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Intertemporal portfolio choice

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1710:. In dynamic programming, the last period decision rule, contingent on available wealth and the realizations of all previous periods' asset returns, is devised in advance; then the next-to-last period's decision rule is devised, taking into account how the results of this period will influence the final period's decisions; and so forth backward in time. This procedure becomes complex very quickly if there are more than a few time periods or more than a few assets. 1747:
is young that turn out badly can be reacted to by supplying more labor than anticipated in subsequent time periods to at least partially offset the lost wealth; since an older person with fewer subsequent time periods is less able to offset bad investment returns in this way, it is optimal for an investor to take on less investment risk at an older age.
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from the portfolio of the period before that, etc. However, under certain circumstances the optimal portfolio decisions can be arrived at in a way that is separated in time, so that the shares of wealth placed in particular assets depend only on the stochastic asset return distributions of that particular period.
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Intertemporal portfolio models in which portfolio choice is conducted jointly with intertemporal labor supply decisions can lead to the age effect of conservatism increasing with age as advocated by many investment advisors. This result follows from the fact that risky investments when the investor
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for choice under risk, including the log and power utility functions dealt with above. Mossin showed that under HARA utility, optimal portfolio choice involves partial time-independence of decisions if there is a risk-free asset and there is serial independence of asset returns: to find the optimal
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after the first will depend on the amount of wealth that results from the previous period's portfolio, which depends on the asset returns that occurred in the previous period as well as that period's portfolio size and allocation, the latter having depended in turn on the amount of wealth resulting
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If there is not serial independence of returns through time, then the expectations operator cannot be applied separately to the various multiplicative terms. Thus the optimal portfolio for any period will depend on the probability distribution of returns for the various assets contingent on their
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for intertemporal portfolio choice states that, when asset return distributions are identical in all periods, a particular portfolio replicated each period will outperform all other portfolio sequences in the long run. Here the long run is an arbitrarily large number of time periods such that the
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Hence under this condition we again have intertemporal independence of portfolio decisions. Note that the log utility function, unlike the power utility function, did not require the assumption of intertemporal independence of returns to obtain intertemporal independence of portfolio decisions.
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Moreover, the optimal actions in a particular period will have to be chosen based on knowledge of how decisions will be made in future periods, because the realizations in the present period for the asset returns affect not just the portfolio outcome for the present period, but also the
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is gradual entry into risky assets; it is frequently advocated by investment advisors. As indicated above, it is not confirmed by models with log utility. However, it can emerge from an intertemporal mean-variance model with negative serial correlation of returns.
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distributions of observed outcomes for all assets match their ex ante probability distributions. The Kelly criterion gives rise to the same portfolio decisions as does the maximization of the expected value of the log utility function as described above.
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With HARA utility, asset returns that are independently and identically distributed through time, and a risk-free asset, risky asset proportions are independent of the investor's remaining lifetime. Under certain assumptions including
1689: 550: 1256: 1271:—that is, if the realization of the return on any asset in any period is not related to the realization of the return on any asset in any other period—then this expected utility expression becomes 1739:(1,1) process, a necessary but not sufficient condition for increasing conservatism (decreasing holding of the risky asset) over time (which is often advocated by investment advisors) is negative first-order 1567: 1130: 890: 421: 1014: 172: 1433: 1277: 1776:
through time, and with a risk-free asset, one can obtain an explicit solution for the demand for the unique optimal portfolio, and that demand is linear in initial wealth.
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These considerations apply to utility functions in general with the exceptions noted previously. In general the expected utility expression to be maximized is
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portfolio return in any period (the imperfectly predictable amount that the average dollar in the portfolio grows or shrinks to in a given period
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for the optimal shares in a particular period do not contain the stochastic return information or the decision information for any other period.
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current-period portfolio, one needs to know no future distributional information about the asset returns except the future risk-free returns.
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The mathematical method of dealing with this need for current decision-making to take into account future decision-making is
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then decisions are intertemporally separate. Let initial wealth (the amount that is investable in the initial period) be
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Balvers, Ronald J., and Mitchell, Douglas W., "Autocorrelated returns and optimal intertemporal portfolio choice",
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involves taking the derivatives of one additively separate expression with respect to the various shares, and the
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refers to the stochastic return (the imperfectly predictable amount that the average dollar grows to) of asset
1756: 1377:{\displaystyle a\cdot W_{0}^{a}\cdot {\text{E}}R_{1}^{a}\cdot {\text{E}}R_{2}^{a}\cdots {\text{E}}R_{T}^{a};} 1993: 1398: 1998: 1945: 1815: 1909:
Balvers, Ronald J., and Mitchell, Douglas W., "Efficient gradualism in intertemporal portfolios",
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maximization of this expected utility expression is equivalent to separate maximization (if
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with hyperbolic absolute risk aversion, with asset returns whose evolution is described by
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As per the above, the expected utility of final wealth with a power utility function is
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of the value of the portfolio after a certain number of time periods—that is, the
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that are attained by withdrawing some funds from the portfolio after each time period.
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inherited from the previous period that are allocated at the start of period
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of final wealth. Alternatively, it may be a function of the various levels of
1987: 1684:{\displaystyle {\text{E}}U(W_{T})={\text{E}}U(W_{0}R_{1}R_{2}\cdots R_{T}),} 32: 95: 1967: 1896: 1870: 1573:
previous-period realizations, and so cannot be determined in advance.
545:{\displaystyle R_{t}=w_{1t}r_{1t}+w_{2t}r_{2t}+\cdots +w_{nt}r_{nt},} 1251:{\displaystyle R_{t}=w_{1t}r_{1t}+w_{2t}r_{2t}+\cdots +w_{nt}r_{nt}} 1888: 35:
some criterion. The set of asset proportions at any time defines a
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above to express outcome-contingent utility, substituting in for
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Stochastic programming § Multistage portfolio optimization
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In a general context the optimal portfolio allocation in any
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depends on the portfolio allocation—the fractions
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gives the expected utility expression to be maximized:
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for future asset returns and hence future decisions.
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are additively separate, giving rise to the result of
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If the investor's utility function is the risk averse
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If there is serial independence of the asset returns
1019:with positive or negative, but non-zero, parameter 1873:(1968). "Optimal multiperiod portfolio policies". 1842: 1683: 1561: 1427: 1376: 1250: 1124: 1008: 917: 884: 708: 677: 650: 615: 577: 544: 415: 323: 290: 260: 234: 196: 166: 120: 1562:{\displaystyle a\cdot W_{0}^{a}\cdot {\text{E}}.} 1125:{\displaystyle a\cdot W_{0}^{a}\cdot {\text{E}},} 885:{\displaystyle \ln+\sum _{t=1}^{T}{\text{E}}\ln.} 631:) are constrained to sum to 1. Taking the log of 416:{\displaystyle W_{T}=W_{0}R_{1}R_{2}\cdots R_{T}} 1985: 933:: optimizing for any particular decision period 931:intertemporal independence of optimal decisions 966:for any value of the power parameter exhibits 689:, and taking the expected value of the log of 1735:and a single asset with returns following an 76: 43:into account. Typically the criterion is the 31:, repeatedly over time, in such a way as to 1833: 1831: 1455: 1009:{\displaystyle {\text{Utility}}=aW_{T}^{a}} 167:{\displaystyle {\text{Utility}}=\ln W_{T},} 1966: 1837: 1796:Intertemporal capital asset pricing model 1774:independently and identically distributed 1449:von Neumann-Morgenstern utility functions 1912:Journal of Economic Dynamics and Control 1849:. Totowa, NJ: Rowman & Littlefield. 1828: 1713: 1447:(HARA) is a feature of a broad class of 895:The terms containing the choice shares 1986: 1939: 1869: 1701: 1930:43(11), November 1997, pp. 1537-1551. 1579:conditional probability distributions 1428:{\displaystyle {\text{E}}R_{t}^{a}.} 1845:Theory of Financial Decision Making 962:Like the log utility function, the 19:is the process of allocating one's 13: 1750: 944: 14: 2010: 1903: 1445:Hyperbolic absolute risk aversion 957: 65: 1791:Intertemporal budget constraint 1439: 968:constant relative risk aversion 1933: 1918: 1863: 1725: 1675: 1629: 1615: 1602: 1553: 1499: 1116: 1062: 876: 783: 745: 732: 89: 17:Intertemporal portfolio choice 1: 1821: 1959:10.1016/0022-0531(71)90038-X 1395:<0) of each of the terms 7: 1779: 1391:>0) or minimization (if 10: 2015: 1946:Journal of Economic Theory 1757:Merton's portfolio problem 1754: 77:Time-independent decisions 69: 1816:Two-moment decision model 1698:is the utility function. 98:function of final wealth 1456:Time-dependent decisions 1975:Continuous-Time Finance 1811:Modern portfolio theory 593:, and where the shares 324:{\displaystyle W_{t-1}} 1839:Ingersoll, Jonathan E. 1685: 1563: 1429: 1378: 1252: 1126: 1010: 964:power utility function 939:first-order conditions 919: 918:{\displaystyle w_{it}} 886: 771: 710: 679: 652: 617: 616:{\displaystyle w_{it}} 579: 578:{\displaystyle r_{it}} 546: 417: 325: 292: 291:{\displaystyle w_{it}} 262: 236: 235:{\displaystyle R_{t}.} 198: 168: 122: 121:{\displaystyle W_{T},} 1719:Dollar cost averaging 1714:Dollar cost averaging 1686: 1564: 1430: 1379: 1261:for each time period 1253: 1127: 1011: 920: 887: 751: 711: 709:{\displaystyle W_{T}} 680: 678:{\displaystyle R_{t}} 653: 651:{\displaystyle W_{T}} 618: 580: 547: 418: 326: 293: 263: 261:{\displaystyle R_{t}} 237: 199: 197:{\displaystyle W_{0}} 169: 123: 1801:Intertemporal choice 1591: 1467: 1399: 1278: 1142: 1030: 977: 899: 723: 693: 662: 635: 597: 559: 433: 354: 302: 272: 245: 216: 181: 134: 102: 1994:Financial economics 1876:Journal of Business 1806:Investment strategy 1733:exponential utility 1708:dynamic programming 1702:Dynamic programming 1552: 1534: 1516: 1490: 1421: 1370: 1347: 1324: 1301: 1115: 1097: 1079: 1053: 1005: 1999:Portfolio theories 1927:Management Science 1741:serial correlation 1681: 1559: 1538: 1520: 1502: 1476: 1425: 1407: 1374: 1356: 1333: 1310: 1287: 1248: 1122: 1101: 1083: 1065: 1039: 1006: 991: 915: 882: 706: 675: 648: 613: 575: 542: 413: 321: 298:of current wealth 288: 258: 232: 194: 164: 118: 57:goods and services 23:wealth to various 1941:Merton, Robert C. 1624: 1597: 1497: 1405: 1354: 1331: 1308: 1060: 983: 775: 140: 2006: 1978: 1972: 1970: 1937: 1931: 1922: 1916: 1915:24, 2000, 21-38. 1907: 1901: 1900: 1867: 1861: 1860: 1848: 1835: 1762:Robert C. Merton 1690: 1688: 1687: 1682: 1674: 1673: 1661: 1660: 1651: 1650: 1641: 1640: 1625: 1622: 1614: 1613: 1598: 1595: 1568: 1566: 1565: 1560: 1551: 1546: 1533: 1528: 1515: 1510: 1498: 1495: 1489: 1484: 1434: 1432: 1431: 1426: 1420: 1415: 1406: 1403: 1383: 1381: 1380: 1375: 1369: 1364: 1355: 1352: 1346: 1341: 1332: 1329: 1323: 1318: 1309: 1306: 1300: 1295: 1257: 1255: 1254: 1249: 1247: 1246: 1234: 1233: 1212: 1211: 1199: 1198: 1183: 1182: 1170: 1169: 1154: 1153: 1135:where as before 1131: 1129: 1128: 1123: 1114: 1109: 1096: 1091: 1078: 1073: 1061: 1058: 1052: 1047: 1015: 1013: 1012: 1007: 1004: 999: 984: 981: 924: 922: 921: 916: 914: 913: 891: 889: 888: 883: 875: 874: 862: 861: 840: 839: 827: 826: 811: 810: 798: 797: 776: 773: 770: 765: 744: 743: 715: 713: 712: 707: 705: 704: 684: 682: 681: 676: 674: 673: 657: 655: 654: 649: 647: 646: 622: 620: 619: 614: 612: 611: 584: 582: 581: 576: 574: 573: 551: 549: 548: 543: 538: 537: 525: 524: 503: 502: 490: 489: 474: 473: 461: 460: 445: 444: 422: 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1145: 1143: 1140: 1139: 1110: 1105: 1092: 1087: 1074: 1069: 1057: 1048: 1043: 1031: 1028: 1027: 1000: 995: 980: 978: 975: 974: 960: 951:Kelly criterion 947: 945:Kelly criterion 906: 902: 900: 897: 896: 867: 863: 854: 850: 832: 828: 819: 815: 803: 799: 790: 786: 772: 766: 755: 739: 735: 724: 721: 720: 700: 696: 694: 691: 690: 669: 665: 663: 660: 659: 642: 638: 636: 633: 632: 604: 600: 598: 595: 594: 566: 562: 560: 557: 556: 530: 526: 517: 513: 495: 491: 482: 478: 466: 462: 453: 449: 440: 436: 434: 431: 430: 407: 403: 394: 390: 384: 380: 374: 370: 361: 357: 355: 352: 351: 309: 305: 303: 300: 299: 279: 275: 273: 270: 269: 252: 248: 246: 243: 242: 223: 219: 217: 214: 213: 188: 184: 182: 179: 178: 155: 151: 137: 135: 132: 131: 109: 105: 103: 100: 99: 92: 79: 74: 68: 12: 11: 5: 2012: 2002: 2001: 1996: 1980: 1979: 1953:(4): 373–413. 1932: 1917: 1902: 1889:10.1086/295078 1883:(2): 215–229. 1862: 1855: 1826: 1825: 1823: 1820: 1819: 1818: 1813: 1808: 1803: 1798: 1793: 1788: 1781: 1778: 1772:and which are 1755:Main article: 1752: 1749: 1727: 1724: 1715: 1712: 1703: 1700: 1692: 1691: 1680: 1677: 1672: 1668: 1664: 1659: 1655: 1649: 1645: 1639: 1635: 1631: 1628: 1620: 1617: 1612: 1608: 1604: 1601: 1570: 1569: 1558: 1555: 1550: 1545: 1541: 1537: 1532: 1527: 1523: 1519: 1514: 1509: 1505: 1501: 1493: 1488: 1483: 1479: 1475: 1472: 1457: 1454: 1441: 1438: 1424: 1419: 1414: 1410: 1385: 1384: 1373: 1368: 1363: 1359: 1350: 1345: 1340: 1336: 1327: 1322: 1317: 1313: 1304: 1299: 1294: 1290: 1286: 1283: 1259: 1258: 1245: 1242: 1238: 1232: 1229: 1225: 1221: 1218: 1215: 1210: 1207: 1203: 1197: 1194: 1190: 1186: 1181: 1178: 1174: 1168: 1165: 1161: 1157: 1152: 1148: 1133: 1132: 1121: 1118: 1113: 1108: 1104: 1100: 1095: 1090: 1086: 1082: 1077: 1072: 1068: 1064: 1056: 1051: 1046: 1042: 1038: 1035: 1017: 1016: 1003: 998: 994: 990: 987: 959: 956: 946: 943: 925:for differing 912: 909: 905: 893: 892: 881: 878: 873: 870: 866: 860: 857: 853: 849: 846: 843: 838: 835: 831: 825: 822: 818: 814: 809: 806: 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1871:Mossin, Jan 1726:Age effects 589:for period 96:log utility 90:Log utility 83:time period 60:consumption 1988:Categories 1856:0847673596 1822:References 335:to assets 206:stochastic 70:See also: 21:investable 1663:⋯ 1536:⋯ 1518:⋅ 1492:⋅ 1474:⋅ 1349:⋯ 1326:⋅ 1303:⋅ 1285:⋅ 1217:⋯ 1099:⋯ 1081:⋅ 1055:⋅ 1037:⋅ 845:⋯ 781:⁡ 753:∑ 730:⁡ 685:for each 627:=1, ..., 508:⋯ 401:⋯ 343:=1, ..., 314:− 149:⁡ 37:portfolio 1841:(1987). 1780:See also 47:of some 33:optimize 1897:2351447 982:Utility 347:). So: 139:Utility 1895:  1853:  1694:where 555:where 426:where 25:assets 1893:JSTOR 212:) be 1851:ISBN 1737:ARMA 949:The 1963:hdl 1955:doi 1885:doi 1265:. 1990:: 1977:). 1961:. 1949:. 1891:. 1881:41 1879:. 1830:^ 778:ln 727:ln 146:ln 1971:. 1965:: 1957:: 1951:3 1899:. 1887:: 1859:. 1696:U 1679:, 1676:) 1671:T 1667:R 1658:2 1654:R 1648:1 1644:R 1638:0 1634:W 1630:( 1627:U 1623:E 1619:= 1616:) 1611:T 1607:W 1603:( 1600:U 1596:E 1557:. 1554:] 1549:a 1544:T 1540:R 1531:a 1526:2 1522:R 1513:a 1508:1 1504:R 1500:[ 1496:E 1487:a 1482:0 1478:W 1471:a 1423:. 1418:a 1413:t 1409:R 1404:E 1393:a 1389:a 1372:; 1367:a 1362:T 1358:R 1353:E 1344:a 1339:2 1335:R 1330:E 1321:a 1316:1 1312:R 1307:E 1298:a 1293:0 1289:W 1282:a 1263:t 1244:t 1241:n 1237:r 1231:t 1228:n 1224:w 1220:+ 1214:+ 1209:t 1206:2 1202:r 1196:t 1193:2 1189:w 1185:+ 1180:t 1177:1 1173:r 1167:t 1164:1 1160:w 1156:= 1151:t 1147:R 1120:, 1117:] 1112:a 1107:T 1103:R 1094:a 1089:2 1085:R 1076:a 1071:1 1067:R 1063:[ 1059:E 1050:a 1045:0 1041:W 1034:a 1021:a 1002:a 997:T 993:W 989:a 986:= 935:t 927:t 911:t 908:i 904:w 880:. 877:] 872:t 869:n 865:r 859:t 856:n 852:w 848:+ 842:+ 837:t 834:2 830:r 824:t 821:2 817:w 813:+ 808:t 805:1 801:r 795:t 792:1 788:w 784:[ 774:E 768:T 763:1 760:= 757:t 749:+ 746:] 741:0 737:W 733:[ 702:T 698:W 687:t 671:t 667:R 644:T 640:W 629:n 625:i 623:( 609:t 606:i 602:w 591:t 587:i 571:t 568:i 564:r 540:, 535:t 532:n 528:r 522:t 519:n 515:w 511:+ 505:+ 500:t 497:2 493:r 487:t 484:2 480:w 476:+ 471:t 468:1 464:r 458:t 455:1 451:w 447:= 442:t 438:R 409:T 405:R 396:2 392:R 386:1 382:R 376:0 372:W 368:= 363:T 359:W 345:n 341:i 339:( 337:i 333:t 317:1 311:t 307:W 284:t 281:i 277:w 254:t 250:R 230:. 225:t 221:R 210:t 190:0 186:W 162:, 157:T 153:W 143:= 116:, 111:T 107:W

Index

investable
assets
financial assets
optimize
portfolio
financial risk
expected value
concave function
expected utility
goods and services
consumption
Stochastic programming § Multistage portfolio optimization
time period
log utility
stochastic
first-order conditions
Kelly criterion
power utility function
constant relative risk aversion
Hyperbolic absolute risk aversion
von Neumann-Morgenstern utility functions
conditional probability distributions
dynamic programming
Dollar cost averaging
exponential utility
ARMA
serial correlation
Merton's portfolio problem
Robert C. Merton
continuous time

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