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Mark Kamstra

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Mark J. Kamstra & Robert J. Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Cowles Foundation Discussion Papers 1717, Cowles Foundation for Research in Economics, Yale University.

    Mentioned in:

    1. Financial Innovation and Risk Management
      by Steve Cecchetti and Kim Schoenholtz in Money, Banking and Financial Markets on 2014-12-29 19:17:22

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March.

    Mentioned in:

    1. Winter Blues: A SAD Stock Market Cycle (AER 2003) in ReplicationWiki ()

Working papers

  1. Mark J. Kamstra & Robert J. Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Cowles Foundation Discussion Papers 1717, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Consiglio, Andrea & Zenios, Stavros A., 2018. "Pricing and hedging GDP-linked bonds in incomplete markets," Journal of Economic Dynamics and Control, Elsevier, vol. 88(C), pages 137-155.
    2. Pienkowski Alex, 2017. "Debt Limits and the Structure of Public Debt," Journal of Globalization and Development, De Gruyter, vol. 8(2), pages 1-16, December.
    3. Eguren-Martin, Fernando & Meldrum, Andrew & Yan, Wen, 2020. "No-arbitrage pricing of GDP-linked bonds," Bank of England working papers 849, Bank of England.
    4. Andrea Consiglio & Michele Tumminello & Stavros A. Zenios, 2018. "Pricing Sovereign Contingent Convertible Debt," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-36, December.
    5. Diaw, Abdou & Bacha, Obiyathulla Ismath & Lahsasna, Ahcene, 2011. "Public Sector Funding and Debt Management: A Case for GDP-Linked Sukuk," MPRA Paper 46008, University Library of Munich, Germany, revised 2011.
    6. Stavros A. Zenios, 2013. "The Cyprus Debt: Perfect Crisis and a Way Forward," Cyprus Economic Policy Review, University of Cyprus, Economics Research Centre, vol. 7(1), pages 3-45, June.
    7. Giuseppe Grande & Ignazio Visco, 2010. "A public guarantee of a minimum return to defined contribution pension scheme members," Temi di discussione (Economic working papers) 762, Bank of Italy, Economic Research and International Relations Area.
    8. Sarah Mouabbi & Jean-Paul Renne & Jean-Guillaume Sahuc, 2021. "Debt-Stabilizing Properties of GDP-Linked Securities: A Macro-Finance Perspective," Working papers 844, Banque de France.
    9. Consiglio, Andrea & Zenios, Stavros A., 2015. "The Case for Contingent Convertible Debt for Sovereignst," Working Papers 15-13, University of Pennsylvania, Wharton School, Weiss Center.
    10. Nicolas Carnot & Stéphanie Pamies Sumner, 2017. "GDP-linked Bonds: Some Simulations on EU Countries," European Economy - Discussion Papers 073, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    11. Robert J. Shiller, 2014. "Speculative Asset Prices (Nobel Prize Lecture)," Cowles Foundation Discussion Papers 1936, Cowles Foundation for Research in Economics, Yale University.
    12. Consiglio Andrea & Zenios Stavros A., 2018. "Contingent Convertible Bonds for Sovereign Debt Risk Management," Journal of Globalization and Development, De Gruyter, vol. 9(1), pages 1-24, June.
    13. Jean-Marc Fournier & Jakob Lehr, 2018. "Issuing GDP-linked bonds: Supply and demand can match," OECD Economics Department Working Papers 1500, OECD Publishing.

  2. Ian Garrett & Mark Kamstra & Lisa Kramer, 2004. "Winter blues and time variation in the price of risk," FRB Atlanta Working Paper 2004-8, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Jacobsen, Ben & Marquering, Wessel, 2008. "Is it the weather?," Journal of Banking & Finance, Elsevier, vol. 32(4), pages 526-540, April.
    2. Tingqiu Cao & Xianhang Qian & Le Zhang, 2024. "The price of the slow lane: Traffic congestion and stock block trading premium," International Review of Finance, International Review of Finance Ltd., vol. 24(1), pages 30-52, March.
    3. Nicholas Apergis & Alexandros Gabrielsen & Lee A. Smales, 2016. "(Unusual) weather and stock returns—I am not in the mood for mood: further evidence from international markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 63-94, February.
    4. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    5. Kaustia, Markku & Rantapuska, Elias, 2013. "Does mood affect trading behavior?," SAFE Working Paper Series 4, Leibniz Institute for Financial Research SAFE.
    6. Kamstra, Mark J. & Kramer, Lisa A. & Levi, Maurice D. & Wermers, Russ, 2017. "Seasonal Asset Allocation: Evidence from Mutual Fund Flows," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(1), pages 71-109, February.
    7. Wilson, Matthew S., 2020. "Disaggregation and the equity premium puzzle," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 1-18.
    8. Matti Keloharju & Juhani T. Linnainmaa & Peter Nyberg, 2014. "Common Factors in Return Seasonalities," NBER Working Papers 20815, National Bureau of Economic Research, Inc.
    9. Shen, Yu & Yang, Qingqing & Zhao, Chenyang, 2023. "Food safety risks and defensive behavior: Evidence from health insurance," Finance Research Letters, Elsevier, vol. 58(PA).
    10. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2019. "Temperature Volatility Risk," Working Papers 2019:05, Department of Economics, University of Venice "Ca' Foscari".
    11. Qadan, Mahmoud & Kliger, Doron, 2016. "The short trading day anomaly," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 62-80.
    12. Yochi Cohen-Charash & Charles A Scherbaum & John D Kammeyer-Mueller & Barry M Staw, 2013. "Mood and the Market: Can Press Reports of Investors' Mood Predict Stock Prices?," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-15, August.
    13. Jacobsen, Ben & Marquering, Wessel, 2009. "Is it the weather? Response," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 583-587, March.
    14. Kang, Sang Hoon & Jiang, Zhuhua & Lee, Yeonjeong & Yoon, Seong-Min, 2010. "Weather effects on the returns and volatility of the Shanghai stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 91-99.
    15. Svetlana Vlady & Ekrem Tufan, PhD, 2011. "Causality Of Weather Conditions In Australian Stock Equity Returns," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(17), pages 184-197, November.
    16. Kamstra, Mark J. & Kramer, Lisa A. & Levi, Maurice D., 2012. "A careful re-examination of seasonality in international stock markets: Comment on sentiment and stock returns," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 934-956.
    17. Steven D. Dolvin & Stephanie A. Fernhaber, 2014. "Seasonal Affective Disorder and IPO underpricing: implications for young firms," Venture Capital, Taylor & Francis Journals, vol. 16(1), pages 51-68, January.
    18. Kliger, Doron & Raviv, Yaron & Rosett, Joshua & Bayer, Thomas & Page, John, 2015. "Seasonal affective disorder and seasoned art auction prices: New evidence from old masters," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 59(C), pages 74-84.
    19. Bohl, Martin T. & Goodfellow, Christiane & Bialkowski, Jedrzej, 2010. "Individual investors surpass their reputation: Trading behaviour on the Polish futures market," Economic Systems, Elsevier, vol. 34(4), pages 480-492, December.
    20. Nicholas Apergis & Rangan Gupta, 2016. "Can Weather Conditions in New York Predict South African Stock Returns?," Working Papers 201634, University of Pretoria, Department of Economics.
    21. Vidal-García, Javier & Vidal, Marta, 2014. "Seasonality and idiosyncratic risk in mutual fund performance," European Journal of Operational Research, Elsevier, vol. 233(3), pages 613-624.
    22. Song, Jian & Balvers, Ronald J., 2022. "Seasonality and momentum across national equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    23. Keef, Stephen P. & Khaled, Mohammed S., 2011. "A review of the seasonal affective disorder hypothesis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(6), pages 959-967.
    24. John R. Nofsinger & Corey A. Shank, 2019. "DEEP sleep: The impact of sleep on financial risk taking," Review of Financial Economics, John Wiley & Sons, vol. 37(1), pages 92-105, January.
    25. Ronald Doeswijk, 2008. "The Optimism Cycle: Sell in May," De Economist, Springer, vol. 156(2), pages 175-200, June.
    26. Dirk Brounen & Yair Ben-Hamo, 2009. "Calendar Anomalies: The Case of International Property Shares," The Journal of Real Estate Finance and Economics, Springer, vol. 38(2), pages 115-136, February.
    27. Svetlana Vlady & Ekrem Tufan & Bahattin Hamarat, 2011. "Causality Of Weather Conditions In Australian Stock Equity Returns," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(16), pages 161-175, April.
    28. Daskalakis, George & Symeonidis, Lazaros & Markellos, Raphael, 2009. "Does the weather affect stock market volatility?," MPRA Paper 34128, University Library of Munich, Germany.
    29. Andrew Worthington, 2009. "An Empirical Note on Weather Effects in the Australian Stock Market," Economic Papers, The Economic Society of Australia, vol. 28(2), pages 148-154, June.
    30. Lin, Mei-Chen, 2015. "Seasonal affective disorder and investors’ response to earnings news," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 211-221.
    31. Kaplanski, Guy & Levy, Haim, 2012. "Real estate prices: An international study of seasonality's sentiment effect," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 123-146.
    32. Jacobsen, B. & Marquering, W.A., 2004. "Is it the weather?," ERIM Report Series Research in Management ERS-2004-100-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    33. Xu, Alan, 2022. "Air pollution and mediation effects in stock market, longitudinal evidence from China," International Review of Financial Analysis, Elsevier, vol. 83(C).
    34. Kaustia, Markku & Rantapuska, Elias, 2016. "Does mood affect trading behavior?," Journal of Financial Markets, Elsevier, vol. 29(C), pages 1-26.
    35. Shanaev, Savva & Shuraeva, Arina & Fedorova, Svetlana, 2022. "The Groundhog Day stock market anomaly," Finance Research Letters, Elsevier, vol. 47(PA).
    36. Muhammad Fayyaz Sheikh & Syed Zulfiqar Ali Shah & Shahid Mahmood, 2017. "Weather Effects on Stock Returns and Volatility in South Asian Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 24(2), pages 75-107, June.
    37. Frühwirth, Manfred & Sögner, Leopold, 2015. "Weather and SAD related mood effects on the financial market," The Quarterly Review of Economics and Finance, Elsevier, vol. 57(C), pages 11-31.
    38. Tihana Škrinjarić & Branka Marasović & Boško Šego, 2021. "Does the Croatian Stock Market Have Seasonal Affective Disorder?," JRFM, MDPI, vol. 14(2), pages 1-16, February.
    39. Michael Donadelli & Marcus Jüppner & Antonio Paradiso & Christian Schlag, 2021. "Computing Macro-Effects and Welfare Costs of Temperature Volatility: A Structural Approach," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 347-394, August.
    40. Kamstra, Mark J. & Kramer, Lisa A. & Levi, Maurice D., 2009. "Is it the weather? Comment," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 578-582, March.

  3. Glen Donaldson & Mark Kamstra, 2004. "Volatility forecasts, trading volume, and the ARCH versus option-implied volatility trade-off," FRB Atlanta Working Paper 2004-6, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Christophe Perignon & D. Smith, 2009. "The Level and Quality of Value-at-Risk Disclosure by Commercial Banks," Post-Print hal-00496102, HAL.
    3. Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
    4. Le, Van & Zurbruegg, Ralf, 2014. "Forecasting option smile dynamics," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 32-45.
    5. Allan Timmermann, 2018. "Forecasting Methods in Finance," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 449-479, November.
    6. Luca Di Persio & Matteo Garbelli & Kai Wallbaum, 2021. "Forward-Looking Volatility Estimation for Risk-Managed Investment Strategies during the COVID-19 Crisis," Risks, MDPI, vol. 9(2), pages 1-16, February.
    7. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
    8. Shengli Chen & Zili Zhang, 2019. "Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism," Papers 1912.11059, arXiv.org.
    9. Kozarski, R., 2013. "Pricing and hedging in the VIX derivative market," Other publications TiSEM 221fefe0-241e-4914-b6bd-c, Tilburg University, School of Economics and Management.
    10. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    11. Todorova, Neda & Souček, Michael, 2014. "The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range," Economic Modelling, Elsevier, vol. 36(C), pages 332-340.
    12. Keith Pilbeam & Kjell Langeland, 2015. "Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts," International Economics and Economic Policy, Springer, vol. 12(1), pages 127-142, March.
    13. Liu, Min & Taylor, James W. & Choo, Wei-Chong, 2020. "Further empirical evidence on the forecasting of volatility with smooth transition exponential smoothing," Economic Modelling, Elsevier, vol. 93(C), pages 651-659.
    14. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
    15. Wing Hong Chan & Ranjini Jha & Madhu Kalimipalli, 2009. "The Economic Value Of Using Realized Volatility In Forecasting Future Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 32(3), pages 231-259, September.
    16. Nicholas Taylor, 2008. "The predictive value of temporally disaggregated volatility: evidence from index futures markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 721-742.
    17. Ma, Chaoqun & Mi, Xianhua & Cai, Zongwu, 2020. "Nonlinear and time-varying risk premia," China Economic Review, Elsevier, vol. 62(C).
    18. Le, Van & Zurbruegg, Ralf, 2010. "The role of trading volume in volatility forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(5), pages 533-555, December.
    19. Liu, Zhicao & Ye, Yong & Ma, Feng & Liu, Jing, 2017. "Can economic policy uncertainty help to forecast the volatility: A multifractal perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 181-188.
    20. T. Bazhenov & D. Fantazzini, 2019. "Forecasting Realized Volatility of Russian stocks using Google Trends and Implied Volatility," Russian Journal of Industrial Economics, MISIS, vol. 12(1).
    21. Antonakakis, Nikolaos & Floros, Christos & Kizys, Renatas, 2016. "Dynamic spillover effects in futures markets: UK and US evidence," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 406-418.
    22. Ana-Maria Fuertes & Elena Kalotychou & Natasa Todorovic, 2015. "Daily volume, intraday and overnight returns for volatility prediction: profitability or accuracy?," Review of Quantitative Finance and Accounting, Springer, vol. 45(2), pages 251-278, August.
    23. Fuertes, Ana-Maria & Izzeldin, Marwan & Kalotychou, Elena, 2009. "On forecasting daily stock volatility: The role of intraday information and market conditions," International Journal of Forecasting, Elsevier, vol. 25(2), pages 259-281.
    24. Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
    25. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    26. Kao, Yu-Sheng & Chuang, Hwei-Lin & Ku, Yu-Cheng, 2020. "The empirical linkages among market returns, return volatility, and trading volume: Evidence from the S&P 500 VIX Futures," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

  4. Glen Donaldson & Mark Kamstra & Lisa Kramer, 2003. "Stare down the barrel and center the crosshairs: Targeting the ex ante equity premium," FRB Atlanta Working Paper 2003-4, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Hsu, Jason C., 2012. "What drives equity market non-participation?," The North American Journal of Economics and Finance, Elsevier, vol. 23(1), pages 86-114.

  5. Mark Kamstra & Lisa Kramer & Maurice D. Levi, 2002. "Winter blues: a SAD stock market cycle," FRB Atlanta Working Paper 2002-13, Federal Reserve Bank of Atlanta.

    Cited by:

    1. Baillon, Aurélien & Koellinger, Philipp D. & Treffers, Theresa, 2016. "Sadder but wiser: The effects of emotional states on ambiguity attitudes," Journal of Economic Psychology, Elsevier, vol. 53(C), pages 67-82.
    2. Lepori, Gabriele M., 2015. "Investor mood and demand for stocks: Evidence from popular TV series finales," Journal of Economic Psychology, Elsevier, vol. 48(C), pages 33-47.
    3. Hwang, Byoung-Hyoun, 2011. "Country-specific sentiment and security prices," Journal of Financial Economics, Elsevier, vol. 100(2), pages 382-401, May.
    4. Yihao Zhang & Yu Jiang & Yongji Guo, 2017. "The effects of haze pollution on stock performances: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 49(23), pages 2226-2237, May.
    5. Andrew W. Lo & Dmitry V. Repin & Brett N. Steenbarger, 2005. "Fear and Greed in Financial Markets: A Clinical Study of Day-Traders," NBER Working Papers 11243, National Bureau of Economic Research, Inc.
    6. Christopher Boyce & Mikolaj Czajkowski & Nick Hanley & Charles Noussair & Michael Townsend & Steve Tucker, 2015. "The effects of emotions on preferences and choices for public goods," Discussion Papers in Environment and Development Economics 2015-08, University of St. Andrews, School of Geography and Sustainable Development.
    7. Lee, Li Way, 2010. "The mood of a firm," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(6), pages 615-618, December.
    8. Qadan, Mahmoud & Nisani, Doron & Eichel, Ron, 2022. "Irregularities in forward-looking volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 489-501.
    9. Terence Tai-Leung Chong & Siqi Hou, 2021. "Will stock rise on Valentine’s Day?," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 14(5), pages 646-667, May.
    10. Jacobsen, Ben & Marquering, Wessel, 2008. "Is it the weather?," Journal of Banking & Finance, Elsevier, vol. 32(4), pages 526-540, April.
    11. Stefanescu, Răzvan & Dumitriu, Ramona, 2016. "The impact of the Great Lent and of the Nativity Fast on the Bucharest Stock Exchange," MPRA Paper 89023, University Library of Munich, Germany, revised 22 Dec 2016.
    12. James J. Forest & Ben S. Branch & Brian T. Berry, 2024. "Trading Activity in the Corporate Bond Market: A SAD Tale of Macro-Announcements and Behavioral Seasonality?," Risks, MDPI, vol. 12(5), pages 1-25, May.
    13. Tingqiu Cao & Xianhang Qian & Le Zhang, 2024. "The price of the slow lane: Traffic congestion and stock block trading premium," International Review of Finance, International Review of Finance Ltd., vol. 24(1), pages 30-52, March.
    14. Jie Hou & Wendong Shi & Jingwei Sun, 2019. "Stock Returns, weather, and air conditioning," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-10, July.
    15. Kaplanski, Guy & Levy, Haim, 2010. "Sentiment and stock prices: The case of aviation disasters," Journal of Financial Economics, Elsevier, vol. 95(2), pages 174-201, February.
    16. Christos Floros, 2011. "On the relationship between weather and stock market returns," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 28(1), pages 5-13, March.
    17. Balázs Zélity, 2024. "Seasonality and consumer confidence," Bulletin of Economic Research, Wiley Blackwell, vol. 76(3), pages 813-821, July.
    18. Nicholas Apergis & Alexandros Gabrielsen & Lee A. Smales, 2016. "(Unusual) weather and stock returns—I am not in the mood for mood: further evidence from international markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 63-94, February.
    19. Kim, Jae H., 2017. "Stock returns and investors' mood: Good day sunshine or spurious correlation?," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 94-103.
    20. Hyein Shim & Maria H. Kim & Doojin Ryu, 2017. "Effects of intraday weather changes on asset returns and volatilities," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 35(2), pages 301-330.
    21. Yun Zhang & Qun Wu & Ting Zhang & Lingxiao Yang, 2022. "Vulnerability and fraud: evidence from the COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    22. Joëts, Marc, 2015. "Heterogeneous beliefs, regret, and uncertainty: The role of speculation in energy price dynamics," European Journal of Operational Research, Elsevier, vol. 247(1), pages 204-215.
    23. Lee, Yuan-Ming & Wang, Kuan-Min, 2011. "The effectiveness of the sunshine effect in Taiwan's stock market before and after the 1997 financial crisis," Economic Modelling, Elsevier, vol. 28(1), pages 710-727.
    24. Yuan Li, 2022. "Mood Beta, Sentiment and Stock Returns in China," SAGE Open, , vol. 12(1), pages 21582440221, February.
    25. Corrado Giulietti & Mirco Tonin & Michael Vlassopoulos, 2018. "When the Market Drives you Crazy: Stock Market Returns and Fatal Car Accidents," CESifo Working Paper Series 7182, CESifo.
    26. Apergis, Nicholas & Gupta, Rangan, 2017. "Can (unusual) weather conditions in New York predict South African stock returns?," Research in International Business and Finance, Elsevier, vol. 41(C), pages 377-386.
    27. Wu, Qinqin & Chou, Robin K. & Lu, Jing, 2020. "How does air pollution-induced fund-manager mood affect stock markets in China?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    28. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    29. Stefanescu, Răzvan & Dumitriu, Ramona, 2020. "Efectul Turn-of-the-Year pe piaţa valutară din România [The Turn-of-the-Year Effect in the Romanian foreign exchange market]," MPRA Paper 99365, University Library of Munich, Germany, revised 30 Mar 2020.
    30. Dumitriu, Ramona & Stefanescu, Razvan & Nistor, Costel, 2012. "The Halloween effect during quiet and turbulent times," MPRA Paper 41539, University Library of Munich, Germany, revised 25 Sep 2012.
    31. Fjesme, Sturla Lyngnes & Lv, Jin Roc & Shekhar, Chander, 2023. "The world cup in football and the US IPO market," Journal of Corporate Finance, Elsevier, vol. 80(C).
    32. Razvan STEFANESCU & Ramona DUMITRIU, 2011. "The SAD Cycle for the Bucharest Stock Exchange," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 372-377.
    33. Berument Hakan & Akdi Yilmaz & Atakan Cemal, 2005. "An Empirical Analysis of Istanbul Stock Exchange Sub-Indexes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(3), pages 1-14, September.
    34. Guo, Biao & Luo, Xingguo & Zhang, Ziding, 2014. "Sell in May and Go Away: Evidence from China," Finance Research Letters, Elsevier, vol. 11(4), pages 362-368.
    35. Gavriilidis, Konstantinos & Kallinterakis, Vasileios & Tsalavoutas, Ioannis, 2016. "Investor mood, herding and the Ramadan effect," Journal of Economic Behavior & Organization, Elsevier, vol. 132(S), pages 23-38.
    36. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    37. John E. Grable & Michael J. Roszkowski, 2008. "The influence of mood on the willingness to take financial risks," Journal of Risk Research, Taylor & Francis Journals, vol. 11(7), pages 905-923, October.
    38. Brian Lucey, 2010. "Lunar seasonality in precious metal returns?," Applied Economics Letters, Taylor & Francis Journals, vol. 17(9), pages 835-838.
    39. Kaplanski, Guy & Levy, Haim, 2010. "Exploitable Predictable Irrationality: The FIFA World Cup Effect on the U.S. Stock Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 535-553, April.
    40. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    41. He, Ling T. & Casey, K.M., 2015. "Forecasting ability of the investor sentiment endurance index: The case of oil service stock returns and crude oil prices," Energy Economics, Elsevier, vol. 47(C), pages 121-128.
    42. Palomino, F.A. & Renneboog, L.D.R. & Zhang, C., 2008. "Information Salience, Investor Sentiment, and Stock Returns : The Case of British Soccer Betting," Discussion Paper 2008-99, Tilburg University, Center for Economic Research.
    43. Gennaro Bernile & Vineet Bhagwat & Ambrus Kecskés & Phuong‐Anh Nguyen, 2021. "Are the risk attitudes of professional investors affected by personal catastrophic experiences?," Financial Management, Financial Management Association International, vol. 50(2), pages 455-486, June.
    44. Beladi, Hamid & Chao, Chi Chur & Hu, May, 2016. "Another January effect—Evidence from stock split announcements," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 123-138.
    45. Baddeley, M. & Burke, C. & Schultz, W. & Tobler, P., 2012. "Herding in Financial Behaviour: A Behavioural and Neuroeconomic Analysis of Individual Differences," Cambridge Working Papers in Economics 1225, Faculty of Economics, University of Cambridge.
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    320. Claus, Edda & Nguyen, Viet Hoang, 2018. "Consumptor economicus: How do consumers form expectations on economic variables?," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 254-275.
    321. Zhou Tianbao & Li Xinghao & Zhao Junguang, 2022. "Solar Term Anomaly in China Stock Market: Evidence from Shanghai Index," Papers 2203.12603, arXiv.org, revised Feb 2023.
    322. Kostopoulos, Dimitrios & Meyer, Steffen & Uhr, Charline, 2020. "Google search volume and individual investor trading," Journal of Financial Markets, Elsevier, vol. 49(C).
    323. Weng, Pei-Shih, 2018. "Lucky issuance: The role of numerological superstitions in irrational return premiums," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 79-91.
    324. Lu, Jing & Chou, Robin K., 2012. "Does the weather have impacts on returns and trading activities in order-driven stock markets? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 79-93.
    325. Durand, Robert B. & Khuu, Joyce & Smales, Lee A., 2023. "Lost in translation. When sentiment metrics for one market are derived from two different languages," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    326. Maggie Rong Hu & Adrian D. Lee, 2020. "Outshine to Outbid: Weather-Induced Sentiment and the Housing Market," Management Science, INFORMS, vol. 66(3), pages 1440-1472, March.
    327. Kostopoulos, Dimitrios & Meyer, Steffen & Uhr, Charline, 2022. "Ambiguity about volatility and investor behavior," Journal of Financial Economics, Elsevier, vol. 145(1), pages 277-296.
    328. Treffers, T. & Koellinger, Ph.D. & Picot, A.O., 2012. "In the Mood for Risk? A Random-Assignment Experiment Addressing the Effects of Moods on Risk Preferences," ERIM Report Series Research in Management ERS-2012-014-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    329. Tefft, Nathan, 2012. "Mental health and employment: The SAD story," Economics & Human Biology, Elsevier, vol. 10(3), pages 242-255.
    330. Claudio Boido & Antonio Fasano, 2015. "CAPM with Sentiment," Journal of Financial Management, Markets and Institutions, Società editrice il Mulino, issue 2, pages 265-288, December.
    331. Ghosh, Saibal, 2023. "Does climate legislation matter for bank lending? Evidence from MENA countries," Ecological Economics, Elsevier, vol. 212(C).
    332. Mugerman, Yevgeny & Yidov, Orr & Wiener, Zvi, 2020. "By the light of day: The effect of the switch to winter time on stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    333. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    334. Dowling, Michael & Lucey, Brian M., 2008. "Robust global mood influences in equity pricing," Journal of Multinational Financial Management, Elsevier, vol. 18(2), pages 145-164, April.
    335. Wu, Qinqin & Hao, Ying & Lu, Jing, 2018. "Air pollution, stock returns, and trading activities in China," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 342-365.
    336. Rupel Nargunam & William W. S. Wei & N. Anuradha, 2021. "Investigating seasonality, policy intervention and forecasting in the Indian gold futures market: a comparison based on modeling non-constant variance using two different methods," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
    337. Sperb, Luis Felipe Costa & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2019. "Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 35(1), pages 321-335.
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    340. Yasmeen Idilbi-Bayaa & Mahmoud Qadan, 2022. "Tell Me Why I Do Not Like Mondays," Mathematics, MDPI, vol. 10(11), pages 1-22, May.
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    Cited by:

    1. Mark Kamstra, 2003. "Pricing firms on the basis of fundamentals," Economic Review, Federal Reserve Bank of Atlanta, vol. 88(Q1), pages 49-70.

  7. Donaldson, R.G. & Kamstra, M., 2001. "Volatility Forecasts, Trading Volume and the ARCH vs. Option-Implied Volatility Tradeoff," Discussion Papers dp01-1, Department of Economics, Simon Fraser University.

    Cited by:

    1. Gonzalez, Liliana & Powell, John G. & Shi, Jing & Wilson, Antony, 2005. "Two centuries of bull and bear market cycles," International Review of Economics & Finance, Elsevier, vol. 14(4), pages 469-486.
    2. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.

  8. Kamstra, M.J. & Kramer, L.A. & Levi, M.D., 1998. "Losing Sleep at the Market: The Daylight-Savings Anomaly," Discussion Papers dp98-04, Department of Economics, Simon Fraser University.

    Cited by:

    1. Baillon, Aurélien & Koellinger, Philipp D. & Treffers, Theresa, 2016. "Sadder but wiser: The effects of emotional states on ambiguity attitudes," Journal of Economic Psychology, Elsevier, vol. 53(C), pages 67-82.
    2. Daniel Kuehnle & Christoph Wunder, 2016. "Using the Life Satisfaction Approach to Value Daylight Savings Time Transitions: Evidence from Britain and Germany," Journal of Happiness Studies, Springer, vol. 17(6), pages 2293-2323, December.
    3. Falato, Antonio, 2009. "Happiness maintenance and asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1247-1262, June.
    4. Jacobsen, Ben & Marquering, Wessel, 2008. "Is it the weather?," Journal of Banking & Finance, Elsevier, vol. 32(4), pages 526-540, April.
    5. Stefanescu, Răzvan & Dumitriu, Ramona, 2016. "The impact of the Great Lent and of the Nativity Fast on the Bucharest Stock Exchange," MPRA Paper 89023, University Library of Munich, Germany, revised 22 Dec 2016.
    6. Patrick L. Brockett & Mulong Wang & Chuanhou Yang, 2005. "Weather Derivatives and Weather Risk Management," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 8(1), pages 127-140, March.
    7. Tomas Havranek & Zuzana Irsova & Dominik Herman, 2016. "Does Daylight Saving Save Energy? A Meta-Analysis," Working Papers IES 2016/24, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2016.
    8. Levy, Ori & Galili, Itai, 2008. "Stock purchase and the weather: Individual differences," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 755-767, September.
    9. Giuntella, Osea & Han, Wei & Mazzonna, Fabrizio, 2016. "Circadian Rhythms, Sleep and Cognitive Skills: Evidence from an Unsleeping Giant," IZA Discussion Papers 9774, Institute of Labor Economics (IZA).
    10. Tingqiu Cao & Xianhang Qian & Le Zhang, 2024. "The price of the slow lane: Traffic congestion and stock block trading premium," International Review of Finance, International Review of Finance Ltd., vol. 24(1), pages 30-52, March.
    11. Nicholas Apergis & Alexandros Gabrielsen & Lee A. Smales, 2016. "(Unusual) weather and stock returns—I am not in the mood for mood: further evidence from international markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 30(1), pages 63-94, February.
    12. Glenn Boyle & Brett Walter, 2003. "Reflected glory and failure: international sporting success and the stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 13(3), pages 225-235.
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    14. Ender Demir, 2015. "Aviation Accidents and Stock Market Reaction: Evidence from Borsa Istanbul," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 3(1), pages 51-56.
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    44. Mehra, Rajnish & Sah, Raaj, 2002. "Mood fluctuations, projection bias, and volatility of equity prices," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 869-887, May.
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    47. Hugo Salas & Pedro Ignacio Hancevic, 2023. "The unexpected effects of daylight-saving time: Traffic accidents in Mexican municipalities," EconoQuantum, Revista de Economia y Finanzas, Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas, Departamento de Metodos Cuantitativos y Maestria en Economia., vol. 20(1), pages 1-29, Enero-Jun.
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    50. Dimic, Nebojsa & Neudl, Manfred & Orlov, Vitaly & Äijö, Janne, 2018. "Investor sentiment, soccer games and stock returns," Research in International Business and Finance, Elsevier, vol. 43(C), pages 90-98.
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    58. Weiqiang Tan & Jian Zhang, 2021. "Good Days, Bad Days: Stock Market Fluctuation and Taxi Tipping Decisions," Management Science, INFORMS, vol. 67(6), pages 3965-3984, June.
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    63. Svetlana Vlady & Ekrem Tufan, PhD, 2011. "Causality Of Weather Conditions In Australian Stock Equity Returns," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(17), pages 184-197, November.
    64. Mirza, Faisal Mehmood & Bergland, Olvar, 2011. "The impact of daylight saving time on electricity consumption: Evidence from southern Norway and Sweden," Energy Policy, Elsevier, vol. 39(6), pages 3558-3571, June.
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  9. Kamstra, M. & Kennedy, P. & Suan, T.-K., 1998. "Combining Bond Rating Forecasts Using Logit," Discussion Papers dp98-10, Department of Economics, Simon Fraser University.

    Cited by:

    1. Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015. "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 273-292.
    2. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    3. Bao, Xin & Han, Meini & Lau, Raymond & Xu, Xiaowei, 2024. "Corporate integrity culture and credit rating assessment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 93(C).
    4. Guglielmo Maria Caporale & Roman Matousek & Chris Stewart, 2009. "Rating Assignments: Lessons from International Banks," CESifo Working Paper Series 2618, CESifo.
    5. Shen, Chung-Hua & Huang, Yu-Li & Hasan, Iftekhar, 2012. "Asymmetric benchmarking in bank credit rating," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 171-193.
    6. Matthies, Alexander B., 2013. "Empirical research on corporate credit-ratings: A literature review," SFB 649 Discussion Papers 2013-003, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    7. Mafudi & Negina Kencono Putri, 2012. "The Impact of Corporate Governance Implementation on Public Company Bond Ratings and Yield: a Case of Indonesia," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 8(6), pages 88-98, December.
    8. Rubina Shaheen & Attiya Yasmin Javid, 2014. "Effect of Credit Rating on Firm Performance and Stock Return; Evidence form KSE Listed Firms," PIDE-Working Papers 2014:104, Pakistan Institute of Development Economics.
    9. Jaspreet Kaur & Madhu Vij & Ajay Kumar Chauhan, 2023. "Signals influencing corporate credit ratings—a systematic literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 50(1), pages 91-114, March.
    10. Rosemarie Bröker Bone & Eduardo P Ribeiro, 2013. "Informational content of corporate ratings in a developing country: the case of Brazilian firms," Economics Bulletin, AccessEcon, vol. 33(1), pages 35-45.
    11. Kamphol Panyagometh & Gordon S. Roberts, 2010. "Do Lead Banks Exploit Syndicate Participants? Evidence from Ex Post Risk," Financial Management, Financial Management Association International, vol. 39(1), pages 273-299, March.
    12. Riddha Basu & James P. Naughton, 2020. "The Real Effects of Financial Statement Recognition: Evidence from Corporate Credit Ratings," Management Science, INFORMS, vol. 66(4), pages 1672-1691, April.
    13. Themistokles Lazarides & Evaggelos Drimpetas, 2016. "Defining the factors of Fitch rankings in the European banking sector," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 315-339, August.
    14. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
    15. Graziani, Carlo & Rosner, Robert & Adams, Jennifer M. & Machete, Reason L., 2021. "Probabilistic recalibration of forecasts," International Journal of Forecasting, Elsevier, vol. 37(1), pages 1-27.
    16. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan-level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
    17. Golbayani, Parisa & Florescu, Ionuţ & Chatterjee, Rupak, 2020. "A comparative study of forecasting corporate credit ratings using neural networks, support vector machines, and decision trees," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    18. Patrick Behr & Darren J. Kisgen & Jérôme P. Taillard, 2018. "Did Government Regulations Lead to Inflated Credit Ratings?," Management Science, INFORMS, vol. 64(3), pages 1034-1054, March.
    19. Salvador, Carlos & Pastor, Jose Manuel & Fernández de Guevara, Juan, 2014. "Impact of the subprime crisis on bank ratings: The effect of the hardening of rating policies and worsening of solvency," Journal of Financial Stability, Elsevier, vol. 11(C), pages 13-31.
    20. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    21. Petropoulos, Anastasios & Siakoulis, Vasilis & Stavroulakis, Evangelos & Vlachogiannakis, Nikolaos E., 2020. "Predicting bank insolvencies using machine learning techniques," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1092-1113.
    22. Parisa Golbayani & Ionuc{t} Florescu & Rupak Chatterjee, 2020. "A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees," Papers 2007.06617, arXiv.org.
    23. Shen, Chung-Hua & Huang, Yu-Li & Hasan, Iftekhar, 2012. "Asymmetric benchmarking in bank credit rating," Bank of Finland Research Discussion Papers 13/2012, Bank of Finland.
    24. Irving Fisher Committee, 2019. "The use of big data analytics and artificial intelligence in central banking," IFC Bulletins, Bank for International Settlements, number 50.

  10. Donaldson, R.G. & Kamstra, M., 1996. "Forecasting Fundamental Asset Return Distributions and Tests for Excess Volatility and Bubbles," Discussion Papers dp96-02, Department of Economics, Simon Fraser University.

    Cited by:

    1. Lucy Ackert & William Hunter, 2001. "An Empirical Examination of the Price-Dividend Relation with Dividend Management," Journal of Financial Services Research, Springer;Western Finance Association, vol. 19(2), pages 115-129, April.

  11. Harrald, P. & Kamstra, M., 1995. "Evolving Artificial Neural Networks to Combine Financial Forecasts," Discussion Papers dp95-04, Department of Economics, Simon Fraser University.

    Cited by:

    1. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.
    2. Luis Fernando Melo & Héctor Núñez, 2004. "Combinación de Pronósticos de la Inflación en Presencia de cambios Estructurales," Borradores de Economia 286, Banco de la Republica de Colombia.

  12. Kamstra, M., 1991. "A Neural Network Test for Heteroskedasticity," Discussion Papers dp91-06, Department of Economics, Simon Fraser University.

    Cited by:

    1. Peguin-Feissolle, A., 1999. "A Comparison of the Power of Some Tests for Conditional Heteroscedasticity," G.R.E.Q.A.M. 99a22, Universite Aix-Marseille III.
    2. John Barkoulas & Nickolaos Travlos, 1998. "Chaos in an emerging capital market? The case of the Athens Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 8(3), pages 231-243.

  13. R. Glen Donaldson & Mark Kamstra, "undated". "Forecasting Fundamental Asset Return Distributions," Computing in Economics and Finance 1997 176, Society for Computational Economics.

    Cited by:

    1. Lucy Ackert & William Hunter, 2001. "An Empirical Examination of the Price-Dividend Relation with Dividend Management," Journal of Financial Services Research, Springer;Western Finance Association, vol. 19(2), pages 115-129, April.

Articles

  1. Kamstra Mark J & Shiller Robert J., 2010. "Trills Instead of T-Bills: It's Time to Replace Part of Government Debt with Shares in GDP," The Economists' Voice, De Gruyter, vol. 7(3), pages 1-5, September.

    Cited by:

    1. John H. Cochrane, 2015. "A New Structure for U.S. Federal Debt," Economics Working Papers 15108, Hoover Institution, Stanford University.
    2. Carl Christian von Weizsäcker, 2011. "Public Debt Requirements in A Regime of Price Stability," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2011_20, Max Planck Institute for Research on Collective Goods.
    3. Juan Carlos Hatchondo & Leonardo Martinez, 2012. "On the benefits of GDP-indexed government debt: lessons from a model of sovereign defaults," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 98(2Q), pages 139-157.
    4. Carl Christian von Weizsäcker, 2014. "Public Debt and Price Stability," German Economic Review, Verein für Socialpolitik, vol. 15(1), pages 42-61, February.
    5. Alessandro Missale, 2012. "Sovereign debt management and fiscal vulnerabilities," BIS Papers chapters, in: Bank for International Settlements (ed.), Threat of fiscal dominance?, volume 65, pages 157-176, Bank for International Settlements.

  2. Donaldson, R. Glen & Kamstra, Mark J. & Kramer, Lisa A., 2010. "Estimating the Equity Premium," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(4), pages 813-846, August.

    Cited by:

    1. Avdis, Efstathios & Wachter, Jessica A., 2017. "Maximum likelihood estimation of the equity premium," Journal of Financial Economics, Elsevier, vol. 125(3), pages 589-609.
    2. Efstathios Avdis & Jessica A. Wachter, 2013. "Maximum likelihood estimation of the equity premium," NBER Working Papers 19684, National Bureau of Economic Research, Inc.
    3. Kaustia, Markku & Lehtoranta, Antti & Puttonen, Vesa, 2013. "Does sophistication affect long-term return expectations? Evidence from financial advisers' exam scores," SAFE Working Paper Series 3, Leibniz Institute for Financial Research SAFE.
    4. Tatiana PÎŞCHINA & Romeo Fortuna, 2017. "Moldova’s Phenomenon: Can Foreign Investments Help Out of the Poverty Circle?," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 3, ejes_v3_i.
    5. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Discussion Papers 46/2020, Deutsche Bundesbank.
    6. Kuntz, Laura-Chloé, 2020. "Beta dispersion and market timing," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 235-256.

  3. Kamstra, Mark J. & Kramer, Lisa A. & Levi, Maurice D., 2009. "Is it the weather? Comment," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 578-582, March.

    Cited by:

    1. Wagner, Moritz & Lee, John Byong-Tek & Margaritis, Dimitris, 2022. "Mutual fund flows and seasonalities in stock returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    2. Qi, Howard, 2011. "Value and capacity of tax shields: An analysis of the slicing approach," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 166-173, January.
    3. Mamatzakis, E, 2013. "Does weather affect US bank loan efficiency?," MPRA Paper 51616, University Library of Munich, Germany.
    4. Doyle, John R. & Chen, Catherine Huirong, 2012. "A multidimensional classification of market anomalies: Evidence from 76 price indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1237-1257.
    5. Kamstra, Mark J. & Kramer, Lisa A. & Levi, Maurice D., 2012. "A careful re-examination of seasonality in international stock markets: Comment on sentiment and stock returns," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 934-956.
    6. Shigeki Sakakibara & Takashi Yamasaki & Katsuhiko Okada, 2013. "The Calendar Structure of the Japanese Stock Market: The ‘Sell in May Effect’ versus the ‘Dekansho-bushi Effect’," International Review of Finance, International Review of Finance Ltd., vol. 13(2), pages 161-185, June.
    7. Coakley, Jerry & Kuo, Jing-Ming & Wood, Andrew, 2012. "The School’s Out effect: A new seasonal anomaly!," The British Accounting Review, Elsevier, vol. 44(3), pages 133-143.
    8. Keef, Stephen P. & Khaled, Mohammed S., 2011. "A review of the seasonal affective disorder hypothesis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(6), pages 959-967.
    9. Khaled, Mohammed S. & Keef, Stephen P., 2013. "Seasonal affective disorder: onset and recovery," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 42(C), pages 136-139.
    10. Dorfleitner, Gregor & Wimmer, Maximilian, 2010. "The pricing of temperature futures at the Chicago Mercantile Exchange," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1360-1370, June.
    11. Degenhardt, Thomas & Auer, Benjamin R., 2018. "The “Sell in May” effect: A review and new empirical evidence," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 169-205.
    12. Wei-han Liu, 2013. "Lunar calendar effect: evidence of the Chinese Farmer's Calendar on the equity markets in East Asia," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 18(4), pages 560-593.
    13. Frühwirth, Manfred & Sögner, Leopold, 2015. "Weather and SAD related mood effects on the financial market," The Quarterly Review of Economics and Finance, Elsevier, vol. 57(C), pages 11-31.
    14. Tihana Škrinjarić & Branka Marasović & Boško Šego, 2021. "Does the Croatian Stock Market Have Seasonal Affective Disorder?," JRFM, MDPI, vol. 14(2), pages 1-16, February.

  4. Mark Kamstra & Rpbert J. Shiller, 2008. "The Case for Trills: Giving Canadians and their Pension Funds a Stake in the Wealth of the Nation," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 271, August.

    Cited by:

    1. Mark J. Kamstra & Robert J. Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Cowles Foundation Discussion Papers 1717, Cowles Foundation for Research in Economics, Yale University.
    2. Norma L. Nielson, 2012. "Annuities and Your Nest Egg: Reforms to Promote Optimal Annuitization of Retirement Capital," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 358, August.
    3. Arthur J. Cockfield, 2008. "Finding Silver Linings in the Storm: An Evaluation of Recent Canada-US Crossborder Developments," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 272, September.
    4. Peter W. Hogg, 2008. "A Question of Parliamentary power: Criminal Law and the Control of Greenhouse Gas Emissions," C.D. Howe Institute Backgrounder, C.D. Howe Institute, issue 114, August.

  5. R. Glen Donaldson & Mark J. Kamstra, 2005. "Volatility Forecasts, Trading Volume, And The Arch Versus Option‐Implied Volatility Trade‐Off," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(4), pages 519-538, December.
    See citations under working paper version above.
  6. Garrett, Ian & Kamstra, Mark J. & Kramer, Lisa A., 2005. "Winter blues and time variation in the price of risk," Journal of Empirical Finance, Elsevier, vol. 12(2), pages 291-316, March.
    See citations under working paper version above.
  7. Mark Kamstra & Moshe Milevsky, 2005. "Waiting for returns: using space-time duality to calibrate financial diffusions," Quantitative Finance, Taylor & Francis Journals, vol. 5(3), pages 237-244.

    Cited by:

    1. Vodopivec, Neža & Miller-Hooks, Elise, 2017. "An optimal stopping approach to managing travel-time uncertainty for time-sensitive customer pickup," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 22-37.

  8. Mark Kamstra, 2003. "Pricing firms on the basis of fundamentals," Economic Review, Federal Reserve Bank of Atlanta, vol. 88(Q1), pages 49-70.

    Cited by:

    1. Mark J. Kamstra & Robert J. Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Cowles Foundation Discussion Papers 1717, Cowles Foundation for Research in Economics, Yale University.
    2. Mark Kamstra & Rpbert J. Shiller, 2008. "The Case for Trills: Giving Canadians and their Pension Funds a Stake in the Wealth of the Nation," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 271, August.
    3. Thillaikkoothan Palanichamy & Parthajit Kayal, 2022. "Multiple Dimensions of Cyclicality in Investing," Working Papers 2022-216, Madras School of Economics,Chennai,India.
    4. Joshi, Ravi & Narayanan, Rajesh P. & Pace, R. Kelley, 2023. "Valuation when disaster risks increase at an increasing rate," Economics Letters, Elsevier, vol. 224(C).
    5. Guglielmo D'Amico & Riccardo De Blasis, 2020. "A review of the Dividend Discount Model: from deterministic to stochastic models," Papers 2001.00465, arXiv.org.

  9. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March.
    See citations under working paper version above.
  10. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2002. "Losing Sleep at the Market: The Daylight Saving Anomaly: Reply," American Economic Review, American Economic Association, vol. 92(4), pages 1257-1263, September.

    Cited by:

    1. Daniel Kuehnle & Christoph Wunder, 2016. "Using the Life Satisfaction Approach to Value Daylight Savings Time Transitions: Evidence from Britain and Germany," Journal of Happiness Studies, Springer, vol. 17(6), pages 2293-2323, December.
    2. Lawrence Jin & Nicolas Ziebarth, 2016. "Sleep and Human Capital: Evidence from Daylight Saving Time," Working Papers 160001, Canadian Centre for Health Economics.
    3. Siganos, Antonios, 2019. "The daylight saving time anomaly in relation to firms targeted for mergers," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 36-43.
    4. Nower, Michael, 2024. "Losing sleep at the international market: Daylight Saving Time and exchange rates," Economics Letters, Elsevier, vol. 241(C).
    5. Joan Costa-Font & Sarah Fleche & Ricardo Pagan, 2021. "The Welfare Effects of Time Reallocation: Evidence from Daylight Saving Time," Working Papers halshs-03322741, HAL.
    6. Brian M. Lucey & Michael Dowling, 2005. "The Role of Feelings in Investor Decision‐Making," Journal of Economic Surveys, Wiley Blackwell, vol. 19(2), pages 211-237, April.
    7. Matthew J. Kotchen & Laura E. Grant, 2008. "Does Daylight Saving Time Save Energy? Evidence from a Natural Experiment in Indiana," NBER Working Papers 14429, National Bureau of Economic Research, Inc.
    8. Tihana Škrinjarić, 2018. "Testing for Seasonal Affective Disorder on Selected CEE and SEE Stock Markets," Risks, MDPI, vol. 6(4), pages 1-26, December.
    9. Joseph Engelberg & Christopher A. Parsons, 2016. "Worrying about the Stock Market: Evidence from Hospital Admissions," Journal of Finance, American Finance Association, vol. 71(3), pages 1227-1250, June.
    10. Müller, Luisa & Schiereck, Dirk & Simpson, Marc W. & Voigt, Christian, 2009. "Daylight saving effect," Journal of Multinational Financial Management, Elsevier, vol. 19(2), pages 127-138, April.
    11. Jin, Lawrence & Ziebarth, Nicolas R., 2015. "Does Daylight Saving Time Really Make Us Sick?," IZA Discussion Papers 9088, Institute of Labor Economics (IZA).
    12. John R. Nofsinger & Corey A. Shank, 2019. "DEEP sleep: The impact of sleep on financial risk taking," Review of Financial Economics, John Wiley & Sons, vol. 37(1), pages 92-105, January.
    13. Dowling, Michael & Lucey, Brian M., 2005. "Weather, biorhythms, beliefs and stock returns--Some preliminary Irish evidence," International Review of Financial Analysis, Elsevier, vol. 14(3), pages 337-355.
    14. Jonathan James, 2023. "Let there be light: Daylight saving time and road traffic collisions," Economic Inquiry, Western Economic Association International, vol. 61(3), pages 523-545, July.
    15. Chiah, Mardy & Zhong, Angel, 2021. "Tuesday Blues and the day-of-the-week effect in stock returns," Journal of Banking & Finance, Elsevier, vol. 133(C).
    16. Steigerwald, Douglas G & Conte, Marc, 2007. "Do Daylight-Saving Time Adjustments Really Impact Stock Returns?," University of California at Santa Barbara, Economics Working Paper Series qt3kd37630, Department of Economics, UC Santa Barbara.
    17. Mugerman, Yevgeny & Yidov, Orr & Wiener, Zvi, 2020. "By the light of day: The effect of the switch to winter time on stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    18. Dowling, Michael & Lucey, Brian M., 2008. "Robust global mood influences in equity pricing," Journal of Multinational Financial Management, Elsevier, vol. 18(2), pages 145-164, April.
    19. Tihana Škrinjarić & Branka Marasović & Boško Šego, 2021. "Does the Croatian Stock Market Have Seasonal Affective Disorder?," JRFM, MDPI, vol. 14(2), pages 1-16, February.

  11. Kamstra, Mark & Kennedy, Peter & Suan, Teck-Kin, 2001. "Combining Bond Rating Forecasts Using Logit," The Financial Review, Eastern Finance Association, vol. 36(2), pages 75-96, May.
    See citations under working paper version above.
  12. Lisa A. Kramer & Mark J. Kamstra & Maurice D. Levi, 2000. "Losing Sleep at the Market: The Daylight Saving Anomaly," American Economic Review, American Economic Association, vol. 90(4), pages 1005-1011, September.
    See citations under working paper version above.
  13. Kamstra, Mark & Kennedy, Peter, 1998. "Combining qualitative forecasts using logit," International Journal of Forecasting, Elsevier, vol. 14(1), pages 83-93, March.

    Cited by:

    1. Rodrigues, Bruno Dore & Stevenson, Maxwell J., 2013. "Takeover prediction using forecast combinations," International Journal of Forecasting, Elsevier, vol. 29(4), pages 628-641.
    2. Andrea Bastianin & Marzio Galeotti & Matteo Manera, 2014. "Forecasting the Oil-gasoline Price Relationship: Should We Care about the Rockets and the Feathers?," Working Papers 2014.21, Fondazione Eni Enrico Mattei.
    3. Clements, Michael P & Harvey, David I, 2006. "Forecast Encompassing Tests and Probability Forecasts," The Warwick Economics Research Paper Series (TWERPS) 774, University of Warwick, Department of Economics.
    4. Guglielmo Maria Caporale & Roman Matousek & Chris Stewart, 2009. "Rating Assignments: Lessons from International Banks," CESifo Working Paper Series 2618, CESifo.
    5. Basnet, Anup & Davis, Frederick & Walker, Thomas & Zhao, Kun, 2021. "The effect of securities class action lawsuits on mergers and acquisitions," Global Finance Journal, Elsevier, vol. 48(C).
    6. Kajal Lahiri & Liu Yang, 2015. "A Non-linear Forecast Combination Procedure for Binary Outcomes," CESifo Working Paper Series 5175, CESifo.
    7. Lewis Gaul & Jonathan Jones & Pinar Uysal, 2019. "Forecasting High-Risk Composite CAMELS Ratings," International Finance Discussion Papers 1252, Board of Governors of the Federal Reserve System (U.S.).
    8. Pauwels, Laurent & Vasnev, Andrey, 2013. "Forecast combination for U.S. recessions with real-time data," Working Papers 02/2013, University of Sydney Business School, Discipline of Business Analytics.
    9. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223, April.
    10. Kajal Lahiri & Liu Yang, 2023. "Predicting binary outcomes based on the pair-copula construction," Empirical Economics, Springer, vol. 64(6), pages 3089-3119, June.
    11. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    12. Ana-Maria Fuertes & Elena Kalotychou, 2004. "Elements in the Design of an Early Warning System for Sovereign Default," Computing in Economics and Finance 2004 231, Society for Computational Economics.
    13. Salvador, Carlos & Pastor, Jose Manuel & Fernández de Guevara, Juan, 2014. "Impact of the subprime crisis on bank ratings: The effect of the hardening of rating policies and worsening of solvency," Journal of Financial Stability, Elsevier, vol. 11(C), pages 13-31.
    14. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    15. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "Optimal design of early warning systems for sovereign debt crises," International Journal of Forecasting, Elsevier, vol. 23(1), pages 85-100.
    16. Laurent L. Pauwels & Andrey L. Vasnev, 2017. "Forecast combination for discrete choice models: predicting FOMC monetary policy decisions," Empirical Economics, Springer, vol. 52(1), pages 229-254, February.
    17. Giovanni De Luca & Alfonso Carfora, 2014. "Predicting U.S. recessions through a combination of probability forecasts," Empirical Economics, Springer, vol. 46(1), pages 127-144, February.
    18. Xiao, Liye & Wang, Jianzhou & Hou, Ru & Wu, Jie, 2015. "A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting," Energy, Elsevier, vol. 82(C), pages 524-549.
    19. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.

  14. Donaldson, R. Glen & Kamstra, Mark, 1997. "An artificial neural network-GARCH model for international stock return volatility," Journal of Empirical Finance, Elsevier, vol. 4(1), pages 17-46, January.

    Cited by:

    1. Valeriy Gavrishchaka & Supriya Banerjee, 2006. "Support Vector Machine as an Efficient Framework for Stock Market Volatility Forecasting," Computational Management Science, Springer, vol. 3(2), pages 147-160, April.
    2. Bildirici, Melike E. & Sonustun, Bahri, 2021. "Chaotic behavior in gold, silver, copper and bitcoin prices," Resources Policy, Elsevier, vol. 74(C).
    3. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
    4. Glen Donaldson & Mark Kamstra, 2004. "Volatility forecasts, trading volume, and the ARCH versus option-implied volatility trade-off," FRB Atlanta Working Paper 2004-6, Federal Reserve Bank of Atlanta.
    5. Trong‐Nghia Nguyen & Minh‐Ngoc Tran & Robert Kohn, 2022. "Recurrent conditional heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1031-1054, August.
    6. Bucci, Andrea, 2019. "Realized Volatility Forecasting with Neural Networks," MPRA Paper 95443, University Library of Munich, Germany.
    7. Kanas, Angelos & Yannopoulos, Andreas, 2001. "Comparing linear and nonlinear forecasts for stock returns," International Review of Economics & Finance, Elsevier, vol. 10(4), pages 383-398, December.
    8. Arie Preminger & Uri Ben-zion & David Wettstein, 2007. "The extended switching regression model: allowing for multiple latent state variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 457-473.
    9. Aneessa Firdaus Jumoorty & Ruben Thoplan & Jason Narsoo, 2023. "High frequency volatility forecasting: A new approach using a hybrid ANN‐MC‐GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4156-4175, October.
    10. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    11. Hamid, Shaikh A. & Iqbal, Zahid, 2004. "Using neural networks for forecasting volatility of S&P 500 Index futures prices," Journal of Business Research, Elsevier, vol. 57(10), pages 1116-1125, October.
    12. Lux, Thomas & Kaizoji, Taisei, 2007. "Forecasting volatility and volume in the Tokyo Stock Market: Long memory, fractality and regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1808-1843, June.
    13. Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," Econometric Institute Research Papers EI 2005-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Deep Kernel Gaussian Process Based Financial Market Predictions," Papers 2105.12293, arXiv.org.
    15. Wang, Yuejing & Ye, Wuyi & Jiang, Ying & Liu, Xiaoquan, 2024. "Volatility prediction for the energy sector with economic determinants: Evidence from a hybrid model," International Review of Financial Analysis, Elsevier, vol. 92(C).
    16. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    17. Maya Malinda & Jo-Hui Chen, 2022. "The forecasting of consumer exchange-traded funds (ETFs) via grey relational analysis (GRA) and artificial neural network (ANN)," Empirical Economics, Springer, vol. 62(2), pages 779-823, February.
    18. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    19. Ushir HARRILALL & Yudhvir SEETHARAM, 2015. "Forecasting changes in the South African volatility index: A comparison of methods," EuroEconomica, Danubius University of Galati, issue 2(34), pages 51-70, November.
    20. Arie Preminger & Uri Ben-Zion & David Wettstein, 2006. "Extended switching regression models with time-varying probabilities for combining forecasts," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 455-472.
    21. Manel Hamdi & Walid Chkili, 2019. "An artificial neural network augmented GARCH model for Islamic stock market volatility: Do asymmetry and long memory matter?," Working Papers 13, Economic Research Forum, revised 21 Aug 2019.
    22. Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
    23. Nenubari Ikue John & Emeka Nkoro & Jeremiah Anietie, 2021. "Time-Gap effects of crude oil prices on the foreign exchange rates: Evidence from Nigeria," Bussecon Review of Social Sciences (2687-2285), Bussecon International Academy, vol. 3(3), pages 31-44, July.
    24. M. Karanasos & J. Kim, 2003. "Moments of the ARMA--EGARCH model," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 146-166, June.
    25. Huang, Yujun, 2024. "Do ESG ETFs provide downside risk protection during Covid-19? Evidence from forecast combination models," International Review of Financial Analysis, Elsevier, vol. 94(C).
    26. Gradojevic, Nikola & Kukolj, Dragan & Adcock, Robert & Djakovic, Vladimir, 2023. "Forecasting Bitcoin with technical analysis: A not-so-random forest?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 1-17.
    27. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    28. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    29. Lucien Boulet, 2021. "Forecasting High-Dimensional Covariance Matrices of Asset Returns with Hybrid GARCH-LSTMs," Papers 2109.01044, arXiv.org.
    30. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
    31. Raffaele Mattera & Philipp Otto, 2023. "Network log-ARCH models for forecasting stock market volatility," Papers 2303.11064, arXiv.org.
    32. Almeida e Santos Nogueira, R.J. & Basturk, N. & Kaymak, U. & Costa Sousa, J.M., 2013. "Estimation of flexible fuzzy GARCH models for conditional density estimation," ERIM Report Series Research in Management ERS-2013-013-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    33. Robert Taylor, 2024. "Evaluating Credit VIX (CDS IV) Prediction Methods with Incremental Batch Learning," Papers 2408.15404, arXiv.org.
    34. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    35. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March.
    36. François-Éric Racicot & Raymond Théoret & Alain Coën, 2008. "Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 112-124, February.
    37. Guillermo Santamaría-Bonfil & Juan Frausto-Solís & Ignacio Vázquez-Rodarte, 2015. "Volatility Forecasting Using Support Vector Regression and a Hybrid Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 111-133, January.
    38. Chen, Rui & Ren, Jinjuan, 2022. "Do AI-powered mutual funds perform better?," Finance Research Letters, Elsevier, vol. 47(PA).
    39. Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2013. "Modeling and predicting the CBOE market volatility index," Textos para discussão 342, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    40. Curtis Nybo, 2021. "Sector Volatility Prediction Performance Using GARCH Models and Artificial Neural Networks," Papers 2110.09489, arXiv.org.
    41. Szabolcs Blazsek & Anna Downarowicz, 2013. "Forecasting hedge fund volatility: a Markov regime-switching approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(4), pages 243-275, April.
    42. Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
    43. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    44. Rita Laura D’Ecclesia & Daniele Clementi, 2021. "Volatility in the stock market: ANN versus parametric models," Annals of Operations Research, Springer, vol. 299(1), pages 1101-1127, April.
    45. Darrat, Ali F & Zhong, Maosen, 2000. "On Testing the Random-Walk Hypothesis: A Model-Comparison Approach," The Financial Review, Eastern Finance Association, vol. 35(3), pages 105-124, August.
    46. T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
    47. Zhang, Ningning & Lin, Aijing & Shang, Pengjian, 2017. "Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 161-173.
    48. Thierry Warin & Aleksandar Stojkov, 2021. "Machine Learning in Finance: A Metadata-Based Systematic Review of the Literature," JRFM, MDPI, vol. 14(7), pages 1-31, July.
    49. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics.
    50. Özgür Ömer Ersin & Melike Bildirici, 2023. "Financial Volatility Modeling with the GARCH-MIDAS-LSTM Approach: The Effects of Economic Expectations, Geopolitical Risks and Industrial Production during COVID-19," Mathematics, MDPI, vol. 11(8), pages 1-26, April.
    51. Xiaolong Tang & Yuping Song & Xingrui Jiao & Yankun Sun, 2024. "On Forecasting Realized Volatility for Bitcoin Based on Deep Learning PSO–GRU Model," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 2011-2033, May.
    52. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & Georgios P. Kouretas, 2006. "Regime switching and artificial neural network forecasting of the Cyprus Stock Exchange daily returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 371-383.
    53. Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
    54. Chen, Shiyi & Jeong, Kiho & Härdle, Wolfgang Karl, 2008. "Support vector regression based GARCH model with application to forecasting volatility of financial returns," SFB 649 Discussion Papers 2008-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    55. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism," Papers 2101.02736, arXiv.org.
    56. Chen Liu & Chao Wang & Minh-Ngoc Tran & Robert Kohn, 2023. "Deep Learning Enhanced Realized GARCH," Papers 2302.08002, arXiv.org, revised Oct 2023.
    57. Caio Mário Mesquita & Cristiano Arbex Valle & Adriano César Machado Pereira, 2024. "Scenario Generation for Financial Data with a Machine Learning Approach Based on Realized Volatility and Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1879-1919, May.
    58. Darrat, Ali F. & Gilley, Otis W. & Li, Bin & Wu, Yanhui, 2011. "Revisiting the risk/return relations in the Asian Pacific markets: New evidence from alternative models," Journal of Business Research, Elsevier, vol. 64(2), pages 199-206, February.

  15. Donaldson, R Glen & Kamstra, Mark, 1996. "A New Dividend Forecasting Procedure That Rejects Bubbles in Asset Prices: The Case of 1929's Stock Crash," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 333-383.

    Cited by:

    1. Mark J. Kamstra & Robert J. Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Cowles Foundation Discussion Papers 1717, Cowles Foundation for Research in Economics, Yale University.
    2. Bucci, Andrea, 2019. "Realized Volatility Forecasting with Neural Networks," MPRA Paper 95443, University Library of Munich, Germany.
    3. Kanas, Angelos & Yannopoulos, Andreas, 2001. "Comparing linear and nonlinear forecasts for stock returns," International Review of Economics & Finance, Elsevier, vol. 10(4), pages 383-398, December.
    4. Bergeron, Claude, 2013. "Dividend sensitivity to economic factors, stock valuation, and long-run risk," Finance Research Letters, Elsevier, vol. 10(4), pages 184-195.
    5. Lubos Pastor & Pietro Veronesi, 2004. "Was There a Nasdaq Bubble in the Late 1990s?," NBER Working Papers 10581, National Bureau of Economic Research, Inc.
    6. Carlos, Ann M. & Moyen, Nathalie & Hill, Jonathan, 2002. "Royal African Company Share Prices during the South Sea Bubble," Explorations in Economic History, Elsevier, vol. 39(1), pages 61-87, January.
    7. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    8. Ripamonti, Alexandre, 2013. "Rational Valuation Formula (RVF) and Time Variability in Asset Rates of Return," MPRA Paper 79460, University Library of Munich, Germany.
    9. Eugene N. White, 2004. "Bubbles and Busts: The 1990s in the Mirror of the 1920s," FRU Working Papers 2004/09, University of Copenhagen. Department of Economics. Finance Research Unit.
    10. Raymond Tse & James Webb, 2008. "Housing markets in China: an empirical evaluation of present-value model," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 6(1), pages 67-75.
    11. Angelos Kanas & Yue Ma, 2004. "Intrinsic bubbles revisited: evidence from nonlinear cointegration and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 237-250.
    12. Glen Donaldson & Mark Kamstra & Lisa Kramer, 2003. "Stare down the barrel and center the crosshairs: Targeting the ex ante equity premium," FRB Atlanta Working Paper 2003-4, Federal Reserve Bank of Atlanta.
    13. Günster, N.K. & Kole, H.J.W.G. & Jacobsen, B., 2009. "Riding Bubbles," ERIM Report Series Research in Management ERS-2009-058-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    14. Bourdeau-Brien, Michael & Kryzanowski, Lawrence, 2020. "Natural disasters and risk aversion," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 818-835.
    15. Guglielmo D'Amico, 2016. "Generalized semi-Markovian dividend discount model: risk and return," Papers 1605.02472, arXiv.org.
    16. Chris Brooks & Apostolos Katsaris, 2003. "Rational Speculative Bubbles: An Empirical Investigation of the London Stock Exchange," Bulletin of Economic Research, Wiley Blackwell, vol. 55(4), pages 319-346, October.
    17. William Quinn & John D. Turner, 2023. "Bubbles in history," Business History, Taylor & Francis Journals, vol. 65(4), pages 636-655, May.
    18. Chow, Gregory C. & Fan, Zhao-zhi & Hu, Jin-yan, 1999. "Shanghai Stock Prices as Determined by the Present-Value Model," Journal of Comparative Economics, Elsevier, vol. 27(3), pages 553-561, September.
    19. Marcos álvarez Díaz & Josep Mateu-Sbert, 2011. "Forecasting Daily Air Arrivals in Mallorca Island Using Nearest Neighbour Methods," Tourism Economics, , vol. 17(1), pages 191-208, February.
    20. Bley, Jorg, 2011. "Are GCC stock markets predictable?," Emerging Markets Review, Elsevier, vol. 12(3), pages 217-237, September.
    21. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    22. Guglielmo D’Amico, 2013. "A semi-Markov approach to the stock valuation problem," Annals of Finance, Springer, vol. 9(4), pages 589-610, November.
    23. Robert A. Jarrow, 2015. "Asset Price Bubbles," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 201-218, December.
    24. Zhong, Maosen & Darrat, Ali F. & Anderson, Dwight C., 2003. "Do US stock prices deviate from their fundamental values? Some new evidence," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 673-697, April.
    25. Mark Kamstra & Rpbert J. Shiller, 2008. "The Case for Trills: Giving Canadians and their Pension Funds a Stake in the Wealth of the Nation," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 271, August.
    26. Ian Tonks & Andy Snell & George Bulkley, 1996. "Excessive Dispersion of US Stock Prices: A Regression Test of Cross-Sectional Volatility," FMG Discussion Papers dp246, Financial Markets Group.
    27. Davide Pettenuzzo & Riccardo Sabbatucci & Allan Timmermann, 2020. "Cash Flow News and Stock Price Dynamics," Journal of Finance, American Finance Association, vol. 75(4), pages 2221-2270, August.
    28. Debdatta Pal & Subrata K. Mitra, 2017. "Diesel and soybean price relationship in the USA: evidence from a quantile autoregressive distributed lag model," Empirical Economics, Springer, vol. 52(4), pages 1609-1626, June.
    29. Mark Kamstra, 2001. "Rational exuberance: The fundamentals of pricing firms, from blue chip to “dot com”," FRB Atlanta Working Paper 2001-21, Federal Reserve Bank of Atlanta.
    30. Zhijie Xiao, 2009. "Quantile Cointegrating Regression," Boston College Working Papers in Economics 708, Boston College Department of Economics.
    31. Miguel A. Iraola & Manuel S. Santos, 2009. "Long Term Asset Price Volatility and Macroeconomic Fluctuations," Working Papers 2010-1, University of Miami, Department of Economics.
    32. Mark Kamstra & Robert Shiller, 2009. "The Case for Trills: Giving the People and Their Pension Funds a Stake in the Wealth of the Nation," Yale School of Management Working Papers amz2418, Yale School of Management.
    33. Guglielmo D'Amico & Riccardo De Blasis, 2020. "A review of the Dividend Discount Model: from deterministic to stochastic models," Papers 2001.00465, arXiv.org.
    34. Darrat, Ali F & Zhong, Maosen, 2000. "On Testing the Random-Walk Hypothesis: A Model-Comparison Approach," The Financial Review, Eastern Finance Association, vol. 35(3), pages 105-124, August.
    35. Taipalus, Katja, 2006. "Bubbles in the Finnish and US equities markets," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2006_035, July.
    36. Campbell, Gareth & Turner, John, 2010. "‘The Greatest Bubble in History’: Stock Prices during the British Railway Mania," MPRA Paper 21820, University Library of Munich, Germany.
    37. R. Glen Donaldson & Mark Kamstra, "undated". "Forecasting Fundamental Asset Return Distributions," Computing in Economics and Finance 1997 176, Society for Computational Economics.
    38. Campbell, Gareth, 2012. "Myopic rationality in a Mania," Explorations in Economic History, Elsevier, vol. 49(1), pages 75-91.
    39. Dimitra Papadovasilaki & Federico Guerrero & Rattaphon Wuthisatian & Bhraman Gulati, 2022. "The 1920s technological revolution and the crash of 1929: the role of RCA, DuPont, General Motors, and Union Carbide," SN Business & Economics, Springer, vol. 2(5), pages 1-22, May.
    40. Anderson, Keith & Brooks, Chris, 2014. "Speculative bubbles and the cross-sectional variation in stock returns," International Review of Financial Analysis, Elsevier, vol. 35(C), pages 20-31.
    41. Kirman, Alan & Teyssiere, Gilles, 2005. "Testing for bubbles and change-points," Journal of Economic Dynamics and Control, Elsevier, vol. 29(4), pages 765-799, April.
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    43. Hamidi Sahneh, Mehdi, 2017. "News, Noise, and Tests of Present Value Models," MPRA Paper 82715, University Library of Munich, Germany.
    44. Quinn, William, 2016. "Technological revolutions and speculative finance: Evidence from the British Bicycle Mania," QUCEH Working Paper Series 2016-06, Queen's University Belfast, Queen's University Centre for Economic History.
    45. Debdatta PAL & Subrata Kumar MITRA, 2015. "Impact of price realization on India's tea export: Evidence from Quantile Autoregressive Distributed Lag Model," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 61(9), pages 422-428.
    46. Black, Angela & Fraser, Patricia, 2002. "Stock market short-termism--an international perspective," Journal of Multinational Financial Management, Elsevier, vol. 12(2), pages 135-158, April.
    47. Bansal, Ravi & Lundblad, Christian, 2002. "Market efficiency, asset returns, and the size of the risk premium in global equity markets," Journal of Econometrics, Elsevier, vol. 109(2), pages 195-237, August.

  16. Granger, C. W. J. & White, Halbert & Kamstra, Mark, 1989. "Interval forecasting : An analysis based upon ARCH-quantile estimators," Journal of Econometrics, Elsevier, vol. 40(1), pages 87-96, January.

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    1. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    2. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    3. Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
    4. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    5. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    6. Amisano, Gianni & Geweke, John, 2009. "Optimal Prediction Pools," Working Paper Series 1017, European Central Bank.
    7. Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
    8. Hansen, Bruce E., 2006. "Interval forecasts and parameter uncertainty," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 377-398.
    9. Robert F. Engle & Simone Manganelli, 1999. "CAViaR: Conditional Value at Risk by Quantile Regression," NBER Working Papers 7341, National Bureau of Economic Research, Inc.
    10. James Taylor & Derek Bunn, 1998. "Combining forecast quantiles using quantile regression: Investigating the derived weights, estimator bias and imposing constraints," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 193-206.
    11. Clements, Michael P., 2003. "Some possible directions for future research," International Journal of Forecasting, Elsevier, vol. 19(1), pages 1-3.
    12. Karine Bouthevillain, 1993. "La prévision macro-économique : précision relative et consensus," Économie et Prévision, Programme National Persée, vol. 108(2), pages 97-126.
    13. Zongwu Cai & Chaoqun Ma & Xianhua Mi, 2020. "Realized Volatility Forecasting Based on Dynamic Quantile Model Averaging," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202016, University of Kansas, Department of Economics, revised Sep 2020.
    14. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    15. Anthony Tay & Kenneth F. Wallis, 2000. "Density Forecasting: A Survey," Econometric Society World Congress 2000 Contributed Papers 0370, Econometric Society.
    16. Xiaoping Xu & Zongwu Cai, 2013. "Nonparametric Quantile Estimations For Dynamic Smooth Coefficient Models," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    17. Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
    18. Roberto Buizza & James W. Taylor, 2004. "A comparison of temperature density forecasts from GARCH and atmospheric models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(5), pages 337-355.
    19. Yushu Li & Jonas Andersson, 2020. "A likelihood ratio and Markov chain‐based method to evaluate density forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 47-55, January.
    20. Jose A. Lopez, 1997. "Regulatory evaluation of value-at-risk models," Research Paper 9710, Federal Reserve Bank of New York.
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    22. Gourieroux, C. & Jasiak, J., 2008. "Dynamic quantile models," Journal of Econometrics, Elsevier, vol. 147(1), pages 198-205, November.
    23. Clements, Michael P., 2006. "Internal consistency of survey respondentsíforecasts: Evidence based on the Survey of Professional Forecasters," Economic Research Papers 269742, University of Warwick - Department of Economics.
    24. Fabio Busetti, 2017. "Quantile Aggregation of Density Forecasts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 495-512, August.
    25. Christian Kascha & Francesco Ravazzolo, 2008. "Combining inflation density forecasts," Working Paper 2008/22, Norges Bank.
    26. Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    27. Taylor, James W. & Buizza, Roberto, 2006. "Density forecasting for weather derivative pricing," International Journal of Forecasting, Elsevier, vol. 22(1), pages 29-42.
    28. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
    29. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    30. Wallis, Kenneth F., 2002. "Chi-squared tests of interval and density forecasts, and the Bank of England's fan charts," Royal Economic Society Annual Conference 2002 181, Royal Economic Society.
    31. Reeves, Jonathan J., 2005. "Bootstrap prediction intervals for ARCH models," International Journal of Forecasting, Elsevier, vol. 21(2), pages 237-248.
    32. Gensler, André & Sick, Bernhard & Vogt, Stephan, 2018. "A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 352-379.
    33. Domínguez, Manuel A., 1997. "Consistent specification testing of quantile regression models," DES - Working Papers. Statistics and Econometrics. WS 6211, Universidad Carlos III de Madrid. Departamento de Estadística.
    34. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    35. Chollete, Lorán, 2009. "The Propagation of Financial Extremes," Discussion Papers 2008/25, Norwegian School of Economics, Department of Business and Management Science.
    36. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    37. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
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    39. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    40. Taylor, James W. & Buizza, Roberto, 2003. "Using weather ensemble predictions in electricity demand forecasting," International Journal of Forecasting, Elsevier, vol. 19(1), pages 57-70.
    41. Chollete, Lorán, 2008. "The Propagation of Financial Extremes: An Application to Subprime Market Spillovers," Discussion Papers 2008/2, Norwegian School of Economics, Department of Business and Management Science.
    42. Arunraj, Nari Sivanandam & Ahrens, Diane, 2015. "A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 321-335.
    43. George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
    44. Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
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