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Dilip Kumar

Personal Details

First Name:Dilip
Middle Name:
Last Name:Kumar
Suffix:
RePEc Short-ID:pku604
[This author has chosen not to make the email address public]
https://scholar.google.co.in/citations?user=N8y4jzMAAAAJ&hl=en

Affiliation

Indian Institute of Management Kashipur

Kashipur, India
http://www.iimkashipur.ac.in/
RePEc:edi:iimkain (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.

Articles

  1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.
  2. Shegorika Rajwani & Dilip Kumar, 2019. "Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach," Global Business Review, International Management Institute, vol. 20(4), pages 962-980, August.
  3. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Informational inefficiency of Bitcoin: A study based on high-frequency data," Research in International Business and Finance, Elsevier, vol. 47(C), pages 344-353.
  4. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Long range dependence in the Bitcoin market: A study based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 625-640.
  5. Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.
  6. Srinivasa Rao Gangadharan & Dilip Kumar, 2017. "Integration of the Indian stock market with the world market: a study based on the time-varying Kalman filter approach," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 7(2), pages 110-126.
  7. Dilip Kumar & Srinivasan Maheswaran, 2017. "Value-at-risk and expected shortfall using the unbiased extreme value volatility estimator," Studies in Economics and Finance, Emerald Group Publishing, vol. 34(4), pages 506-526, October.
  8. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.
  9. Dilip Kumar, 2017. "A Study of Risk Spillover in the Crude Oil and the Natural Gas Markets," Global Business Review, International Management Institute, vol. 18(6), pages 1465-1477, December.
  10. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.
  11. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
  12. Ashish Kumar Garg & Subrata Kumar Mitra & Dilip Kumar, 2016. "Do foreign institutional investors herd in emerging markets? A study of individual stocks," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 43(3), pages 281-300, September.
  13. Dilip Kumar, 2015. "Risk Spillover Between the GIPSI Economies and Egypt, Saudi Arabia, and Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(6), pages 1193-1208, November.
  14. Dilip Kumar & S. Maheswaran, 2015. "Long memory in Indian exchange rates: an application of power-law scaling analysis," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 8(1-2), pages 90-107, July.
  15. Dilip Kumar & Srinivasan Maheswaran, 2015. "Return and volatility spillover among the PIIGS economies and India," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(1), pages 28-49.
  16. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
  17. Kumar, Dilip, 2014. "Long range dependence in the high frequency USD/INR exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 134-148.
  18. Dilip Kumar & Srinivasan Maheswaran, 2014. "Are major global stock markets efficient? An application of the martingale difference hypothesis with wild bootstrap," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 3(2/3/4), pages 217-233.
  19. Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.
  20. Kumar, Dilip & Maheswaran, S., 2014. "A reflection principle for a random walk with implications for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 38(C), pages 33-44.
  21. Dilip Kumar, 2014. "Correlations, Return and Volatility Spillovers in Indian Exchange Rates," Global Business Review, International Management Institute, vol. 15(1), pages 77-91, March.
  22. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
  23. Kumar, Dilip & Maheswaran, S., 2013. "Detecting sudden changes in volatility estimated from high, low and closing prices," Economic Modelling, Elsevier, vol. 31(C), pages 484-491.
  24. Dilip Kumar, 2013. "Are PIIGS stock markets efficient?," Studies in Economics and Finance, Emerald Group Publishing, vol. 30(3), pages 209-225, July.
  25. Dilip Kumar & S. Maheswaran, 2013. "Asymmetric long memory volatility in the PIIGS economies," Review of Accounting and Finance, Emerald Group Publishing, vol. 12(1), pages 23-43, February.
  26. Dilip Kumar & S. Maheswaran, 2013. "Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 61-91, February.
  27. Maheswaran, S. & Kumar, Dilip, 2013. "An automatic bias correction procedure for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 33(C), pages 701-712.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.

    Cited by:

    1. Jian, Zhihong & Zhu, Zhican & Zhou, Jie & Wu, Shuai, 2020. "Intraday price jumps, market liquidity, and the magnet effect of circuit breakers," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 168-186.

  2. Shegorika Rajwani & Dilip Kumar, 2019. "Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach," Global Business Review, International Management Institute, vol. 20(4), pages 962-980, August.

    Cited by:

    1. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).

  3. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Informational inefficiency of Bitcoin: A study based on high-frequency data," Research in International Business and Finance, Elsevier, vol. 47(C), pages 344-353.

    Cited by:

    1. Naeem, Muhammad Abubakr & Bouri, Elie & Peng, Zhe & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Asymmetric efficiency of cryptocurrencies during COVID19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    2. Duan, Kun & Li, Zeming & Urquhart, Andrew & Ye, Jinqiang, 2021. "Dynamic efficiency and arbitrage potential in Bitcoin: A long-memory approach," International Review of Financial Analysis, Elsevier, vol. 75(C).
    3. Julien Chevallier & Dominique Guégan & Stéphane Goutte, 2021. "Is It Possible to Forecast the Price of Bitcoin?," Forecasting, MDPI, Open Access Journal, vol. 3(2), pages 1-44, May.
    4. Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
    5. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    6. Samia Nasreen & Aviral Kumar Tiwari & Seong-Min Yoon, 2021. "Dynamic Connectedness and Portfolio Diversification during the Coronavirus Disease 2019 Pandemic: Evidence from the Cryptocurrency Market," Sustainability, MDPI, Open Access Journal, vol. 13(14), pages 1-14, July.
    7. Dulani Jayasuriya Daluwathumullagamage & Alexandra Sims, 2021. "Fantastic Beasts: Blockchain Based Banking," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 14(4), pages 1-43, April.
    8. Klarin, Anton, 2020. "The decade-long cryptocurrencies and the blockchain rollercoaster: Mapping the intellectual structure and charting future directions," Research in International Business and Finance, Elsevier, vol. 51(C).
    9. Tetsuya Takaishi & Takanori Adachi, 2020. "Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 145-154, March.
    10. Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
    11. Tran, Vu Le & Leirvik, Thomas, 2020. "Efficiency in the markets of crypto-currencies," Finance Research Letters, Elsevier, vol. 35(C).
    12. Wang, Pengfei & Li, Xiao & Shen, Dehua & Zhang, Wei, 2020. "How does economic policy uncertainty affect the bitcoin market?," Research in International Business and Finance, Elsevier, vol. 53(C).
    13. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    14. Wang, Gang-Jin & Ma, Xin-yu & Wu, Hao-yu, 2020. "Are stablecoins truly diversifiers, hedges, or safe havens against traditional cryptocurrencies as their name suggests?," Research in International Business and Finance, Elsevier, vol. 54(C).
    15. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-17, April.
    16. Manahov, Viktor & Urquhart, Andrew, 2021. "The efficiency of Bitcoin: A strongly typed genetic programming approach to smart electronic Bitcoin markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    17. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.

  4. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Long range dependence in the Bitcoin market: A study based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 625-640.

    Cited by:

    1. Bruno Ferreira Frascaroli, 2020. "Bitcoin's innovative aspects, return volatility and uncertainty shocks," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 7(3), pages 224-245.
    2. Aggarwal, Divya & Chandrasekaran, Shabana & Annamalai, Balamurugan, 2020. "A complete empirical ensemble mode decomposition and support vector machine-based approach to predict Bitcoin prices," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    3. Matthias Schnaubelt & Jonas Rende & Christopher Krauss, 2019. "Testing Stylized Facts of Bitcoin Limit Order Books," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(1), pages 1-30, February.
    4. T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
    5. Chaim, Pedro & Laurini, Márcio P., 2019. "Nonlinear dependence in cryptocurrency markets," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 32-47.
    6. Ahmed, Walid M.A. & Al Mafrachi, Mustafa, 2021. "Do higher-order realized moments matter for cryptocurrency returns?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 483-499.
    7. Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-17, April.
    8. Wu, Chuanzhen, 2021. "Window effect with Markov-switching GARCH model in cryptocurrency market," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    9. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.

  5. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.

    Cited by:

    1. Salisu, Afees A. & Raheem, Ibrahim D. & Ndako, Umar B., 2019. "A sectoral analysis of asymmetric nexus between oil price and stock returns," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 241-259.
    2. Mensi, Walid & Sensoy, Ahmet & Aslan, Aylin & Kang, Sang Hoon, 2019. "High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    4. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, Open Access Journal, vol. 11(5), pages 1-24, May.
    5. Pal, Debdatta & Mitra, Subrata K., 2019. "Oil price and automobile stock return co-movement: A wavelet coherence analysis," Economic Modelling, Elsevier, vol. 76(C), pages 172-181.
    6. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les & Xu, Danyang, 2021. "Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 55-81.
    7. Lin, Boqiang & Su, Tong, 2020. "Mapping the oil price-stock market nexus researches: A scientometric review," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 133-147.
    8. Lin, Tiantian & Liu, Dehong & Zhang, Lili & Lung, Peter, 2019. "The information content of realized volatility of sector indices in China’s stock market," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 625-640.
    9. Libo Yin & Jing Nie & Liyan Han, 2021. "Intermediary capital risk and commodity futures volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(5), pages 577-640, May.
    10. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    11. Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
    12. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  6. Shegorika Rajwani & Dilip Kumar, 2016. "Asymmetric Dynamic Conditional Correlation Approach to Financial Contagion: A Study of Asian Markets," Global Business Review, International Management Institute, vol. 17(6), pages 1339-1356, December.

    Cited by:

    1. Oussama Tilfani & Paulo Ferreira & My Youssef El Boukfaoui, 2021. "Dynamic cross-correlation and dynamic contagion of stock markets: a sliding windows approach with the DCCA correlation coefficient," Empirical Economics, Springer, vol. 60(3), pages 1127-1156, March.
    2. Handika, Rangga & Soepriyanto, Gatot & Havidz, Shinta Amalina Hazrati, 2019. "Are cryptocurrencies contagious to Asian financial markets?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 416-429.

  7. Dilip Kumar, 2015. "Risk Spillover Between the GIPSI Economies and Egypt, Saudi Arabia, and Turkey," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(6), pages 1193-1208, November.

    Cited by:

    1. Mensi, Walid & Boubaker, Ferihane Zaraa & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2018. "Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets," Finance Research Letters, Elsevier, vol. 25(C), pages 230-238.
    2. Balcilar, Mehmet & Kutan, Ali M. & Yaya, Mehmet E., 2017. "Financial integration in small Islands: The case of Cyprus," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 201-219.

  8. Dilip Kumar & S. Maheswaran, 2015. "Long memory in Indian exchange rates: an application of power-law scaling analysis," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 8(1-2), pages 90-107, July.

    Cited by:

    1. Abderrazak Ben Maatoug & Rim Lamouchi & Russell Davidson, 2018. "Modelling Foreign Exchange Realized Volatility Using High Frequency Data: Long Memory versus Structural Breaks," Post-Print hal-01982032, HAL.

  9. Dilip Kumar & Srinivasan Maheswaran, 2015. "Return and volatility spillover among the PIIGS economies and India," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(1), pages 28-49.

    Cited by:

    1. Fowowe, Babajide & Shuaibu, Mohammed, 2016. "Dynamic spillovers between Nigerian, South African and international equity markets," International Economics, Elsevier, vol. 148(C), pages 59-80.
    2. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    3. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.

  10. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.

    Cited by:

    1. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2016. "Stock return predictability and determinants of predictability and profits," Emerging Markets Review, Elsevier, vol. 26(C), pages 153-173.
    2. Ahmed, Walid M.A., 2019. "Islamic and conventional equity markets: Two sides of the same coin, or not?," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 191-205.
    3. Koubaa, Yosra & Slim, Skander, 2019. "The relationship between trading activity and stock market volatility: Does the volume threshold matter?," Economic Modelling, Elsevier, vol. 82(C), pages 168-184.
    4. El-Shazly, Alaa, 2016. "Structural breaks and monetary dynamics: A time series analysis," Economic Modelling, Elsevier, vol. 53(C), pages 133-143.
    5. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach, 2016. "Asset price bubbles and economic welfare," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 139-148.
    6. Auer, Benjamin R., 2016. "How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models," Energy Policy, Elsevier, vol. 98(C), pages 621-628.
    7. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.
    8. Narayan, Paresh Kumar & Ahmed, Huson Ali & Narayan, Seema, 2017. "Can investors gain from investing in certain sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 160-177.
    9. Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
    10. Ahmed, Walid M.A., 2017. "The impact of foreign equity flows on market volatility during politically tranquil and turbulent times: The Egyptian experience," Research in International Business and Finance, Elsevier, vol. 40(C), pages 61-77.
    11. Ng, Kok Haur & Peiris, Shelton & Chan, Jennifer So-kuen & Allen, David & Ng, Kooi Huat, 2017. "Efficient modelling and forecasting with range based volatility models and its application," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 448-460.

  11. Kumar, Dilip, 2014. "Long range dependence in the high frequency USD/INR exchange rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 134-148.

    Cited by:

    1. BenSaïda, Ahmed & Slim, Skander, 2016. "Highly flexible distributions to fit multiple frequency financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 203-213.
    2. Bentes, Sónia R., 2021. "On the hysteresis of financial crises in the US: Evidence from S&P 500," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    3. Zargar, Faisal Nazir & Kumar, Dilip, 2019. "Long range dependence in the Bitcoin market: A study based on high-frequency data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 625-640.
    4. Lahmiri, Salim, 2017. "Investigating existence of chaos in short and long term dynamics of Moroccan exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 655-661.

  12. Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.

    Cited by:

    1. Tan, Shay-Kee & Ng, Kok-Haur & Chan, Jennifer So-Kuen & Mohamed, Ibrahim, 2019. "Quantile range-based volatility measure for modelling and forecasting volatility using high frequency data," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 537-551.

  13. Kumar, Dilip & Maheswaran, S., 2014. "A reflection principle for a random walk with implications for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 38(C), pages 33-44.

    Cited by:

    1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.
    2. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    3. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
    4. Muneer Shaik & S. Maheswaran, 2020. "A new unbiased additive robust volatility estimation using extreme values of asset prices," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 313-347, September.
    5. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.
    6. Muneer Shaik & S. Maheswaran, 2019. "Robust Volatility Estimation with and Without the Drift Parameter," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(1), pages 57-91, March.
    7. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
    8. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    9. Vortelinos, Dimitrios I., 2015. "The Greek equity market in European equity portfolios," Economic Modelling, Elsevier, vol. 49(C), pages 144-153.
    10. Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.

  14. Dilip Kumar, 2014. "Correlations, Return and Volatility Spillovers in Indian Exchange Rates," Global Business Review, International Management Institute, vol. 15(1), pages 77-91, March.

    Cited by:

    1. Nurul Anisak & Azhar Mohamad, 2020. "Foreign Exchange Exposure of Indonesian Listed Firms," Global Business Review, International Management Institute, vol. 21(4), pages 918-936, August.
    2. Pami Dua & Ritu Suri, 2019. "Interlinkages Between USD–INR, EUR–INR, GBP–INR and JPY–INR Exchange Rate Markets and the Impact of RBI Intervention," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(1_suppl), pages 102-136, April.
    3. Smile Dube, 2019. "GARCH Modelling of Conditional Correlations and Volatility of Exchange rates in BRICS Countries," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(1), pages 1-7.

  15. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.

    Cited by:

    1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.
    2. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    3. Dimitrios I. Vortelinos & Konstantinos Gkillas, 2018. "Intraday realised volatility forecasting and announcements," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 9(1), pages 88-118.
    4. Dilip Kumar, 2016. "Estimating and forecasting value-at-risk using the unbiased extreme value volatility estimator," Proceedings of Economics and Finance Conferences 3205528, International Institute of Social and Economic Sciences.
    5. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
    6. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    7. Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.

  16. Kumar, Dilip & Maheswaran, S., 2013. "Detecting sudden changes in volatility estimated from high, low and closing prices," Economic Modelling, Elsevier, vol. 31(C), pages 484-491.

    Cited by:

    1. Fenghua Wen & Jihong Xiao & Chuangxia Huang & Xiaohua Xia, 2018. "Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 319-334, January.
    2. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    3. Dilip Kumar, 2016. "Sudden changes in crude oil price volatility: an application of extreme value volatility estimator," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 4(3/4), pages 215-234.
    4. Reem Khamis Hamdan & Allam Mohammed Hamdan, 2020. "Liner and nonliner sectoral response of stock markets to oil price movements: The case of Saudi Arabia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 336-348, July.
    5. Alexey Yurievich Mikhaylov, 2018. "Volatility Spillover Effect between Stock and Exchange Rate in Oil Exporting Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 321-326.
    6. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    7. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    8. Kumar, Dilip & Maheswaran, S., 2014. "A new approach to model and forecast volatility based on extreme value of asset prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 128-140.
    9. Sensoy, Ahmet, 2013. "Dynamic relationship between precious metals," Resources Policy, Elsevier, vol. 38(4), pages 504-511.
    10. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2015. "Structural breaks, dynamic correlations, asymmetric volatility transmission, and hedging strategies for petroleum prices and USD exchange rate," Energy Economics, Elsevier, vol. 48(C), pages 46-60.
    11. Yong Jiang & Chao-Qun Ma & Xiao-Guang Yang & Yi-Shuai Ren, 2018. "Time-Varying Volatility Feedback of Energy Prices: Evidence from Crude Oil, Petroleum Products, and Natural Gas Using a TVP-SVM Model," Sustainability, MDPI, Open Access Journal, vol. 10(12), pages 1-17, December.
    12. Anthony Msafiri Nyangarika & Alexey Yurievich Mikhaylov & Bao-jun Tang, 2018. "Correlation of Oil Prices and Gross Domestic Product in Oil Producing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 42-48.
    13. Walid Mensi & Shawkat Hammoude & Seong-Min Yoon, 2014. "Structural Breaks, Dynamic Correlations, Volatility Transmission, and Hedging Strategies for International Petroleum Prices and U.S. Dollar Exchange Rate," Working Papers 884, Economic Research Forum, revised Dec 2014.
    14. Ahmed, Walid M.A., 2017. "The impact of foreign equity flows on market volatility during politically tranquil and turbulent times: The Egyptian experience," Research in International Business and Finance, Elsevier, vol. 40(C), pages 61-77.
    15. Mansour Khalili Araghi & Majid Mirzaee Ghazani, 2015. "Abrupt Changes in Volatility: Evidence from TEPIX Index in Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(3), pages 377-393, Autumn.
    16. Samit Paul, 2020. "Time Varying Efficiency in Indian Sectors: An Event Study on Demonetization," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(1), pages 103-127, March.

  17. Dilip Kumar & S. Maheswaran, 2013. "Asymmetric long memory volatility in the PIIGS economies," Review of Accounting and Finance, Emerald Group Publishing, vol. 12(1), pages 23-43, February.

    Cited by:

    1. Ngene, Geoffrey & Tah, Kenneth A. & Darrat, Ali F., 2017. "Long memory or structural breaks: Some evidence for African stock markets," Review of Financial Economics, Elsevier, vol. 34(C), pages 61-73.
    2. Heitham Al-Hajieh, 2017. "Evaluated the Success of Fractionally Integrated-GARCH Models on Prediction Stock Market Return Volatility in Gulf Arab Stock Markets," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(7), pages 200-213, July.
    3. Moussa Wajdi & Mgadmi Nidhal & Regaïeg Rym, 2018. "On the Co-movements between Exchange Rate and Stock Price from Japan: A Multivariate FIGARCH-DCC Approach," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 7(4), pages 1-4.

  18. Dilip Kumar & S. Maheswaran, 2013. "Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 61-91, February.

    Cited by:

    1. Muhammad Ali, Khalid M. Iraqi, Abdul Waheed Khan, 2019. "Impact of Oil Prices on Stock Market Performance: Evidence from Top Oil Importing Countries," Journal of Finance and Economics Research, Geist Science, Iqra University, Faculty of Business Administration, vol. 4(2), pages 1-14, October.
    2. Dilip Kumar, 2019. "Structural Breaks in Volatility Transmission from Developed Markets to Major Asian Emerging Markets," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 18(2), pages 172-209, August.
    3. Kumar, Dilip, 2017. "Realized volatility transmission from crude oil to equity sectors: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 149-167.

  19. Maheswaran, S. & Kumar, Dilip, 2013. "An automatic bias correction procedure for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 33(C), pages 701-712.

    Cited by:

    1. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Modeling unbiased extreme value volatility estimator in presence of heterogeneity and jumps: A study with economic significance analysis," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 25-41.
    2. Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    3. Muneer Shaik & S. Maheswaran, 2016. "Modelling the Paradox in Stock Markets by Variance Ratio Volatility Estimator that Utilises Extreme Values of Asset Prices," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 15(3), pages 333-361, December.
    4. Kumar, Dilip & Maheswaran, S., 2014. "Modeling and forecasting the additive bias corrected extreme value volatility estimator," International Review of Financial Analysis, Elsevier, vol. 34(C), pages 166-176.
    5. Muneer Shaik & S. Maheswaran, 2020. "A new unbiased additive robust volatility estimation using extreme values of asset prices," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 313-347, September.
    6. Parthajit Kayal & S. Maheswaran, 2017. "Is USD-INR Really an Excessively Volatile Currency Pair?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(2), pages 329-342, June.
    7. Zargar, Faisal Nazir & Kumar, Dilip, 2020. "Heterogeneous market hypothesis approach for modeling unbiased extreme value volatility estimator in presence of leverage effect: An individual stock level study with economic significance analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 271-285.
    8. Kumar, Dilip & Maheswaran, S., 2014. "A reflection principle for a random walk with implications for volatility estimation using extreme values of asset prices," Economic Modelling, Elsevier, vol. 38(C), pages 33-44.
    9. Dilip Kumar, 2018. "Modeling and Forecasting Unbiased Extreme Value Volatility Estimator in Presence of Leverage Effect," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 313-335, June.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (1) 2016-03-17. Author is listed
  2. NEP-FOR: Forecasting (1) 2016-03-17. Author is listed
  3. NEP-ORE: Operations Research (1) 2016-03-17. Author is listed
  4. NEP-RMG: Risk Management (1) 2016-03-17. Author is listed

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