SECOND EDITION FINANCIAL MARKET BUBBLES AND CRASHES FEATURES, CAUSES, AND EFFECTS HAROLD L VOGEL Financial Market Bubbles and Crashes, Second Edition Harold L. Vogel Financial Market Bubbles and Crashes, Second Edition Features, Causes, and Effects Harold L. Vogel New York, NY, USA ISBN 978-3-319-71527-8 ISBN 978-3-319-71528-5 (eBook) https://doi.org/10.1007/978-3-319-71528-5 Library of Congress Control Number: 2018935300 © The Editor(s) (if applicable) and The Author(s) 2018 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 The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Cover image © Anna Nikonorova / Alamy Stock Photo Cover design by Jenny Vong Printed on acid-free paper This Palgrave Macmillan imprint is published by the registered company Springer International Publishing AG part of Springer Nature The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland To my dear parents, who would have greatly enjoyed seeing this Reprinted with permission from Kevin KAL Kallaugher, www.Kaltoons.com Prologue Bubbles are wonders to behold They take your breath away and make your pulse race They make fortunes and—just as fast or faster, in the inevitable stomach-churning crash aftermath—destroy them too But more broadly, bubbles create important distortions in the wealth (e.g., pensions), psychology, aspirations, policies, and strategies of the society as a whole Bubbles, in other words, have significant social effects and aftereffects One would think, given the importance of the subject, that economists would by now have already developed a solid grip on how bubbles form and how to measure and compare them No way! Despite the thousands of articles in the professional literature and the millions of times that the word “bubble” has been used in the business press, there still does not appear to be a cohesive theory or persuasive empirical approach with which to study bubble and crash conditions This book, adapted from my Ph.D dissertation at the University of London, presents what is meant to be a plausible and accessible descriptive theory and empirical approach to the analysis of such financial market conditions It surely will not be the last word on the subject of bubble characteristics and theory, but it is offered as an early step forward in a new direction Development in this new direction requires an approach that appreciates the thinking behind the standard efficient-market, random-walk, and capital asset pricing models, but that also recognizes the total uselessness of these concepts when describing the extreme behavior seen in the events that are loosely referred to as bubbles or crashes What is known as behavioral finance, extended here via the notion of a behavioral risk premium, ends up being much more pragmatic Yet none of this gets to the heart of the matter: when it comes to asset price bubbles and crashes, the most visibly striking and mathematically important feature is their exponentiality—a term that describes the idea that starting even at relatively slow rates of growth, price changes in each period must soon, by dint of the underlying arithmetic, become astonishingly large Exponentials appear when the rate at which a quantity changes is proportional to the size of the quantity itself ix x Prologue Although exponentiality is the essence of any and all bubbles, it is merely a manifestation of short-rationed quantities (not to be confused with the practice of short-selling) In plain English, this means that people make trading decisions based mainly on the amount that, for whatever reasons—fundamental, psychological, or emotional—they need to buy or sell now Considerations of current prices thus begin to take a backseat to considerations of quantities; in bubbles you can never own enough of the relevant asset classes And in crashes you cannot own too little of them The problem, though, is that this rubs against the neoclassical economist’s empirically unproven approach in which the participant is presumed to be “rational” calculating automatons tuned into a world with perfect, market to quickly arrive at “equilibrium.” However, this will never happen because, if it did, the market would cease to exist; it would disappear as there would be no further need for it In extreme market events, as ever more investors stop denying and fighting the tide and join the herd, the rising urgency to adjust quantities is reflected by visible acceleration of trading volume and price changes noticeably biased, to one side or the other And this is where the magical constant e, which approximately equals 2.718, enters as a way to describe the exponential price-change trajectory that is so distinguishable of bubbles (and crashes) What a number this e is It suggests steady growth upon growth, which leads to acceleration Keep the pedal to the metal in your car or rocket ship and you go faster and faster with each additional moment of elapsed time It is the mechanism of compound interest In calculus, it is its own derivative—no other function has this characteristic Best of all, even a non-mathematician such as I can figure it out using only basic arithmetic A brief example suffices to demonstrate the power of compounding (i.e., geometric progression) I sometimes ask MBA students in finance whom I occasionally have the privilege of addressing: “Quick, if I give you one penny today and steadily double the resulting amount every day for the next 30 days after, what will the total then be?” Remember, we’re talking here about only one single penny, one measly little hundredth of a dollar and only a month’s time Most guesses of even these bright students are, as most of ours would be, far off the mark The answer is $10,737,418 That’s—starting from a penny— nearly $11 million in a month! It is the ultimate bubble More specifically, though, all such compounding begins unimpressively with a largely unremarkable buildup so that on the 8th day of doubling the total is only $2.56, a sum barely sufficient to buy a decent cup of coffee Yet flash forward to the 29th next-to-last day and the total has reached $5.369 million, which means that valuation rises by $5.369 million in the single last day Given that bubbles and crashes exemplify such exponential-like price-change patterns (e.g., see Figs 8.6 to 8.8), it should thus not be surprising that the largest magnitude changes per unit time—market “melt-ups” and “crash-downs”— typically occur in the crescendo of buying in approach to the top and the capitulative selling in approach to the bottom Short-rationing behavior is most evident and intense during such times Prologue xi This work should first of all be of interest to financial economists of all stripes and to general readers interested in markets and finance Yet the potential audience ought to extend also to MBA- and Ph.D.-level students, central bank policy makers and researchers, commercial and investment bankers, investors and speculators, and technical and fundamental market analysts In this pursuit I have aimed for comprehensibility and comprehensiveness to appeal to and accommodate both generalist and academic readers To this end, the text is structured so that the first four chapters at most require for assimilation only a background that might include college-level finance and economics courses A brief glossary of terms and acronyms has also been appended as a convenience for general readers Meanwhile, the deeper academic material that might be primarily of interest to serious researchers and financial specialists appears in Part II, where the goal is not to provide extensive coverage of theories that have been around a long time but to instead provide contextual and historical perspectives in support of the new approach that is presented in Part III. This structure allows modules to be readily tailored to different audiences This second edition, shaped by the bubble and crash events of the eight intervening years since the first edition, has been enlarged, updated, and reorganized There are new sections on the global central bank-induced yield-chasing bubble that occurred between 2009 and 2017, on the important relationship between trust and credit, on quantitative easing and other unconventional central bank policies that have been experimentally implemented, on the development of volatility metrics and crash intensity measures, and on the more recent math-imbued stochastic dynamic approaches to modeling bubbles and crashes This project would have never been completed without the many great works that came before and the many kind people who provided encouragement, help, and good cheer during its production The following stand out for particular relevancy, clarity of exposition, and stimulative effects: Asset Pricing, rev ed., by John H. Cochrane; Quantitative Financial Economics, 2nd ed., by Keith Cuthbertson and Dirk Nitzsche; Applied Econometric Time Series, 2nd ed., by Walter Enders; Options, Futures, and Other Derivatives, 5th ed., by John C. Hull; Thinking, Fast and Slow by Daniel Kahneman; Behavioural Finance: Insights into Irrational Minds and Markets by James Montier; An Introduction to the Mathematics of Financial Derivatives, 2nd ed., by Salih Neftci; Robert Prechter’s The Socionomic Theory of Finance; Richard Thaler’s extensive works on behavioral economics; and Chaos Theory Tamed by Garnett Williams I am fortunate to have met at Birkbeck, University of London, Professor Zacharias Psaradakis, who encouraged my enrollment; Professor John Driffill, who supervised my academic endeavor there; Mr Nigel Foster, who provided timely clues in programming; and Professor Jerry Coakley, of the University of Essex, for review of an early draft It was also my pleasure and great fortune to meet Professor Richard A Werner of Southampton University, whose work xii Prologue significantly influenced this project He and Dr Luca Deidda, Associate Professor in Economics at Università di Sassari (and also with SOAS, University of London) interrupted their busy schedules to serve as examiners At Palgrave Macmillan, thanks also to senior editor for finance, Tula Weis, and assistant editor for economics, Allison Neuburger, who steadily guided its progress into print I’m further indebted to the anonymous readers who vetted the text and provided numerous suggestions that have made it far better than it would have otherwise been Appreciation too for Karen Maloney and Scott Parris of Cambridge University Press who had been supportive through the processing of several editions of my earlier books (Entertainment Industry Economics and Travel Industry Economics) and for this one’s first edition For any errors and deficiencies that may inadvertently remain, the responsibility is, of course, mine alone Bubbles and crashes have long been of immense interest not only to economists but also to the investing public at large The many illustrious tales of sometimes massive wins and losses incurred within such episodes indeed still fascinate us all It is my hope and expectation that by the end of this book readers will have a much deeper understanding of such dramatic events and will see them from an entirely new perspective New York City March 2018 Harold L. Vogel INDEX analysis-of-runs; characterizational issues, xvi; mean-variance of length, xvi; number/variance lengths, xvi autocorrelation/serial dependence of returns; duration dependence, 249n24; launch zone conditions, 364n13; length and number of runs, xvi; leptokurtosis, xxiiin7; peak zone conditions, 364n13, 364n14; skewness of distribution, 227, 250n29 transactions volume aspects, 316–318 Financial risk premium (FRP), 300, 338–340, 346n5, 378 Finding bubbles, 365n15 methodological details for; stage 1, elasticity calculations and quasi- equilibrium sample counting, 365n15; stage 2, exponential curve fitting, 365n15; stage 3, microbubble WABSIs, clusters, time-centering, 365n15 steps for microbubbles/microcrashes, 351, 365n15 First Law of Thermodynamics, xxiiin7, 17 Fischer, E. O’N., 246n6 Fisher, I., 15, 31n46, 146, 161n7 Fleckenstein, W. A., 33n61, 137n40, 166n41, 325n36, 367n20 Flood, R. P., 18, 227, 231, 247n11, 251n35 Florida land boom, 55, 85n23, 150, 324n25, 380n17 Flow of funds factors, 233–234 FOMC, 151, 167n42, 169n44, 325n36 Forecasting, xviii, 35n67, 92n60, 166n39, 168n43, 176n76, 208n29, 253n51, 297, 299, 321n11, 351–362, 378 ex ante and ex post, 367n28 See also Predictability Foreign exchange (FX) bubbles, xviii, 154, 228, 376 markets, 72, 154, 228, 309 Fractal, xiii, xiv, xvii, xix, 7, 135n27, 164n27, 196, 207n22, 209n32, 236, 237–239, 252n44, 254n57, 463 297, 314, 351, 355, 356, 367n24, 376, 377, 379 Fractal scalings, xiv, 237 Framing, 272 France, 3, 52 annual real equity returns, 1900–2005, 303 house price gaps in, 91n55 Mississippi Bubble and; speculative madness during, 3, 52 overlapping wheat price peak comparisons in, 24 panics of 1800s in, 133n19 Frankel, D. M., 236 Frank, R. H., 101n91, 248n12 Franses, P. H., 262, 413, 418 French, K. R., 210n38, 286n31, 319n4, 322n19 Frenzies, 12, 69, 254n54, 283n7 Friedman, B. M., 207n23, 241 Friedman, M., 100n83, 146, 161n7, 219 Froot, K. A., 224, 228, 230–232, 251n34 Fundamentals, x, xi, xxivn18, xxvin26, 13, 15, 17, 18, 24n1, 32n61, 33n61, 34n62, 48, 86n26, 87n34, 91n55, 129, 165n35, 167n41, 168n43, 173n58, 174n62, 190, 191, 194, 203n4, 196, 212n50, 221–230, 232, 236, 241–243, 244n1, 246n6, 247n10, 249n23, 249n28, 251n36, 255n64, 256n73, 287n31, 299, 307, 313, 320n9, 321n13, 339, 340, 355, 373, 375, 376, 378 Fundamental value approach, 17, 189, 202n1, 202 Futures and options markets, first, 48 G Gains and losses, asymmetry between, 272, 275 Gala, V. D., 321n13 Galbraith, J. K., 55, 31n46, 85n20, 91n53, 133n22 Gale, D., xxvn20, 29n34, 35n70, 88n36, 134n23 Gallin, J., 98n71 Gambling, relation to speculation, 464 INDEX Gann, William, 280 Gao, L., 282n7, 327n48 GARCH (generalized ARCH) models, 210n37 Garnsey, P., Garrison, R. W., 96n66, 163n18, 164n25, 165n37, 171n51, 172n54, 245n3 Garside, W. R., 86n26 Gascoigne, B., Gasparino, C., 90n49, 93n61, 94n65, 95n66 Gaussian distribution finite variance of, 209n32 Lévy stable non-Gaussian model, 255n65 See also Normal distribution Gay, G., 248n19 GDP bubble, 28n31 Geary, R. C., 363n7, 353 Geary’s test, 363n7, 353 Gehring, W. J., 134n22 Geman, H., 209n32 General Electric (GE), 252n39 Generalized ARCH (GARCH) model, 210n37 General Motors (GM), 64, 223 General specification tests, 231 Germany annual real equity returns, 1900–2005, 303 crash in, 119 house price gaps in, 91n55 Gernet, J., Gertler, M., 17, 137n36, 154, 161n7, 176n78 Giffen (experience) goods, 285n19, 379n6 Gilchrist, S, 101n89, 165n37, 243 Gilles, C., 255n66 Glassman, J. K., 55, 325n32 Gleeson, J., 49, 84n10, 84n12, 84n14, 85n15 Glimcher, P. W., 283n7 Global Crossing, 65 Goetzmann, W. N., xxiin1, xxiiin7, 25n2, 29n40, 32n60, 52, 84n11, 287n31, 287n34, 320n5, 320n6, 329n63 Gold price bubble, 150 Gomes, F., 321n13 Goode, E., 282n7 Goodman, P. S., 102n105, 137n40 Google, xxivn15 Gordon model, 308, 325–326n38 Gorton, G., xxvn22, 169n44, 225 Graham, J. R., 31n49, 207n23, 323n23 Granger, C. W J., 202n1, 384 Grantham, J., 33n61, 101n94, 207n23, 249n23, 325n32 Grant, J., 33n61, 34n61, 78, 85n22, 87n30, 138n47 Grassberger, P., 254n55 Great Britain house price gaps in, 91n55 Internet-related stock buying in, 65, 90n48 panics of 1800s in, 133n19 South Seas Bubble, 49 Great Depression, xxiiin11, 21, 56, 86n25, 86n26, 123, 146, 246n6, 321n12, 321n13 debt as percent of GDP during, 21, 123 Greene, W. H., 251n37, 322n19 Greenspan, A., xxvn20, 10, 14, 29–30n44, 68, 79, 92n57, 96n66, 98n71, 132n9, 133n21, 133n22, 136n34, 137n40, 154, 155, 162–163n16, 164n24, 167n42, 168n43, 171n49, 172n55, 175n70, 176n78, 285n23, 319n1, 325n36, 346n3, 367n20 Greenspan Doctrine, 30n44 Greenspan put, 325n36 Greenwald, B., xvi, 21, 35n70, 164n28, 204, 221, 247n12, 325n38 Grimaldi, M., 229 Gross leverage ratios, 93n62 Grossman, R. S., 208n28 Growth valuation formula, 308 Gruley, B., 102n106 Guan, W., 247n12 Guesnerie, R., 246n6 Gujarati, D. N., 251n34, 252n37, 363n7 Gurkaynak, R. S., 243 INDEX H Haacke, C., 10, 227 Hagerman, R. L., 209n32 Hall, S. G., 250n33 Hamilton, J. D., 101n89, 134n23, 136n32, 191, 224, 250n32, 251n33, 320n10 Hammurabi, 25n2 Hansell, S., 135n26 Hansen-Jagannathan bounds, 326n40 Hardouvelis, G., 224, 248n18, 230 Harrison, M. J., 25n1, 83n5 Hartcher, P., xxiiin13, 137n40 Harvey, C., 323n23, 367n21 Hassett, K. A., 30n44, 34n61, 55, 204n13, 325n32 Hausman spec test, 231 Hayford, M. D., 30n44, 154 Heaton, J. B., 241, 280 Hedge funds, 69, 91n53, 95n66, 71, 76, 102n104, 134n25, 136n35, 211n49, 380n12 black-box, 380n12 Hedonic treadmill, 28n26 Heisenberg Principle, 158 Henriques, D. B., 63, 89n42, 102n106 Hensel, C. R., 286n31 Hens, T., 229 Herding empirical herding, 278 feedback trading, 278 informational cascades, 278 investigative herding, 278 reputational herding, 278 winner’s curse and, 278 Herrera, S., 132n11, 221 High entropy, 380n15 High minus low book/market (HML), 207n23 Hilborn, R. C., 253n51 Hilsenrath, J. E., 88n35, 93n60, 95n66, 101n89, 101n92, 165n37, 166n41, 168n44, 169n44, 175n71, 380n17 Himmelberg, C., 97n69 Hirshleifer, D., 283 Hodrick, R. J., 18, 231 Hogg, T., 295, 453 Holmes, S. A., 95n66 465 Home equity line-of-credit (HELOC), 71 Homo economicus, 189 House price gaps, 91n55 Housing and credit, 2002–2008 aftermath, 68, 74 costliness of housing market, 68 disappearance of standards during, 82 early recognition of housing bubble deflation, 30n45 hedge funds, 69, 71, 76 homebuilders shares rise, 70 housing prices, 69, 72 housing wealth connection to consumption, 91n55 leveraged speculation, 69 long-term trends, 1890–2007, 70, 71 outstanding debt, personal, 68, 159 refinancings on existing properties, 71 securities, 69, 71, 74 structured finance products, 69 subprime loans, 93n61, 96n66, 134n25 warnings, 71 Housing bubble, xxvin28, 22, 30n45, 31n45, 66, 68, 71, 91n55, 92n57, 94n65, 96–97n66, 97n69, 98n71, 98n72, 100n86, 101n91, 135n26, 155, 159, 162n16, 380–381n17 Hsieh, D., 253n53 Hudson, R. L., xxiiin6, 204n12, 212n50, 238, 242, 256n77, 321n13 Hulbert, M., 286n31, 287n33, 324n26 Hunter, W. C., xxvin24, 209n30, 325n37 Hurst exponent, development of, 207n22 Hurst, H. E., 206–207n22 Hybrid capital instruments, 94n66 Hyperbolic absolute risk aversion (HARA), 28n24 Hyperinflation, xxvin31, 119, 132n12, 247n8 I Ibbotson Associates, 303, 323n24 Ibbotson dataset, 319n5, 323n24 Ibbotson, R. G., 21, 303, 319n5, 320n6, 320n9, 323n24, 348n24 IBM, xvii, 62, 64, 249n23, 324n26 466 INDEX Icahn, C., 252n39 ICAPM framework, 210n38 Ijiri, Y., 253n48 Implied equity risk premium, 320n9 Implied volatility, 27n21, 200, 208n29, 338, 360 Incomplete markets, 229, 236, 362 Independently and identically distributed (i.i.d.) data, 190 Indeterminacy, 153 Indirect vs direct tests, 232 Inductive vs deductive approach, xxivn16 Infinite-variance stable distribution, xiv, 209n32 Informational cascades, 278 Information asymmetry, 225 Information theory, on unfolding of bubbles, xxvin31 Institutional investors, 24, 62, 78, 99n72, 229, 250n29, 345n1 Intel, 14, 62 Internet bubble of 1990s, 30 Intertemporal competitive equilibrium, 230 Intertemporal consumption, 375 Intrinsic bubble, 228, 373 Investigative herding, 278 Ip, G., 30n44, 86n26, 99n75, 325n36, 381n17 Ireland, house price gaps in, 91n55 Irrational exuberance, 7, 14, 34n63, 71, 137n40, 329n71 Irrationality, xxvin26, 33n61, 189, 205n15, 207n23, 227, 243, 272, 279, 282n7, 287n31, 358 Italy, house price gaps in, 91n55 Ito, T., xxiiin7, 87n34 Iwaisako, T., 87n34 J Jagannathan, R., 301 Janes, T. D., 283 Janszen, E., xxvin31 January effect, 280, 286n31 Japan, 56–61, 76, 77, 87, 88n38–40, 91n55, 94n66, 102n106, 119, 120, 133n20, 137n36, 152, 153, 157, 161n7, 165n37, 167n41, 173n61, 174n66, 303 annual real equity returns, 1900–2005, 303 automobile industry in, 58 bank loan creation effect on bubbles, 151–152 bubble in, xxiii, 24, 60, 102n106, 153 credit availability, 32n59, 58, 59 Dojima Rice Exchange, house price gaps in, 91n55 macro-scale bubble, 19 Nikkei 224, 225, 1984–1990, xxiiin14, 15; tripling of, 57, 61 overlapping price peak comparisons, 24 real estate/equity bubble in, xxiin2, 3, 19, 24, 57, 59, 61, 153 stock and land value relation to GDP, 1981–1992, 57, 59 stock market bubble in; causes of, 56, 89n42, 165n35; nonfinancial corporation funds and, 58; rate cutting effects, 88n40 technology sector in, 62 value of shares traded per GDP unit, 61 volume of shares traded per GDP unit, 62 zai-tech (financial engineering) in, 87n34 Jensen, M. C., 191, 211n49 Johansen, A., 229, 233, 235 Johnson, E., 284n15 Johnson, L., 170n45 Jones, C., 346n9 Joulin, A., 284n10 Juglar, C., 133n19 K Kahneman, D., xi, xvi, 28n27, 243, 256n69, 272–274, 284n10, 284n12, 285n16, 345n3 Kamarck, A. M., xxivn18 Kamstra, M. L., 283n7 Katsaris, A., 133n22, 232, 330n73 Kaufman, H., 29n43, 170n45, 376 Kelly criterion, 322n16 Kelly, K., 93n62, 322n16 Kennedy, P., 362 Keuzenkamp, H. A., xxivn17, 35n66 INDEX Keynes, J. M., xx, xxvn20, 10, 25n1, 83n5, 91n54, 146, 160n4, 201, 205n13, 211n46, 219, 245n4, 247n10, 362, 368n32 Kim, C.-J., 210n38 Kindleberger, C., 26n14, 32n61, 34n61, 88n39, 132n15, 133n20, 136n35, 137n39, 243, 246n8, 256n68 Kindleberger/Minsky model, 136n35 Kinney, W. R., Jr., 286n31 Kleidon, A. W., 208n30 Klemperer, P., 254n54 Kohn, D., 168n44, 302 Koivu, M., 138n41 Krainer, J., 98n71 Kreps, D., 25n1, 83n5 Krueger, A. B., xxiin1, 84n10 Kruger, R., Kurz, M., 246n7, 319n4 L Lahart, J., 136n35, 168n44 Laherrère, J., 252n41, 253n48 Lakonishok, J., 211n49, 285n23, 323n23 Law, J., 49, 50, 84n12–14, 50, 51, 52 Law of one price (LOOP), 32n59, 219, 223, 245n2, 248n13, 374, 377 LeBaron, B., xxiiin10 LeDoux, J. E., 282n7 Lee, C. M C., 330n73 Lee, I. H., 231, 235 Lee, T., 31n50, 90n44, 90n46, 227, 322n18, 324n28 Lehman, B. N., 82, 94n65, 95n66, 135n26, 165n34, 208n25 Lehnert, D., 240 Leonhardt, D., 30n45, 96n66, 98n71, 135n26, 380n17 Leptokurtosis, xxiiin7, 197, 207n23 LeRoy, S. F., 208n30, 227, 255n66, 319n2 Levy, A., 282n7 Lévy distribution, see Pareto distribution Lévy-Mandelbrot distribution, see Pareto distribution Lévy stable non-Gaussian model, 197 Liar loan, 92n58 Li, D., 93n61 467 Lin, G., 134n23 Liquidity cost of borrowing/trading and, 308 defining, xxv effects on crashes, 65, 75, 344, 358 in efficient market hypothesis, xxvn20, 139n52, 164n28 role in sustenance/propagation of bubble, 137n35 Liu, T., 254n55 Lo, A. W., 11, 117, 190, 191, 201, 203n1, 203n3, 206n19, 207n22, 211n46, 282n7, 359, 380n12 Loeys, J., 60, 242 Log-normal probability distribution, 195 Long-horizon returns, 209n33 Long-Term Capital Management (LTCM), 11, 280, 357 Lovell, M. C., 247n8 Lowenstein, R., 93n61, 93n64, 132n9, 135n26, 212n51, 256n77 Low volatility error, 204n13, 255n65 L-stable distribution, see Pareto distribution Lucas, Robert, Jr., 245n3, 256n67 Lucchetti, A., 89n42 Lux, T., 230, 236 Lyapunov exponent, 232, 233, 254n54 M MacKay, C., 3, 47, 83n4, 83n5, 286n27 MacKinlay, A. C., 11, 203n3 Maddala, G. S., 246n8, 251n34 Madoff, B., 82, 102n106 Makin, J., 33n61 Malkiel, B., 11, 102n95, 195, 204n10, 205n14, 205n15, 206n17, 206n18, 211n47 Malliaris, A. G., 30n44, 89n42, 154, 163n23, 221, 237 Managed currency, 85n14 Mandelbrot, B., xiii, xiv, xiv, xvii, xxiiin6, 196, 204n12, 207n22, 209n32, 212n50, 237, 238, 242, 321n13, 314 Mania, replaced by bubble, 33n61 Manne, H. G., 273 468 INDEX Mantegna, R. N., xxiiin6, 28n30, 207n22, 209n31, 209n32, 209n34, 210n37 Marginal utility of consumption, 18, 222, 256n71, 320n7 Marginal utility theory, 243 Market bubble, features of, 14, 15 Market efficiency, 191, 195, 202n1, 243, 251n34 Market peak, 234, 275, 344, 354 Market price of risk, 193 Market risk premium, 193, 210n38, 301, 303, 321n13, 322n19 Market Vane’s Bullish Consensus, 345n1 Markov switching model, 232 Markowitz, H. M., 191, 203n7, 205n13, 206n18, 212n50, 244 MAR ratio, 326n43 Marshall, A., 163n24 Marsh, P., 9, 162n14, 303 Martingale process, 254n57 Mathews, P. H., 34n64 Mauboussin, M. J., 91n54, 209n36, 279 Mayer, C., 98n71, 381n17 MBIA, 203n4 McCarthy, J., 98n71 McCauley, J. L., xxivn19, 255n63 McConnell, J. J., 287n31 McQueen, G., 222, 224, 227, 228, 231, 248n17, 251n35, 363n5, 364n8 Mean, 376 adjusted mean absolute deviation, 247n12 mean-variance model of decision making, 206n19 mean-variance of run length, 353, 364n10, 364n11 Medici-era Italy, Meese, R. A., 228, 230, 231, 249n26 Mehrling, P., xxvn23, 138n50, 165n33, 165n36, 171n47, 212n53, 219, 256n77 Meltzer, A. H., 170n45, 175n73, 247n9 Merck, xvii Merrill Lynch, 82, 93n65, 94n65, 98n70, 134n25 Merton, R. C., xxiiin7, 66, 197, 204n9, 241, 246n6, 254n56, 322n16, 311, 324n29, 327n49 Merton, R. K., 246n6 Mesopotamia, 3, 25n2 Microbubble, xix, 297, 351, 356, 361, 365n15, 366n15, 366n18, 377, 378 Microcrash, xix, 351, 356, 377, 378 Microsoft, xxivn15, 14, 62, 76, 353 Milgrom, P., 282n7 Miller, R. M., 136n35 Millionaire, coining of, 84n10 Mills, T. C., 207n22, 210n37, 240 Minsky, Hyman, 136n35, 161n7, 211n46 Minsky moment, 136n35 Mishkin, F. S., 26n10, 86n26, 131n7, 136n35, 150, 161n7, 166n40, 171n51 Mississippi Bubble criticism as bubble, 98n72 speculative madness during, 10, 28n30, 32n61, 53, 320n10 Model misspecifications, 228 Modern Portfolio Theory (MPT), 194 assumptions, 275, 324n31 volatility and, 194–196 See also Capital Asset Pricing Model (CAPM) Monetary policy, 30n44, 35n70, 81, 86n26, 96n66, 97n66, 122, 146, 150, 154, 160n4, 162n15, 166n40, 166n41, 167n43, 168n43, 168n44, 169n44, 170n44, 170n45, 171n51, 172n58, 173n58, 175n70 Money and credit features, 4, 86n26, 153–156, 158, 165n35 bank loan creation, 152, 155 of bubbles bank credit creation, 159 central banks role; as lenders of last resort, 4, 86n26, 153, 155, 158, 165n35; neoclassical perspectives on, 154; policies during/after crashes, 156; policies to slow/act against bubbles, 154 cheap credit effects on production/ consumption, 159 excessive lending effects, 164n25 government power to create money/ credit, 161n8 historical perspectives, 145–151 interest rate policy levers, 158 liquidity issues, 150–153 INDEX monthly money/credit series, 158 regression effects of WABSI, 376 tests using WABSI, 376 Montier, J., xi, 136n35, 204n8, 206n19, 223, 235, 274, 275, 285n16, 323n21, 325n34 Mood, A., 190, 352 Moral hazard, 153, 165n35 See also Information asymmetry Mora, N., 87n30 Morgan, I. G., 330n73 Morgenson, G., 94n65, 95n66, 97n69, 100n77, 102n105 Mortgage-backed securities (MBS), 69, 93n61, 94–96n66, 99n77, 157, 208n25 Mortgage packaging, xxi M1 Sup time series, 100n83, 152 Muth, J. A., 219, 246n8 Mutual funds closed-end, 223, 280 MZM time series, 129, 152 N Nagel, S., 91n53, 229, 249n28 Napier, R., 85n21, 85n22, 86n26, 362n2 Narrativity error, 255n65 Nature, relevance to bubbles and crashes, xviii Neal, L. D., 25n2, 51, 52, 83n6, 85n16, 85n18, 156, 165n33 Near-neighbor algorithms, 235, 353, 363n7 Neftci, S. N., 319n3, 322n19, 346n5 Neoclassical economic deductive approach in, xxivn16 defining, 300 equilibrium notion in, 201 as framework for bubble studies, 222 on role of central banks, 154 Neoclassical equilibrium, x, xvii, 154, 297, 311, 328n53 Netherlands house price gaps in, 91n55 money and credit extension mechanisms, Neuroeconomics, 282n7 469 Neurofinance, xx, 282n7 News release, link to stock price movement, 284n10 Nikkei 224, 225, 1984–1990 closing prices vs S&P 500 Index, 23 NINA loans, 68 NINJA loans, 68 tripling of, 57, 61 Nitzsche, D., xi, 208n23, 210n40, 244n1, 326n40 No-doc loans, 68 Nofsinger, J. R., 29n33, 278, 281n3 Noguchi, Y., 27n16, 32n59, 87n34, 226, 319n5 Nonborrowed reserves, 152, 159, 376 defining, 376 Nonbubble vs bubble, 138n50, 307, 308 Noncrash market decline, 308 Nondiversifiable aggregate risk, 301 Non-Gaussian distribution Lévy stable, xiv, 235 nonlinear dependence, xxiiin10 nonlinear dynamics, xiv, xv, xxiiin11 variance of stable, 197, 209n32 See also Chaos theory; Nonstationarity Nonstationarity, xv, 34n63, 207n23, 208n30, 245n1, 251n34, 287n31, 302, 319n4 Non-Walrasian quantity-rationed disequilibrium, 227 Normal distribution, 207n23, 209n32, 326n43 Norris, F., 89n42, 174n67 Northern Rock, run on, 132n13 No-Speculation Theorem, 282n7 Null hypothesis, 201, 248n18, 231, 250n31, 254n55, 352, 366n17 Nychka, D. W., 232 O Oates, J., 25n2 Observation lookup table, 209n32 Observed excess return, 323n22 Obstfeld, M., 224, 228, 230–232, 251n34 Odean, T., 272 470 INDEX O’Driscoll, G. P., Jr., 30n44, 97n66, 170n45 Ofek, E., 90n50, 134n22 Oliver, M. J., 27n15, 89n42, 132n13, 136n33, 163n17 On-balance volume (OBV), 330n73 O’Neal, S., 93n65, 94n65 1/f noise, 237, 253n45 Open-end fund format, 201 Option-implied volatility, 362n3 Orthodox peak, 365n14 Overlapping generations (OLG) model, 88n38, 220, 224–226, 230, 246n6 P Panic of 1800s, 133n19 vs crash, 29n34, 117–122, 129, 133n20, 134n23, 376 relationship to crashes, 29n34, 117–122, 129, 133n20, 134n23, 376 Parent company “puzzles”, 223 Pareto distribution, 386, 387 Pareto (Zipf’s) Law, 238, 253n46, 253n48 Pareto-Lévy distribution, 196 Pareto, V., xxiin5, 166n40, 237, 253n46, 282n7, 386, 387 Parisi, F., 282n7 Parker, W. D., 283n7, 286n28, 287n31 Parke, W. R., 208n30 Park, J. Y., 232 Parks, T., Partial equilibrium, 251n36 Paster, L., 27n15 Patel, J., 285n23 Path length, 307–309 Paulson, H., 31n53, 32n53 Peace dividend, 63 Peach, R. W., 98n71 Peak of bubble, 19 market, 344, 354 orthodox, 365n14 Pearce, D. W., 327n49 Pepper, G., 89n42, 136n33, 163n17 Periodically collapsing bubble, 227, 249n25, 250n33 Perron, P., 251n33 Perry, G. E., 132n11, 221 Personal computer, introduction of, 60 Peters, E. E., 132n9, 206n19, 206n22, 207n22, 279 Peterson, R. L., 282n5, 283n7 Pierce, J. R., 253n47 Plaza Accord, of G-5 countries, 87n30 Plunge Protection Team, 166n41 Poon, S., 352, 362n3 Porter, D., 170n45, 225, 229, 319n2 Portfolio approach, 256n71 to asset pricing, 256n71 Portfolio diversification, 75 Portfolio insurance, 62, 63, 89n42 Portfolio theory, 191, 194–196, 201, 204n10, 324n31 Posen, A. S., 26n10, 165n38, 319n5 Positivism, 12–13, 156, 278 Posthumus, N. W., 83n5, 83n6 Postmodern portfolio theory (PMPT), 195 Poterba, J., xv, 11, 87n30, 207n22, 210n38, 322n20 Poundstone, W., 35n73, 245n1, 250n28, 282n6, 322n16 Power laws Cisco Systems and, 238 income distribution and, 237 See also Pareto distribution Prechter, R. R., Jr., xvi, 29n34, 100n85, 132n10, 164n27, 206n19, 245n1, 252n44, 253n50, 256n74, 273, 276, 277, 283n7, 284n10, 286n28, 287n31, 328n59, 345n3, 347n14, 362n1, 365n14, 367n26, 388 Predictability, 246n8 prediction error, 246n8 See also Forecasting Predictable irrationality, 272 Present discounted value (PDV), 220, 231, 250n31 Pribram, K., 85n14 Price change percentages vs variance, xix Price-dividend ratio (P/D ratio), 34n63, 250n31, 319n1, 343, 367n27 Price-earnings (P/E) ratio, 20, 56, 64, 65, 87n30, 127, 134n22, 197, 245n1, 305, 307, 338, 343, 344, 375, 387 INDEX Price elasticity of demand, 285n19, 385 Price peak comparisons, overlapping, 24 Price return variance, 300 Prince, Chuck, xxvin29 Probability distribution, xiv, 146, 190, 195, 208n30, 256n66, 363n7, 386, 388 Probability distribution functions (pdfs), 210n37 Procaccia, I., 254n55 Prospect theory, 11, 256n72, 272, 275, 307, 329n68 Psaradakis, Z., xi, 251n33 Psychological risk premium, 340 Psychological traits of behavioral finance ambiguity aversion, 274 anchoring, 13, 189 dynamic prospect theory, 307 Punctuated equilibrium, 328n59 p-values, 152, 200, 357, 366n16, 386, 389 Q Q-ratio, 14, 362n2 Quandt, R. E., 328n60 Quantity-rationed disequilibrium, 227 Quant models, 255n65 Quasi-equilibrium, 377, 378 absolute, 326n47 behavioral risk features, 338, 342 equity risk premium and, 365n15 sample counting, 365n15 strong, 339, 342, 348n22 Qwest, 65 R Ramsey, J. B., 240 Randomness, 240, 257n77, 363n4 Random variable, 93n61, 196, 197 Random walks, 189, 192, 193, 196–200, 203n7, 205n13 capital asset pricing model and, 189, 191–194, 361; asset allocation and, 203n7; capital market line, 192, 193; higher expected returns and risk, 192, 205n13; optimal portfolios, 192, 193; risk specification and, 189 conditional expectation, 190, 192 471 defining, 387 efficient market hypothesis, 10, 190–191, 195, 201, 220, 228, 255n64, 271 log-normal as geometric, 35n73 martingale process, 322n19 runs tests, 190 Security Market Line, 193 stock market as not, 201 volatility and; implications, 196–200; market changes, 196; over long run, 196 Range over standard deviation (R/S) analysis, 206n22 Rappoport, P., 85n25, 89n42 Rational bubble, 34n63, 87n34, 168n43, 373 Rational bubble component, 230 Rational expectations hypothesis (REH) compared to other approaches, 27n22, 146 criticism of, 220 weaknesses of, 247n8 Rational expectations theory rationality-optimization assumption, xxivn18 Rational valuation approach, 326n40 Rational valuation component, xvii, 326n40 of bubble, 219 Rationed buyers, 328n55, 312, 313 Rationed sellers, 328n55, 312, 313 Realized or historical volatility, 200 Rebello, J., 30n44 Recession, 378 causes, 75, 122 Red-lining, 96n66 Reductionism, 66, 75, 118, 136n35, 160n4, 171n51, 233, 234, 324n29 RE equilibrium and OLGs, 230 Rees-Mogg, W., 83n4 Regime-shift in productivity, 164n26 Regression analysis defining, 388 See also Autoregression; Money and credit features, regression effects of WABSI Regression equation specification error test (RESET), 250n32 Reinforcement bias, 284n13 472 INDEX Reinhart, C. M., 35n69, 99n72, 122, 132n16 Related regret theory, 282n4 Replacement bias, 305 Representative studies overview, 230–231 Rescaled range analysis, 206n22 Research future, 378–379 general properties of, 284n10 returns, 199 Returns-generating process, 255n65 RE with OLG model, 230 RE with periodically collapsing bubbles, 230 Rich, M., 30n45, 380n17 Richardson, K., 287n31 Richardson, M., 90n50, 134n22 Risk market price of risk, 193 market risk premium, 194, 210n38, 301, 321n13, 322n19 systematic risk, 194, 205n14, 208n23, 330n73 time as source of, xxvn23 vs uncertainty, 248n12 unsystematic risk, 194 See also Equity risk premium (ERP) Risk aversion utility functions, 11, 28n24 Risk neutrality, 244n1 Risk obliviousness (complacency), 275 Risk premiums, ix, xvi, xix, 17, 32n59, 127, 137n40, 162n15, 170n44, 193, 194, 210n38, 210n39, 249n23, 271, 297, 299–301, 303, 304, 306–310, 320n7, 320n8, 321n11, 321n13, 322n19, 323n22, 323n23, 325n32, 337, 338, 338, 340, 346n4, 360, 375, 378, 380n17 Ritter, L. S., 162n12 Rm statistic, 194 Roberts, R., 96n66 Roehner, B. M., 22, 24, 28n29, 35n71, 50, 102n106, 120, 137n41, 329n64 Rogoff, K. S., 21, 99n72, 122, 132n16 Roman Empire, speculation in, Romer, D. H., 284n10 Rosen, H. S., 328n60 Rosenberg, J., xix, 210n38, 211n40 Rosenberg, M., 286n31 Ross, S. M., 203n4 Rostovtzeff, M., 4, 25n4 Round number phobia, 84n10 Rowley, R., 255n64 Rozeff, M. S., 286n31 Rule 80B, 339 Runs analysis of, xv, xvi, 352, 364n13; WABSI, 228, 363n5 duration dependence tests, 363n5 Russia destabilization of currency in, 357 Rynecki, D., 14 S Saddle point behavior, 246n5 Saller, R., 4, 26n6 Santoni, G. J., 224, 228 Sarbanes-Oxley, 84n11 Sarno, L., 251n34 Satchell, S., 229 Schacter, S., 85n16 Schaller, H., 221, 251n35, 358 Scheinkman, J. A., xxiiin10, 83n5, 84n10, 102n99, 225, 248n18, 328n59, 330n73 Schlesinger, J. M., 102n106, 173n61 Schmidt, U., 282n7, 327n48 Schumpeter, J. A., 9, 27n16, 133n19, 326n47, 327n49 Schwartz, A., 33n61, 85n23, 134n26, 150 Schwartz, D. G., 5, 324n26 Schwartz, N. D., 92n58, 99n73 Schwert, G. W., 134n23, 198, 210n38, 322n20, 329n70 Science of economics, 84n14 Scott, L. O., 232 Second law of thermodynamics, xxiiin7, 17 Security Market Line (SML), 193, 194, 205n13 Security price series data, 227 Self-fulfilling prophecy, 33n61, 223, 231, 246n6 Self-liquidating credit, xxiiin13 Self-organized critical (SOC) systems, 328n59, 367n24 INDEX Sensitive dependence on initial conditions (SDIC), xv, xxiiin11, 240, 253n54, 254n55 Serial autocorrelation, 352 Serial defaults role in, 122 Series generating equations, 210n37 Serletis, A., 232, 253n52, 254n55, 285n16 Shalen, C. T., 330n73 Shanghai Stock Exchange, 330n72 Sharpe ratio, 203n6, 204n9, 310, 326n40, 326n43, 367n27 Sharpe, W. F., 191, 192, 203n5, 204n9, 212n50, 256n77, 379n5 Sheehan, F., 33n61, 137n40, 166n41, 325n36, 367n20 Shefrin, H., 272, 283n7 Shermer, M., 283n7 Shiller, R. J., xx, 14, 20, 29n34, 30n45, 32n58, 32n61, 34n63, 71, 85n23, 98n70, 98n71, 196, 197, 201, 202, 203n8, 208n30, 212n51, 212n53, 225–227, 230, 231, 247n10, 251n34, 319n2, 319n4, 326n40, 345n1, 347n15, 380n17 on cointegration, 34n63 on commitment to investments during bubble, 227 critique of, 208n30 on definition of bubble, 32n61 on efficient market hypothesis, 202, 203n8, 204n8, 326n40 on epidemic bubble, 32n58 on fundamentals, 32n61, 33n61 on historical context of RE, 247n10 on irrational exuberance, 14, 34n63, 71 on volatility, 196, 319n4, 326n40 Shleifer, A., 86n26, 223, 287n31, 379n4 Short-horizon returns, short-side principle, 209n33, 313 Short-side rationed theory, 299, 378 Short-side rationing principle, 339 Shumway, T., 283n7, 287n34 Sias, R. W., 283n7, 278, 287n34, 348n20 Sibert, A., 138n47 Siegel, J. J., 30n44, 89n42, 122, 123, 137n40, 320n7, 321n12, 322n18, 304, 324n26, 326n38 473 Silber, W. L., 98n72, 162n12 Silverberg, G., 240 Simon, H. A., 253n48, 272, 282n6 Sinai, T., 98n71, 381n17 Sloan, R. G., 287n31 Small stocks minus return on big stocks (SMB), 207n23 Smant, D. J C., 208n30, 319n2 Smets, F., 26n10, 97n66, 164n25 Smithers, A., 14, 30n44 Smith, V. L., 85n24, 97n66, 161n6, 229, 249n28, 282n7, 345n3 Social rationality, 12, 28n29 Sola, M., 232, 250n33, 251n33 Song (Sung) Dynasty, Sornette, D., 34n65, 98n71, 132n11, 164n26, 206n18, 229, 230, 233, 235, 252n41, 253n48, 278, 358, 362n2, 367n24 South Sea Act, 49 South Sea bubble of 1720 aftermath, 84n11 share prices, 50, 51 South Sea bubble of 1700s, xxiin2, 49 South Sea Company (SSC), 6, 49, 50, 52, 83n7, 84n11, 84n13 The South Sea Sufferers Act, 84n11 Spain annual real equity returns, 1900–2005, 303 house price gaps in, 91n55 Speculation in ancient Athens, bubble as frenzy of speculation, 3, 53 in classical Athens, defining, 6, 83n5 historical roots of vehicles for, 9, 47–48, 90n50 relationship to gambling, in Roman Empire, speculative bubble, xxi, 10, 12, 14, 28n30, 32n61, 81, 228, 320n10 trade and, 24n1, 83n4 S&P 500 Index as benchmark, 127, 324n28 daily closing prices vs Nikkei 225, 23 S&P 500 annual ratios, 304, 343 stock market capitalization as percentage of nominal GDP, 57, 64, 67, 357 474 INDEX S&P Housing Price Index, 126, 323n24 Spotton, B., 255n64 Stable distribution defining, xiv Lévy stable non-Gaussian model, 197 See also Pareto distribution Stable equilibrium, xxvn19 Stambaugh, R. F., 320n6 Standard deviations of returns, risk measured by, 192, 195, 204n13, 324n30 Standard dividend-discount model, 196 Stanley, H. E., xxiiin6, 28n30, 207n22, 209n32, 209n34, 210n37 Stationarity, xv, 197, 232, 251n37, 252n38, 275, 300, 378 Statman, M., 205n13, 271, 272 Staunton, M., 9, 162n14, 303 Stein, B., 94n66 Stiglitz, J. E., xvi, 21, 33n61, 35n70, 102n106, 160n5, 164n28, 245n3, 326n46, 329n60, 374 Stochastic discount factor (SDF), 222, 248n13 Stochastic processes linear/nonlinear, 240, 254n55 stochastic stock price dynamics, 197 Stock market bubble, 22, 30n44, 32n58, 33n61, 153, 154, 167n42, 196, 247n10 See also Bubble; Financial-market price bubbles theory Stock market, volatility shocks to, 210n38 Stock-market wealth connection to consumption, 91n55 Stock repurchase programs, 252n39 Stokey, N., 282n7 Strength indicator of bubble, xix, 356, 357, 366n15, 376 choice of weighting scheme, 91n53 cluster-weighted WABSI, 366n18 evenly weighted WABSI, 366n15 Stress testing, 100n86, 134n25, 255n65 Stretched exponential family of probability distribution functions (pdfs), 253n48 Strogatz, S., 164n27, 238, 253n50, 285n22 Strong quasi-equilibrium, 339, 342, 348n22 Structural vs cyclical bubble, 227 Structured finance products, 69 Structured investment vehicles (SIVs), 69 Stylized facts, general properties of, 24 Subjective Expected Utility (SEU), 28n22 Subprime lending, xxvin29, 101n93 Summers, L. H., xv, 11, 138n49, 191, 201, 202, 207n22, 210n38, 212n51, 322n20 Sunspot equilibria, 220, 246n6, 255n66 Sunspots, 122, 135n28, 146, 206n22, 223, 234, 246n6, 255n66, 283n7 Supply and demand, financial vs goods/ services, xviii, xx, 160, 351 Survivorship bias, 284n11, 321n13 Swaminathan, B., 330n73 Switzerland, annual real equity returns, 1900–2005, 303 Sylla, R., Synchronicity, 253n50 Systematic risk, 194, 205n14, 208n23, 330n73 Szafarz, A., 223, 227, 230 T Tails, xxiin5, xxiiin7, 131n8, 149, 153, 204n13, 196, 228, 230, 235, 243, 253n48, 256n75, 376, 387 Taiwan (TSE) market, 317 Taleb, N. N., xxiin5, xxivn16, 78, 134n22, 204n13, 212n50, 248n12, 255n65, 282n7, 321n13, 367n24 Tanggaard, C., 250n31, 251n36 Tattonnement, xvii Taxpayer Relief Act of 1997, 96n66 Taylor, M. P., 251n34 Taylor rule, 167n42 Taylor, S., 35n74, 130n2 Tech/Internet stocks 1987 and 2000, 60–67 bond market, xv, 60, 62, 64, 78, 149 causes of 1987 crash, 89n42 Dow-Jones Industrials/FTSE-100 losses, 54, 59, 60, 62, 63, 131n8, 138n44, 235, 319n5 INDEX emotion as driving force in, 90n49 equity market, 15, 64 Gulf War effects, 64, 88n38 mini-boom in tech stocks, 62 October 1987 crash, 63, 325n36 summary of key technology events affecting, 64 Telecom Act of 1996 affect on, warnings about, 64 Technical vs fundamentalist approaches, forerunner of, 48 Technology personal computer introduction, 60 trading-platform, 342 See also Tech/Internet stocks Technology, media, and telecom (TMT) bubble, 15, 19, 65, 67, 70, 79, 227, 249n28, 315, 357 Telecom Act of 1996, 64 Temin, P., 84n10, 229 Templeton, J., 29n43, 271 Terra Networks, 65 Testing methods, 231–233, 362n3 Thaler, R., xi, xvi, 208n24, 212n51, 271, 272, 278, 280, 284n15, 288n41, 368n32, 374 Thermodynamics, xxiiin7, 17 Thorley, S., 222, 224, 227, 228, 231, 248n17, 251n35, 363n5, 364n8 Thornton, D. L., 174n62 Three-factor model (FF3), 207n23 Time series autocorrelation of, 361, 375 bubble tests of, 231, 243 MZM, 89n42, 129, 152 time-varying risk premiums, 287n31 Timmermann, A., 367n21 Tirole, J., 224, 225, 246n6, 248n17, 230, 363n5 Tobin, J., 14, 191, 362n2, 387 Tobin’s Separation Theorem, 192 Townsend, R. M., 226 Trading-platform technology, 342 Trading volume as precursor to crash, 62, 133n22, 345, 378 as proxy measure, 330n73 Trajectory, x, xiv, xv, 66, 70, 152, 236, 239, 253n51, 254n57, 319, 365n15, 362, 389 475 Transactions per unit time (TPUT) annual average estimate comparison, 343 annual ERP/BRP comparison, 343, 344 BRP/ERP vs S&P 500 P/E ratio, 341, 344 during quasi-equilibrium, 326n47, 327n48, 338, 339, 341, 342, 348n22, 348n23, 364n9, 365n15, 387 during strong quasi-equilibrium, 339, 342, 348n22 growth of NYSE TPUT, 342 regression of S&P 500 P/E ratio against FRP/BRP, 344 Transactions volume aspects, 316–318 Transversality condition, 138n47, 244n1, 245n3 Treynor, J. L., 191, 29n31, 203n6, 204n9, 363n7 TRIN index, see Arms Index Tsay, R., 210n36 t-statistic, defining, 389 Tulipmania of 1600s behavior similarities with Internet craze, 84n7 economic consequences of, 47 notarized written contracts effect on, 47 scams and frauds during, 48 speculation as result of, 3, 47–48 tulips as status symbol, 47, 83n1 Turner, A. L., 94n65, 207n23 Turnovsky, S. J., 246n5 Tversky, A., xvi, 272, 274, 285n16 Twin securities, 223 Two-component (ICAPM-framework) process, 210n38 U Uncertainty decision making under, 271 price anchoring and, 274 role in crash/panic/collapse, vs risk, 117–122 Uncertainty Principle, 158 United Kingdom annual real equity returns, 1900–2005, 303 crashes/booms/recessions, 1890–1940 & 2005, 476 INDEX United States annual real equity returns, 1900–2005, 303 house price gaps in, 91n55 panics of 1800s in, 119, 133n19 See also S&P 500 Index Unit root test, 210n37, 232, 250n33, 251n33, 252n38 Unit root testing, 251n33 Unobservables, 99n73, 244, 321n11, 323n22 Unsystematic risk, 194 Upside-down, 124 Ursua, J. F., 118, 131n5 U.S. Treasury Bills, 192 U.S. Treasury bonds, 127, 320n5 Utility, 379 defining, 389 direct utility model, 256n72 expected utility theory, 282n7 marginal utility theory, 243 risk aversion utility functions, 28n24 Subjected Expected Utility (SEU), 28n22 Utility preferences, 338, 375, 377 V Vaga, T., xxiiin6, xxiiin10, 279 Valuation aspect, 299 Value-at-Risk (VaR), 69, 92n60, 93n630, 135n26, 322n16 Vandewalle, N., 89n42, 134n22, 209n36 Van Norden, S., 221, 231, 251n35, 358 Van Overtveldt, J., 167n42 Variance, 329n64 analysis-of-runs and, 353, 361, 364n11, 364n13, 365n14 bounds violations, 230, 300, 326n40, 341 constant variance, 210n38, 322n19 defining, 356, 389 elasticity of (see Elasticity of variance) equity risk premium and, 300, 303, 316, 318, 322n20, 326n47, 329n64, 352, 362, 365n15 of Gaussian distribution, 235 infinite-variance distribution, xiv, xxiiin7, 196, 197, 209n32, 237 mean-variance model of decision making, 206n19, 326n43 of non-Gaussian distribution, 197, 209n32 price change percentages vs., xix price return variance, 300 risk premium decline and, 300, 307, 356 runs and, 242 trading volume and, 240 volatility and, 360, 361 Varian, H. R., 287n31 Vector autoregression (VAR), 251n34 Viacom, 64 Vines, S., 139n54 Vishny, R. W., 223, 379n4 Visibility, of bubbles, 29n44 Volatility, 379 clustering of, 134n22, 199, 209n36, 210n37, 373 conditional, 209n35 implied, 27n21, 200, 208n29, 338, 360, 361 low volatility error, 199, 204n13 measuring risk via, 204n13, 208n24, 247n12, 306 Modern Portfolio Theory and, 194–196 option-implied, 362n3 percentage changes in prices and, 199, 364n8 random walks and, 194–200 time-series model, 362n3 volume-volatility relationship, 329n70 Volcker, P., 60, 98n72, 173n58 Volume relation to variance in returns, 240 trading volume as proxy measure, 330n73 volume–volatility relationship, 329n70 Volume on-balance volume (OBV), 330n73 Voth, H.-J., xxvin24, 18, 31n48, 84n10, 86n25, 87n30, 101n91, 132n12, 229, 232, 379n2 INDEX W WABSI, see Weighted-Average Bubble Strength Indicator WACC, see Weighted average cost of capital Wachtel, S. B., 286n31 Walrasian equilibrium, x, xvii, 230, 297, 328n53, 312 Walras, Leon, xxivn18, xxivn18 Warburg, P., 91n53 Warnings, about bubbles, 29n43 Watson, M. W., xvii, 220, 225, 228, 230, 248n22, 249n26, 329n63, 364n8 Weber, M., 272 Weigel, E. J., 207n23 Weighted-Average Bubble Strength Indicator (WABSI) clustering tendency, 210n36 cluster-weighted, 366n18 estimates, 365n15 evenly weighted, 366n15 microbubble WABSI, 365n15 weaker than expected readings, 357 Weighted-Average Crash Strength Indicator (WACSI) clustering tendency, 210n36 cluster-weighted, 209n36 evenly weighted, 356 WABSI and, 210n36, 356 Werner, R. A., xi, xxiiin14, xxivn16, xxvin24, 27n16, 27n22, 28n29, 32n59, 35n70, 59, 87n32, 88n36, 128, 132n12, 134n24, 160n3, 161n8, 162n9, 162n11, 164n25, 164n28, 165n37, 165n38, 166n39, 200, 225, 319n5, 327n51, 328n56, 379n3 West, K. D., 231 Whang, Y. J., 232 White, E. N., 26n10, 51, 86n26, 89n42, 150, 166n40 477 Whiteman, C. H., 224, 251n33 White noise, 253n52, 254n55 Williams, G. P., 253n51, 255n57 Willoughby, A. R., 134n22 Wilmott, P., 93n61, 93n63, 118, 132n9, 136n35, 206n19, 211n43, 211n45, 255n63, 285n18, 329n66, 346n5, 368n31 Wilson, J. W., 133n20 Winner’s curse, 278 Witter, L., 30n45 Woodford, 171n51, 212n51, 225, 230, 328n59 Woo, W. T., 249n26, 368n31 WorldCom, 65, 341 Wright, S., xi, 14 Wu, Y., 225 X Xiong, W., 83n5, 248n18, 225, 330n73 Xu, W., 287n31 Y Ying, C. C., 330n73 Youssefmir, M., 285n23 Z Zai-tech (financial engineering), 87n34 Zeckhauser, R., 284n14 Zeitgeist, xx, 12, 28n29, 159 Ziemba, R. E S., 131n7, 134n25, 285n16 Ziemba, W. T., 35n67, 86n27, 87n28, 87n29, 87n29, 60, 61, 126, 127, 131n7, 134n25, 138n43, 285n16, 286n31, 326n43 Zipf’s Law, 237, 238, 253n46 .. .Financial Market Bubbles and Crashes, Second Edition Harold L. Vogel Financial Market Bubbles and Crashes, Second Edition Features, Causes, and Effects Harold L. Vogel... underlying and almost universally accepted assumption that supply and demand in the financial markets can be portrayed and modeled in the same way as in the markets for utilitarian goods and services... extend also to MBA- and Ph.D.-level students, central bank policy makers and researchers, commercial and investment bankers, investors and speculators, and technical and fundamental market analysts