1. Equity Markets Volatility, Regime Dependence and Economic Uncertainty: The Case of Pacific Basin. (2025). Chatrath, Arjun ; Hatamerad, Saman ; Raffiee, Kambiz ; Adrangi, Bahram.
   In: Bulletin of Applied Economics.
   RePEc:rmk:rmkbae:v:12:y:2025:i:1:p:75-105.

   Full description at Econpapers || Download paper

2. Economic and Policy Uncertainties and Firm Value: The Case of Consumer Durable Goods. (2025). Raffiee, Kambiz ; Kolay, Madhuparna ; Hatamerad, Saman ; Adrangi, Bahram.
   In: Papers.
   RePEc:arx:papers:2506.07476.

   Full description at Econpapers || Download paper

1. Adrangi, B., Chatrath, A., Dhanda, K. K., & Raffiee, K. (2001). Chaos in oil prices? Evidence from futures markets. Energy Economics, 23(4), 405–425.

2. Adrangi, B., Chatrath, A., Macri, J., & Raffiee, K. (2015). Crude oil price volatility spillovers into major equity markets. Journal of Energy Markets, 8(1), 77–95.
   Paper not yet in RePEc: Add citation now
   

3. Al‐Thaqeb, S. A., & Algharabali, B. G. (2019). Economic policy uncertainty: A literature review. The Journal of Economic Asymmetries, 20, e00133.

4. Alizadeh, A. H., & Nomikos, N. K. (2011). Dynamics of the term structure and volatility of shipping freight rates. Journal of Transport Economics and Policy (JTEP), 45(1), 105–128.

5. Altig, D., Baker, S., Barrero, J. M., Bloom, N., Bunn, P., Chen, S., & Thwaites, G. (2020). Economic uncertainty before and during the COVID‐19 pandemic. Journal of Public Economics, 191, 104274.

6. Amado, C., Silvennoinen, A., & Teräsvirta, T. (2019). Models with multiplicative decomposition of conditional variances and correlations. Financial mathematics, volatility and covariance modelling 2, pp. 217–260).
   Paper not yet in RePEc: Add citation now
   
7. Amendola, A., Candila, V., & Gallo, G. M. (2019). On the asymmetric impact of macro–variables on volatility. Economic Modelling, 76, 135–152.
   Paper not yet in RePEc: Add citation now
   

8. Amendola, A., Candila, V., & Scognamillo, A. (2017). On the influence of US monetary policy on crude oil price volatility. Empirical Economics, 52(1), 155–178.

9. Ang, A., & Bekaert, G. (2015). International asset allocation with regime shifts. The Review of Financial Studies, 15, 1137–1187.
   Paper not yet in RePEc: Add citation now
   

10. Ang, A., & Chen, J. (2002). Asymmetric correlations of equity portfolios. Journal of Financial Economics, 63, 443–494.

11. Antonakakis, N., Chatziantoniou, I., & Filis, G. (2013). Dynamic co‐movements of stock market returns, implied volatility and policy uncertainty. Economics Letters, 120, 87–92.
    Paper not yet in RePEc: Add citation now
    
12. Arouri, M., Estay, C., Rault, C., & Roubaud, D. (2016). Economic policy uncertainty and stock markets: Long‐run evidence from the US. Finance Research Letters, 18, 136–141.
    Paper not yet in RePEc: Add citation now
    

13. Asgharian, H., Hou, A. J., & Javed, F. (2013). The importance of the macroeconomic variables in forecasting stock return variance: A GARCH‐MIDAS approach. Journal of Forecasting, 32(7), 600–612.

14. Awartani, B. M., & Corradi, V. (2005). Predicting the volatility of the S&P‐500 stock index via GARCH models: The role of asymmetries. International Journal of Forecasting, 21(1), 167–183.
    Paper not yet in RePEc: Add citation now
    

15. Bai, J., & Perron, P. (2003). Critical values for multiple structural change tests. The Econometrics Journal, 6(1), 72–78.

16. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645–1680.
    Paper not yet in RePEc: Add citation now
    

17. Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economic Perspectives, 21(2), 129–152.

18. Baker, S. R., Bloom, N., & Davis, S. J. (2012a). Has economic policy uncertainty hampered the recovery? (Becker Friedman Institute for Research in Economics Working Paper No. 2012‐003). SSRN.
    Paper not yet in RePEc: Add citation now
    

19. Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593–1636.

20. Baker, S. R., Bloom, N., Davis, S. J., & Kost, K. J. (2019). Policy news and stock market volatility (No. w25720). National Bureau of Economic Research.
    Paper not yet in RePEc: Add citation now
    
21. Baker, S. R., Bloom, N., Davis, S. J., & Renault, T. (2021). Twitter‐derived measures of economic uncertainty. Available online: PolicyUncertainty.com.
    Paper not yet in RePEc: Add citation now
    
22. Baker, S., Bloom, N., & Davis, S. J. (2012b). Measuring economic policy uncertainty. University of Chicago and Stanford University. Available at www.policyuncertainty.com.
    Paper not yet in RePEc: Add citation now
    
23. Barrodale, I., & Roberts, F. D. (1973). An improved algorithm for discrete l_1 linear approximation. SIAM Journal on Numerical Analysis, 10(5), 839–848.
    Paper not yet in RePEc: Add citation now
    
24. Beckmann, J., & Czudaj, R. (2014). Non‐linearities in the relationship of agricultural futures prices. European Review of Agricultural Economics, 41(1), 1–23.
    Paper not yet in RePEc: Add citation now
    

25. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327.

26. Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A capital asset pricing model with time‐varying covariances. Journal of Political Economy, 96(1), 116–131.

27. Bonaime, A., Gulen, H., & Ion, M. (2018). Does policy uncertainty affect mergers and acquisitions? Journal of Financial Economics Forthcoming, 129(3), 531–558.

28. Borup, D., & Jakobsen, J. S. (2019). Capturing volatility persistence: A dynamically complete realized EGARCH‐MIDAS model. Quantitative Finance, 19(11), 1839–1855.

29. Carnero, M. A., Peña, D., & Ruiz, E. (2012). Estimating GARCH volatility in the presence of outliers. Economics Letters, 114(1), 86–90.

30. Chang, K. L. (2022). Do economic policy uncertainty indices matter in joint volatility cycles between US and Japanese stock markets? Finance Research Letters, 47, 102579.

31. Choi, K., & Hammoudeh, S. (2010). Volatility behavior of oil, industrial commodity and stock markets in a regime‐switching environment. Energy Policy, 38(8), 4388–4399.e99.

32. Chow, G. C., & Lin, A. L. (1971). Best linear unbiased interpolation, distribution, and extrapolation of time series by related series. The Review of Economics and Statistics, 53, 372–375.

33. Colak, G., Durnev, A., & Qian, Y. (2017). Political uncertainty and IPO activity: Evidence from U.S. gubernatorial elections. Journal of Financial and Quantitative Analysis, 52, 2523–2564.

34. Conrad, C., & Kleen, O. (2020). Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models. Journal of Applied Econometrics, 35(1), 19–45.

35. Conrad, C., & Loch, K. (2015). Anticipating long‐term stock market volatility. Journal of Applied Econometrics, 30(7), 1090–1114.
    Paper not yet in RePEc: Add citation now
    
36. Conrad, C., Custovic, A., & Ghysels, E. (2018). Long‐and short‐term cryptocurrency volatility components: A GARCH‐MIDAS analysis. Journal of Risk and Financial Management, 11(2), 23.
    Paper not yet in RePEc: Add citation now
    
37. Corsi, F. (2009). A simple approximate long‐memory model of realized volatility. Journal of Financial Econometrics, 7(2), 174–196.
    Paper not yet in RePEc: Add citation now
    

38. Demir, E., & Ersan, O. (2017). Economic policy uncertainty and cash holdings: Evidence from BRIC countries. Emerging Markets Review, 33, 189–200.

39. Denton, F. T. (1971). Adjustment of monthly or quarterly series to annual totals: An approach based on quadratic minimization. Journal of the American Statistical Association, 66(333), 99–102.
    Paper not yet in RePEc: Add citation now
    

40. Di Fonzo, T. (1990). The estimation of M disaggregate time series when contemporaneous and temporal aggregates are known. The Review of Economics and Statistics, 72, 178–182.

41. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431.
    Paper not yet in RePEc: Add citation now
    

42. Ding, Z., & Granger, C. W. (1996). Modeling volatility persistence of speculative returns: A new approach. Journal of Econometrics, 73(1), 185–215.

43. Dutta, A., Bouri, E., & Saeed, T. (2021). News‐based equity market uncertainty and crude oil volatility. Energy, 222, 119930.
    Paper not yet in RePEc: Add citation now
    
44. Edwards, G. C., III, Mitchell, W., & Welch, R. (1995). Explaining presidential approval: The significance of issue salience. American Journal of Political Science, 39, 108–134.
    Paper not yet in RePEc: Add citation now
    

45. Engle, R. F., & Lee, G. (1999). A permanent and transitory component model of stock return volatility. In R. Engle & H. White (Eds.), Cointegration, causality, and forecasting: A festschrift in honor of Clive W.J. Granger (pp. 475–497). Oxford University Press.

46. Engle, R. F., Ghysels, E., & Sohn, B. (2013). Stock market volatility and macroeconomic fundamentals. Review of Economics and Statistics, 95(3), 776–797.

47. Eve, R. A., Eve, R. A., Horsfall, S., & Lee, M. E. (Eds.). (1997). Chaos, complexity, and sociology: Myths, models, and theories. Sage.
    Paper not yet in RePEc: Add citation now
    
48. Fama, E. F. (1965). The behavior of stock‐market prices. The journal of Business, 38(1), 34–105.
    Paper not yet in RePEc: Add citation now
    

49. Fang, L., Qian, Y., Chen, Y., & Yu, H. (2018). How does stock market volatility react to NVIX? Evidence from developed countries. Physica A: Statistical Mechanics and its Applications, 505, 490–499.

50. Fissler, T., & Ziegel, J. F. (2016). Higher order elicitability and Osband's principle. The Annals of Statistics, 44(4), 1680–1707.
    Paper not yet in RePEc: Add citation now
    

51. Galvao, A. F., Gu, J., & Volgushev, S. (2020). On the unbiased asymptotic normality of quantile regression with fixed effects. Journal of Econometrics, 218(1), 178–215.

52. Geraci, M. (2019). Modelling and estimation of nonlinear quantile regression with clustered data. Computational Statistics & Data Analysis, 136, 30–46.

53. Ghysels, E., Kvedaras, V., & Zemlys, V. (2016). Mixed frequency data sampling regression models: The R package midasr. Journal of Statistical Software, 72(4), 1–35. 10.18637/jss.v072.i04.

54. Ghysels, E., Santa‐Clara, P., & Valkanov, R. (2004). The MIDAS touch: Mixed data sampling regression models. UCLA Publications. https://escholarship.org/content/qt9mf223rs/qt9mf223rs.pdf.

55. Gulen, H., & Ion, M. (2015). Policy uncertainty and corporate investment. Review of Financial Studies, 29(3), 523–564.
    Paper not yet in RePEc: Add citation now
    
56. Hajizadeh, E., Seifi, A., Zarandi, M. F., & Turksen, I. B. (2012). A hybrid modeling approach for forecasting the volatility of S&P 500 index return. Expert Systems with Applications, 39(1), 431–436.
    Paper not yet in RePEc: Add citation now
    
57. Hall, P., & Sheather, S. J. (1988). On the distribution of a studentized quantile. Journal of the Royal Statistical Society: Series B (Methodological), 50(3), 381–391.
    Paper not yet in RePEc: Add citation now
    

58. Hansen, P. R., Huang, Z., & Shek, H. H. (2012). Realized GARCH: A joint model for returns and realized measures of volatility. Journal of Applied Econometrics, 27(6), 877–906.

59. Hendricks, W., & Koenker, R. (1992). Hierarchical spline models for conditional quantiles and the demand for electricity. Journal of the American statistical Association, 87(417), 58–68.
    Paper not yet in RePEc: Add citation now
    

60. Im, H. J., Park, H., & Zhao, G. (2017). Uncertainty and the value of cash holdings. Economics Letters, 155, 43–48.

61. Javaheri, A., Wilmott, P., & Haug, E. G. (2004). GARCH and volatility swaps. Quantitative Finance, 4(5), 589–595.

62. Jens, C. E. (2017). Political uncertainty and investment: Causal evidence from US gubernatorial elections. Journal of Financial Economics, 124(3), 563–579.

63. Jiang, Y., Zhu, Z., Tian, G., & Nie, H. (2019). Determinants of within and cross‐country economic policy uncertainty spillovers: Evidence from US and China. Finance Research Letters, 31(2019), 195–206.

64. Kang, S., Hernandez, J. A., Sadorsky, P., & McIver, R. (2021). Frequency spillovers, connectedness, and the hedging effectiveness of oil and gold for US sector ETFs. Energy Economics, 99, 105278.

65. Kelly, B., Pástor, L., & Veronesi, P. (2016). The price of political uncertainty: Theory and evidence from the option market. The Journal of Finance, 71(5), 2417–2480.

66. Koenker, R. W., & d'Orey, V. (1987). Algorithm AS 229: Computing regression quantiles. Applied statistics, 383–393.
    Paper not yet in RePEc: Add citation now
    
67. Koenker, R., & Machado, J. A. (1999). Goodness of fit and related inference processes for quantile regression. Journal of the American Statistical Association, 94(448), 1296–1310.
    Paper not yet in RePEc: Add citation now
    
68. Koenker, R., & Ng, P. (2005). A Frisch‐Newton algorithm for sparse quantile regression. Acta Mathematicae Applicatae Sinica, 21(2), 225–236.
    Paper not yet in RePEc: Add citation now
    

69. Krol, R. (2014). Economic policy uncertainty and exchange rate volatility. International Finance, 17(2), 241–256.

70. Lindblad, A. (2017). Sentiment indicators and macroeconomic data as drivers for low‐frequency stock market volatility (MPRA Paper 80266). University Library of Munich.
    Paper not yet in RePEc: Add citation now
    
71. Lindblad, A. (2019). Evaluating macro‐finance interactions using mixed frequency methods (Doctoral dissertation). Helsinki Center of Economic Research.
    Paper not yet in RePEc: Add citation now
    

72. Liow, K. H., Liao, W. C., & Huang, Y. (2018). Dynamics of international spillovers and interaction: Evidence from financial market stress and economic policy uncertainty. Economic Modelling, 68, 96–116.

73. Litterman, R. B. (1983). A random walk, Markov model for the distribution of time series. Journal of Business & Economic Statistics, 1(2), 169–173.

74. Liu, H. C., & Hung, J. C. (2010). Forecasting S&P‐100 stock index volatility: The role of volatility asymmetry and distributional assumption in GARCH models. Expert Systems with Applications, 37(7), 4928–4934.
    Paper not yet in RePEc: Add citation now
    

75. Liu, L., & Zhang, T. (2015). Economic policy uncertainty and stock market volatility. Finance Research Letters, 15, 99–105.

76. Ludvigson, S. C., Ma, S., & Ng, S. (2021). Uncertainty and business cycles: Exogenous impulse or endogenous response? American Economic Journal: Macroeconomics, 13(4), 369–410.

77. Manela, A., & Moreira, A. (2017). News implied volatility and disaster concerns. Journal of Financial Economics, 123(1), 137–162.

78. Nguyen, N. H., & Phan, H. V. (2017). Policy uncertainty and mergers and acquisitions. Journal of Financial and Quantitative Analysis, 52(2), 613–644.

79. Pan, Z., Wang, Y., & Liu, L. (2021). Macroeconomic uncertainty and expected shortfall (and value at risk): A new dynamic semiparametric model. Quantitative Finance, 1–15.

80. Pan, Z., Wang, Y., Wu, C., & Yin, L. (2017). Oil price volatility and macroeconomic fundamentals: A regime switching GARCH‐MIDAS model. Journal of Empirical Finance, 43, 130–142.

81. Panousi, V., & Papanikolaou, D. (2012). Investment, idiosyncratic risk, and ownership. Journal of Finance, 67(3), 1113–1148.

82. Patrick, R. H. (2021). Durbin–Wu–Hausman specification tests. In Handbook of financial econometrics, mathematics, statistics, and machine learning (pp. 1075–1108). World Scientific.
    Paper not yet in RePEc: Add citation now
    

83. Perron, P., & Phillips, P. C. (1987). Does GNP have a unit root?: A re‐evaluation. Economics Letters, 23(2), 139–145.

84. Peters, E. E. (1994). Fractal market analysis: Applying chaos theory to investment and economics (Vol. 24). John Wiley & Sons.
    Paper not yet in RePEc: Add citation now
    

85. Phan, H. V., Nguyen, N. H., Nguyen, H. T., & Hegde, S. (2019). Policy uncertainty and firm cash holdings. Journal of Business Research, 95, 71–82.

86. Powell, J. L. (1986). Censored regression quantiles. Journal of Econometrics, 32(1), 143–155.

87. Robe, M. A., & Wallen, J. (2016). Fundamentals, derivatives market information and oil price volatility. Journal of Futures Markets, 36(4), 317–344.

88. Sharif, A., Aloui, C., & Yarovaya, L. (2020). COVID‐19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet‐based approach. International Review of Financial Analysis, 70, 101496.

89. Shephard, N., & Sheppard, K. (2010). Realising the future: forecasting with high‐frequency‐based volatility (HEAVY) models Journal of Applied Econometrics, 25(2), 197–231.

90. Su, Z., Fang, T., & Yin, L. (2017). The role of news‐based implied volatility among US financial markets. Economics Letters, 157, 24–27.

91. Su, Z., Fang, T., & Yin, L. (2019). Understanding Stock Market Volatility: What is the Role of U.S. Uncertainty? North American Journal of Economics and Finance, 48, 582–590.

92. Su, Z., Lu, M., & Yin, L. (2018). Oil prices and news‐based uncertainty: Novel evidence. Energy Economics, 72, 331–340.
    Paper not yet in RePEc: Add citation now
    

93. Tsai, I. C. (2017). The source of global stock market risk: A viewpoint of economic policy uncertainty. Economic Modelling, 60, 122–131.

94. Walkup, B. (2016). The impact of uncertainty on payout policy. Managerial Finance, 42(11), 1054–1072.

95. Wen, F., Xiao, Y., & Wu, H. (2019). The effects of foreign uncertainty shocks on China's macro‐economy: Empirical evidence from a nonlinear ARDL model. Physica A: Statistical Mechanics and its Applications, 532, 121879.
    Paper not yet in RePEc: Add citation now
    
96. Whaley, R. E. (1993). Derivatives on market volatility: Hedging tools long overdue. The journal of Derivatives, 1(1), 71–84.
    Paper not yet in RePEc: Add citation now
    
97. Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98–105.
    Paper not yet in RePEc: Add citation now
    
98. Xu, Y., Wang, X., & Liu, H. (2021). Quantile‐based GARCH‐MIDAS: Estimating value‐at‐risk using mixed‐frequency information. Finance Research Letters, 43, 101965.
    Paper not yet in RePEc: Add citation now
    
99. Yu, K., Lu, Z., & Stander, J. (2003). Quantile regression: Applications and current research areas. Journal of the Royal Statistical Society: Series D (The Statistician), 52(3), 331–350.
    Paper not yet in RePEc: Add citation now
    

100. Zhu, S., Liu, Q., Wang, Y., Wei, Y., & Wei, G. (2019). Which fear index matters for predicting US stock market volatilities: Text‐counts or option based measurement? Physica A: Statistical Mechanics and its Applications, 536, 122567.

1. Forecasting Oil Price Using Web-based Sentiment Analysis. (2019). Zhao, Lu-Tao ; Zhang, Zhi-Gang ; Wang, Wen-Jing ; Zeng, Guan-Rong.
   In: Energies.
   RePEc:gam:jeners:v:12:y:2019:i:22:p:4291-:d:285712.

   Full description at Econpapers || Download paper

2. Does Chaos Matter in Financial Time Series Analysis?. (2019). Bruno, Bruna ; Faggini, Marisa ; Parziale, Anna.
   In: International Journal of Economics and Financial Issues.
   RePEc:eco:journ1:2019-04-3.

   Full description at Econpapers || Download paper

3. Are the Crude Oil Markets Really Becoming More Efficient over Time? Some New Evidence. (2018). Krištoufek, Ladislav.
   In: Working Papers IES.
   RePEc:fau:wpaper:wp2018_07.

   Full description at Econpapers || Download paper

4. The lead-lag relationships between spot and futures prices of natural gas. (2018). Zhang, Yahui ; Liu, LI.
   In: Physica A: Statistical Mechanics and its Applications.
   RePEc:eee:phsmap:v:490:y:2018:i:c:p:203-211.

   Full description at Econpapers || Download paper

5. “CHAOS” IN ENERGY AND COMMODITY MARKETS: A CONTROVERSIAL MATTER. (2017). Vellucci, Pierluigi ; Mastroeni, Loretta.
   In: Departmental Working Papers of Economics - University 'Roma Tre'.
   RePEc:rtr:wpaper:0218.

   Full description at Econpapers || Download paper

6. A multi-criteria approach to selecting an optimal portfolio of refinery upgrade projects under margin and tax regime uncertainty. (2017). Korotin, Vladimir ; Popov, Victor ; Islamov, Rustam ; Ulchenkov, Arseniy ; Tolokonsky, Andrey .
   In: Omega.
   RePEc:eee:jomega:v:72:y:2017:i:c:p:50-58.

   Full description at Econpapers || Download paper

7. The stability of the international heat pump trade pattern based on complex networks analysis. (2017). Hao, Xiaoqing ; Feng, Sida ; Liu, Nairong ; An, Haizhong.
   In: Applied Energy.
   RePEc:eee:appene:v:196:y:2017:i:c:p:100-117.

   Full description at Econpapers || Download paper

8. Crude Oil Price Volatility Spillovers and Agricultural Commodities: A Study in Time and Frequency Domains. (2017). Macri, Joseph ; Raffiee, Kambiz ; Adrangi, Bahram ; Chatrath, Arjun.
   In: Review of Economics & Finance.
   RePEc:bap:journl:170304.

   Full description at Econpapers || Download paper

9. Chaos in energy and commodity markets: a controversial matter. (2017). Vellucci, Pierluigi ; Mastroeni, Loretta.
   In: Papers.
   RePEc:arx:papers:1611.07432.

   Full description at Econpapers || Download paper

10. “Butterfly Effect vs Chaos in Energy Futures Markets. (2016). Vellucci, Pierluigi ; Mastroeni, Loretta.
    In: Departmental Working Papers of Economics - University 'Roma Tre'.
    RePEc:rtr:wpaper:0209.

    Full description at Econpapers || Download paper

11. Testing Non-Linear Dynamics, Long Memory and Chaotic Behaviour of Energy Commodities. (2016). Gencer, Murat ; Unal, Gazanfer.
    In: MPRA Paper.
    RePEc:pra:mprapa:74115.

    Full description at Econpapers || Download paper

12. Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market. (2016). Gu, Rongbao ; Zhang, Bing.
    In: Energy Economics.
    RePEc:eee:eneeco:v:53:y:2016:i:c:p:151-158.

    Full description at Econpapers || Download paper

13. Butterfly Effect vs Chaos in Energy Futures Markets. (2016). Vellucci, Pierluigi ; Mastroeni, Loretta.
    In: Papers.
    RePEc:arx:papers:1610.05697.

    Full description at Econpapers || Download paper

14. Multifractal spectrum analysis of Brent crude oil futures prices volatility in intercontinental exchange. (2015). Chen, Lianghua.
    In: International Journal of Global Energy Issues.
    RePEc:ids:ijgeni:v:38:y:2015:i:1/2/3:p:93-108.

    Full description at Econpapers || Download paper

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    In: Journal of Systems Science and Information.
    RePEc:bpj:jossai:v:3:y:2015:i:2:p:111-132:n:2.

    Full description at Econpapers || Download paper

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    In: Journal for Economic Forecasting.
    RePEc:rjr:romjef:v::y:2014:i:3:p:108-135.

    Full description at Econpapers || Download paper

17. The role of fluctuating modes of autocorrelation in crude oil prices. (2014). Ding, Yinghui ; Huang, Xuan ; Gao, Xiangyun ; Fang, Wei.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:393:y:2014:i:c:p:382-390.

    Full description at Econpapers || Download paper

18. Features and evolution of international crude oil trade relationships: A trading-based network analysis. (2014). Chen, Yurong ; Gao, Xiangyun ; Zhong, Weiqiong ; Li, Huajiao ; An, Haizhong.
    In: Energy.
    RePEc:eee:energy:v:74:y:2014:i:c:p:254-259.

    Full description at Econpapers || Download paper

19. Predicting oil price movements: A dynamic Artificial Neural Network approach. (2014). Jamasb, Tooraj ; Amiri, Rohollah Madadi ; Talaei, Alireza ; Godarzi, Ali Abbasi .
    In: Energy Policy.
    RePEc:eee:enepol:v:68:y:2014:i:c:p:371-382.

    Full description at Econpapers || Download paper

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    In: Energy Policy.
    RePEc:eee:enepol:v:63:y:2013:i:c:p:504-513.

    Full description at Econpapers || Download paper

21. Testing for nonlinearity and chaos in economic time series with noise titration. (2013). Caraiani, Petre.
    In: Economics Letters.
    RePEc:eee:ecolet:v:120:y:2013:i:2:p:192-194.

    Full description at Econpapers || Download paper

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    In: Review of Economics & Finance.
    RePEc:bap:journl:130301.

    Full description at Econpapers || Download paper

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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:391:y:2012:i:22:p:5546-5556.

    Full description at Econpapers || Download paper

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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:391:y:2012:i:14:p:3770-3782.

    Full description at Econpapers || Download paper

25. Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?. (2012). Wang, Yudong ; Wu, Chongfeng.
    In: Energy Economics.
    RePEc:eee:eneeco:v:34:y:2012:i:6:p:2167-2181.

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26. Energy prices and exchange rates of the U.S. dollar: Further evidence from linear and nonlinear causality analysis. (2012). Wang, Yudong ; Wu, Chongfeng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:29:y:2012:i:6:p:2289-2297.

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27. Chaotic Time Series Analysis in Economics: Balance and Perspectives. (2011). Faggini, Marisa.
    In: Working papers.
    RePEc:tur:wpaper:25.

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28. Is there co-movement of agricultural commodities futures prices and crude oil?. (2011). McKenzie, Andrew ; Natanelov, Valeri ; Alam, Mohammad J. ; van Huylenbroeck, Guido.
    In: Energy Policy.
    RePEc:eee:enepol:v:39:y:2011:i:9:p:4971-4984.

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29. Can GARCH-class models capture long memory in WTI crude oil markets?. (2011). WEI, Y ; Wang, Yudong ; Wu, Chongfeng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:28:y:2011:i:3:p:921-927.

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30. Exchange Rates and Inflation Rates: Exploring Nonlinear Relationships. (2011). Allender, Mary E. ; Raffiee, Kambiz ; Adrangi, Bahram.
    In: Review of Economics & Finance.
    RePEc:bap:journl:110201.

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31. Is There Co-Movement of Agricultural Commodities Futures Prices and Crude Oil?. (2011). McKenzie, Andrew ; Natanelov, Valeri ; Alam, Mohammad J. ; van Huylenbroeck, Guido.
    In: 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland.
    RePEc:ags:eaae11:114626.

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32. Is Price Behavior Scaling and Multiscaling in a Dealer Market? Perspectives from Multi-Agent Based Experiments. (2010). He, Ling-Yun.
    In: Computational Economics.
    RePEc:kap:compec:v:36:y:2010:i:3:p:263-282.

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33. Oil Price Volatility and Stock Price Fluctuations in an Emerging Market: Evidence from South Korea. (2010). Sanjay, PETERS ; Rumi, MASIH .
    In: EcoMod2003.
    RePEc:ekd:003307:330700096.

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34. Wavelet domain correlation between the futures prices of natural gas and oil. (2010). Tonn, Victor Lux ; McCarthy, Joseph ; Li, H. C..
    In: The Quarterly Review of Economics and Finance.
    RePEc:eee:quaeco:v:50:y:2010:i:4:p:408-414.

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35. Multifractal spectrum analysis of nonlinear dynamical mechanisms in China’s agricultural futures markets. (2010). He, Ling-Yun ; Chen, Shu-Peng.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:389:y:2010:i:7:p:1434-1444.

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36. Are developed and emerging agricultural futures markets multifractal? A comparative perspective. (2010). He, Ling-Yun ; Chen, Shu-Peng.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:389:y:2010:i:18:p:3828-3836.

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37. Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives. (2010). He, Ling-Yun ; Chen, Shu-Peng.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:389:y:2010:i:16:p:3218-3229.

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38. Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis. (2010). Wang, Yudong ; Gu, Rongbao ; Chen, Hongtao.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:389:y:2010:i:14:p:2805-2815.

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39. Forecasting crude oil market volatility: Further evidence using GARCH-class models. (2010). Wang, Yudong ; Wei, YU ; Huang, Dengshi.
    In: Energy Economics.
    RePEc:eee:eneeco:v:32:y:2010:i:6:p:1477-1484.

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40. A novel algorithm for prediction of crude oil price variation based on soft computing. (2009). Zare, Samaneh ; Ghaffari, Ali.
    In: Energy Economics.
    RePEc:eee:eneeco:v:31:y:2009:i:4:p:531-536.

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41. Impact of speculators expectations of returns and time scales of investment on crude oil price behaviors. (2009). Wei, Yi-Ming ; He, Ling-Yun ; Fan, Ying.
    In: Energy Economics.
    RePEc:eee:eneeco:v:31:y:2009:i:1:p:77-84.

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42. Forecasting volatility of crude oil markets. (2009). Yoon, Seong-Min ; Kang, Sang Hoon.
    In: Energy Economics.
    RePEc:eee:eneeco:v:31:y:2009:i:1:p:119-125.

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43. Short-term predictability of crude oil markets: A detrended fluctuation analysis approach. (2008). Alvarez-Ramirez, Jose ; Rodriguez, Eduardo.
    In: Energy Economics.
    RePEc:eee:eneeco:v:30:y:2008:i:5:p:2645-2656.

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44. Can the dynamics of the term structure of petroleum futures be forecasted? Evidence from major markets. (2008). Skiadopoulos, George ; Chantziara, Thalia.
    In: Energy Economics.
    RePEc:eee:eneeco:v:30:y:2008:i:3:p:962-985.

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45. A generalized pattern matching approach for multi-step prediction of crude oil price. (2008). Wei, Yi-Ming ; Fan, Ying ; Liang, Qiang.
    In: Energy Economics.
    RePEc:eee:eneeco:v:30:y:2008:i:3:p:889-904.

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46. Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility. (2007). Tabak, Benjamin ; Cajueiro, Daniel.
    In: Energy Economics.
    RePEc:eee:eneeco:v:29:y:2007:i:1:p:28-36.

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47. Modeling dynamic conditional correlations in WTI oil forward and futures returns. (2006). Manera, Matteo ; Lanza, Alessandro.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:3:y:2006:i:2:p:114-132.

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48. Empirical asset return distributions: is chaos the culprit?. (2004). Muckley, Cal.
    In: Applied Economics Letters.
    RePEc:taf:apeclt:v:11:y:2004:i:2:p:81-86.

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49. Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets. (2003). Akin, Rita Madarassy .
    In: Santa Cruz Department of Economics, Working Paper Series.
    RePEc:cdl:ucscec:qt1n04g31b.

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50. Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets. (2003). Akin, Rita Madarassy .
    In: Santa Cruz Center for International Economics, Working Paper Series.
    RePEc:cdl:scciec:qt1n04g31b.

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