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Investors’ behavior and dynamics of ship prices: A heterogeneous agent model

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  • Alizadeh, Amir H.
  • Thanopoulou, Helen
  • Yip, Tsz Leung

Abstract

Distinguishing investors into speculators and operators, and classifying the former group into momentum and contrarian investors, we develop a heterogeneous agent model (HAM) to examine the dynamics of price of second-hand dry bulk ships. The results suggest that momentum strategies based on short-term measures of earnings perform significantly better than the contrarian or passive (buy-and-hold) strategies. The HAM seems to capture the dynamics of vessel prices and the investors’ behavior in the market for ships very well. Finally, an increase in participation of momentum investors tends to increase price volatility, whereas higher demand from contrarian investors seems to lower price variability.

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  • Alizadeh, Amir H. & Thanopoulou, Helen & Yip, Tsz Leung, 2017. "Investors’ behavior and dynamics of ship prices: A heterogeneous agent model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 98-114.
    • Handle: RePEc:eee:transe:v:106:y:2017:i:c:p:98-114
    DOI: 10.1016/j.tre.2017.07.012
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    as
    1. Matthijs Lof, 2015. "Rational Speculators, Contrarians, and Excess Volatility," Management Science, INFORMS, vol. 61(8), pages 1889-1901, August.
    2. Stefan Reitz & Ulf Slopek, 2009. "Non‐Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?," German Economic Review, Verein für Socialpolitik, vol. 10(3), pages 270-283, August.
    3. Stefan Reitz & Frank Westerhoff, 2007. "Commodity price cycles and heterogeneous speculators: a STAR–GARCH model," Empirical Economics, Springer, vol. 33(2), pages 231-244, September.
    4. Bruno Biais & Peter Bossaerts, 1998. "Asset Prices and Trading Volume in a Beauty Contest," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 307-340.
    5. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    6. Ying Kou & Liming Liu & Meifeng Luo, 2014. "Lead-lag relationship between new-building and second-hand ship prices," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(4), pages 303-327, July.
    7. Gardner, B. M. & Pettit, S. J. & Thanopoulou, H. A., 1996. "Shifting challenges for British maritime policy : A post-war review," Marine Policy, Elsevier, vol. 20(6), pages 517-524, November.
    8. Roar Adland & Haiying Jia & Siri Strandenes, 2006. "Asset Bubbles in Shipping? An Analysis of Recent History in the Drybulk Market," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(3), pages 223-233, September.
    9. Westerhoff, Frank & Reitz, Stefan, 2005. "Commodity price dynamics and the nonlinear market impact of technical traders: empirical evidence for the US corn market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 641-648.
    10. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
    11. Robin Greenwood & Samuel G. Hanson, 2015. "Waves in Ship Prices and Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(1), pages 55-109.
    12. Ellen, Saskia ter & Zwinkels, Remco C.J., 2010. "Oil price dynamics: A behavioral finance approach with heterogeneous agents," Energy Economics, Elsevier, vol. 32(6), pages 1427-1434, November.
    13. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    14. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    15. Nikos C. Papapostolou & Nikos K. Nomikos & Panos K. Pouliasis & Ioannis Kyriakou, 2014. "Investor Sentiment for Real Assets: The Case of Dry Bulk Shipping Market," Review of Finance, European Finance Association, vol. 18(4), pages 1507-1539.
    16. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    17. Gkochari, Christiana C., 2015. "Optimal investment timing in the dry bulk shipping sector," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 102-109.
    18. Manolis G. Kavussanos & Amir H. Alizadeh, 2002. "Efficient pricing of ships in the dry bulk sector of the shipping industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 29(3), pages 303-330.
    19. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    20. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    21. Mordecai Ezekiel, 1938. "The Cobweb Theorem," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 52(2), pages 255-280.
    22. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    23. Rau, Philipp & Spinler, Stefan, 2016. "Investment into container shipping capacity: A real options approach in oligopolistic competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 130-147.
    24. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    25. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    26. Haralambides, H.E. & Tsolakis, S.D. & Cridland, C., 2004. "3. Econometric Modelling Of Newbuilding And Secondhand Ship Prices," Research in Transportation Economics, Elsevier, vol. 12(1), pages 65-105, January.
    27. Alizadeh, Amir H. & Nomikos, Nikos K., 2007. "Investment timing and trading strategies in the sale and purchase market for ships," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 126-143, January.
    28. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    29. Levich, Richard M. & Thomas, Lee III, 1993. "The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach," Journal of International Money and Finance, Elsevier, vol. 12(5), pages 451-474, October.
    30. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    31. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    32. Thomas R. Palfrey & Stephanie W. Wang, 2012. "Speculative Overpricing in Asset Markets With Information Flows," Econometrica, Econometric Society, vol. 80(5), pages 1937-1976, September.
    33. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    34. Robert J. Shiller, 1987. "Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence," NBER Working Papers 2446, National Bureau of Economic Research, Inc.
    35. Manolis Kavussanos, 1997. "The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 433-443.
    36. Baak, Saang Joon, 1999. "Tests for bounded rationality with a linear dynamic model distorted by heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1517-1543, September.
    37. Chavas, Jean-Paul, 2000. "On information and market dynamics: The case of the U.S. beef market," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 833-853, June.
    38. Stephanie Wang, 2012. "Speculative Overpricing in Asset Markets with Information Flows," Working Paper 489, Department of Economics, University of Pittsburgh, revised Jan 2012.
    39. Drobetz, Wolfgang & Menzel, Christina & Schröder, Henning, 2016. "Systematic risk behavior in cyclical industries: The case of shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 129-145.
    40. Myrto Kalouptsidi, 2014. "Time to Build and Fluctuations in Bulk Shipping," American Economic Review, American Economic Association, vol. 104(2), pages 564-608, February.
    41. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    42. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    43. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    44. Stefan Reitz & Ulf Slopek, 2009. "Non‐Linear Oil Price Dynamics: A Tale of Heterogeneous Speculators?," German Economic Review, Verein für Socialpolitik, vol. 10(3), pages 270-283, August.
    45. Aror O S Ådland & Steen Koekebakker, 2004. "Market Efficiency in the Second-hand Market for Bulk Ships," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 6(1), pages 1-15, March.
    46. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    47. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    48. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

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    2. Yi Zhang & Zhe Li & Yongchao Zhang, 2020. "Validation and Calibration of an Agent-Based Model: A Surrogate Approach," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-9, January.
    3. Roar Adland & Haakon Ameln & Eirik A. Børnes, 2020. "Hedging ship price risk using freight derivatives in the drybulk market," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-18, December.
    4. Konstantinos D. Melas & Photis M. Panayides & Dimitris A. Tsouknidis, 2022. "Dynamic volatility spillovers and investor sentiment components across freight-shipping markets," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(2), pages 368-394, June.
    5. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2020. "Asset pricing with mean reversion: The case of ships," Journal of Banking & Finance, Elsevier, vol. 111(C).
    6. Maitra, Debasish & Chandra, Saurabh & Dash, Saumya Ranjan, 2020. "Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    7. Moutzouris, Ioannis C. & Nomikos, Nikos K., 2019. "Earnings yield and predictability in the dry bulk shipping industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 140-159.
    8. Görçün, Ömer Faruk, 2022. "A novel integrated MCDM framework based on Type-2 neutrosophic fuzzy sets (T2NN) for the selection of proper Second-Hand chemical tankers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

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