[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/uts/rpaper/285.html
   My bibliography  Save this paper

Adaptive Forecasting of Exchange Rates with Panel Data

Author

Listed:
  • Leonardo Morales-Arias

    (University of Kiel)

  • Alexander Dross
Abstract
This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data and alternative predictors. The candidate exchange rate predictors are drawn from (i) macroeconomic 'fundamentals', (ii) return/volatility of asset markets and (iii) cyclical and confidence indices. Exchange rate forecasts at various horizons are obtained from each of the potential predictors using single market, mean group and pooled estimates by means of rolling window and recursive forecasting schemes. The capabilities of single predictors and of adaptive techniques for combining the generated exchange rate forecasts are subsequently examined by means of statistical and economic performance measures. The forward premium and a predictor based on a Taylor rule yield the most promising forecasting results out of the macro 'fundamentals' considered. For recursive forecasting, confidence indices and volatility in-mean yield more accurate forecasts than most of the macro 'fundamentals'. Adaptive forecast combinations techniques improve forecasting precision and lead to better market timing than most single predictors at higher horizons.

Suggested Citation

  • Leonardo Morales-Arias & Alexander Dross, 2010. "Adaptive Forecasting of Exchange Rates with Panel Data," Research Paper Series 285, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:285
    as

    Download full text from publisher

    File URL: https://www.uts.edu.au/sites/default/files/qfr-archive-03/QFR-rp285.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Menzie D. Chinn & Guy Meredith, 2004. "Monetary Policy and Long-Horizon Uncovered Interest Parity," IMF Staff Papers, Palgrave Macmillan, vol. 51(3), pages 409-430, November.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Trapani, Lorenzo & Urga, Giovanni, 2009. "Optimal forecasting with heterogeneous panels: A Monte Carlo study," International Journal of Forecasting, Elsevier, vol. 25(3), pages 567-586, July.
    4. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
    5. Lux, Thomas, 2009. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 638-655, November.
    6. Cheung, Yin-Wong & Chinn, Menzie David & Garcia Pascual, Antonio, 2003. "Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?," Santa Cruz Department of Economics, Working Paper Series qt12z9x4c5, Department of Economics, UC Santa Cruz.
    7. Turgut Kışınbay, 2010. "The use of encompassing tests for forecast combinations," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(8), pages 715-727, December.
    8. Todd E. Clark & Michael W. McCracken, 2009. "Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, May.
    9. repec:bla:scandj:v:78:y:1976:i:2:p:200-224 is not listed on IDEAS
    10. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    11. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    12. Thomas Lux, 2009. "Rational Forecasts or Social Opinion Dynamics? Identification of Interaction Effects in a Business Climate Survey," Post-Print hal-00720175, HAL.
    13. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    14. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    15. Jeremy Berkowitz & Lorenzo Giorgianni, 2001. "Long-Horizon Exchange Rate Predictability?," The Review of Economics and Statistics, MIT Press, vol. 83(1), pages 81-91, February.
    16. repec:bla:ecorec:v:0:y:1986:i:0:p:24-38 is not listed on IDEAS
    17. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
    18. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    19. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    20. Charles Engel & Nelson C. Mark & Kenneth D. West, 2008. "Exchange Rate Models Are Not as Bad as You Think," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 381-441, National Bureau of Economic Research, Inc.
    21. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    22. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    23. Neal, Robert & Wheatley, Simon M., 1998. "Do Measures of Investor Sentiment Predict Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(4), pages 523-547, December.
    24. Engel, Charles, 1996. "The forward discount anomaly and the risk premium: A survey of recent evidence," Journal of Empirical Finance, Elsevier, vol. 3(2), pages 123-192, June.
    25. repec:bla:scandj:v:78:y:1976:i:2:p:229-48 is not listed on IDEAS
    26. Chiquoine, Benjamin & Hjalmarsson, Erik, 2009. "Jackknifing stock return predictions," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 793-803, December.
    27. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    28. Jan J J Groen & Akito Matsumoto, 2004. "Real exchange rate persistence and systematic monetary policy behaviour," Bank of England working papers 231, Bank of England.
    29. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
    30. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    31. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    32. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    33. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    34. Molodtsova, Tanya & Nikolsko-Rzhevskyy, Alex & Papell, David H., 2008. "Taylor rules with real-time data: A tale of two countries and one exchange rate," Journal of Monetary Economics, Elsevier, vol. 55(Supplemen), pages 63-79, October.
    35. Wright, Jonathan H., 2008. "Bayesian Model Averaging and exchange rate forecasts," Journal of Econometrics, Elsevier, vol. 146(2), pages 329-341, October.
    36. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    37. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    38. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    39. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    40. Dumas, Bernard & Solnik, Bruno, 1995. "The World Price of Foreign Exchange Risk," Journal of Finance, American Finance Association, vol. 50(2), pages 445-479, June.
    41. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
    42. Groen, Jan J J, 2005. "Exchange Rate Predictability and Monetary Fundamentals in a Small Multi-country Panel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 495-516, June.
    43. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
    44. Rapach, David E. & Wohar, Mark E., 2004. "Testing the monetary model of exchange rate determination: a closer look at panels," Journal of International Money and Finance, Elsevier, vol. 23(6), pages 867-895, October.
    45. Yufeng Han, 2006. "Asset Allocation with a High Dimensional Latent Factor Stochastic Volatility Model," The Review of Financial Studies, Society for Financial Studies, vol. 19(1), pages 237-271.
    46. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    47. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    48. Aiolfi, Marco & Timmermann, Allan, 2006. "Persistence in forecasting performance and conditional combination strategies," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 31-53.
    49. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    50. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
    51. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
    52. Chen, Jian & Mark, Nelson C, 1996. "Alternative Long-Horizon Exchange-Rate Predictors," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 1(4), pages 229-250, October.
    53. Mark, Nelson C. & Sul, Donggyu, 2001. "Nominal exchange rates and monetary fundamentals: Evidence from a small post-Bretton woods panel," Journal of International Economics, Elsevier, vol. 53(1), pages 29-52, February.
    54. Faust, Jon & Rogers, John H. & H. Wright, Jonathan, 2003. "Exchange rate forecasting: the errors we've really made," Journal of International Economics, Elsevier, vol. 60(1), pages 35-59, May.
    55. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    56. Thomas Lux, 2011. "Sentiment dynamics and stock returns: the case of the German stock market," Empirical Economics, Springer, vol. 41(3), pages 663-679, December.
    57. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    58. Costantini, Mauro & Pappalardo, Carmine, 2010. "A hierarchical procedure for the combination of forecasts," International Journal of Forecasting, Elsevier, vol. 26(4), pages 725-743, October.
    59. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-247, February.
    60. Mark, Nelson C, 1995. "Exchange Rates and Fundamentals: Evidence on Long-Horizon Predictability," American Economic Review, American Economic Association, vol. 85(1), pages 201-218, March.
    61. Daron Acemoglu & Kenneth Rogoff & Michael Woodford, "undated". "Exchange Rate Models Are Not as Bad as You Think: A comment," Working Paper 14895, Harvard University OpenScholar.
    62. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
    63. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gaglianone, Wagner Piazza & Guillén, Osmani Teixeira de Carvalho & Figueiredo, Francisco Marcos Rodrigues, 2018. "Estimating inflation persistence by quantile autoregression with quantile-specific unit roots," Economic Modelling, Elsevier, vol. 73(C), pages 407-430.
    2. Ibrahim D. Raheem & Xuan Vinh Vo, 2022. "A new approach to exchange rate forecast: The role of global financial cycle and time‐varying parameters," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2836-2848, July.
    3. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    4. Alexandros Pasiouras & Theodoros Daglis, 2020. "The Dollar Exchange Rates in the Covid-19 Era: Evidence from 5 Currencies," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 352-361.
    5. Araujo, Gustavo Silva & Gaglianone, Wagner Piazza, 2023. "Machine learning methods for inflation forecasting in Brazil: New contenders versus classical models," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 4(2).
    6. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    7. Caldeira, João F. & Moura, Guilherme V. & Santos, André A.P., 2016. "Predicting the yield curve using forecast combinations," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 79-98.
    8. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
    9. Kouwenberg, Roy & Markiewicz, Agnieszka & Verhoeks, Ralph & Zwinkels, Remco C. J., 2017. "Model Uncertainty and Exchange Rate Forecasting," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(1), pages 341-363, February.
    10. Michał Chojnowski & Piotr Dybka, 2017. "Is Exchange Rate Moody? Forecasting Exchange Rate with Google Trends Data," Econometric Research in Finance, SGH Warsaw School of Economics, Collegium of Economic Analysis, vol. 2(1), pages 1-21, June.
    11. Wagner Piazza Gaglianone & Osmani Teixeira de Carvalho Guillén & Francisco Marcos Rodrigues Figueiredo, 2015. "Local Unit Root and Inflationary Inertia in Brazil," Working Papers Series 406, Central Bank of Brazil, Research Department.
    12. Ren, Yu & Liang, Xuanxuan & Wang, Qin, 2021. "Short-term exchange rate forecasting: A panel combination approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    13. Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021. "Machine learning and oil price point and density forecasting," Energy Economics, Elsevier, vol. 102(C).
    14. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    15. Konstantinos N. Konstantakis & Ioannis G. Melissaropoulos & Theodoros Daglis & Panayotis G. Michaelides, 2023. "The euro to dollar exchange rate in the Covid‐19 era: Evidence from spectral causality and Markov‐switching estimation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2037-2055, April.
    16. Kharrat, Sabrine & Hammami, Yacine & Fatnassi, Ibrahim, 2020. "On the cross-sectional relation between exchange rates and future fundamentals," Economic Modelling, Elsevier, vol. 89(C), pages 484-501.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    2. Kenneth S. Rogoff & Vania Stavrakeva, 2008. "The Continuing Puzzle of Short Horizon Exchange Rate Forecasting," NBER Working Papers 14071, National Bureau of Economic Research, Inc.
    3. Engel, Charles, 2014. "Exchange Rates and Interest Parity," Handbook of International Economics, in: Gopinath, G. & Helpman, . & Rogoff, K. (ed.), Handbook of International Economics, edition 1, volume 4, chapter 0, pages 453-522, Elsevier.
    4. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    5. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
    6. Ince, Onur, 2014. "Forecasting exchange rates out-of-sample with panel methods and real-time data," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 1-18.
    7. Wu, Jyh-Lin & Wang, Yi-Chiuan, 2013. "Fundamentals, forecast combinations and nominal exchange-rate predictability," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 129-145.
    8. Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2016. "Exchange rate predictability in a changing world," Journal of International Money and Finance, Elsevier, vol. 62(C), pages 1-24.
    9. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
    10. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    11. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    12. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    13. Ardic, Oya Pinar & Ergin, Onur & Senol, G. Bahar, 2008. "Exchange Rate Forecasting: Evidence from the Emerging Central and Eastern European Economies," MPRA Paper 7505, University Library of Munich, Germany.
    14. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
    15. Daniel Andrés Jaimes Cárdenas & jair Ojeda Joya, 2010. "Reglas de Taylor y previsibilidad fuera de muestra de la tasa de cambio en Latinoamérica," Borradores de Economia 7308, Banco de la Republica.
    16. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    17. Sarantis, Nicholas, 2006. "On the short-term predictability of exchange rates: A BVAR time-varying parameters approach," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2257-2279, August.
    18. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    19. Christopher J. Neely & Lucio Sarno, 2002. "How well do monetary fundamentals forecast exchange rates?," Review, Federal Reserve Bank of St. Louis, vol. 84(Sep), pages 51-74.
    20. Atsushi Inoue & Lutz Kilian, 2005. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," Econometric Reviews, Taylor & Francis Journals, vol. 23(4), pages 371-402.

    More about this item

    Keywords

    exchange rate forecasting; panel data; forecast combinations; market timing;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:uts:rpaper:285. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Duncan Ford (email available below). General contact details of provider: https://edirc.repec.org/data/qfutsau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.