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Realized Volatility: A Review. (2008). Medeiros, Marcelo ; McAleer, Michael.
In: Econometric Reviews.
RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:10-45.

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  1. Forecasting Realized US Stock Market Volatility: Is there a Role for Economic Policy Uncertainty?. (2024). Pierdzioch, Christian ; GUPTA, RANGAN ; Cepni, Oguzhan ; Bonato, Matteo.
    In: Working Papers.
    RePEc:pre:wpaper:202408.

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  2. Does public information facilitate price consensus? Characterizing USDA announcement effects using realized volatility. (2024). Janzen, Joseph P ; Bunek, Gabriel D.
    In: Journal of Commodity Markets.
    RePEc:eee:jocoma:v:33:y:2024:i:c:s2405851324000011.

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  3. Stabilizing global foreign exchange markets in the time of COVID-19: The role of vaccinations. (2024). Li, Xiao-Ming ; Thanh, Thao Thac ; Pham, Son Duy.
    In: Global Finance Journal.
    RePEc:eee:glofin:v:59:y:2024:i:c:s1044028323001187.

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  4. El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach. (2023). Pierdzioch, Christian ; Gupta, Rangan ; Epni, Ouzhan ; Bonato, Matteo.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:42:y:2023:i:4:p:785-801.

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  5. The effect of intraday periodicity on realized volatility measures. (2023). Kellermann, Janosch ; Golosnoy, Vasyl ; Dette, Holger.
    In: Metrika: International Journal for Theoretical and Applied Statistics.
    RePEc:spr:metrik:v:86:y:2023:i:3:d:10.1007_s00184-022-00875-0.

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  6. Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach. (2023). GUPTA, RANGAN ; Pierdzioch, Christian.
    In: Financial Innovation.
    RePEc:spr:fininn:v:9:y:2023:i:1:d:10.1186_s40854-022-00435-5.

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  7. Financial Stress and Realized Volatility: The Case of Agricultural Commodities. (2023). Pierdzioch, Christian ; Gupta, Rangan ; Cepni, Oguzhan ; Bonato, Matteo.
    In: Working Papers.
    RePEc:pre:wpaper:202320.

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  8. Stock Market Volatility and Multi-Scale Positive and Negative Bubbles. (2023). Pierdzioch, Christian ; Nielsen, Joshua ; Nel, Jacobus ; Gupta, Rangan.
    In: Working Papers.
    RePEc:pre:wpaper:202310.

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  9. Trading strategies and the frequency of time-series. (2023). Isaenko, Sergey.
    In: The Quarterly Review of Economics and Finance.
    RePEc:eee:quaeco:v:90:y:2023:i:c:p:267-283.

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  10. Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic. (2023). Salisu, Afees ; GUPTA, RANGAN ; Demirer, Riza ; van Eyden, Renee.
    In: The Quarterly Review of Economics and Finance.
    RePEc:eee:quaeco:v:88:y:2023:i:c:p:295-302.

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  11. Climate risks and state-level stock market realized volatility. (2023). Pierdzioch, Christian ; GUPTA, RANGAN ; Cepni, Oguzhan ; Bonato, Matteo.
    In: Journal of Financial Markets.
    RePEc:eee:finmar:v:66:y:2023:i:c:s1386418123000526.

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  12. Climate risks and realized volatility of major commodity currency exchange rates. (2023). GUPTA, RANGAN ; Pierdzioch, Christian ; Cepni, Oguzhan ; Bonato, Matteo.
    In: Journal of Financial Markets.
    RePEc:eee:finmar:v:62:y:2023:i:c:s1386418122000519.

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  13. Sample frequency robustness and accuracy in forecasting Value-at-Risk for Brent Crude Oil futures. (2023). Haugom, Erik ; Hadina, Jelena ; Ewald, Christian ; Yahya, Muhammad ; Stordal, Stle ; Lien, Gudbrand.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:58:y:2023:i:pa:s154461232300288x.

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  14. Bayesian estimation of realized GARCH-type models with application to financial tail risk management. (2023). , Edward ; Watanabe, Toshiaki.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:28:y:2023:i:c:p:30-46.

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  15. .

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  17. What matters when developing oil price volatility forecasting frameworks?. (2022). Filis, George ; Degiannakis, Stavros ; Delis, Panagiotis.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:41:y:2022:i:2:p:361-382.

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  18. Mixed?frequency forecasting of crude oil volatility based on the information content of global economic conditions. (2022). Salisu, Afees ; GUPTA, RANGAN ; Bouri, Elie ; Ji, Qiang.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:41:y:2022:i:1:p:134-157.

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  19. Business Applications and State-Level Stock Market Realized Volatility: A Forecasting Experiment. (2022). Pierdzioch, Christian ; Bonato, Matteo ; Cepni, Oguzhan ; Gupta, Rangan.
    In: Working Papers.
    RePEc:pre:wpaper:202247.

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  20. Climate Risks and State-Level Stock-Market Realized Volatility. (2022). Cepni, Oguzhan ; Gupta, Rangan ; Pierdzioch, Christian ; Bonato, Matteo.
    In: Working Papers.
    RePEc:pre:wpaper:202246.

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  21. The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks. (2022). Cepni, Oguzhan ; Bonato, Matteo ; Gupta, Rangan ; Wang, Shixuan.
    In: Working Papers.
    RePEc:pre:wpaper:202219.

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  22. Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model. (2022). , Suchitra ; Kumar, Chetan.
    In: MPRA Paper.
    RePEc:pra:mprapa:114027.

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  23. Oil tail-risk forecasts: from financial crisis to COVID-19. (2022). Kuang, Wei.
    In: Risk Management.
    RePEc:pal:risman:v:24:y:2022:i:4:d:10.1057_s41283-022-00100-2.

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  24. Factor momentum, option-implied volatility scaling, and investor sentiment. (2022). Rutanen, Jere ; Kolari, James W ; Grobys, Klaus.
    In: Journal of Asset Management.
    RePEc:pal:assmgt:v:23:y:2022:i:2:d:10.1057_s41260-021-00229-x.

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  25. Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market. (2022). Guzman, Vicente Alfonso ; Antonio, Esteban Jose ; Pulgar, Nicolas Magner.
    In: Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance).
    RePEc:imx:journl:v:17:y:2022:i:3:a:5.

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  26. The intraday dynamics and intraday price discovery of bitcoin. (2022). Yuan, Yulin ; Wang, Xinyi ; Su, Fei.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:60:y:2022:i:c:s0275531922000137.

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  27. Stock market volatility and the COVID-19 reproductive number. (2022). Winkelried, Diego ; Henriquez, Pablo A ; Diaz, Fernando.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:59:y:2022:i:c:s0275531921001380.

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  28. Value-at-Risk forecasting: A hybrid ensemble learning GARCH-LSTM based approach. (2022). Jain, Ishan ; Kakade, Kshitij ; Mishra, Aswini Kumar.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:78:y:2022:i:c:s0301420722003476.

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  29. Climate risks and forecastability of the realized volatility of gold and other metal prices. (2022). Pierdzioch, Christian ; GUPTA, RANGAN.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001295.

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  30. Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty. (2022). Salisu, Afees ; GUPTA, RANGAN ; Das, Sonali ; Karmakar, Sayar.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:75:y:2022:i:c:s0301420721005341.

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  31. Oil price volatility forecasts: What do investors need to know?. (2022). Filis, George ; Degiannakis, Stavros.
    In: Journal of International Money and Finance.
    RePEc:eee:jimfin:v:123:y:2022:i:c:s026156062100245x.

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  32. Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak. (2022). Lee, Chien-Chiang ; Adewuyi, Adeolu O ; Aikins, Emmanuel Joel ; Tiwari, Aviral Kumar.
    In: Energy Economics.
    RePEc:eee:eneeco:v:113:y:2022:i:c:s0140988322003796.

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  33. Global financial cycle and the predictability of oil market volatility: Evidence from a GARCH-MIDAS model. (2022). Salisu, Afees ; GUPTA, RANGAN ; Demirer, Riza.
    In: Energy Economics.
    RePEc:eee:eneeco:v:108:y:2022:i:c:s0140988322001128.

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  34. Forecasting oil and gold volatilities with sentiment indicators under structural breaks. (2022). GUPTA, RANGAN ; Demirer, Riza ; Ji, Qiang ; Luo, Jiawen.
    In: Energy Economics.
    RePEc:eee:eneeco:v:105:y:2022:i:c:s014098832100596x.

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  35. Empirical study and model simulation of global stock market dynamics during COVID-19. (2022). Li, Jiangcheng ; Jiang, Xiongfei ; Xiong, Long ; Zhang, Jiu ; Ma, Jiahao ; Zheng, BO ; Jin, Lifu.
    In: Chaos, Solitons & Fractals.
    RePEc:eee:chsofr:v:159:y:2022:i:c:s0960077922003484.

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  36. Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models. (2022). Taylor, Robert ; De Angelis, Luca ; Cavaliere, Giuseppe ; Boswijk, Peter H.
    In: Papers.
    RePEc:arx:papers:2202.02532.

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  37. Normative analysis of the impact of Covid-19 on prominent sectors of Indian economy by using ARCH Model. (2022). Suchitra, S ; Rangappa, K B ; Chetan, G K.
    In: Theoretical and Applied Economics.
    RePEc:agr:journl:v:2(631):y:2022:i:2(631):p:151-164.

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  38. .

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  39. VIX futures and its closed?form pricing through an affine GARCH model with realized variance. (2021). Wang, Zerong.
    In: Journal of Futures Markets.
    RePEc:wly:jfutmk:v:41:y:2021:i:1:p:135-156.

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  40. Conditional covariance matrix forecast using the hybrid exponentially weighted moving average approach. (2021). Kuang, Wei.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:40:y:2021:i:8:p:1398-1419.

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  41. Firm-level Business Uncertainty and the Predictability of the Aggregate U.S. Stock Market Volatility during the COVID-19 Pandemic. (2021). Salisu, Afees ; GUPTA, RANGAN ; van Eyden, Renee ; Demirer, Riza.
    In: Working Papers.
    RePEc:pre:wpaper:202157.

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  42. The Effect of Oil Uncertainty Shock on Real GDP of 33 Countries: A Global VAR Approach. (2021). Salisu, Afees ; GUPTA, RANGAN ; Olaniran, Abeeb.
    In: Working Papers.
    RePEc:pre:wpaper:202153.

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  43. Forecasting Oil and Gold Volatilities with Sentiment Indicators Under Structural Breaks. (2021). Demirer, Riza ; Ji, Qiang ; Gupta, Rangan ; Luo, Jiawen.
    In: Working Papers.
    RePEc:pre:wpaper:202130.

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  44. Global Financial Cycle and the Predictability of Oil Market Volatility: Evidence from a GARCH-MIDAS Model. (2021). Salisu, Afees ; GUPTA, RANGAN ; Demirer, Riza.
    In: Working Papers.
    RePEc:pre:wpaper:202121.

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  45. Financial Vulnerability and Volatility in Emerging Stock Markets: Evidence from GARCH-MIDAS Models. (2021). Demirer, Riza ; Gupta, Rangan ; You, YU ; Li, HE.
    In: Working Papers.
    RePEc:pre:wpaper:202112.

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  46. Forecasting Realized Volatility of Bitcoin: The Role of the Trade War. (2021). Pierdzioch, Christian ; GUPTA, RANGAN ; Bouri, Elie ; Gkillas, Konstantinos.
    In: Computational Economics.
    RePEc:kap:compec:v:57:y:2021:i:1:d:10.1007_s10614-020-10022-4.

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  47. Forecasting Daily Volatility of Stock Price Index Using Daily Returns and Realized Volatility. (2021). Omori, Yasuhiro ; Watanabe, Toshiaki ; Takahashi, Makoto.
    In: Discussion paper series.
    RePEc:hit:hiasdp:hias-e-104.

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  48. Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment. (2021). Pierdzioch, Christian ; GUPTA, RANGAN.
    In: Energies.
    RePEc:gam:jeners:v:14:y:2021:i:23:p:8085-:d:693917.

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  49. Dynamic impact of the U.S. monetary policy on oil market returns and volatility. (2021). GUPTA, RANGAN ; Cakan, Esin ; Marfatia, Hardik A.
    In: The Quarterly Review of Economics and Finance.
    RePEc:eee:quaeco:v:80:y:2021:i:c:p:159-169.

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  50. Forecasting power of infectious diseases-related uncertainty for gold realized variance. (2021). Pierdzioch, Christian ; GUPTA, RANGAN ; Bouri, Elie ; Gkillas, Konstantinos.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:42:y:2021:i:c:s1544612321000179.

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  51. Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach. (2021). Marsh, Ian W ; Huang, Chih-Yueh ; Alizadeh, Amir H.
    In: Energy Economics.
    RePEc:eee:eneeco:v:93:y:2021:i:c:s0140988319302063.

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  52. An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution. (2021). Li, Handong ; Tian, Fei ; Song, Shijia.
    In: Journal of Asian Economics.
    RePEc:eee:asieco:v:74:y:2021:i:c:s1049007821000439.

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  53. Predicting risk in energy markets: Low-frequency data still matter. (2021). Výrost, Tomᚠ; Vrost, Toma ; Todorova, Neda ; Lyocsa, Tefan.
    In: Applied Energy.
    RePEc:eee:appene:v:282:y:2021:i:pa:s0306261920315567.

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  54. Biases in variance of decomposed portfolio returns. (2021). Alexeev, Vitali ; Ignatieva, Katja.
    In: International Review of Finance.
    RePEc:bla:irvfin:v:21:y:2021:i:4:p:1152-1178.

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  55. Volatility Bursts: A discrete-time option model with multiple volatility components. (2021). Lilla, Francesca.
    In: Temi di discussione (Economic working papers).
    RePEc:bdi:wptemi:td_1336_21.

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  56. Modeling and Forecasting Intraday Market Returns: a Machine Learning Approach. (2021). Medeiros, Marcelo C ; Ferreira, Iuri H.
    In: Papers.
    RePEc:arx:papers:2112.15108.

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  57. .

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  58. Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation. (2020). Koki, Constandina ; Vrontos, Ioannis ; Meligkotsidou, Loukia.
    In: Journal of Forecasting.
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  59. High-Frequency Movements of the Term Structure of Interest Rates of the United States: The Role of Oil Market Uncertainty. (2020). Kyei, Clement ; GUPTA, RANGAN ; Subramaniam, Sowmya ; Bouri, Elie.
    In: Working Papers.
    RePEc:pre:wpaper:202085.

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  60. Forecasting Oil Volatility Using a GARCH-MIDAS Approach: The Role of Global Economic Conditions. (2020). Salisu, Afees ; GUPTA, RANGAN ; Bouri, Elie.
    In: Working Papers.
    RePEc:pre:wpaper:202051.

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  61. Investor Happiness and Predictability of the Realized Volatility of Oil Price. (2020). GUPTA, RANGAN ; Pierdzioch, Christian ; Gkillas, Konstantinos ; Bonato, Matteo.
    In: Working Papers.
    RePEc:pre:wpaper:202009.

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  62. Forecasting Realized Volatility of Bitcoin: The Role of the Trade War. (2020). GUPTA, RANGAN ; Pierdzioch, Christian ; Gkillas, Konstantinos ; Bouri, Elie.
    In: Working Papers.
    RePEc:pre:wpaper:202003.

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  63. Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience. (2020). Ehouman, Yao Axel.
    In: Post-Print.
    RePEc:hal:journl:hal-02960571.

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  64. Investor Happiness and Predictability of the Realized Volatility of Oil Price. (2020). Pierdzioch, Christian ; GUPTA, RANGAN ; Bonato, Matteo ; Gkillas, Konstantinos.
    In: Sustainability.
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  65. Realized Measures to Explain Volatility Changes over Time. (2020). Floros, Christos ; Gkillas, Konstantinos ; Tsagkanos, Athanasios ; Konstantatos, Christoforos.
    In: JRFM.
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  66. Infectious Diseases, Market Uncertainty and Oil Market Volatility. (2020). Pierdzioch, Christian ; GUPTA, RANGAN ; Demirer, Riza ; Bouri, Elie.
    In: Energies.
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  67. The predictive power of oil price shocks on realized volatility of oil: A note. (2020). Shahzad, Syed Jawad Hussain ; GUPTA, RANGAN ; Demirer, Riza ; Hussain, Syed Jawad ; Pierdzioch, Christian.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:69:y:2020:i:c:s0301420720308874.

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  68. Bayesian sequential stock return prediction through copulas. (2020). Frey, Christoph ; Virbickait, Audron ; Macedo, Demian N.
    In: The Journal of Economic Asymmetries.
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  69. Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss. (2020). Pierdzioch, Christian ; GUPTA, RANGAN ; Gkillas, Konstantinos.
    In: Journal of International Money and Finance.
    RePEc:eee:jimfin:v:104:y:2020:i:c:s0261560619300075.

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  70. Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks. (2020). McAleer, Michael ; GUPTA, RANGAN ; Asai, Manabu.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:3:p:933-948.

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  71. The impact of sentiment and attention measures on stock market volatility. (2020). Audrino, Francesco ; Ballinari, Daniele ; Sigrist, Fabio.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:2:p:334-357.

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  72. Rough volatility of Bitcoin. (2020). Takaishi, Tetsuya.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:32:y:2020:i:c:s154461231930337x.

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  73. Copula stochastic volatility in oil returns: Approximate Bayesian computation with volatility prediction. (2020). Galeano, Pedro ; Ausin, Concepcion M ; Virbickait, Audron.
    In: Energy Economics.
    RePEc:eee:eneeco:v:92:y:2020:i:c:s0140988320303017.

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  74. Volatility spillovers in commodity markets: A large t-vector autoregressive approach. (2020). Wilms, Ines ; Barbaglia, Luca ; Croux, Christophe.
    In: Energy Economics.
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  75. Statistical inferences for realized portfolio weights. (2020). Lazariv, Taras ; Seifert, Miriam Isabel ; Schmid, Wolfgang ; Golosnoy, Vasyl.
    In: Econometrics and Statistics.
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  76. Variance risk: A bird’s eye view. (2020). Simen, Chardin Wese ; Hollstein, Fabian.
    In: Journal of Econometrics.
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  77. Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA. (2020). Pérez-Rodríguez, Jorge ; Lopez-Valcarcel, Beatriz Gonzalez ; Perez-Rodriguez, Jorge V ; Qian, Huanhuan ; Zhou, Xinmiao.
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  78. Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the United States experience. (2020). Ehouman, Yao Axel.
    In: Economic Modelling.
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  79. Price connectedness between green bond and financial markets. (2020). Ugolini, Andrea ; Reboredo, Juan.
    In: Economic Modelling.
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  80. Dimension Reduction for High Dimensional Vector Autoregressive Models. (2020). Hecq, Alain ; Cubadda, Gianluca.
    In: Papers.
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  81. Multivariate realized volatility forecasts of agricultural commodity futures. (2019). Chen, Langnan ; Luo, Jiawen.
    In: Journal of Futures Markets.
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  82. Challenges of integrated variance estimation in emerging stock markets. (2019). Matkovi, Mario ; Arneri, Josip.
    In: Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics.
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  83. Risk Aversion and the Predictability of Crude Oil Market Volatility: A Forecasting Experiment with Random Forests. (2019). Pierdzioch, Christian ; GUPTA, RANGAN ; Demirer, Riza ; Gkillas, Konstantinos.
    In: Working Papers.
    RePEc:pre:wpaper:201972.

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  84. Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks. (2019). McAleer, Michael ; GUPTA, RANGAN ; Asai, Manabu.
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  85. Futures-based forecasts: How useful are they for oil price volatility forecasting?. (2019). Filis, George ; Degiannakis, Stavros ; Chatziantoniou, Ioannis.
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    RePEc:pra:mprapa:96446.

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  86. Oil price volatility forecasts: What do investors need to know?. (2019). Filis, George ; Degiannakis, Stavros.
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  87. Incorporating Realized Quarticity into a Realized Stochastic Volatility Model. (2019). Morimoto, Takayuki ; Nugroho, Didit Budi.
    In: Asia-Pacific Financial Markets.
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  88. Fractal analysis of the multifractality of foreign exchange rates. (2019). Garcin, Matthieu.
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  89. An Experiment on Autoregressive and Threshold Autoregressive Models with Non-Gaussian Error with Application to Realized Volatility. (2019). Li, Wai Keung ; Zhang, Ziyi.
    In: Economies.
    RePEc:gam:jecomi:v:7:y:2019:i:2:p:58-:d:240654.

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  90. A dynamic factor model with stylized facts to forecast volatility for an optimal portfolio. (2019). Belkacem, Lotfi ; Boubaker, Heni ; Karmous, Aida.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119312695.

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  91. Forecasting Bitcoin risk measures: A robust approach. (2019). Trucíos, Carlos ; Trucios, Carlos.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:3:p:836-847.

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  92. Cross-asset relations, correlations and economic implications. (2019). McMillan, David G.
    In: Global Finance Journal.
    RePEc:eee:glofin:v:41:y:2019:i:c:p:60-78.

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  93. Futures-based forecasts: How useful are they for oil price volatility forecasting?. (2019). Filis, George ; Degiannakis, Stavros ; Chatziantoniou, Ioannis.
    In: Energy Economics.
    RePEc:eee:eneeco:v:81:y:2019:i:c:p:639-649.

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  94. Mixed interval realized variance: A robust estimator of stock price volatility. (2019). Vasnev, Andrey ; Sutton, Maxwell ; Gerlach, Richard.
    In: Econometrics and Statistics.
    RePEc:eee:ecosta:v:11:y:2019:i:c:p:43-62.

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  95. Volatility transmission between oil prices and banks stock prices as a new source of instability: Lessons from the US Experience. (2019). Ehouman, Yao Axel.
    In: EconomiX Working Papers.
    RePEc:drm:wpaper:2019-19.

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  96. Rough volatility of Bitcoin. (2019). Takaishi, Tetsuya.
    In: Papers.
    RePEc:arx:papers:1904.12346.

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  97. Time series models for realized covariance matrices based on the matrix-F distribution. (2019). Zhu, Ke ; Li, Wai Keung ; Jiang, Feiyu ; Zhou, Jiayuan.
    In: Papers.
    RePEc:arx:papers:1903.12077.

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  98. Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market. (2018). Su, Fei.
    In: PhD Thesis.
    RePEc:uts:finphd:39.

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  99. Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market. (2018). Su, Fei.
    In: PhD Thesis.
    RePEc:uts:finphd:2-2018.

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  100. Volatility forecasting: combinations of realized volatility measures and forecasting models. (2018). Makushina, Victoria ; Shishlenin, Sergey ; Boasson, Vigdis ; Xiao, Linlan .
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    RePEc:taf:applec:v:50:y:2018:i:13:p:1428-1441.

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  101. Forecasting Realized Volatility Measures with Multivariate and Univariate Models: The Case of The US Banking Sector. (2018). Hecq, Alain ; Cubadda, Gianluca ; Riccardo, Antonio.
    In: CEIS Research Paper.
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  102. Estimating and Forecasting Conditional Risk Measures with Extreme Value Theory: A Review. (2018). Trapin, Luca ; Bee, Marco.
    In: Risks.
    RePEc:gam:jrisks:v:6:y:2018:i:2:p:45-:d:142858.

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  103. Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis. (2018). Maheu, John ; Jensen, Mark.
    In: JRFM.
    RePEc:gam:jjrfmx:v:11:y:2018:i:3:p:52-:d:167993.

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  104. Does US Economic Policy Uncertainty matter for European stock markets volatility?. (2018). Mei, Dexiang ; Hou, Wenjing ; Zhang, Yaojie ; Zeng, Qing.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:512:y:2018:i:c:p:215-221.

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  105. Bias correction in the realized stochastic volatility model for daily volatility on the Tokyo Stock Exchange. (2018). Takaishi, Tetsuya.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:500:y:2018:i:c:p:139-154.

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  106. Dynamics of financial returns densities: A functional approach applied to the Bovespa intraday index. (2018). Horta, Eduardo ; Ziegelmann, Flavio.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:34:y:2018:i:1:p:75-88.

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  107. MGARCH models: Trade-off between feasibility and flexibility. (2018). Ruiz, Esther ; Hotta, Luiz ; de Almeida, Daniel .
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:34:y:2018:i:1:p:45-63.

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  108. The G-20′s regulatory agenda and banks’ risk. (2018). Cabrera, Matias ; Nieto, Maria J ; Dwyer, Gerald P.
    In: Journal of Financial Stability.
    RePEc:eee:finsta:v:39:y:2018:i:c:p:66-78.

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  109. Are low-frequency data really uninformative? A forecasting combination perspective. (2018). Ma, Feng ; Zhang, Yaojie ; Liu, LI.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:44:y:2018:i:c:p:92-108.

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  110. The G-20 regulatory agenda and bank risk. (2018). Nieto, Maria J ; Dwyer, Gerald P ; Cabrera, Matias.
    In: Working Papers.
    RePEc:bde:wpaper:1829.

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  111. Value at risk forecasting for volatility index. (2017). Park, Seul-Ki ; Shin, Dong Wan ; Choi, Ji-Eun.
    In: Applied Economics Letters.
    RePEc:taf:apeclt:v:24:y:2017:i:21:p:1613-1620.

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  112. Portfolio choice with high frequency data: CRRA preferences and the liquidity effect. (2017). Sebastião, Helder ; Godinho, Pedro ; Brito, Rui ; Sebastio, H.
    In: Portuguese Economic Journal.
    RePEc:spr:portec:v:16:y:2017:i:2:d:10.1007_s10258-017-0131-3.

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  113. Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data. (2017). Wilfling, Bernd ; Lau, Chi Keung ; GUPTA, RANGAN ; Segnon, Mawuli.
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  114. Forecasting oil price realized volatility using information channels from other asset classes. (2017). Filis, George ; Degiannakis, Stavros.
    In: MPRA Paper.
    RePEc:pra:mprapa:96276.

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  115. Forecasting Financial Market Volatility Using a Dynamic Topic Model. (2017). Kawasaki, Yoshinori ; Morimoto, Takayuki.
    In: Asia-Pacific Financial Markets.
    RePEc:kap:apfinm:v:24:y:2017:i:3:d:10.1007_s10690-017-9228-z.

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  116. Testing for Extreme Volatility Transmission with Realized Volatility Measures. (2017). Tokpavi, Sessi ; Dumitrescu, Elena Ivona ; de Truchis, Gilles ; Boucher, Christophe.
    In: Working Papers.
    RePEc:hal:wpaper:hal-04141651.

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  117. Volatility and public information flows: Evidence from disclosure and media coverage in the Japanese stock market. (2017). Aman, Hiroyuki ; Moriyasu, Hiroshi.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:51:y:2017:i:c:p:660-676.

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  118. Forecasting oil price realized volatility using information channels from other asset classes. (2017). Filis, George ; Degiannakis, Stavros.
    In: Journal of International Money and Finance.
    RePEc:eee:jimfin:v:76:y:2017:i:c:p:28-49.

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  119. Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?. (2017). Molnár, Peter ; Lyócsa, Štefan ; Todorova, Neda ; Molnar, Peter ; Lyocsa, Tefan.
    In: Journal of International Financial Markets, Institutions and Money.
    RePEc:eee:intfin:v:51:y:2017:i:c:p:228-247.

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  120. Uncertainties in global radiation time series forecasting using machine learning: The multilayer perceptron case. (2017). Voyant, Cyril ; Motte, Fabrice ; Fouilloy, Alexis ; Darras, Christophe ; Notton, Gilles.
    In: Energy.
    RePEc:eee:energy:v:125:y:2017:i:c:p:248-257.

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  121. Econometric analysis of multivariate realised QML: Estimation of the covariation of equity prices under asynchronous trading. (2017). Shephard, Neil ; Xiu, Dacheng.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:201:y:2017:i:1:p:19-42.

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  122. Forecasting the oil futures price volatility: A new approach. (2017). Ma, Feng ; Chen, Wang ; Huang, Dengshi ; Liu, Jing.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:64:y:2017:i:c:p:560-566.

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  123. Forecasting the realized range-based volatility using dynamic model averaging approach. (2017). , ; Wei, YU ; Liu, Jing ; Ma, Feng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:61:y:2017:i:c:p:12-26.

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  124. Testing for Extreme Volatility Transmission with Realized Volatility Measures. (2017). Tokpavi, Sessi ; Dumitrescu, Elena Ivona ; DE TRUCHIS, Gilles ; Boucher, Christophe.
    In: EconomiX Working Papers.
    RePEc:drm:wpaper:2017-20.

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  125. Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data. (2017). Wilfling, Bernd ; Lau, Chi Keung ; GUPTA, RANGAN ; Segnon, Mawuli.
    In: CQE Working Papers.
    RePEc:cqe:wpaper:6117.

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  126. Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach. (2017). Wilms, Ines ; Barbaglia, Luca ; Croux, Christophe.
    In: Papers.
    RePEc:arx:papers:1708.02073.

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  127. Modeling and forecasting exchange rate volatility in time-frequency domain. (2016). Vacha, Lukas ; Krehlik, Tomas ; Baruník, Jozef ; Barunik, Jozef.
    In: FinMaP-Working Papers.
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  128. Pricing under rough volatility. (2016). Bayer, Christian ; Gatheral, Jim ; Friz, Peter .
    In: Quantitative Finance.
    RePEc:taf:quantf:v:16:y:2016:i:6:p:887-904.

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  129. Forecasting oil price realized volatility: A new approach. (2016). Filis, George ; Degiannakis, Stavros.
    In: MPRA Paper.
    RePEc:pra:mprapa:69105.

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  130. Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect. (2016). Sebastião, Helder ; Godinho, Pedro ; Sebastio, Helder ; Brito, Rui Pedro .
    In: GEMF Working Papers.
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  131. Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect. (2016). Sebastio, Helder ; Brito, Rui Pedro ; Godinho, Pedro.
    In: GEMF Working Papers.
    RePEc:gmf:wpaper:2016-13.

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  132. Gold, oil, and stocks: Dynamic correlations. (2016). Vacha, Lukas ; Kočenda, Evžen ; Baruník, Jozef ; Koenda, Even ; Barunik, Jozef.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:42:y:2016:i:c:p:186-201.

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  133. Global equity market volatility spillovers: A broader role for the United States. (2016). Buncic, Daniel.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:4:p:1317-1339.

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  134. Modeling and forecasting exchange rate volatility in time-frequency domain. (2016). Vacha, Lukas ; Krehlik, Tomas ; Baruník, Jozef ; Barunik, Jozef.
    In: European Journal of Operational Research.
    RePEc:eee:ejores:v:251:y:2016:i:1:p:329-340.

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  135. The uncertainty of conditional returns, volatilities and correlations in DCC models. (2016). Ruiz, Esther ; Fresoli, Diego E.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:100:y:2016:i:c:p:170-185.

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  136. Modeling and forecasting persistent financial durations. (2015). Baruník, Jozef ; Zikes, Filip ; Shenai, Nikhil ; Barunik, Jozef.
    In: FinMaP-Working Papers.
    RePEc:zbw:fmpwps:36.

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  137. A Dynamic Fuzzy Money Management Approach for Controlling the Intraday Risk‐Adjusted Performance of AI Trading Algorithms. (2015). Vella, Vince ; Ng, Wing Lon.
    In: Intelligent Systems in Accounting, Finance and Management.
    RePEc:wly:isacfm:v:22:y:2015:i:2:p:153-178.

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  138. Global Equity Market Volatility Spillovers: A Broader Role for the United States. (2015). Buncic, Daniel ; Gisler, Katja I. M., .
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  139. Testing the lag structure of assets’ realized volatility dynamics. (2015). Camponovo, Lorenzo ; Audrino, Francesco ; Roth, Constantin .
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    RePEc:usg:econwp:2015:01.

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  140. Equity portfolio diversification with high frequency data. (2015). Dungey, Mardi ; Alexeev, Vitali.
    In: Quantitative Finance.
    RePEc:taf:quantf:v:15:y:2015:i:7:p:1205-1215.

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  141. Selection of Minimum Variance Portfolio Using Intraday Data: An Empirical Comparison Among Different Realized Measures for BM&FBovespa Data. (2015). Ziegelmann, Flavio Augusto ; Caldeira, Joo F ; Borges, Bruna .
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    RePEc:sbe:breart:v:35:y:2015:i:1:a:21453.

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  142. FloGARCH : Realizing long memory and asymmetries in returns volatility. (2015). Vander Elst, Harry.
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  143. Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity. (2015). Kvedaras, Virmantas ; Ishida, Isao.
    In: Econometrics.
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  144. Model-free volatility indexes in the financial literature: A review. (2015). Gonzalez-Perez, Maria T.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:40:y:2015:i:c:p:141-159.

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  145. Is volatility clustering of asset returns asymmetric?. (2015). Xu, Dinghai ; Ning, Cathy ; Wirjanto, Tony S..
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:52:y:2015:i:c:p:62-76.

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  146. A Lagrangian multiplier test for market microstructure noise with applications to sampling interval determination for realized volatilities. (2015). Shin, Dong Wan ; Hwang, Eunju.
    In: Economics Letters.
    RePEc:eee:ecolet:v:129:y:2015:i:c:p:95-99.

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  147. The course of realized volatility in the LME non-ferrous metal market. (2015). Todorova, Neda.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:51:y:2015:i:c:p:1-12.

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  148. Volatility forecast of country ETF: The sequential information arrival hypothesis. (2015). Lee, Chien-Chiang ; Tseng, Tseng-Chan ; Chen, Mei-Ping.
    In: Economic Modelling.
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  149. MGARCH models: tradeoff between feasibility and flexibility. (2015). Ruiz, Esther ; Hotta, Luiz ; de Almeida, Daniel .
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws1516.

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  150. Gold, Oil, and Stocks: Dynamic Correlations. (2015). Vacha, Lukas ; Kočenda, Evžen ; Baruník, Jozef ; Barunik, Jozef.
    In: CESifo Working Paper Series.
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  151. Modeling and forecasting exchange rate volatility in time-frequency domain. (2015). Vacha, Lukas ; Krehlik, Tomas ; Baruník, Jozef ; Barunik, Jozef.
    In: Papers.
    RePEc:arx:papers:1204.1452.

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  152. A SIMULATION ANALYSIS OF HERDING AND UNIFRACTAL SCALING BEHAVIOUR. (2014). Phelps, Steve ; Ng, Wing Lon .
    In: Intelligent Systems in Accounting, Finance and Management.
    RePEc:wly:isacfm:v:21:y:2014:i:1:p:39-58.

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  153. Regime Switching Stochastic Volatility with Skew, Fat Tails and Leverage using Returns and Realized Volatility Contemporaneously. (2014). Trojan, Sebastian .
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2013:41.

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  154. A Realized Stochastic Volatility Model With Box-Cox Transformation. (2014). Song, Tao ; Zheng, Tingguo .
    In: Journal of Business & Economic Statistics.
    RePEc:taf:jnlbes:v:32:y:2014:i:4:p:593-605.

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  155. Estimation of Long Memory in Integrated Variance. (2014). Santucci de Magistris, Paolo ; Rossi, Eduardo.
    In: Econometric Reviews.
    RePEc:taf:emetrv:v:33:y:2014:i:7:p:785-814.

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  156. Is Volatility Clustering of Asset Returns Asymmetric?. (2014). Xu, Dinghai ; Ning, Cathy ; Wirjanto, Tony.
    In: Working Papers.
    RePEc:rye:wpaper:wp050.

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  157. Exponential Smoothing, Long Memory and Volatility Prediction. (2014). Proietti, Tommaso.
    In: CEIS Research Paper.
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  158. Economic gains of realized volatility in the Brazilian stock market. (2014). Medeiros, Marcelo ; Garcia, Marcio ; Francisco Eduardo de Luna e Almeida Santos, .
    In: Textos para discussão.
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  159. Exponential Smoothing, Long Memory and Volatility Prediction. (2014). Proietti, Tommaso.
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  160. Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk. (2014). Balatsky, Alexander V ; Borysov, Stanislav S.
    In: PLOS ONE.
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  161. A noise-robust estimator of volatility based on interquantile ranges. (2014). Kuan, Chung-Ming ; Wang, Jying-Nan ; Yeh, Jin-Huei.
    In: Review of Quantitative Finance and Accounting.
    RePEc:kap:rqfnac:v:43:y:2014:i:4:p:751-779.

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  162. Asymmetric Realized Volatility Risk. (2014). Scharth, Marcel ; McAleer, Michael ; Allen, David.
    In: JRFM.
    RePEc:gam:jjrfmx:v:7:y:2014:i:2:p:80-109:d:37458.

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  163. Risk, Return, and Volatility Feedback: A Bayesian Nonparametric Analysis. (2014). Maheu, John ; Jensen, Mark.
    In: FRB Atlanta Working Paper.
    RePEc:fip:fedawp:2014-06.

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  164. Cojumps in stock prices: Empirical evidence. (2014). Shackleton, Mark ; Gilder, Dudley ; Taylor, Stephen J..
    In: Journal of Banking & Finance.
    RePEc:eee:jbfina:v:40:y:2014:i:c:p:443-459.

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  165. The impact of trading volume, number of trades and overnight returns on forecasting the daily realized range. (2014). Soucek, Michael ; Souek, Michael ; Todorova, Neda.
    In: Economic Modelling.
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  166. Disentangled jump-robust realized covariances and correlations with non-synchronous prices. (2014). Elst, Harry Vander ; Veredas, David.
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws142416.

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  167. The uncertainty of conditional returns, volatilities and correlations in DCC models. (2014). Ruiz, Esther ; Fresoli, Diego .
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:ws140202.

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  168. Disentangled jump-robust realized covariances and correlations with non-synchronous prices. (2014). Veredas, David ; Elst, Harry Vander.
    In: DES - Working Papers. Statistics and Econometrics. WS.
    RePEc:cte:wsrepe:es142416.

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  169. Economic gains of realized volatility in the Brazilian stock market. (2014). Medeiros, Marcelo ; de Luna, Francisco Eduardo ; Pinto, Marcio Gomes .
    In: Brazilian Review of Finance.
    RePEc:brf:journl:v:12:y:2014:i:3:p:319-349.

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  170. Assessing Day-to-Day Volatility: Does the Trading Time Matter?. (2014). Araujo, Gustavo ; Machado, Jose Valentim ; Tavares, Felipe Noronha ; Fisher, Paula Baio .
    In: Brazilian Review of Finance.
    RePEc:brf:journl:v:12:y:2014:i:1:p:41-66.

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  171. Gold, Oil, and Stocks. (2014). Vacha, Lukas ; Kočenda, Evžen ; Baruník, Jozef.
    In: Papers.
    RePEc:arx:papers:1308.0210.

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  172. Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range. (2013). Asai, Manabu.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:32:y:2013:i:5:p:469-480.

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  173. Additive modeling of realized variance: tests for parametric specifications and structural breaks. (2013). Fengler, Matthias ; Mammen, Enno ; Vogt, Michael.
    In: Economics Working Paper Series.
    RePEc:usg:econwp:2013:32.

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  174. Equity portfolio diversification with high frequency data. (2013). Dungey, Mardi ; Alexeev, Vitali.
    In: Working Papers.
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  176. A COMPARISON OF THE FORECASTING PERFORMANCES OF MULTIVARIATE VOLATILITY MODELS. (2013). Candila, Vincenzo.
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  177. Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. (2013). Degiannakis, Stavros ; Livada, Alexandra .
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  178. Realized Volatility or Price Range: Evidence from a discrete simulation of the continuous time diffusion process. (2013). Degiannakis, Stavros ; Livada, Alexandra .
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  179. On the predictability of stock prices: A case for high and low prices. (2013). Santucci de Magistris, Paolo ; Ranaldo, Angelo ; Caporin, Massimiliano.
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  252. THE TEN COMMANDMENTS FOR MANAGING VALUE AT RISK UNDER THE BASEL II ACCORD. (2009). McAleer, Michael ; Jimenez-Martin, Juan ; Juan-Ángel Jimenez-Martin, ; Perez-Amaral, Teodosio.
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  18. Ghysels E., 2006. Volatility Forecasting and Microstructure Noise
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  19. Gonçalves S., 2005. Boostraping Realized Volatility
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  21. Griffin J. E., 2006. Covariance Measurement in the Presence of Nonsynchronous Trading and Market Microstructure Noise
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  29. Large J., 2006. Estimating Quadratic Variation When Quoted Prices Jump by a Constant Increment

  30. Malmsten H., 2004. Stylized Facts of Financial Time Series and Three Popular Models of Volatility

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  34. Meddahi N., 2001. An Eigenfunction Approach for Volatility Modeling

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Cocites

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  1. Liquidity and realized range-based volatility forecasting: Evidence from China. (2019). Ma, Feng ; Huang, Dengshi ; Xu, Yanyan ; Qiao, Gaoxiu.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:525:y:2019:i:c:p:1102-1113.

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  2. Forecasting oil futures price volatility: New evidence from realized range-based volatility. (2018). Ma, Feng ; Lai, Xiaodong ; Huang, Dengshi ; Zhang, Yaojie.
    In: Energy Economics.
    RePEc:eee:eneeco:v:75:y:2018:i:c:p:400-409.

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  3. Are low-frequency data really uninformative? A forecasting combination perspective. (2018). Ma, Feng ; Zhang, Yaojie ; Liu, LI.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:44:y:2018:i:c:p:92-108.

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  4. Estimation of spot volatility with superposed noisy data. (2018). Liu, Qiang ; Wang, LI.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:44:y:2018:i:c:p:62-79.

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  5. Forecasting the oil futures price volatility: A new approach. (2017). Ma, Feng ; Chen, Wang ; Huang, Dengshi ; Liu, Jing.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:64:y:2017:i:c:p:560-566.

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  6. Forecasting the realized range-based volatility using dynamic model averaging approach. (2017). , ; Wei, YU ; Liu, Jing ; Ma, Feng.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:61:y:2017:i:c:p:12-26.

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  7. The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective. (2016). Caporin, Massimiliano ; Bonaccolto, Giovanni.
    In: JRFM.
    RePEc:gam:jjrfmx:v:9:y:2016:i:3:p:8-:d:73460.

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  8. Volatility forecast of country ETF: The sequential information arrival hypothesis. (2015). Lee, Chien-Chiang ; Tseng, Tseng-Chan ; Chen, Mei-Ping.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:47:y:2015:i:c:p:228-234.

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  9. The impact of overnight returns on realized volatility. (2012). Lin, Cha-Fei ; Tseng, Tseng-Chan ; Lai, Hung-Cheng .
    In: Applied Financial Economics.
    RePEc:taf:apfiec:v:22:y:2012:i:5:p:357-364.

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  10. Efficient and feasible inference for the components of financial variation using blocked multipower variation. (2012). Sheppard, Kevin ; Shephard, Neil ; Mykland, Per A..
    In: Economics Series Working Papers.
    RePEc:oxf:wpaper:593.

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  11. Efficient and feasible inference for the components of financial variation using blocked multipower variation. (2012). Sheppard, Kevin ; Shephard, Neil ; Mykland, Per A..
    In: Economics Papers.
    RePEc:nuf:econwp:1202.

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  12. Jump-robust volatility estimation using nearest neighbor truncation. (2012). Andersen, Torben ; Dobrev, Dobrislav ; Schaumburg, Ernst.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:169:y:2012:i:1:p:75-93.

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  13. Realised quantile-based estimation of the integrated variance. (2010). Christensen, Kim ; Oomen, Roel ; Podolskij, Mark.
    In: Post-Print.
    RePEc:hal:journl:peer-00732538.

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  14. Realised quantile-based estimation of the integrated variance. (2010). Podolskij, Mark ; Christensen, Kim ; Oomen, Roel.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:159:y:2010:i:1:p:74-98.

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  15. Modeling Jump and Continuous Components in the Volatility of Oil Futures. (2009). Huang, Chin-Sheng ; Tseng, Tseng-Chan ; Chung, Huimin.
    In: Studies in Nonlinear Dynamics & Econometrics.
    RePEc:bpj:sndecm:v:13:y:2009:i:3:n:5.

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  16. Realised Quantile-Based Estimation of the Integrated Variance. (2009). Podolskij, Mark ; Oomen, Roel ; Christensen, Kim.
    In: CREATES Research Papers.
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  17. Realized Volatility: A Review. (2008). Medeiros, Marcelo ; McAleer, Michael.
    In: Econometric Reviews.
    RePEc:taf:emetrv:v:27:y:2008:i:1-3:p:10-45.

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  18. Comparison of Volatility Measures: a Risk Management Perspective. (2008). Gallo, Giampiero ; Brownlees, Christian.
    In: Econometrics Working Papers Archive.
    RePEc:fir:econom:wp2008_03.

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  19. A note on the central limit theorem for bipower variation of general functions. (2008). Podolskij, Mark ; Kinnebrock, Silja .
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:118:y:2008:i:6:p:1056-1070.

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  20. A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models. (2008). Podolskij, Mark ; Ziggel, Daniel.
    In: CREATES Research Papers.
    RePEc:aah:create:2008-22.

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  21. Realized range-based estimation of integrated variance. (2007). Podolskij, Mark ; Christensen, Kim.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:141:y:2007:i:2:p:323-349.

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  22. Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps. (2007). Podolskij, Mark ; Vetter, Mathias .
    In: CREATES Research Papers.
    RePEc:aah:create:2007-27.

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  23. A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models. (2007). Podolskij, Mark ; Ziggel, Daniel.
    In: CREATES Research Papers.
    RePEc:aah:create:2007-26.

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  24. Bias-Correcting the Realized Range-Based Variance in the Presence of Market Microstructure Noise. (2006). Podolskij, Mark ; Christensen, Kim ; Vetter, Mathias .
    In: Technical Reports.
    RePEc:zbw:sfb475:200652.

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  25. Estimation of Volatility Functionals in the Simultaneous Presence of Microstructure Noise and Jumps. (2006). Podolskij, Mark ; Vetter, Mathias .
    In: Technical Reports.
    RePEc:zbw:sfb475:200651.

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  26. Volatility Forecast Comparison using Imperfect Volatility Proxies. (2006). Patton, Andrew.
    In: Research Paper Series.
    RePEc:uts:rpaper:175.

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  27. Asymptotic theory for range-based estimation of integrated variance of a continuous semi-martingale. (2005). Christensen, Kim ; Podolski, Mark .
    In: Technical Reports.
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