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1. Antonakakis, N., Balcilar, M., Gupta, R., and Kyei, C.K. (2017). Components of economic policy uncertainty and predictability of US stock returns and volatility: evidence from a nonparametric causality-in-quantile approach. Frontiers in Finance and Economics, 14(2), 20-49.
   Paper not yet in RePEc: Add citation now
   

2. Asgharian, H., Hou , A.J., and Javed , F . (2013). The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH MIDAS Approach. Journal of Forecasting, 32, 600-612. Baker, S.R., Bloom, N.A., Davis, S.J., Kost, K. (Forthcoming). Policy News and Stock Market Volatility. Journal of Financial Economics.

3. Baker, S.R., Bloom, N.A., Davis, S.J., Kost, K., Sammon, M., and Viratyosin, T. (2020). The Unprecedented Stock Market Reaction to COVID-19. Review of Asset Pricing Studies, 10(4), 742-758.

4. Bańbura, M., Giannone, D., and Reichlin, L. (2011). Nowcasting. Oxford Handbook on Economic Forecasting, 63?90, Oxford University Press.
   Paper not yet in RePEc: Add citation now
   

5. Ben Nasr, A. Ajmi, A. N., and Gupta, R. (2014) Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model, Applied Financial Economics, 24(14), 993-1004.

6. Ben Nasr, A., Lux, T., Ajmi, A.N., and Gupta, R. (2016). Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching. International Review of Economics & Finance, 45, 559-571.

7. Caggiano, G., Castelnuovo, E., and Kima, R. (2020). The global effects of Covid-19-induced uncertainty. Economics Letters, 194(C), 109392.

8. Calvet, L., and Fisher, A. (2004). How to forecast long-run volatility: Regime switching and the estimation of multifractal processes. Journal of Financial Econometrics, 2, 49-83.

9. Calvet, L., Fisher, A., and Thompson, S.B. (2006). Volatility comovement: a multifrequency approach. Journal of Econometrics, 131, 179-215.

10. Campbell, J.Y. (2008). Viewpoint: estimating the equity premium, Canadian Journal of Economics, 41, 1-21.

11. Conrad, C., and Loch , K . (2015). Anticipating Long term Stock Market Volatility. Journal of Applied Econometrics, 30, 1090-1114.

12. Conrad, C., Loch, K., and Rittler, D. (2014). On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets. Journal of Empirical Finance, 29, 26?40.

13. Cox, J., Greenwald, D.L., and Ludvigson, S.C. (2020). What Explains the COVID-19 Stock Market? National Bureau of Economic Research (NBER) Working Paper No. 27784.

14. Das, S., Demirer, R., Gupta, R., and Mangisa, S. (2019). The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis. Structural Change and Economic Dynamics, 50, 132-147.

15. Demirer, R., Gupta, R., Li, H., and You, Y. (2021). A Note on Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models. Applied Economics Letters. DOI: https:// doi.org/10.1080/13504851.2021.1971613.

16. Dickey, D., and Fuller, W.A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057-1072.

17. Diebold, F.X. (1986). Comment on Modeling the persistence of conditional variance, by Engle R.F., and Bollerslev T. Econometric Reviews, 5, 51-56.
    Paper not yet in RePEc: Add citation now
    

18. Diebold, F.X., and Mariano, R.S. (1995). Comparing Predictive Accuracy. Journal of Business & Economic Statistics, 13(3), 253-263.

19. Donzwa, W., Gupta, R., and Wohar, M.E. (2019). Volatility Spillovers between Interest Rates and Equity Markets of Developed Economies. Journal of Central Banking Theory and Practice, 8(3), 39-50.

20. Engle, R.F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50, 987-1007.

21. Engle, R.F. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate GARCH Models. Journal of Business and Economic Statistics, 20(3), 339-350.
    Paper not yet in RePEc: Add citation now
    

22. Engle, R.F., and Rangel, J.G. (2008) The Spline-GARCH Model for LowFrequency Volatility and Its Global Macroeconomic Causes, Review of Financial Studies, 21(3), 1187-1222.

23. Engle, R.F., Ghysels, E., and Sohn, B. (2013) Stock Market Volatility and Macroeconomic Fundamentals, Review of Economics and Statistics, 95(3), 776-797.

24. Fang, T., Lee, T-H., and Su, Z. (2020). Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection. Journal of Empirical Finance, 58, 36-49.

25. Ghysels, E., and Valkanov, R. (2012). Forecasting volatility with MIDAS. In L. Bauwens, C. Hafner, and S. Laurent (Eds.) Handbook of Volatility Models and Their Applications, Hoboken, New Jersey, United States : John Wiley & Sons, Inc, 383-401.
    Paper not yet in RePEc: Add citation now
    

26. Gupta, R., and Wohar, M.E. (2019) The role of monetary policy uncertainty in predicting equity market volatility of the United Kingdom: Evidence from over 150 years of data, Economics and Business Letters, 8(3), 138-146.

27. Gupta, R., Sheng, X., Balcilar, M., and Ji, Q. (2021). Time-varying impact of pandemics on global output growth. Finance Research Letters, 41(C), 101823.

28. Hassani, H., Yeganegi, M.R., and Gupta, R. (2020). Historical Forecasting of Interest Rate Mean and Volatility of the United States: Is there a Role of Uncertainty? Annals of Financial Economics, 15(4), 1-17.

29. Hkiri, B., Cunado, J., Balcilar, M., and Gupta, R. (2021). Time-varying relationship between conventional and unconventional monetary policies and risk aversion: international evidence from time- and frequency-domains.

30. Husted, L., Rogers, J., and Sun, B. (2020). Monetary policy uncertainty? Journal of Monetary Economics, 115, 20-36 Istrefi, K., and Mouabbi, S. (2018). Subjective interest rate uncertainty and the macroeconomy: A cross-country analysis. Journal of International Money and Finance, 88(C), 296-313.

31. Kaminska, I., and Roberts-Sklar, M. (2018) Volatility in equity markets and monetary policy rate uncertainty, Journal of Empirical Finance, 45, 68?83.

32. Krippner, L. (2013). Measuring the Stance of Monetary Policy in Zero Lower Bound Environments. Economics Letters, 118, 135-38.

33. Krippner, L. (2015). Zero Lower Bound Term Structure Modeling: A Practitioner ’s Guide. PalgraveMacmillan.
    Paper not yet in RePEc: Add citation now
    

34. Krippner, L. (2020). A Note of Caution on Shadow Rate Estimates. Journal of Money, Credit, and Banking, 52(4), 951-962.

35. Lamoureux, C.G., and Lastrapes, W.D. (1990). Persistence in variance, structural change and the GARCH model. Journal of Business and Economic Statistics, 8, 225-234.

36. Liu, R., and Gupta, R. (2020). Investors? Uncertainty and Forecasting Stock Market Volatility. Journal of Behavioral Finance. DOI: https://doi. org/10.1080/15427560.2020.1867551.

37. Liu, R., Demirer, R., Gupta, R., Wohar, M.E. (2020). Do Bivariate Multifractal Models Improve Volatility Forecasting in Financial Time Series? An Application to Foreign Exchange and Stock Markets. Journal of Forecasting, 39(2), 155-167.

38. Lux, T. (2008). The Markov-switching multifractal model of asset returns: GMM estimation and linear forecasting of volatility. Journal of Business and Economic Statistics, 26(2), 194-210.

39. Mandelbrot, B. (1974). Intermittent Turbulence in Self Similar Cascades: Divergence of High Moments and Dimension of Carrier. Journal of Fluid Mechanics, 62, 331-358.
    Paper not yet in RePEc: Add citation now
    

40. Mandelbrot, B., Fisher, A., Calvet, L. (1997). A Multifractal Model of Asset Returns. Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.

41. Paule-Vianez, J., and Gómez-Martnez, R., and Prado-Román, C. (2020). Effect of Economic and Monetary Policy Uncertainty on stock markets.
    Paper not yet in RePEc: Add citation now
    
42. Pitt, M. K. and N. Shephard (1999). Filtering via simulation based on auxiliary particle filters. J. American Statistical Association 94, 590-599.
    Paper not yet in RePEc: Add citation now
    

43. Poon, S-H, and Granger, C.W.J. (2003). Forecasting Volatility in Financial Markets: A Review. Journal of Economic Literature, 41(2), 478-539.

44. Rajan, R.G. (2006). Has Finance Made the World Riskier? European Financial Management 12, 499-533.

45. Rangel, J.G., and Engle, R.F. (2011) The Factor-Spline-GARCH Model for High and Low Frequency Correlations, Journal of Business & Economic Statistics, 30(1), 109-124.

46. Rapach, D.E., Wohar, M.E., and Strauss, J. (2008). Forecasting Stock Return Volatility in the Presence of Structural Breaks, in Forecasting in the Presence of Structural Breaks and Model Uncertainty, David E. Rapach and Mark E. Wohar (Eds.), Vol. 3 of Frontiers of Economics and Globalization, Bingley, United Kingdom: Emerald, 381-416.
    Paper not yet in RePEc: Add citation now
    
47. Rubin, D. B. (1987). Comment: A noniterative Sampling/Importance Resampling alternative to the data augmentation algorithm for creating a few imputations when fractions of missing information are modest: The SIR algorithm. Journal of the American Statistical Association, 82:543546.
    Paper not yet in RePEc: Add citation now
    

48. Salisu, A.A., Adediran, I.A., and Gupta, R. (2021b) Note on the COVID-19 Shock and Real GDP in Emerging Economies. Emerging Markets, Finance and Trade. DOI: https://doi.org/10.1080/1540496X.2021.1981854.

49. Salisu, A.A., and Gupta, R. (2021). Oil shocks and stock market volatility of the BRICS: A GARCH-MIDAS approach. Global Finance Journal, 48(C), 100546.

50. Salisu, A.A., Ayinde, T.O., Gupta, R., and Wohar, M.E. (2021a). Global Evidence of the COVID-19 Shock on Real Equity Prices and Real Exchange Rates: A Counterfactual Analysis with a Threshold-Augmented GVAR Model. Finance Research letters. DOI: https://doi.org/10.1016/j. frl.2021.102519. Salisu, A.A., Demirer, R., and Gupta, R. (Forthcoming). Financial Turbulence, Systemic Risk and the Predictability of Stock Market Volatility. Global Finance Journal.

51. Salisu, A.A., Gupta, R., and Ogbonna, A.E. (2020). A Moving Average Heterogeneous Autoregressive Model for Forecasting the Realized Volatility of the US Stock Market: Evidence from Over a Century of Data. International Journal of Finance & Economics. DOI: https://doi.org/ 10.1002/ijfe.2158.

52. Tse, Y. and Tsui, A. (2002). A Multivariate GARCH Model with TimeVarying Correlations. Journal of Business and Economic Statistics, 20, 351-362.
    Paper not yet in RePEc: Add citation now
    

53. Valera, H.A.G., Holmes, M.J, and Gazi, H. (2017). Stock market uncertainty and interest rate: A Panel GARCH Approach. Applied Economics Letters, 24(11), 732-735.

54. Wu, J.C., and Xia, F.D. (2016). Measuring the macroeconomic impact of monetary policy at the zero lower bound. Journal of Money, Credit, and Banking, 48(2-3), 253-291.

55. Xu, J. (2007). Interest rate uncertainty and stock market volatility. Unpublished master thesis, Singapore Management University, Singapore.
    Paper not yet in RePEc: Add citation now
    

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   In: Journal of Forecasting.
   RePEc:wly:jforec:v:40:y:2021:i:1:p:17-39.

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   In: Finance Research Letters.
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   In: Working Papers.
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    In: Papers.
    RePEc:arx:papers:2007.12838.

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13. Testing for an omitted multiplicative long-term component in GARCH models. (2019). Schienle, Melanie ; Conrad, Christian.
    In: Working Paper Series in Economics.
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    In: The Journal of Economic Asymmetries.
    RePEc:eee:joecas:v:20:y:2019:i:c:s1703494919300672.

    Full description at Econpapers || Download paper

18. International spillovers of U.S. financial volatility. (2019). Vu, Nam ; Berg, Kimberly.
    In: Journal of International Money and Finance.
    RePEc:eee:jimfin:v:97:y:2019:i:c:p:19-34.

    Full description at Econpapers || Download paper

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    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:61:y:2019:i:c:p:29-36.

    Full description at Econpapers || Download paper

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    In: Energy Economics.
    RePEc:eee:eneeco:v:84:y:2019:i:c:s0140988319303433.

    Full description at Econpapers || Download paper

21. Estimating MIDAS regressions via OLS with polynomial parameter profiling. (2019). Qian, Hang ; Ghysels, Eric.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:9:y:2019:i:c:p:1-16.

    Full description at Econpapers || Download paper

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    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:48:y:2019:i:c:p:582-590.

    Full description at Econpapers || Download paper

23. On the asymmetric impact of macro–variables on volatility. (2019). Gallo, Giampiero ; Amendola, Alessandra ; Candila, Vincenzo.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:76:y:2019:i:c:p:135-152.

    Full description at Econpapers || Download paper

24. Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility. (2019). Caporale, Guglielmo Maria ; Yfanti, Stavroula ; Karanasos, Menelaos.
    In: CESifo Working Paper Series.
    RePEc:ces:ceswps:_8000.

    Full description at Econpapers || Download paper

25. The importance of global economic policy uncertainty in predicting gold futures market volatility: A GARCH‐MIDAS approach. (2018). Qian, Yichuo ; Fang, Libing ; Yu, Honghai ; Chen, Baizhu.
    In: Journal of Futures Markets.
    RePEc:wly:jfutmk:v:38:y:2018:i:3:p:413-422.

    Full description at Econpapers || Download paper

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    In: Working Papers.
    RePEc:pre:wpaper:201858.

    Full description at Econpapers || Download paper

27. Modeling and forecasting commodity market volatility with long-term economic and financial variables. (2018). Walther, Thomas ; Nguyen, Duc Khuong.
    In: MPRA Paper.
    RePEc:pra:mprapa:84464.

    Full description at Econpapers || Download paper

28. Models with Multiplicative Decomposition of Conditional Variances and Correlations. (2018). Teräsvirta, Timo ; Silvennoinen, Annastiina ; Amado, Cristina ; Terasvirta, Timo.
    In: NIPE Working Papers.
    RePEc:nip:nipewp:07/2018.

    Full description at Econpapers || Download paper

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    In: Multinational Finance Journal.
    RePEc:mfj:journl:v:22:y:2018:i:3-4:p:119-172.

    Full description at Econpapers || Download paper

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    In: Energies.
    RePEc:gam:jeners:v:11:y:2018:i:6:p:1372-:d:149403.

    Full description at Econpapers || Download paper

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    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:505:y:2018:i:c:p:931-940.

    Full description at Econpapers || Download paper

32. How does stock market volatility react to NVIX? Evidence from developed countries. (2018). Chen, Ying ; Qian, Yichuo ; Fang, Libing ; Yu, Honghai.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:505:y:2018:i:c:p:490-499.

    Full description at Econpapers || Download paper

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    In: Pacific-Basin Finance Journal.
    RePEc:eee:pacfin:v:51:y:2018:i:c:p:13-31.

    Full description at Econpapers || Download paper

34. Oil and the short-term predictability of stock return volatility. (2018). Yin, Libo ; Wang, Yudong ; Wei, YU ; Wu, Chongfeng.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:47:y:2018:i:c:p:90-104.

    Full description at Econpapers || Download paper

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    In: CREATES Research Papers.
    RePEc:aah:create:2018-14.

    Full description at Econpapers || Download paper

36. On the influence of US monetary policy on crude oil price volatility. (2017). Scognamillo, Antonio ; Amendola, Alessandra ; Candila, Vincenzo.
    In: Empirical Economics.
    RePEc:spr:empeco:v:52:y:2017:i:1:d:10.1007_s00181-016-1069-5.

    Full description at Econpapers || Download paper

37. Forecasting realized volatility: a review. (2017). Bucci, Andrea.
    In: MPRA Paper.
    RePEc:pra:mprapa:83232.

    Full description at Econpapers || Download paper

38. Sentiment indicators and macroeconomic data as drivers for low-frequency stock market volatility. (2017). Lindblad, Annika.
    In: MPRA Paper.
    RePEc:pra:mprapa:80266.

    Full description at Econpapers || Download paper

39. European equity market integration and joint relationship of conditional volatility and correlations. (2017). Virk, Nader ; Javed, Farrukh.
    In: Journal of International Money and Finance.
    RePEc:eee:jimfin:v:71:y:2017:i:c:p:53-77.

    Full description at Econpapers || Download paper

40. Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?. (2017). Wei, YU ; Hu, Yang ; Lai, Xiaodong ; Liu, Jing.
    In: Energy Economics.
    RePEc:eee:eneeco:v:68:y:2017:i:c:p:141-150.

    Full description at Econpapers || Download paper

41. Macroeconomic Variables, Leverage, Stock Returns and Stock Return Volatility. (2017). Magwedere, Margaret Rutendo.
    In: Acta Universitatis Danubius. OEconomica.
    RePEc:dug:actaec:y:2017:i:4:p:264-288.

    Full description at Econpapers || Download paper

42. Forecasting the return volatility of energy prices: A GARCH MIDAS approach. (2017). Salisu, Afees ; Swaray, Raymond.
    In: Working Papers.
    RePEc:cui:wpaper:0029.

    Full description at Econpapers || Download paper

43. MIDAS models in banking sector – systemic risk comparison. (2017). Mestel, Roland ; Gurgul, Henryk ; Syrek, Robert.
    In: Managerial Economics.
    RePEc:agh:journl:v:18:y:2017:i:2:p:165-181.

    Full description at Econpapers || Download paper

44. What drives long-term oil market volatility? Fundamentals versus Speculation. (2016). Yin, Libo ; Zhou, Yimin.
    In: Economics Discussion Papers.
    RePEc:zbw:ifwedp:20162.

    Full description at Econpapers || Download paper

45. Effects of macroeconomic uncertainty on the stock and bond markets. (2015). Christiansen, Charlotte ; Asgharian, Hossein ; Hou, Ai Jun.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:13:y:2015:i:c:p:10-16.

    Full description at Econpapers || Download paper

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    In: Emerging Markets Review.
    RePEc:eee:ememar:v:22:y:2015:i:c:p:43-64.

    Full description at Econpapers || Download paper

47. Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data. (2015). Vander Elst, Harry ; Dominicy, Yves.
    In: Working Papers ECARES.
    RePEc:eca:wpaper:2013/220550.

    Full description at Econpapers || Download paper

48. Misspecification Testing in GARCH-MIDAS Models. (2015). Schienle, Melanie ; Conrad, Christian.
    In: Working Papers.
    RePEc:awi:wpaper:0597.

    Full description at Econpapers || Download paper

49. On the influence of the U.S. monetary policy on the crude oil price volatility. (2015). Scognamillo, Antonio ; Amendola, Alessandra ; Candila, Vincenzo.
    In: 2015 Fourth Congress, June 11-12, 2015, Ancona, Italy.
    RePEc:ags:aiea15:207860.

    Full description at Econpapers || Download paper

50. Effects of Macroeconomic Uncertainty upon the Stock and Bond Markets. (2015). Christiansen, Charlotte ; Asgharian, Hossein ; Hou, Ai Jun.
    In: CREATES Research Papers.
    RePEc:aah:create:2015-15.

    Full description at Econpapers || Download paper

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