FINANCE AND THE BEHAVIORAL PROSPECT Risk, Exuberance, and Abnormal Markets JAMES MING CHEN Quantitative Perspectives on Behavioral Economics and Finance Series Editor James Ming Chen College of Law Michigan State University East Lansing, Michigan, USA Aims of the Series The economic enterprise has firmly established itself as one of evaluating human responses to scarcity not as a rigidly rational game of optimization, but as a holistic behavioral phenomenon The full spectrum of social sciences that inform economics, ranging from game theory to evolutionary psychology, has revealed the extent to which economic decisions and their consequences hinge on psychological, social, cognitive, and emotional factors beyond the reach of classical and neoclassical approaches to economics Bounded rational decisions generate prices, returns, and resource allocation decisions that no purely rational approach to optimization would predict, let alone prescribe Behavioral considerations hold the key to longstanding problems in economics and finance Market imperfections such as bubbles and crashes, herd behavior, and the equity premium puzzle represent merely a few of the phenomena whose principal causes arise from the comprehensible mysteries of human perception and behavior Within the heterodox, broad-ranging fields of behavioral economics, a distinct branch of behavioral finance has arisen Finance has established itself as a distinct branch of economics by applying the full arsenal of mathematical learning on questions of risk management Mathematical finance has become so specialized that its practitioners often divide themselves into distinct subfields Whereas the P branch of mathematical finance seeks to model the future by managing portfolios through multivariate statistics, the Q world attempts to extrapolate the present and guide risk-neutral management through the use of partial differential equations to compute the proper price of derivatives The emerging field of behavioral finance, worthy of designation by the Greek letter psi (ψ), has identified deep psychological limitations on the claims of the more traditional P and Q branches of mathematical finance From Markowitz’s original exercises in mean-variance optimization to the Black-Scholes pricing model, the foundations of mathematical finance rest on a seductively beautiful Gaussian edifice of symmetrical models and crisp quantitative modeling When these models fail, the results are often catastrophic The ψ branch of behavioral finance, along with other “postmodern” critiques of traditional financial wisdom, can guide theorists and practitioners alike toward a more complete understanding of the behavior of capital markets It will no longer suffice to extrapolate prices and forecast market trends without validating these techniques according to the full range of economic theories and empirical data Superior modeling and data-gathering have made it not only possible, but also imperative to harmonize mathematical finance with other branches of economics Likewise, if behavioral finance wishes to fulfill its promise of transcending mere critique and providing a more comprehensive account of financial markets, behavioralists must engage the full mathematical apparatus known in all other branches of finance In a world that simultaneously lauds Eugene Fama’s efficiency hypotheses and heeds Robert Shiller’s warnings against irrational exuberance, progress lies in Lars Peter Hansen’s commitment to quantitative rigor Theory and empiricism, one and indivisible, now and forever More information about this series at http://www.springer.com/series/14524 James Ming Chen Finance and the Behavioral Prospect Risk, Exuberance, and Abnormal Markets James Ming Chen College of Law Michigan State University East Lansing, Michigan, USA Quantitative Perspectives on Behavioral Economics and Finance ISBN 978-3-319-32710-5 ISBN 978-3-319-32711-2 (eBook) DOI 10.1007/978-3-319-32711-2 Library of Congress Control Number: 2016950218 © The Editor(s) (if applicable) and The Author(s) 2016 The author(s) has/have asserted their right(s) to be identified as the author(s) of this work in accordance with the Copyright, Designs and Patents Act 1988 This work is subject to copyright All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made Cover illustration © TongRo Images / Alamy Stock Photo Printed on acid-free paper This Palgrave Macmillan imprint is published by Springer Nature The registered company is Macmillan Publishers Ltd London To Heather Elaine Worland Chen, with all my love ACKNOWLEDGMENTS This book incorporates ideas from papers I have presented at the University of Cincinnati, Florida State University, Georgetown University, Michigan State University, the University of Pennsylvania, the University of Virginia, and the Faculty of Economics of the University of Zagreb (Ekonomski Fakultet, Sveučilište u Zagrebu) The International Atlantic Economic Society and the ACRN Oxford Academic Research Network have provided multiple platforms for the work underlying this book Along the way, I have benefited from scholarly and professional interactions with Anna Agrapetidou, Abdel Razzaq Al Rababa’a, Moisa Altar, Christopher J. Brummer, Irene Maria Buso, Adam Candeub, Seth J. Chandler, Felix B.  Chang, Tendai Charasika, César Crousillat, David Dixon, Robert Dubois, John F.  Duffy, Daniel A.  Farber, Christopher C.  French, Santanu K.  Ganguli, Tomislav Gelo, Periklis Gogas, Gil Grantmore, Andy Greenberg, Losbichler Heimo, Hemantha Herath, Jesper Lyng Jensen, Jagoda Kaszowska, Daniel Martin Katz, Yuri Katz, Imre Kondor, Carolina Laureti, Cordell Lawrence Jr., Cordell Lawrence Sr., Matthew Lee, Othmar Lehner, Heimo Losbichler, Gerry Mahar, Milivoj Marković, L.  Thorne McCarty, Steven C.  Michael, Ludmila Mitkova, José María Montero Lorenzo, Kevin Lynch, Laura Muro, Vivian Okere, Merav Ozair, Elizabeth Porter, Mobeen Ur Rehman, Carol Royal, Bob Schmidt, Jeffrey A. Sexton, Galen Sher, Ted Sichelman, Jurica Šimurina, Nika Sokol Šimurina, Robert Sonora, Lisa Grow Sun, Elvira Takli, Peter Urbani, Robert R.M. Verchick, Benjamin Walther, Karen Wendt, Gal Zahavi, and Johanna F.  Ziegel Christian Diego Alcocer Argüello of Michigan State University’s Department of Economics provided very capable research ix INDEX bifurcation, 75, 76, 103 and Bowman’s paradox, 2, 73–5, 226 cash-flow beta (“bad” beta), 98–103 correlated relative volatility, 77 defined, 82 discount-rate beta (“good” beta), 98–103 and emerging markets, 79, 80, 101 generally, 2, 11, 58–60, 76, 82, 83, 93, 98, 303, 306 and growth stocks, 73, 98–102, 226 high- and low-beta portfolios, 74, 82 single-sided, 79 and value stocks, 73, 74, 98–102, 226 Bhutan, 38 biology and medicine agriculture, 323 ants, 312 biotechnology, 37, 268 blood glucose, brain damage, 13 epidemiology, 323 evolution, 34, 35, 139, 323 infections, 312 magnetic resonance imaging, 220 neuroscience, 323 pigeons, 184, 215 polar bears, 41 punctuated equilibria, 139 unicorns (fallacious medical diagnoses), 30, 153, 173n155 biotechnology, 37, 268 Black, Fischer, 22n79, 22n80, 67n2, 109n12, 158, 178n215, 297n53 Black-Scholes pricing model, 94 bonds generally, 3, 125, 138, 141, 213, 216, 228, 229, 260 liquidity risk, 309 momentum, 304, 306, 309, 315n35 paired with lottery-like investments (“bonds-and-bullets” portfolios), 260, 269 329 performance relative to stocks, 288 sovereign debt default, 153 term structure, 11 treasury bills and notes, 125, 140 Born, Max, 326n14 Boston College, 142 Bowie, David, 154 Bowman, Edward H., 74, 86n20, 86n21, 269 See also Bowman’s paradox Bowman’s paradox and prospect theory, 75, 181, 223–8, 253 and SP/A theory, 4, 67, 181, 248–50, 253–5, 257, 258, 269 Bradley, Brendan, 82, 85n8 brain damage, 13 Brazil, 79 Buffett, Warren, 14, 27n132 C calendar anomalies generally, 7, 11, January effect, 7, 19n39, 293, 299n83 “sell in May and go away”, 6–7, 11 and storytelling, 12 Campbell, John Y., 17n5, 17n7, 91n91, 91n92, 93, 98, 100–3, 105n25, 107n47, 108n48, 109n70, 109n71, 133n68, 151, 152, 165n57, 168n90, 168n103, 172n145, 237n87, 293n9 Canada, 7, 41, 287 capital allocation line, 119, 131 capital asset pricing model (CAPM) and beta, 2, 11, 57–60, 74, 76, 79, 93, 96, 98–103, 226, 303 and consumption smoothing, 95 contrasted with models of behavioral finance, 250 criticism, 67, 260 330 INDEX capital asset pricing model (CAPM) (cont.) and the equity premium puzzle, 1, 3, 95, 137, 143, 144, 148, 152, 153, 155 and the equity risk premium, 3, 137, 143, 144, 148, 152, 153, 155 four-moment (higher-moment) CAPM, 57, 60–7, 76, 97, 116, 203, 222, 247, 250 generally, 1, 57–60, 93, 95–100, 137, 222, 226, 250 and initial public offerings (IPOs), 3, 203, 222 intertemporal CAPM, 67, 76, 93–8, 102, 103, 148, 158, 230 unobservability (Roll’s critique), 96, 155 capital gains, 95, 289, 291–3, 298n78, 308 CAPM See capital asset pricing model Carhart, Mark M., 97, 303, 314n25 See also factor models, momentum carry trade, 310 “catastrophe of success”, 214, 314n16 catching up with the Joneses, 151, 152, 156 See also Abel, Andrew B.; lagged consumption Catholic Church, 220 CBOE See Chicago Board Options Exchange (CBOE) Chen, Joseph, 81, 83, 85n10, 90n81, 91n86 Chen, Zhanhui, 83, 92n108, 102, 103, 104n1 Chicago Board Options Exchange (CBOE), 77 Chile, 79 China, 153 cognitive biases affect heuristic, 5, 11, 31, 41, 293, 325 certainty effect, 126, 183, 202, 203 cognitive dissonance, 305 discounting (exponential, hyperbolic, etc.), 99, 147 disposition effect, 213, 283–6, 292, 304, 308, 312 endowment effect, 29, 149, 187 framing effects, 197, 205 generally, 11, 17, 41, 302, 305, 325 house money effect, 230 loss aversion, 185–9, 198, 201, 228–31, 308 myopic loss aversion, 228–9, 231, 308 narrow framing, 231, 283 projection bias, 97, 150 rank effect, rankings, 31 realization utility, 185, 285, 309 reflection effect, 183, 184 status quo bias, 185 colleges and universities Boston College, 142 Cornell University, 187 university endowments, 157–60, 308 Yale University, 157 commodities markets, 157, 304, 306 concentration (of assets or portfolios), 5, 225, 286 See also diversification conglomerates, 218 conspicuous consumption, 151 Constantinides, George M., 20n40, 133n68, 149–52, 169n106, 172n139, 174n168, 174n170, 174n171, 299n82 constant relative risk aversion (CRRA), 117, 118, 128, 144, 149, 264 consumption smoothing, 95, 154, 158 contagion, 78, 302, 309, 310, 324 Cornell University, 187 corporate distress, 73 corporate social responsibility (CSR), 36 INDEX corporate spin-offs, 218 correlation correlation risk, 78, 80–5, 92n114, 102 correlation tightening, 77–80, 82, 83, 101, 102 disregard, 30, 225, 324 and emerging markets, 78–80, 101, 304 between financial and labor income, 154, 219 in global markets, 157 single-sided (downside), 79, 84, 120 Corzine, Jon, 203 countercyclicality, 155 covariance, 30, 145, 221 crashes and crises financial crisis of 2008-09, 157, 158 stock market crash of 1929, 302 stock market crash of 1987, 82 technology bubble of 2000, 158 crowdfunding, 13, 217, 218 CRRA See constant relative risk aversion (CRRA) cumulative distribution function (CDF), 120, 128, 189–91, 193–7, 250, 266, 267 See also decumulative distribution function cumulative prospect theory, 187, 196–8, 200, 214, 222, 224, 228, 251, 254, 308 cyclicality risk, 155 D Dalbar (financial analytics firm), 287–9 Dándolos, Níkos (Nick the Greek), 252 “death and jackpot” (bankruptcy risk), 219 death anxiety, 214 331 decision weights, 126, 197, 205, 251 decumulative distribution function, 257 See also cumulative distribution function de la Fontaine, Jean, 41, 55n147, 56n149, 156 developed markets, 78–80, 90n68, 109n83 Dichev, Ilia D., 238n88, 287, 296n44, 296n49, 298n74 disaster relief, 29, 54n131 discount brokerages, 292 See also individual investors discounting (exponential, hyperbolic, etc.), 43, 99, 147 disposition effect, 213, 283, 284–6, 292, 304, 308, 312 distributions, statistical extreme value, 66, 257 Fisk (log-logistic), 189 Gaussian (normal), 64, 193, 266, 267, 310, 323 lognormal, 146, 148, 151, 166n75, 171n133, 193–6, 208n81, 209n83 stable Paretian, 118, 131n36 diversification, 14, 31, 77, 78, 81, 82, 87n40, 102, 154, 156, 158, 213, 216, 219, 225, 286, 304 See also concentration (of assets or portfolios); retirement and retirement savings-failure to diversify dividends, 14, 95, 99, 139, 140, 145, 218, 230, 289, 291, 292, 303, 311, 312 Driessen, Joost, 84, 91n88, 92n113–15 dumb money, 287, 288, 302, 311, 312 See also noise, noise trading 332 INDEX E econophysics, 46n30, 323 efficient frontier, 2, 31, 94, 157, 216, 260, 261, 295n30 efficient markets hypothesis, 5, 7, 11, 247 Einstein, Albert, 326n14 emerging markets and capital asset pricing model (CAPM), 79, 101, 109n83 and correlation tightening, 78–80 Endangered Species Act, 42 endowment effect, 29, 149, 187 endowment hoarding, 159 endowment model of investing, 87n40, 157 environmental economics, 2, 31, 38–42 environmental, social, and governancerelated (ESG) corporate practices, 37 Epstein, Larry G., 146–7, 167n80 equity crowdfunding, 217, 218 equity premium puzzle, 1, 3, 95, 111, 117, 137–79, 181, 207n66, 213, 228–9, 231 and prospect theory, 184, 255, 304 risk-free rate puzzle, 148 equity risk premium, 3, 111, 137–79, 228, 230, 231, 244n202 escalation of commitment (to losing strategies), 204, 212n154, 227 Estrada, Javier, 63, 64, 70n33, 70n43, 70n45, 71n61, 79, 80, 83, 85n15, 90n75, 90n77, 90n81, 101–3, 243n176 ETFs See exchange-traded funds (ETFs) Europe, 23n96, 216, 235n40 evolutionary economics and finance, 34, 264 Excel (spreadsheet software), 291 exchange-traded funds (ETFs), 231, 268, 298n64 expected utility theory, 3, 111, 122, 123, 125–7, 182–4, 185, 197, 213, 223, 247, 249, 254, 258 F factor models Fama-French-Carhart four-factor model (size, value and momentum), 97, 100, 226, 303 Fama-French three factor model (size and value), 97, 303 fads, 222, 311 Fama, Eugene F., 1, 7, 19n38, 58, 68n2, 68n5, 68n8, 90n81, 97, 98, 107n42, 118, 131n33, 131n34, 295n36, 303, 314n22, 315n27 See also factor models; French, Kenneth R family-owned firms, 227, 244n189 “fast” vs “slow” thinking, Faulkner, William, 253, 273n80 Federal Reserve System, 141, 142, 203, 301, 313n2 federal securities law See also Securities and Exchange Commission (SEC) accredited investors, 217 equity crowdfunding, 217–18 exchange-traded funds (ETFs), 298n64 fraud on the market, Investment Company Act of 1940, 289 Jump Our Business Startups Act of 2012 (JOBS Act), 217–18 mutual funds, 288 Regulation D, 217, 218, 236n50 structured securities, 106–7n33 INDEX federal tax law capital gains and losses, 292, 298n78, 308 mortgage interest deduction, 163n41 tax loss harvesting, 292, 293, 299n81, 299n83 tax-sheltered retirement and educational savings accounts, 150 Fiegenbaum, Avi, 86n30, 224–6, 241n138, 241n141, 244n193 financial crisis of 2008-09, 82, 157, 158 financial (il)literacy, 142, 216, 234n36 Fishburn, Peter C., 128n4, 132n60, 206n24, 207n48–9, 224, 242 foreign exchange, 90n68, 102, 134n74 carry trade, 310 four-moment (higher-moment) CAPM, 57, 60, 67, 76, 97, 116, 203, 250 France, 80, 139, 140 fraud on the market, French, Kenneth R., 1, 19n35, 68n2, 68n5, 97, 174n164, 295n36, 295n37, 303, 314n22–3, 315n27 See also factor models; Fama, Eugene F Friedman–Savage utility function, 123, 124, 126 Friesen, Geoffrey C., 296n43 fundamental vs technical analysis, 307–8 future consumption utility, 229 G Galbraith, John Kenneth, 24n109, 278n191, 302, 313n3 gambling and gamblers See also lotteries, lottery tickets and lottery-like investments; risk seeking behavior 333 gambler's ruin, 127, 264 house money effect, 230 Kelly criterion, 13, 25n116, 135n83 and SP/A theory, 4, 67, 254, 255, 257, 259 Gaussian mathematics See distributions, statistical-Gaussian (normal) GDP See gross domestic product (GDP) general equilibrium models, 94, 149, 169n103 Germany, 80, 139, 140, 174n164 goal-oriented investing, 32, 33 Graham, John, 138 Great Britain, 80, 139, 140, 174n164, 216, 287 Greenspan, Alan, 301, 313n2 Grizzard, Lewis, 207n55 gross domestic product (GDP), 38, 100, 284 growth stocks, growth investment styles, 73, 74, 98–102, 152, 226 H habit formation, 149–52, 155, 156, 158, 160 HARA See hyperbolic absolute risk aversion (HARA) Harvey, Campbell R., 69n25, 70n42, 89n57, 89n64, 90n68, 138, 161n12, 176n190, 179n231, 315n34 Haugen, Robert A., 74, 85n13, 85n15 hedge funds and hedge fund managers, 287, 301, 302 Heins, A. James, 74, 85n13 herding behavior, 302 heterogeneity, 4, 16, 222, 307–10 higher-moment CAPM, 60, 222, 247 high-frequency trading, 8, 9, 11 334 INDEX hoarding behavior (by endowments), 159 home bias (preference for domestic stock), 156, 157 household portfolios, 133n68, 151, 172n144, 175n178 housing See real estate Huang, Ming, 43n11, 162n30, 210n117, 229–31, 240n121, 244n202, 246n238, 246n245 human capital and human capital risk, 38, 51n102, 96, 154 hyperbolic absolute risk aversion (HARA), 2, 65, 115–18, 128, 132n58, 147, 182 See also risk aversion—quadratic utility I ideal gas law, 248, 270n13 idiosyncratic risk, 81, 82, 84 Iksil, Bruno (“London Whale”), 203 implied volatility, 77 independence axiom, 126 See also Friedman–Savage utility function indexing, index funds, 199, 283 individual companies, by stock symbol Aetna (AET), 8, 10 Anthem/WellPoint (WLP), 8, 10 Humana (HUM), 8, 10 J.P. Morgan Chase (JPM), 203 Myriad Genetics (MYGN), 8, 10 individual investors, 9, 32, 97, 98, 140, 153, 156, 157, 178n213, 213, 219, 231, 283, 284, 286, 288, 303, 308, 309 information trading, informed trading, 11, 288, 302 initial public offerings (IPOs), 3, 13, 37, 51n97, 203, 220–2, 240n120, 269 institutional investing and investors, 2, 30–2, 77, 100, 157, 158, 219, 308 insurance, 8, 47n56, 82, 95, 96, 114–15, 124, 143, 154, 166n66, 182, 183, 196, 197, 202, 204, 249, 261, 278n186 internal rate of return (IRR), 285, 289–92 secant method, 290 intertemporal capital asset pricing model, 2, 93–109 intertemporal substitution, 147 investment gap (between hypothetical and actual returns), 287–8, 302 investor return, 1, 4, 182, 283–99 IPOs See initial public offerings (IPOs) irrational exuberance, 1, 301–22 Islamic finance, 36, 49n84 J Japan, 139, 140, 174n169, 304 K Kahneman, Daniel, 5, 18n11, 18n27, 26n122, 27n128, 43n4, 45n21, 52n115, 53n116, 127, 135n90, 169n108, 182, 183, 185, 187, 188, 196, 197, 199–204, 205n2–3, 207n52, 207n58, 207n68, 214, 230, 232, 249, 261, 270n3, 324 See also “fast” and “slow” thinking; prospect theory; System and System modes of thought; Tversky, Amos Kaplan, Paul D., 120, 131n50, 295n31 kappa, 119–22 Keating, Con, 120, 132n51 INDEX Kelly criterion (Kelly, J.L.), 13, 25n116, 135n83 Keynes, John Maynard, 13, 25n117, 77, 88n49, 107n45 Knowles, James A., 120, 131n50, 132n52, 132n56 Kochenberger, Gary A., 206, 224, 242 Kocherlakota, Narayana R., 148, 161n9, 167n77 Kronecker delta function, 187, 208n69 kurtosis, 1, 57, 61, 63–7, 222, 247 kurtosis preference, 263 L lagged consumption, 152 Las Vegas, 253 "law on the market," 7–11, 21n55 Leeson, Nick, 203, 211n146 leverage, leverage effects, 151 L'Hôpital's rule (L'Hôpital, Guillaume de), 117 life-cycle model, 95, 133n72, 154 linguistics, 139, 325 Lintner, John, 58, 68n2, 130n27 liquidity, 8, 78, 79, 94, 109n83, 125, 260, 307–10, 312, 320n92 funding vs market liquidity, 307 liquidity preference, 94 (see also (Tobin, James)) liquidity risk, 307–10 logarithmic (log) returns, 2, 62, 63, 250, 289 “London whale” (Iksil, Bruno), 203 Longin, Franỗois, 80, 91n82 Long-Term Capital Management, 203, 204, 211n147 Lopes, Lola L., 47n55, 132n58, 248, 249, 270n4, 270n7, 270n14, 271n21, 271n23–5, 271n30, 271n33, 271n34, 271n39–41, 335 271n43, 272n58–60, 272n62, 272n63, 272n65, 272n66, 272n72, 272n76, 273n75, 273n77, 273n81, 273n96, 273n98, 274n106, 275n131, 275n133, 276n141, 276n145, 276n146, 278n187, 278n192, 279n198, 279n199, 325n2, 326n11 loss aversion, 185–9, 198, 201, 207n66, 210n115, 228–31, 298n76 lotteries, lottery tickets and lottery-like investments, 35, 66, 124, 133n66, 196, 203, 213–21, 234n34, 235n41, 249, 250, 252, 260, 261, 263, 269, 271n33, 278n186, 281n248, 281n249 See also prospect theory— xskewness preference lottery bonds, 216 low-volatility anomaly, 1–3, 37, 73–93, 98, 101–3, 148, 223, 225–8, 230, 253 M Maclaurin series (Maclaurin, Colin), 70n31 macroeconomics and distorted savings, 151 and financial risk aversion, 214 generally, 8, 9, 78, 99, 100, 143, 150, 151, 155, 304 and the life cycle model, 150, 155 and momentum, 100, 304, 316n40 Maenhout, Pascal J., 84, 91n88, 92n113–15 magnetic resonance imaging (MRI), 220 Mandelbrot, Benoit B., 118, 130n30, 131n32, 131n33, 131n35 336 INDEX marathons and marathon runners, 30, 43n12 market timing, 286 Markham, Edwin, 42, 56n155 Markowitz, Harry M., 47n42, 47n44–6, 47n50, 47n56, 124, 127, 128, 130n28, 131n46, 132n64, 133n66, 169n104, 169n105, 184, 206n30, 255, 256, 265, 271n29, 271n38, 274n111, 277n165, 278n183, 279n212–14, 280n227, 280n229 Marshall-Arrow-Romer (MAR) spillovers, 243n180 martingale, 127, 135n85 Maslow, Abraham H., 32–6, 46n34, 48n62, 48n70, 48n75 Maslowian portfolio theory hierarchy of needs, 33, 34, 261 self-actualization, 35–8 mathematics, 42, 46n30, 70n31, 87n40, 129n12, 248, 269 mean-variance optimization, 32, 60, 69n10, 78, 98, 152, 259, 260, 264, 265, 284 Mehra, Rajnish, 70n37, 107n33, 130n26, 137–40, 144–9, 151, 158, 160, 160n5–8, 161n13, 162n21, 162n27, 166n68, 166n70–2, 166n74–7, 167n79, 167n86–9, 168n96, 169n109, 170n111–14, 171n129–31, 172n138, 172n146, 173n152, 174n170, 174n174, 175n175, 175n178, 177n199, 244n102 mental accounting, 1, 17, 29–57, 151, 202, 260, 264, 304, 324 Merton, Robert C., 22n80, 24n100, 24n101, 69n17, 93, 94, 97, 98, 104n1, 104n2, 104n9, 105n15, 105n21, 107n34, 129n18, 129n20–2, 133n72, 153, 158, 173n156, 178n217, 245n209, 295n32, 321n115 See also intertemporal capital asset pricing model Mexico, 79 MF Global, 203 modern portfolio theory, 1, 3, 4, 7, 11, 13, 16, 31, 32, 94, 98, 141, 226, 247, 248, 250, 256, 259–61, 264, 324, 326n10 moments-based models, 250 momentum, 1, 4, 36, 79, 97, 100, 108n65, 182, 213, 226, 230, 243n176, 301–22 See also factor models—Fama-French-Carhart four-factor model (size, value and momentum) behavioral explanations, 306 momentum crashes, 182, 301–22 moral hazard, 154 Morningstar (ratings firm), 287–9, 296n42 mortgages See also real estate continuous workout mortgages, 154, 174n167 impact on stock market participation, 141, 142 reverse mortgages, 142 and risk aversion, 154 subprime, 309 multiple discovery, 12, 24n100 mutual funds capital structure, 297n64 closed-end funds, 222 ethically conscious funds, 36 fund flows, 296n43, 296n51, 297n52 generally, 7, 36, 49n83, 94, 231, 283, 284, 286–9, 297n64 and investment gaps, 287–8 two mutual fund theorem, 2, 32 (see also (separation theorem; Tobin, James)) and value investing, 36, 73, 289 INDEX myopic loss aversion, 210n115, 228–9, 231, 298n76, 308 mythology and storytelling, 12, 40, 139 N naïve asset allocation (1/n), 31 narrow framing, 231 NASDAQ, 287 National Bureau of Economic Research (NBER), 160, 168n90, 179n235, 234n36, 235n49, 321n113 NBER See National Bureau of Economic Research net asset value (NAV), 287, 289–92 net present value (NPV), 43n5, 290, 291 New York Stock Exchange (NYSE), 287, 289 Nobel Prizes economics, 182, 205n2, 253, 303 literature, 253, 314n15 noise, noise trading, 288, 297n52, 297n54, 302, 309, 310, 316n42 noisy markets hypothesis, 22n79 Norway, 156 NYSE See New York Stock Exchange (NYSE) O “Obamacare” (Affordable Care Act), 8, 21n66 O'Connor, Flannery, 310, 321n114 Odean, Terrence, 22n74, 26n126, 44n16, 88n48, 176n197, 233n10, 285, 293n6, 294n22–4, 296n39, 297n53, 297n60, 298n75–7, 299n81, 303, 314n17, 317n46, 317n60 omega, 86n22, 120, 121, 132n55, 248 337 optimism and pessimism, 15, 34, 156, 213, 214, 263, 308, 309 options pricing, 22n80, 81, 96, 101, 106n33, 185, 319n85 overconfidence sex-based differences, 14 over-the-counter (OTC) stocks, 219, 238n93 P Panel Study of Income Dynamics, 140 paradoxes and puzzles See also anomalies Allais paradox, 122–6 contrasted with normal science, equity premium puzzle, 3, 137–79, 181, 228–9 low-volatility anomaly, 1–3, 37, 73–92, 223, 225–8 risk-free rate puzzle, 148 St Petersburg paradox, 122, 126–8 stock market participation puzzle, 140 Pascal, Blaise, 220, 239n103 passive indexing and investment, 284, 286 patent law, pensions, pension funds, and pension managers, 28n150, 100, 140, 143, 157, 158, 178n215, 204, 320 perfect competition, 225 Petkova, Railitsa, 83, 84, 92n108, 92n114, 92n117, 92n119, 92n120, 102, 103, 104n1, 109n79, 109n82 pharmaceutical industry, 226 physical perception, 184 pigeons, 184, 215, 233n26, 234n27 polar bears, 41, 56n153 postmodern portfolio theory, 17n1, 18n11, 49n83, 131n48, 202, 281n237, 281n249, 306, 314n16, 321n114, 323 338 INDEX Postmodern Portfolio Theory (book), 1, 5, 67, 75, 76, 80, 84, 97, 101, 102, 120, 214, 226, 247, 265, 266 Pratt, John W., 111, 114–15, 129n8, 129n13, 132n61 precautionary saving, 54n127, 150, 158, 172n143, 178n225 Prescott, Edward, 70n37, 130n26, 137, 138, 140, 144–9, 151, 158, 160n4–8, 162n27, 166n68, 166n70–2, 166n74, 166n75–7, 167n79, 167n86, 167n88, 167n89, 168n96, 170n111, 170n113, 170n114, 171n129–31, 172n138, 173n152, 174n174, 175n175, 175n178, 177n199 price-to-book value ratio, 73 See also value factor (book-to-market), value stocks private equity, 44n14, 216, 217 prize-linked savings accounts, 215, 216 probability distribution function (PDF), 61 procyclicality, 148, 310 projection bias, 97, 150, 238n100 prospect theory adaptation level, 184–6, 188, 189, 206n39 and Bowman's paradox, 3, 73–5, 181, 223–8, 253 certainty effect, 183, 203 cumulative prospect theory, 187, 196–8, 200, 210n115, 210n124, 214, 222, 224, 228, 251, 254, 308 descriptive vs normative theory, 204 diminishing sensitivity, 186–9, 196, 201, 203, 257 and the disposition effect, 213, 284–6, 304, 308 and the equity premium puzzle, 3, 105n20, 137–79, 181, 207n66, 213, 228–9, 231 fourfold pattern, 3, 181, 201–5, 211n133, 213, 223, 253, 269 framing effects, 197, 205 gain-loss asymmetry, 201 generally, 3, 4, 67, 75, 128, 156, 181–255, 257, 258, 269, 285, 304, 306, 308, 324 loss aversion, 185–9, 198, 201, 207n66, 210n115, 228–31, 308 lottery (or possibility) effect, 202, 203, 213 and momentum, 4, 213, 226, 230, 243n176, 301–22 nonlinear probabilities, 201 realization utility, 185, 285 reference point, 3, 181, 184–6, 188–91, 196, 223, 225, 232, 252, 254, 257, 285 reflection effect, 183, 184 and skewness preference, 3, 203, 204, 213–20, 222, 231 source dependence, 198 and SP/A theory, 4, 67, 181, 248–50, 253–5, 257, 269 status quo bias, 185 value function, 128, 184–8, 190, 193, 196, 197, 199, 224, 228, 232, 249, 250, 254, 285 weighting function, 15, 197, 198–202, 210n115, 214, 215, 228, 251, 252, 254 psi (ψ), 289 See also investment gap psychology, 18n27, 20n48, 23n87, 24n110, 26n121, 26n122, 28n158, 34, 35, 37, 38, 42, 44n12, 52n115, 53n116, 55n138, 105n2, 142, 149, 215, 220, 221, 248, 253, 260, 289, 302, 324, 325n3, 326n15 INDEX R Rabin, Matthew, 107n43, 126, 134n79, 170n16 random walk, 229 rational expectations hypothesis, 12 real estate See also mortgages and the disposition effect, 285 generally, 39, 96, 125, 133n68, 285 and risk aversion, 125 and speculative bubbles, 311 and stock market participation, 140 wealth effects, 39 recessions, 155, 157 reference point, 3, 30, 77, 181, 184–6, 188–91, 196, 223, 225, 232, 252, 254, 257, 285, 293, 308 relative welfare, 77 religion, 12, 220 retirement and retirement savings defined contribution plans, 16, 140 failure to diversify, 156 and intertemporal CAPM, 97, 98 and life cycle theory, 150 and myopic loss aversion, 228, 229 participant-directed retirement accounts, 15 pensions, pension funds and pension managers, 106n31, 140, 143, 150, 158 retirement planning, 142, 214, 259 retirement preparedness, 142 and risk aversion, 228 and SP/A theory, 259, 260 target-age retirement funds, 229 tax-sheltered retirement accounts (e.g., 401(k)), 150 return on equity, 144–6, 224 reversion to the mean, 162n20, 225 risk aversion absolute, 2, 65, 111–13, 115–19, 123, 132n58, 132n61, 147, 182, 208n72 and the Allais paradox, 122, 126, 183, 198, 249 339 constant relative (CRRA), 117, 128, 149, 264 and consumption smoothing, 149, 152–4 decreasing absolute, 65, 116, 123, 132n61, 208n72 hyperbolic absolute (HARA), 2, 65, 115–18, 132n58, 147, 182 quadratic utility, 182 relative, 94, 111, 114, 117, 128, 146, 147, 149, 264 risk-averse insurance premium, 114, 115 and the St Petersburg paradox, 121, 122, 126 risk-free rate risk-free rate puzzle, 148 risk-free return, 60, 131n48, 145 risk premium See equity premium puzzle; equity risk premium risk-return relationship, 74, 139, 224, 225, 227, 242 See also Bowman's paradox; low-volatility anomaly risk-seeking behavior, 3, 34, 67, 122, 181, 201, 223, 258, 269 See also gambling and gamblers; lotteries, lottery tickets, and lottery-like investments; prospect theory— skewness preference risk tolerance, 47n56, 115, 116, 119, 122, 147, 220, 259 risk, types of default, 253 downside, 13, 39, 82, 120, 121, 137, 202, 214 human capital, 154 idiosyncratic, 81, 82, 84 macroeconomic, 316n40 procyclicality, 148 sequence-of-returns, 96, 155, 264, 276n156 systematic, 36, 73, 76, 80, 96, 143, 226, 227, 306, 321n114 rogue trading, 203 340 INDEX Roll, Richard, 19n38, 19n39, 69n20, 90n68, 108n57, 109n84 Roll's critique, 96, 155 Roy, Arthur D., 274n107–10, 275n120 Roy's safety-first criterion, 254–7, 265 Runyon, Damon, 252 Russia, 153 S SAD See seasonal affective disorder (SAD) safety-first criterion, 254–7, 260, 263, 265 Sagoff, Mark, 41, 56n152 Samuelson, Paul A, 42n3, 127, 128, 130n30, 133n72, 135n89, 135n92, 245n209 Santos, Tano, 229, 230, 240n121, 245n212, 245n217, 245n222, 245n226, 246n227, 246n250 Sapp, Travis R.A., 287, 296n43, 296n45, 296n50, 298n73 Scandinavia, 156 science, history and philosophy of anomalies, 2, 4–6 multiple discovery, 12 normal science, seasonal affective disorder (SAD), 20n48 Securities and Exchange Commission (SEC), 106n33, 217, 218, 289 See also federal securities law security-potential/aspiration theory See SP/A theory semiconductors, 37 separation theorem, 2, 32, 94, 95, 118, 141, 260 sequence of returns risk, 96, 155, 264, 276n156 sex-based differences, 14, 16 Shadwick, William F., 120, 132n51 Sharpe ratio, 60, 119–21, 305 and Roy's safety-first criterion, 254–7 Sharpe, William F., 58, 68n2, 69n16, 69n22, 69n23, 276n157, 279n212, 295n37 See also Sharpe ratio Shefrin, Hersh, 22n79, 23n82, 23n84, 27n133, 45n24, 46n31, 105n19, 132n64, 165n54, 255, 273n93, 274n100, 274n101, 274n115, 275n122, 275n127, 276n147, 277n159, 277n164, 277n168, 277n170, 278n175, 278n180, 278n184, 278n186, 278n196, 279n200, 279n206, 280n215–18, 280n224, 281n249, 284, 293n11, 316n42, 317n48, 317n56, 320n100, 320n103, 322n120 Shiller, Robert J., 23n87, 23n89, 24n108, 24n110, 24n111, 88n49, 88n50, 105n25, 108n60, 109n71, 161n14, 170n125, 174n166, 174n167, 176n188, 240n119, 303, 310, 313n2, 313n3, 314n15, 322n121–4, 322n126–8, 322n133, 322n138, 322n139, 325n3 “short-termism”, 143 Sierra Leone, 263 sigmoid curves, 186, 189 skewness and higher-moment CAPM, 60, 222, 247 negative skewness preference, 204 skewness preference, 3, 35, 71n59, 116, 203, 204, 213–20, 222, 231 small firm factor, small-cap stocks, 99, 100, 102, 226, 286, 303 INDEX smart money, 288, 302, 311, 312 See also arbitrage; information trading, informed trading Social Security, 142, 143 Solnik, Bruno, 80, 91n82, 174n164, 294n29 Spain, 227 SP/A (security, potential, aspiration) theory aspiration level, 257–9, 262, 265, 266 and behavioral portfolio theory, 4, 67, 181, 248–50, 253–5, 257–60, 262, 265, 268, 269 conflicts within risky choice, 253 curvature and elevation parameters, 251 dispositional vs aspirational factors, 250, 253 generally, 250, 253 high- and low-aspiration accounts, 258, 261, 263 265, 266 and modern portfolio theory, 3, 4, 248, 250, 259, 265, 266 probability of ruin, 257, 258 and prospect theory, 3, 4, 67, 181, 248–50, 253–5, 257, 258, 269 and retirement planning, 259 Roy's safety-first criterion, 254, 255, 257, 265 security-seeking vs potential-seeking dispositions, 3, 4, 248, 251, 253–5, 257–9, 262 and value-at-risk (VaR) analysis, 4, 248, 265, 266, 269 speculative bubbles, 1, 3, 4, 139, 182, 301–22 spillover effects and knowledge spillovers, 226, 243n180 Standard & Poor's (S&P) 500 (securities index), 77 standard score, 267 341 Statman, Meir, 22n79, 23n82, 23n84, 26n122, 45n23, 45n24, 46n31, 47n42, 47n44–6, 47n50, 47n56, 52n113, 52n115, 53n124, 132n64, 163n39, 169n104, 176n191, 232n6, 233n23, 238n91, 255, 271n38, 274n101, 274n115, 275n122, 275n127, 276n147, 277n159, 277n164, 277n165, 277n168, 277n170, 278n175, 278n180, 278n183, 278n184, 278n186, 278n196, 279n206, 279n212, 279n213, 280m224, 280n214–18, 280n226, 280n229, 281n249, 284, 293n11, 295m30, 316n42, 317n48, 317n56, 320n100, 320n103, 321n104, 279n200 stochastic dominance, 71n59, 92n104, 197, 222 stock exchanges American Stock Exchange (AMEX), 287 Chicago Board Options Exchange (CBOE), 77 NASDAQ, 287 New York Stock Exchange (NYSE), 287, 289 stock options (as part of executive compensation), 219 St Petersburg paradox, 122, 126–8 strategic management, 67, 74, 75, 223, 225, 227, 228 See also Bowman’s paradox structural breaks, 139 structured financial products, 96 sunk costs, 29, 42n1 Supreme Court of the United States, 8, 9, 11, 186 Sweden, 156 Swensen, David F., 157, 177n203, 177n209, 297n61 342 INDEX sympathetic magic, 14 synchronization, 302 System and System modes of thought, 5, 6, 18n11, 324 systematic risk, 36, 73, 76, 80, 96, 143, 226, 227, 306, 321n114 T Taiwan, 219, 284 target return, 33, 120, 121, 185, 223–5 disastrous rate of return, 256 (see also (Roy, Arthur D.-Roy's safety-first criterion)) Taylor series expansion (Taylor, Brook) and absolute risk aversion, 2, 65, 113, 115, 116 generally, 2, 66, 250 and higher-moment CAPM, 60 as a polynomial equation, 66 and the risk-averse insurance premium, 114, 115 and skewness preference, 116, 203 technical analysis, 307 technology bubble (of 2000), 158 Thaler, Richard H., 19n38, 43n4, 44n15, 45n19, 45n20, 46n27, 54n133, 105n19, 162n25, 162n26, 162n30, 165n54, 165n55, 165n58, 169n108, 170n23, 170n24, 171n28, 175n185, 175n186, 177n200, 177n210, 177n212, 178n214, 178n220, 207n52, 207n53, 207n64, 207n68, 210n111, 210n115, 228, 229, 232n9, 237n82, 239n115, 240n130, 244n198, 245n203, 245n210, 245n221, 246n245, 298n76, 316n38, 317n58, 320n95 Their Eyes Were Watching God (novel), 16 Thomas, Howard, 86n30, 224–6, 241n138, 241n142, 241n149, 241n151, 242n155, 242n157, 242n172, 243n178, 243n185, 243n187, 244n188, 244n192, 244n194 thrill-seeking, 220 time-series analysis, 318n70 Tobin, James, 94, 105n14, 141, 158, 163n40, 178n216, 237n73 Tolkein, J.R.R., 160, 177n207, 179n233 trading strategies corporate spinoffs, 219 dumb money effect, 287, 288 Maslowian self-actualization, 35–7 Treynor ratio (Treynor, Jack L.), 59, 60 turnover, 292, 309 Tversky, Amos, 20n42, 44n13, 45n21, 45n22, 127, 134n75, 135n90, 182, 183, 185, 187, 188, 196, 197, 199–204, 205n2, 205n11, 205n14, 206n22, 206n23, 206n25, 206n31, 207n56, 207n58, 207n63, 209n86, 209n90, 209n94, 209n101, 209n102, 210n105, 210n106, 210n112, 210n115, 210n116, 210n118, 210n120, 210n124, 211n125, 211n133, 211n134, 212n151, 212n158, 214, 230, 232, 233n19, 233n21, 241n147, 242n162, 245n224–6, 246n247, 249, 260n40, 261, 270n3, 271n24, 278n179, 324, 326n8 See also Kahneman, Daniel; prospect theory two-piece utility functions, 224 INDEX 343 U underwriting and underwriters, 221, 222, 239n113 unicorns (companies valued at $1 billion or more), 30, 173n155 unicorns (fallacious medical diagnoses), 153 United Kingdom (UK) See Great Britain United States of America (USA), 7, 8, 41, 51n104, 56n153, 80, 133n68, 138–41, 151, 165n61, 186, 200, 217, 220, 287, 289, 298n76, 304 universities and university endowments, 157–60 USA See United States of America (USA) low-volatility anomaly, 1–3, 37, 67, 73–93, 98, 101–3, 148, 223, 225–8, 230, 253 volume, 1, 11, 203, 219, 247, 270n13, 304, 307, 309, 316n42 Vuolteenaho, Tuomo, 98, 100, 108n48, 108n51, 108n55, 108n58, 108n61, 108n66, 108n67 V value-at-risk (VaR) analysis, 4, 248, 265–9 value factor (book-to-market), value stocks, 73, 74, 83, 98–102, 226, 303 vaunted Volatility Index (VIX), 77, 80, 81 venture capital, 13, 218, 222 Vilkov, Grigory, 84, 91n88, 92n113–15 volatility clustering, 230, 307 high-volatility portfolios, 82 implied, 77 in initial public offerings (IPOs), 3, 37, 222 X X-inefficiency, 226 Xing, Yuhang, 83, 85n10, 85n14, 86n17, 91n92, 91n93, 91n96, 91n98, 92n105, 92n107, 106n26, 109n74, 169n104, 238n90 W Wile E. Coyote, 58 Williams, Tennessee, 214, 233n22 World War II, 153 Wurgler, Jeffrey, 53n123, 82, 85n8, 85n11, 85n14, 85n19, 86n16, 88n52, 91n95, 91n99, 92n103, 109n77, 168n98, 321n105 Y Yale University, 157 Z Zhang, Lu, 85n4, 85n9, 102, 109n82, 175n180, 316n39 Zin, Stanley E., 146, 147, 167n80 ... Postmodern Portfolio Theory, this © The Editor(s) (if applicable) and The Author(s) 2016 J.M Chen, Finance and the Behavioral Prospect, Quantitative Perspectives on Behavioral Economics and Finance, DOI 10.1007/978-3-319-32711-2_1... Premium Puzzle 137 Prospect Theory 181 xi xii CONTENTS Specific Applications of Prospect Theory to Behavioral Finance 213 10 Beyond Hope and Fear: Behavioral Portfolio Theory 247 11 Behavioral Gaps... in portfolio theory and, more generally, in mathematical finance Like any other story in the history and philosophy of science, the transformation of portfolio theory begins with the identification