1234.4, 1233.4, 1234.5, 1237.2, 1241, 1239.5, 1237.4, 1236, 1233.3, 1236.5, 1234.8, 1236.4, 1239.2, 1239.8, 1242.1, 1235.1, 1239.1, 1233.6, 1233.7, 1234.5, 1237.5, 1239, 1237.6, 1236.5, 1238.1, 1240, 1239.6, 1237, 1231.4, 1233.1, 1233.4, 1236.6, 1237.1, 1229.3, 1227.6, 1217.5, 1219.2, 1220.4, 1222.3, 1226.2, 1224.9, 1222.8, 1221.9, 1221.8, 1226.4, 1226.4, 1225.2, 1226.8, 1229, 1227.3, 1230.8, 1234.1, 1235.1, 1234.9, 1229.9, 1231.3, 1229.2, 1234.6, 1232.4, 1233.8, 1232.6, 1234.6, 1239.6, 1240.9, 1239.3, 1241.1, 1241.4, 1247.2, 1244.8, 1244.4, 1245.7), 
   .Dim = c(1000L, 1L), index = structure(c(1451386800, 1451390400, 1451394000, 1451397600, 1451401200, 1451404800, 1451408400, 1451412000, 1451415600, 1451419200, 1451422800, 1451430000, 1451433600, 1451437200, 1451440800, 1451444400, 1451448000, 1451451600, 1451455200, 1451458800, 1451462400, 1451466000, 1451469600, 1451473200, 1451476800, 1451480400, 1451484000, 1451487600, 1451491200, 1451494800, 1451498400, 1451502000, 1451505600, 1451509200, 1451516400, 1451520000, 1451523600, 1451527200, 1451530800, 1451534400, 1451538000, 1451541600, 1451545200, 1451548800, 1451552400, 1451556000, 1451559600, 1451563200, 1451566800, 1451570400, 1451574000, 1451577600, 1451581200, 1451584800, 1451588400, 1451592000, 1451595600, 1451862000, 1451865600, 1451869200, 1451872800, 1451876400, 1451880000, 1451883600, 1451887200, 1451890800, 1451894400, 1451898000, 1451901600, 1451905200, 1451908800, 1451912400, 1451916000, 1451919600, 1451923200, 1451926800, 1451930400, 1451934000, 1451937600, 1451941200, 1451948400, 1451952000, 1451955600, 1451959200, 1451962800, 1451966400, 1451970000, 1451973600, 1451977200, 1451980800, 1451984400, 1451988000, 1451991600, 1451995200, 1451998800, 1452002400, 1452006000, 1452009600, 1452013200, 1452016800, 1452020400, 1452024000, 1452027600, 1452034800, 1452038400, 1452042000, 1452045600, 1452049200, 1452052800, 1452056400, 1452060000, 1452063600, 1452067200, 1452070800, 1452074400, 1452078000, 1452081600, 1452085200, 1452088800, 1452092400, 1452096000, 1452099600, 1452103200, 1452106800, 1452110400, 1452114000, 1452121200, 1452124800, 1452128400, 1452132000, 1452135600, 1452139200, 1452142800, 1452146400, 1452150000, 1452153600, 1452157200, 1452160800, 1452164400, 1452168000, 1452171600, 1452175200, 1452178800, 1452182400, 1452186000, 1452189600, 1452193200, 1452196800, 1452200400, 1452207600, 1452211200, 1452214800, 1452218400, 1452222000, 1452225600, 1452229200, 1452232800, 1452236400, 1452240000, 1452243600, 1452247200, 1452250800, 1452254400, 1452258000, 1452261600, 1452265200, 1452268800, 1452272400, 1452276000, 1452279600, 1452283200, 1452286800, 1452466800, 1452470400, 1452474000, 1452477600, 1452481200, 1452484800, 1452488400, 1452492000, 1452495600, 1452499200, 1452502800, 1452506400, 1452510000, 1452513600, 1452517200, 1452520800, 1452524400, 1452528000, 1452531600, 1452535200, 1452538800, 1452542400, 1452546000, 1452553200, 1452556800, 1452560400, 1452564000, 1452567600, 1452571200, 1452574800, 1452578400, 1452582000, 1452585600, 1452589200, 1452592800, 1452596400, 1452600000, 1452603600, 1452607200, 1452610800, 1452614400, 1452618000, 1452621600, 1452625200, 1452628800, 1452632400, 1452639600, 1452643200, 1452646800, 1452650400, 1452654000, 1452657600, 1452661200, 1452664800, 1452668400, 1452672000, 1452675600, 1452679200, 1452682800, 1452686400, 1452690000, 1452693600, 1452697200, 1452700800, 1452704400, 1452708000, 1452711600, 1452715200, 1452718800, 1452726000, 1452729600, 1452733200, 1452736800, 1452740400, 1452744000, 1452747600, 1452751200, 1452754800, 1452758400, 1452762000, 1452765600, 1452769200, 1452772800, 1452776400, 1452780000, 1452783600, 1452787200, 1452790800, 1452794400, 1452798000, 1452801600, 1452805200, 1452812400, 1452816000, 1452819600, 1452823200, 1452826800, 1452830400, 1452834000, 1452837600, 1452841200, 1452844800, 1452848400, 1452852000, 1452855600, 1452859200, 1452862800, 1452866400, 1452870000, 1452873600, 1452877200, 1452880800, 1452884400, 1452888000, 1452891600, 1453071600, 1453075200, 1453078800, 1453082400, 1453086000, 1453089600, 1453093200, 1453096800, 1453100400, 1453104000, 1453107600, 1453111200, 1453114800, 1453118400, 1453122000, 1453125600, 1453129200, 1453132800, 1453136400, 1453158000, 1453161600, 1453165200, 1453168800, 1453172400, 1453176000, 1453179600, 1453183200, 1453186800, 1453190400, 1453194000, 1453197600, 1453201200, 1453204800, 1453208400, 1453212000, 1453215600, 1453219200, 1453222800, 
   1453226400, 1453230000, 1453233600, 1453237200, 1453244400, 1453248000, 1453251600, 1453255200, 1453258800, 1453262400, 1453266000, 1453269600, 1453273200, 1453276800, 1453280400, 1453284000, 1453287600, 1453291200, 1453294800, 1453298400, 1453302000, 1453305600, 1453309200, 1453312800, 1453316400, 1453320000, 1453323600, 1453330800, 1453334400, 1453338000, 1453341600, 1453345200, 1453348800, 1453352400, 1453356000, 1453359600, 1453363200, 1453366800, 1453370400, 1453374000, 1453377600, 1453381200, 1453384800, 1453388400, 1453392000, 1453395600, 1453399200, 1453402800, 1453406400, 1453410000, 1453417200, 1453420800, 1453424400, 1453428000, 1453431600, 1453435200, 1453438800, 1453442400, 1453446000, 1453449600, 1453453200, 1453456800, 1453460400, 1453464000, 1453467600, 1453471200, 1453474800, 1453478400, 1453482000, 1453485600, 1453489200, 1453492800, 1453496400, 1453676400, 1453680000, 1453683600, 1453687200, 1453690800, 1453694400, 1453698000, 1453701600, 1453705200, 1453708800, 1453712400, 1453716000, 1453719600, 1453723200, 1453726800, 1453730400, 1453734000, 1453737600, 1453741200, 1453744800, 1453748400, 1453752000, 1453755600, 1453762800, 1453766400, 1453770000, 1453773600, 1453777200, 1453780800, 1453784400, 1453788000, 1453791600, 1453795200, 1453798800, 1453802400, 1453806000, 1453809600, 1453813200, 1453816800, 1453820400, 1453824000, 1453827600, 1453831200, 1453834800, 1453838400, 1453842000, 1453849200, 1453852800, 1453856400, 1453860000, 1453863600, 1453867200, 1453870800, 1453874400, 1453878000, 1453881600, 1453885200, 1453888800, 1453892400, 1453896000, 1453899600, 1453903200, 1453906800, 1453910400, 1453914000, 1453917600, 1453921200, 1453924800, 1453928400, 1453935600, 1453939200, 1453942800, 1453946400, 1453950000, 1453953600, 1453957200, 1453960800, 1453964400, 1453968000, 1453971600, 1453975200, 1453978800, 1453982400, 1453986000, 1453989600, 1453993200, 1453996800, 1454000400, 1454004000, 1454007600, 1454011200, 1454014800, 1454022000, 1454025600, 1454029200, 1454032800, 1454036400, 1454040000, 1454043600, 1454047200, 1454050800, 1454054400, 1454058000, 1454061600, 1454065200, 1454068800, 1454072400, 1454076000, 1454079600, 1454083200, 1454086800, 1454090400, 1454094000, 1454097600, 1454101200, 1454281200, 1454284800, 1454288400, 1454292000, 1454295600, 1454299200, 1454302800, 1454306400, 1454310000, 1454313600, 1454317200, 1454320800, 1454324400, 1454328000, 1454331600, 1454335200, 1454338800, 1454342400, 1454346000, 1454349600, 1454353200, 1454356800, 1454360400, 1454367600, 1454371200, 1454374800, 1454378400, 1454382000, 1454385600, 1454389200, 1454392800, 1454396400, 1454400000, 1454403600, 1454407200, 1454410800, 1454414400, 1454418000, 1454421600, 1454425200, 1454428800, 1454432400, 1454436000, 1454439600, 1454443200, 1454446800, 1454454000, 1454457600, 1454461200, 1454464800, 1454468400, 1454472000, 1454475600, 1454479200, 1454482800, 1454486400, 1454490000, 1454493600, 1454497200, 1454500800, 1454504400, 1454508000, 1454511600, 1454515200, 1454518800, 1454522400, 1454526000, 1454529600, 1454533200, 1454540400, 1454544000, 1454547600, 1454551200, 1454554800, 1454558400, 1454562000, 1454565600, 1454569200, 1454572800, 1454576400, 1454580000, 1454583600, 1454587200, 1454590800, 1454594400, 1454598000, 1454601600, 1454605200, 1454608800, 1454612400, 1454616000, 1454619600, 1454626800, 1454630400, 1454634000, 1454637600, 1454641200, 1454644800, 1454648400, 1454652000, 
   1454655600, 1454659200, 1454662800, 1454666400, 1454670000, 1454673600, 1454677200, 1454680800, 1454684400, 1454688000, 1454691600, 1454695200, 1454698800, 1454702400, 1454706000, 1454709600, 1454886000, 1454889600, 1454893200, 1454896800, 1454900400, 1454904000, 1454907600, 1454911200, 1454914800, 1454918400, 1454922000, 1454925600, 1454929200, 1454932800, 1454936400, 1454940000, 1454943600, 1454947200, 1454950800, 1454954400, 1454958000, 1454961600, 1454965200, 1454972400, 1454976000, 1454979600, 1454983200, 1454986800, 1454990400, 1454994000, 1454997600, 1455001200, 1455004800, 1455008400, 1455012000, 1455015600, 1455019200, 1455022800, 1455026400, 1455030000, 1455033600, 1455037200, 1455040800, 1455044400, 1455048000, 1455051600, 1455058800, 1455062400, 1455066000, 1455069600, 1455073200, 1455076800, 1455080400, 1455084000, 1455087600, 1455091200, 1455094800, 1455098400, 1455102000, 1455105600, 1455109200, 1455112800, 1455116400, 1455120000, 1455123600, 1455127200, 1455130800, 1455134400, 1455138000, 1455141600, 1455145200, 1455148800, 1455152400, 1455156000, 
   1455159600, 1455163200, 1455166800, 1455170400, 1455174000, 1455177600, 1455181200, 1455184800, 1455188400, 1455192000, 1455195600, 1455199200, 1455202800, 1455206400, 1455210000, 1455213600, 1455217200, 1455220800, 1455224400, 1455231600, 1455235200, 1455238800, 1455242400, 1455246000, 1455249600, 1455253200, 1455256800, 1455260400, 1455264000, 1455267600, 1455271200, 1455274800, 1455278400, 1455282000, 1455285600, 1455289200, 1455292800, 1455296400, 1455300000, 1455303600, 1455307200, 1455310800, 1455490800, 1455494400, 1455498000, 1455501600, 1455505200, 1455508800, 1455512400, 1455516000, 1455519600, 1455523200, 1455526800, 1455530400, 1455534000, 1455537600, 1455541200, 1455544800, 1455548400, 1455552000, 1455555600, 1455577200, 1455580800, 1455584400, 1455588000, 1455591600, 1455595200, 1455598800, 1455602400, 1455606000, 1455609600, 1455613200, 1455616800, 1455620400, 1455624000, 1455627600, 1455631200, 1455634800, 1455638400, 1455642000, 1455645600, 1455649200, 1455652800, 1455656400, 1455663600, 1455667200, 1455670800, 1455674400, 1455678000, 1455681600, 1455685200, 1455688800, 1455692400, 1455696000, 1455699600, 1455703200, 1455706800, 1455710400, 1455714000, 1455717600, 1455721200, 1455724800, 1455728400, 1455732000, 1455735600, 1455739200, 1455742800, 1455750000, 1455753600, 1455757200, 1455760800, 1455764400, 1455768000, 1455771600, 1455775200, 1455778800, 1455782400, 1455786000, 1455789600, 1455793200, 1455796800, 1455800400, 1455804000, 1455807600, 1455811200, 1455814800, 1455818400, 1455822000, 1455825600, 1455829200, 1455836400, 1455840000, 1455843600, 1455847200, 1455850800, 1455854400, 1455858000, 1455861600, 1455865200, 1455868800, 1455872400, 1455876000, 1455879600, 1455883200, 1455886800, 1455890400, 1455894000, 1455897600, 1455901200, 1455904800, 1455908400, 1455912000, 1455915600, 1456095600, 1456099200, 1456102800, 1456106400, 1456110000, 1456113600, 1456117200, 1456120800, 1456124400, 1456128000, 1456131600, 1456135200, 1456138800, 1456142400, 1456146000, 1456149600, 1456153200, 1456156800, 1456160400, 1456164000, 1456167600, 1456171200, 1456174800, 1456182000, 1456185600, 1456189200, 1456192800, 1456196400, 1456200000, 1456203600, 1456207200, 1456210800, 1456214400, 1456218000, 1456221600, 1456225200, 1456228800, 1456232400, 1456236000, 1456239600, 1456243200, 1456246800, 1456250400, 1456254000, 1456257600, 1456261200, 1456268400, 1456272000, 1456275600, 1456279200, 1456282800, 1456286400, 1456290000, 1456293600, 1456297200, 1456300800, 1456304400, 1456308000, 1456311600, 1456315200, 1456318800, 1456322400, 1456326000, 1456329600, 1456333200, 1456336800, 1456340400, 1456344000, 1456347600, 1456354800, 1456358400, 1456362000, 1456365600, 1456369200, 1456372800, 1456376400, 1456380000, 1456383600, 1456387200, 1456390800, 1456394400, 1456398000, 1456401600, 1456405200, 1456408800, 1456412400, 1456416000, 1456419600, 1456423200, 1456426800, 1456430400, 1456434000, 1456441200, 1456444800, 1456448400, 1456452000, 1456455600, 1456459200, 1456462800, 1456466400, 1456470000, 1456473600, 1456477200, 1456480800, 1456484400, 1456488000, 1456491600, 1456495200, 1456498800, 1456502400, 1456506000, 1456509600, 1456513200, 1456516800, 1456520400, 1456700400, 1456704000, 1456707600, 1456711200, 1456714800, 1456718400, 1456722000, 1456725600, 1456729200, 1456732800, 1456736400, 1456740000, 1456743600, 1456747200, 1456750800, 1456754400, 1456758000, 1456761600, 1456765200, 1456768800, 1456772400, 1456776000, 1456779600, 1456786800, 1456790400, 1456794000, 1456797600, 1456801200, 1456804800), 
   tzone = "", tclass = c("POSIXlt","POSIXt")), class = c("xts", "zoo"), .indexCLASS = c("POSIXlt", "POSIXt"), tclass = c("POSIXlt", "POSIXt"), .indexTZ = "", tzone = "", .CLASS = "double")

#get 1st Friday of every Month
NFPFri <- DATSxts[.indexmday(DATSxts) >= 1 & .indexmday(DATSxts) <= 7 &.indexwday(DATSxts) == 5] #1st Friday of every Month

#get following Monday => if 1st Friday is days 1:4 then 1st Monday, otherwise 2nd Monday
ifelse (.indexwday(NFPFri) >=1 &  .indexwday(NFPFri) <= 4 ,
PostNFPMon <- DATSxts[.indexmday(DATSxts) >= 4 & .indexmday(DATSxts) <= 7 &.indexwday(DATSxts) == 1],
PostNFPMon <- DATSxts[.indexmday(DATSxts) >= 8 & .indexmday(DATSxts) <= 10 &.indexwday(DATSxts) == 1]) 

#merge Friday and Monday, put into one column, and eliminate NA's
NFP <- merge(NFPFri, PostNFPMon)
NFP <- rowSums(NFP,na.rm = TRUE)

Code provides a subset called NFP containing all prices for those two days. But it has one problem: using rowSums results in NFP having no DateTime index.

  • Question: how to merge xts objects into one column without losing the DateTime information?
  • Bonus: would it be possible to achieve the same subset with just one line of code? (i.e. the use of ifelse, merge and rowSums seems very inefficient)

****(Note: for some odd reason if I put all data/xts code in less than 8 lines loading the data gives an error message)****

EDIT: replaced cbind by merge to preserve the column names.

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  • Any anticipated difficulty with "first Fridays" where Friday is a National Holiday? – IRTFM Apr 22 '16 at 03:11
  • Yes. That's step #2. Haven't attempted to tackle it yet. There is an official calendar that I hope to be able to use to avoid manually inputting/adjusting dates. – Krug Apr 22 '16 at 03:14

2 Answers2

2

The BLS website has already listed the recent and forthcoming dates http://www.bls.gov/schedule/news_release/empsit.htm :

Reference Month Release Date    Release Time
October 2015    Nov. 06, 2015   08:30 AM
November 2015   Dec. 04, 2015   08:30 AM
December 2015   Jan. 08, 2016   08:30 AM
January 2016    Feb. 05, 2016   08:30 AM
February 2016   Mar. 04, 2016   08:30 AM
March 2016  Apr. 01, 2016   08:30 AM
April 2016  May 06, 2016    08:30 AM
May 2016    Jun. 03, 2016   08:30 AM
June 2016   Jul. 08, 2016   08:30 AM
July 2016   Aug. 05, 2016   08:30 AM
August 2016 Sep. 02, 2016   08:30 AM
September 2016  Oct. 07, 2016   08:30 AM
October 2016    Nov. 04, 2016   08:30 AM
November 2016   Dec. 02, 2016   08:30 AM

Notice the two items where this is not the "first Friday". The method suggested by Dirk in the cited posting for Fridays would be implemented with:

 library(RcppBDT)
 for( y in 2015:2016){ for(m in 1:12){print( getNthDayOfWeek(first, Fri, m, y))}}

[1] "2015-01-02"
[1] "2015-02-06"
[1] "2015-03-06"
[1] "2015-04-03"
[1] "2015-05-01"
[1] "2015-06-05"
[1] "2015-07-03"
[1] "2015-08-07"
[1] "2015-09-04"
[1] "2015-10-02"
[1] "2015-11-06"
[1] "2015-12-04"
[1] "2016-01-01"
[1] "2016-02-05"
[1] "2016-03-04"
[1] "2016-04-01"
[1] "2016-05-06"
[1] "2016-06-03"
[1] "2016-07-01"
[1] "2016-08-05"
[1] "2016-09-02"
[1] "2016-10-07"
[1] "2016-11-04"
[1] "2016-12-02"

And for the Fridays:next Mondays request, just this added device:

i=-1; for( y in 2015:2016){ for(m in 1:12){
                                i=i+2;
                                x[i] <- getNthDayOfWeek(first, Fri, m, y)
                                x[i+1] <- x[1] + 3 }}
#---------
 x
 [1] "2015-01-02" "2015-01-05" "2015-02-06" "2015-01-05" "2015-03-06" "2015-01-05"
 [7] "2015-04-03" "2015-01-05" "2015-05-01" "2015-01-05" "2015-06-05" "2015-01-05"
[13] "2015-07-03" "2015-01-05" "2015-08-07" "2015-01-05" "2015-09-04" "2015-01-05"
[19] "2015-10-02" "2015-01-05" "2015-11-06" "2015-01-05" "2015-12-04" "2015-01-05"
[25] "2016-01-01" "2015-01-05" "2016-02-05" "2015-01-05" "2016-03-04" "2015-01-05"
[31] "2016-04-01" "2015-01-05" "2016-05-06" "2015-01-05" "2016-06-03" "2015-01-05"
[37] "2016-07-01" "2015-01-05" "2016-08-05" "2015-01-05" "2016-09-02" "2015-01-05"
[43] "2016-10-07" "2015-01-05" "2016-11-04" "2015-01-05" "2016-12-02" "2015-01-05"

Note: I'm on a Mac with R 3.3.0 and a new gfortran compiler, but this seems to still "just work".

IRTFM
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  • Relying on RcppBDT is the (IMHO) correct approach as this needs calendar arithmetic. – Dirk Eddelbuettel Apr 22 '16 at 04:02
  • Very useful. Thanks very much! Guess not an issue using a loop performance-wise given that we are looking at an event that only takes place once a month. Still would like to know how to bind xts objects without messing/lossing the DateTime index. – Krug Apr 22 '16 at 05:31
  • I would have expected there to be either a `merge.xts` or a `merge.zoo` function that would let you maintain the index. I didn't actually understand what was desired since the expression "Y-axis" was not interpretable (by me anyway) in the context of a data structure. – IRTFM Apr 22 '16 at 06:33
  • I'll edit the y axis comment to make it clearer, thanks. – Krug Apr 22 '16 at 21:26
  • BTW this answer was extremely helpful but does not address the question. I'll edit the question to make it clearer. I purposely made the question lengthier than it need be as thought some people may find the finding NFP day useful. I realize the responsible for the xts object losing the DateTime index is `rowSums`. – Krug Apr 22 '16 at 22:58
  • I don't understand what you intend. You made one subset with 15 rows and then merged with a subset that had 23 rows but the result had 38 rows because none of the indexes were the same, so what is rowSums supposed to be doing/ – IRTFM Apr 23 '16 at 00:27
0

Found the answer thanks to @hvollmeier answer to this question: Excel or R: Merge time series with missing values. Had to save the result of rowSums in NFP$FriAndMon rather than just NFP. Now DateTime index is preserved.

NFP <- merge(NFPFri, PostNFPMon)
NFP$FriAndMon <- rowSums(result,na.rm = TRUE) 
NFP <- NFP[,3]
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