IDEAS home Printed from https://ideas.repec.org/a/eee/techno/v120y2023ics016649722200030x.html
   My bibliography  Save this article

Frequency connectedness and cross-quantile dependence among medicare, medicine prices and health-tech equity

Author

Listed:
  • Sohag, Kazi
  • Shams, S.M. Riad
  • Gainetdinova, Anna
  • Nappo, Fabio

Abstract

We investigate the dynamic connectedness among health-tech equity and medicine prices (producer and consumer) and Medicare cost indices for the US market. In doing so, we apply Cross-Quantilogram Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR) approaches to analyse historical high-frequency time-series data. TVP-VAR results show that health-tech equity is the highest volatility transmitter while Medicare price is the highest volatility receiver. We also find medicine producer price is the net volatility contributor while the retail price of medicine is the net volatility receiver. The Cross-Quantilogram analysis confirms a strong bivariate quantile dependence between respective markets at a higher quantile of each market. Cross-quantilogram demonstrates a higher level of connectedness among the markets when considering medium and long memory. We observe health-tech equity turned to be a profound volatility contributor, while medicine price (both producer and retail prices) and Medicare appeared to net volatility receiver during the time of COVID19 Pandemic. The financial performance of health-tech equity returns elevates the price volatility of medicine and eventually Medicare cost, which imply that equity return should be incorporated forming medicine prices.

Suggested Citation

  • Sohag, Kazi & Shams, S.M. Riad & Gainetdinova, Anna & Nappo, Fabio, 2023. "Frequency connectedness and cross-quantile dependence among medicare, medicine prices and health-tech equity," Technovation, Elsevier, vol. 120(C).
    • Handle: RePEc:eee:techno:v:120:y:2023:i:c:s016649722200030x
    DOI: 10.1016/j.technovation.2022.102483
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016649722200030X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.technovation.2022.102483?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Büyükşahin, Bahattin & Robe, Michel A., 2014. "Speculators, commodities and cross-market linkages," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 38-70.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Jaime Casassus & Freddy Higuera, 2011. "Stock Return Predictability and Oil Prices," Documentos de Trabajo 406, Instituto de Economia. Pontificia Universidad Católica de Chile..
    4. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    5. Ewing, Bradley T. & Malik, Farooq, 2016. "Volatility spillovers between oil prices and the stock market under structural breaks," Global Finance Journal, Elsevier, vol. 29(C), pages 12-23.
    6. Barbara Rossi, 2012. "The Changing Relationship Between Commodity Prices and Equity Prices in Commodity Exporting Countries," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(4), pages 533-569, December.
    7. Satish Nambisan, 2017. "Digital Entrepreneurship: Toward a Digital Technology Perspective of Entrepreneurship," Entrepreneurship Theory and Practice, , vol. 41(6), pages 1029-1055, November.
    8. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    9. Kanavos, Panos G. & Vandoros, Sotiris, 2011. "Determinants of branded prescription medicine prices in OECD countries," Health Economics, Policy and Law, Cambridge University Press, vol. 6(3), pages 337-367, July.
    10. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    11. Bakas, Dimitrios & Triantafyllou, Athanasios, 2020. "Commodity price volatility and the economic uncertainty of pandemics," Economics Letters, Elsevier, vol. 193(C).
    12. Husain, Shaiara & Tiwari, Aviral Kumar & Sohag, Kazi & Shahbaz, Muhammad, 2019. "Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA," Resources Policy, Elsevier, vol. 62(C), pages 57-65.
    13. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2011. "Crude oil hedging strategies using dynamic multivariate GARCH," Energy Economics, Elsevier, vol. 33(5), pages 912-923, September.
    14. Arouri, Mohamed El Hedi & Lahiani, Amine & Nguyen, Duc Khuong, 2011. "Return and volatility transmission between world oil prices and stock markets of the GCC countries," Economic Modelling, Elsevier, vol. 28(4), pages 1815-1825, July.
    15. Souček, Michael & Todorova, Neda, 2013. "Realized volatility transmission between crude oil and equity futures markets: A multivariate HAR approach," Energy Economics, Elsevier, vol. 40(C), pages 586-597.
    16. Bessler, Wolfgang & Wolff, Dominik, 2015. "Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 1-20.
    17. Ehouman, Yao Axel, 2020. "Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience," Economic Modelling, Elsevier, vol. 91(C), pages 198-217.
    18. Tian, Shuairu & Hamori, Shigeyuki, 2016. "Time-varying price shock transmission and volatility spillover in foreign exchange, bond, equity, and commodity markets: Evidence from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 163-171.
    19. Barbara Rossi, 2012. "The changing relationship between commodity prices and equity prices in commodity exporting," Economics Working Papers 1405, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Jones, Charles M & Kaul, Gautam, 1996. "Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-491, June.
    21. Yao Axel Ehouman, 2020. "Volatility transmission between oil prices and banks’ stock prices as a new source of instability: Lessons from the United States experience," Post-Print hal-02960571, HAL.
    22. Elia, Gianluca & Margherita, Alessandro & Passiante, Giuseppina, 2020. "Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    23. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    24. Narayan, Paresh Kumar & Thuraisamy, Kannan S. & Wagner, Niklas F., 2017. "How do bond, equity and commodity cycles interact?," Finance Research Letters, Elsevier, vol. 21(C), pages 151-156.
    25. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," Finance Research Letters, Elsevier, vol. 23(C), pages 152-164.
    26. Rippa, Pierluigi & Secundo, Giustina, 2019. "Digital academic entrepreneurship: The potential of digital technologies on academic entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 900-911.
    27. Ramaswamy, Venkat & Ozcan, Kerimcan, 2018. "What is co-creation? An interactional creation framework and its implications for value creation," Journal of Business Research, Elsevier, vol. 84(C), pages 196-205.
    28. Geetesh Bhardwaj & Gary Gorton & Geert Rouwenhorst, 2015. "Facts and Fantasies about Commodity Futures Ten Years Later," NBER Working Papers 21243, National Bureau of Economic Research, Inc.
    29. Youngjin Yoo & Ola Henfridsson & Kalle Lyytinen, 2010. "Research Commentary ---The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research," Information Systems Research, INFORMS, vol. 21(4), pages 724-735, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qin, Meng & Su, Ai-Hsuan & Li, Ruifeng & Su, Chi-Wei, 2024. "Speculation, climate or pandemic: Who drives the Chinese herbal medicine bubbles?," China Economic Review, Elsevier, vol. 87(C).
    2. Lee, Min-Jae & Choi, Sun-Yong, 2024. "Insights into the dynamics of market efficiency spillover of financial assets in different equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 641(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    2. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    3. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    4. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    5. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    6. Stavros Degiannakis & George Filis & Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, , vol. 39(5), pages 85-130, September.
    7. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    8. Jose Arreola Hernandez & Sang Hoon Kang & Seong-Min Yoon, 2022. "Spillovers and portfolio optimization of precious metals and global/regional equity markets," Applied Economics, Taylor & Francis Journals, vol. 54(20), pages 2320-2342, April.
    9. Lombardi, Marco J. & Ravazzolo, Francesco, 2016. "On the correlation between commodity and equity returns: Implications for portfolio allocation," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 45-57.
    10. Spanò, Rosanna & Massaro, Maurizio & Iacuzzi, Silvia, 2023. "Blockchain for value creation in the healthcare sector," Technovation, Elsevier, vol. 120(C).
    11. Dahl, Roy Endré & Jonsson, Erlendur, 2018. "Volatility spillover in seafood markets," Journal of Commodity Markets, Elsevier, vol. 12(C), pages 44-59.
    12. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
    13. Chandrarin, Grahita & Sohag, Kazi & Cahyaningsih, Diyah Sukanti & Yuniawan, Dani & Herdhayinta, Heyvon, 2022. "The response of exchange rate to coal price, palm oil price, and inflation in Indonesia: Tail dependence analysis," Resources Policy, Elsevier, vol. 77(C).
    14. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    15. Yousaf, Imran & Jareño, Francisco & Tolentino, Marta, 2023. "Connectedness between Defi assets and equity markets during COVID-19: A sector analysis," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    16. Ruokolainen, Jari & Nätti, Satu & Juutinen, Milla & Puustinen, Juha & Holm, Anu & Vehkaoja, Antti & Nieminen, Hannu, 2023. "Digital healthcare platform ecosystem design: A case study of an ecosystem for Parkinson's disease patients," Technovation, Elsevier, vol. 120(C).
    17. Zhang, Xi & Wei, Xin & Zhang, Te & Tan, Yahe & Xu, Dongming & Ordóñez de Pablos, Patricia, 2023. "How platform-based internet hospital innovation affects doctors’ active stress coping efforts: The conservation of resource theory perspective," Technovation, Elsevier, vol. 121(C).
    18. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    19. Huifu Nong, 2024. "Connectedness and risk transmission of China’s stock and currency markets with global commodities," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-24, February.
    20. Mensi, Walid & Reboredo, Juan C. & Ugolini, Andrea, 2021. "Price-switching spillovers between gold, oil, and stock markets: Evidence from the USA and China during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 73(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:techno:v:120:y:2023:i:c:s016649722200030x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/01664972 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.