The international business cycle and gold-price fluctuations

The Quarterly Review of Economics and Finance - Tập 54 - Trang 292-305 - 2014
Christian Pierdzioch1, Marian Risse1, Sebastian Rohloff1
1Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O. Box 700822, 22008 Hamburg, Germany

Tài liệu tham khảo

Aiolfi, 2005, Model uncertainty, thick modelling and the predictability of stock returns, Journal of Forecasting, 24, 233, 10.1002/for.958

Akaike, 1973, Information Theory and an Extension of the Maximum Likelihood Principle

Alcock, 2005, Forecasting stock returns using model-selection criteria, Economic Record, 81, 135, 10.1111/j.1475-4932.2005.00239.x

Balvers, 1990, Predicting stock returns in an efficient market, Journal of Finance, 45, 1109, 10.1111/j.1540-6261.1990.tb02429.x

Batchelor, 1998, Rationality testing under asymmetric loss, Economics Letters, 61, 49, 10.1016/S0165-1765(98)00157-8

Blanchard, 1981, Output, the stock market, and interest rates, American Economic Review, 71, 132

Blose, 2010, Gold prices, cost of carry, and expected inflation, Journal of Economics and Business, 62, 35, 10.1016/j.jeconbus.2009.07.001

Bohl, 2008, Real-time forecasting and political stock market anomalies: Evidence for the United States, Financial Review, 43, 323, 10.1111/j.1540-6288.2008.00196.x

Bossaerts, 1999, Implementing statistical criteria to select return forecasting models: What do we learn?, Review of Financial Studies, 12, 405, 10.1093/rfs/12.2.405

Campbell, 2008, Predicting excess stock returns out of sample: Can anything beat the historical average?, Review of Financial Studies, 21, 1509, 10.1093/rfs/hhm055

Capie, 2005, Gold as a hedge against the dollar, Journal of International Financial Markets, Institutions and Money, 15, 343, 10.1016/j.intfin.2004.07.002

Christodoulakis, 2005, Financial forecasts in the presence of asymmetric loss aversion, skewness and excess kurtosis, Finance Research Letters, 2, 227, 10.1016/j.frl.2005.08.002

Christodoulakis, 2013, Behavioural asymmetries in the G7 foreign exchange market, International Review of Financial Analysis, 29, 261, 10.1016/j.irfa.2013.02.012

Christodoulakis, 2008, An assessment of the EU growth forecasts under asymmetric preferences, Journal of Forecasting, 27, 483, 10.1002/for.1073

Christoffersen, 1997, Optimal prediction under asymmetric loss, Econometric Theory, 13, 808, 10.1017/S0266466600006277

Cooper, 2009, Time-varying risk premiums and the output gap, Review of Financial Studies, 22, 2801, 10.1093/rfs/hhn087

Döpke, 2008, Shocking! Do Forecasters share a common belief?, Applied Economics Letters, 15, 355, 10.1080/13504850600605978

Döpke, 2008, Real-time macroeconomic data and ex-ante stock return predictability, International Review of Financial Analysis, 17, 274, 10.1016/j.irfa.2006.11.004

Elliott, 2008, Biases in macroeconomic forecasts: Irrationality or asymmetric loss?, Journal of the European Economic Association, 6, 122, 10.1162/JEEA.2008.6.1.122

Elliott, 2005, Estimation and testing of forecast rationality under flexible loss, Review of Economic Studies, 72, 1107, 10.1111/0034-6527.00363

Fuertes, 2010, Tactical allocation in commodity futures markets: Combining momentum and term structure signals, Journal of Banking and Finance, 34, 2530, 10.1016/j.jbankfin.2010.04.009

Ghosh, 2004, Gold as an inflation hedge?, Studies in Economics and Finance, 22, 1, 10.1108/eb043380

Granger, 2004, Thick modeling, Economic Modelling, 21, 323, 10.1016/S0264-9993(03)00017-8

Guidolin, 2009, Forecasts of US short-term interest rates: A flexible forecast combination approach, Journal of Econometrics, 150, 297, 10.1016/j.jeconom.2008.12.004

Hartmann, 2008, Economic and financial crises and the predictability of US stock returns, Journal of Empirical Finance, 15, 468, 10.1016/j.jempfin.2007.07.003

Ho, 1985, A test of the incrementally efficient market hypothesis for the London gold market, Economics Letters, 19, 67, 10.1016/0165-1765(85)90105-3

Lucas, 1978, Asset prices in an exchange economy, Econometrica, 46, 1429, 10.2307/1913837

Mahdavi, 1997, Gold and commodity prices as leading indicators of inflation: Tests of long-run relationship and predictive performance, Journal of Economics and Business, 49, 475, 10.1016/S0148-6195(97)00034-9

Marshall, 2008, Can commodity futures be profitably traded with quantitative market timing strategies?, Journal of Banking and Finance, 32, 1810, 10.1016/j.jbankfin.2007.12.011

Neill Fortune, 1987, The inflation rate of the price of gold, expected prices and interest rates, Journal of Macroeconomics, 9, 71, 10.1016/S0164-0704(87)80007-1

Nitschka, 2012

Paye, 2006, Instability of return prediction models, Journal of Empirical Finance, 13, 274, 10.1016/j.jempfin.2005.11.001

Perez-Quiros, 2000, Firm size and cyclical Variations in stock returns, Journal of Finance, 55, 1229, 10.1111/0022-1082.00246

Pesaran, 1992, A simple nonparametric test of predictive performance, Journal of Business and Economic Statistics, 10, 461

Pesaran, 1995, Predictability of stock returns: Robustness and economic significance, Journal of Finance, 50, 1201, 10.1111/j.1540-6261.1995.tb04055.x

Pesaran, 2000, A recursive modelling approach to predicting UK stock returns, Economic Journal, 110, 159, 10.1111/1468-0297.00495

Pesaran, 2002, Market timing and return prediction under model instability, Journal of Empirical Finance, 9, 495, 10.1016/S0927-5398(02)00007-5

Pierdzioch, 2013, A note on forecasting the prices of gold and silver, Quarterly Review of Economics and Finance, 53, 294, 10.1016/j.qref.2013.04.002

Politis, 1994, The stationary Bootstrap, Journal of the American Statistical Association, 89, 1303, 10.1080/01621459.1994.10476870

Pukthuanthong, 2011, Gold and the Dollar (and the Euro, Pound, and Yen), Journal of Banking and Finance, 35, 2070, 10.1016/j.jbankfin.2011.01.014

R Development Core Team (2012). R: A language and environment for statistical computing. Vienna, Austria R Foundation for Statistical Computing ISBN 3-900051-07-0. http://www.R-project.org. April 2012 (Version 2.15.2).

Rangvid, 2006, Output and expected returns, Journal of Financial Economics, 81, 595, 10.1016/j.jfineco.2005.07.010

Rapach, 2010, Out-of-sample equity premium prediction: Combination forecasts and links to the real economy, Review of Financial Studies, 23, 821, 10.1093/rfs/hhp063

Rapach, 2006, Structural breaks and predictive regression models of aggregate U.S. stock returns, Journal of Financial Econometrics, 4, 238, 10.1093/jjfinec/nbj008

Reboredo, 2013, Is gold a safe haven or a hedge for the U.S. Dollar? Implications for risk management, Journal of Banking and Finance, 37, 2665, 10.1016/j.jbankfin.2013.03.020

Sarno, 2009, Exchange rates and fundamentals: Footloose or evolving relationship?, Journal of the European Economic Association, 7, 786, 10.1162/JEEA.2009.7.4.786

Schwarz, 1978, Estimating the dimension of a model, Annals of Statistics, 6, 416, 10.1214/aos/1176344136

Sjaastad, 2008, The price of gold and the exchange rates: Once again, Resources Policy, 33, 118, 10.1016/j.resourpol.2007.10.002

Solt, 1981, On the efficiency of the markets for gold and silver, Journal of Business, 54, 453, 10.1086/296140

Sullivan, 1999, Data-snooping, technical trading rule performance, and the bootstrap, Journal of Finance, 54, 1647, 10.1111/0022-1082.00163

Timmermann, 2001, Structural breaks, incomplete information, and stock prices, Journal of Business and Economic Statistics, 19, 299, 10.1198/073500101681019954

Tschoegl, 1980, Efficiency in the gold market—A note, Journal of Banking and Finance, 4, 371, 10.1016/0378-4266(80)90015-1

Vivian, 2013, The output gap and stock returns: Do cyclical fluctuations predict portfolio returns?, International Review of Financial Analysis, 26, 40, 10.1016/j.irfa.2012.05.002

Vrugt, 2007, Dynamic Commodity Timing Strategies, 419

White, 2000, Reality check for data snooping, Econometrica, 68, 1097, 10.1111/1468-0262.00152

Thông tin
Thông tin xuất bản

The Quarterly Review of Economics and Finance

Tập 54

292-305

Thông tin tác giả