Part I: Decision Making Under Uncertainty 1
Section A. Arbitrage and Asset Pricing 3
1. Ross, SA (1976). The arbitrage theory of capital asset pricing.
Journal of Economic Theory, 13(3), 341–360. 11
2. Schachermayer, W (2010a). The fundamental theorem of asset pricing.
In R Cont (Ed.), Encyclopedia of Quantitative Finance, 2, 792–801.
New York: Wiley. 31
3. Schachermayer, W (2010b). Risk neutral pricing. In R Cont (Ed.),
Encyclopedia of Quantitative Finance, 4, 1581–1585. New York: Wiley. 49
4. Kallio, M and WT Ziemba (2007). Using Tucker’s theorem
of the alternative to provide a framework for proving basic arbitrage
results. Journal of Banking and Finance, 31, 2281–2302. 57
Section B. Utility Theory 79
5. Fishburn, P (1969). A general theory of subjective probabilities
and expected utilities. Annals of Mathematical Statistics, 40(4),
1419–1429. 87
6. Kahneman, D and A Tversky (1979). Prospect theory:
An analysis of decisions under risk. Econometrica, 47(2), 263–291. 99
7. Levy, M and H Levy (2002). Prospect theory: Much ado about
nothing? Management Science, 48(10), 1334–1349. 129
8. Wakker, PP (2003). The data of Levy and Levy (2002) “Prospect
theory: Much ado about nothing?” Actually support prospect theory.
Management Science, 49(7), 979–981. 145
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9. Levy, M and H Levy (2004). Prospect theory and mean-variance
analysis. Review of Financial Studies, 17(4), 1015–1041. 149
10. Baltussen, G, T Post and PV Vliet (2006). Violations of cumulative
prospect theory in mixed gambles with moderate probabilities.
Management Science, 52(8), 1288–1290. 177
11. Kreps, DM and EL Porteus (1979). Temporal von
Neumann–Morgenstern and induced preferences.
Journal of Economic Theory, 20(1), 81–109. 181
12. Epstein, LG and SE Zin (1989). Substitution, risk aversion
and the temporal behavior of consumption and asset returns:
A theoretical framework. Econometrica, 57(4), 937–969. 207
13. Rabin, M (2000). Risk aversion and expected-utility theory:
A calibration theorem. Econometrica, 68(5), 1281–1292. 241
14. Machina, M (2004). Non-expected utility theory.
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of Actuarial Science, 2, 1173–1179. New York: Wiley. 253
15. Tversky, A and D Kahneman (1974). Judgment under uncertainty:
Heuristics and biases. Science, 185(4157), 1124–1131. 261
16. Kahneman, D and A Tversky (1984). Choices, values, and frames.
American Psychologist, 39(4), 341–350. 269
Section C. Stochastic Dominance 279
17. Hanoch, G and H Levy (1969). The efficiency analysis of choices
involving risk. Review of Economic Studies, 36(3), 335–346. 287
18. Levy, H (1973). Stochastic dominance, efficiency criteria,
and efficient portfolios: The multi-period case.
American Economic Review, 63(5), 986–994. 299
Section D. Risk Aversion and Static Portfolio Theory 309
19. Pratt, JW (1964). Risk aversion in the small and in the large.
Econometrica, 32(1–2), 122–136. 317
20. Li, Y and WT Ziemba (1993). Univariate and multivariate measures of
risk aversion and risk premiums. Annals of Operations Research, 45,
265–296. 333
21. Chopra, VK and WT Ziemba (1993). The effect of errors in means,
variances, and co-variances on optimal portfolio choice.
Journal of Portfolio Management, 19, 6–11. 365
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22. Ziemba, WT, C Parkan and R Brooks-Hill (1974). Calculation
of investment portfolios with risk free borrowing and lending.
Management Science, 21(2), 209–222. 375
23. Kallberg, JG and WT Ziemba (1983). Comparison of alternative
utility functions in portfolio selection problems.
Management Science, 29(11), 1257–1276. 389
24. Li, Y and WT Ziemba (1989). Characterizations of optimal
portfolios by univariate and multivariate risk aversion.
Management Science, 35(3), 259–269. 409
25. Ziemba, WT (1975). Choosing investment portfolios when the returns
have stable distributions. In WT Ziemba and RG Vickson (Eds.),
Stochastic Optimization Models in Finance, 243–266. San Diego:
Academic Press. 421
26. MacLean, LC, ME Foster and WT Ziemba (2007). Covariance
complexity and rates of return on assets. Journal of Banking
and Finance, 31(11), 3503–3523. 445
27. Rabin, M and RH Thaler (2001). Anomalies: Risk aversion.
Journal of Economic Perspectives, 15(1), 219–232. 467
Part II: From Decision Making to Measurement
and Dynamic Modeling 481
Section E. Risk Measures 483
28. Geyer, A and WT Ziemba (2008). The innovest Austrian
pension fund planning model InnoALM. Operations Research,
56(4), 797–810. 491
29. Rockafellar, RT and WT Ziemba (2000). Modified risk measures and
acceptance sets. 505
30. F¨
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law-invariance and beyond, asymptotics for large portfolios. 507
31. Krokhmal, P, M Zabarankin and S Uryasev (2011). Modeling and
optimization of risk. Surveys in Operations Research
and Management Science, 16(2), 49–66. 555
Section F. Dynamic Portfolio Theory and Asset Allocation 601
32. Edirisinghe, C, X Zhang and S-C Shyi (2012). DEA-based firm
strengths and market efficiency in US and Japan. 611
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33. MacLean, LC and WT Ziemba (2012). The Kelly strategy for
investing: Risk and reward. 637
34. Browne, S (1999a). Reaching goals by a deadline: Digital options
and continuous-time active portfolio management.
Advances in Applied Probability, 31, 551–577. 683
35. Browne, S (1999b). Beating a moving target: Optimal portfolio
strategies for outperforming a stochastic benchmark.
Finance and Stochastics, 3, 275–294. 711
36. Browne, S (2000). Stochastic differential portfolio games.
Journal of Applied Probability, 37(1), 126–147. 731
37. Davis, M, and S Lleo (2012). Fractional Kelly strategies in continuous
time: Recent developments. 753
38. Bahsoun, W, IV Evstigneev and MI Taksar (2012). Growth-optimal
investments and numeraire portfolios under transactions costs. 789
39. Campbell, JY, YL Chan and LM Viceira (2003). A multivariate
model of strategic asset allocation. Journal of Financial Economics,
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40. Thorp, EO, and Mizusawa, S (2012). Maximizing capital growth with
black swan protection.