IDEAS home Printed from https://ideas.repec.org/p/fip/feddwp/96951.html
   My bibliography  Save this paper

Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market

Author

Listed:
  • Michael D. Plante

Abstract

A large number of companies operating in the EV and battery supply chain have listed on a U.S. stock exchange in recent years. I compile a unique data set of high-frequency stock returns for those companies and investigate the extent to which an “industry” factor specific to the EV and battery supply chain (an “EV” factor) can explain their returns. Those returns are decomposed into systematic and idiosyncratic components, with the former given by a set of latent factors extracted from a large panel of stock returns using high-frequency principal components. It is found that a market factor and a factor associated with tech stocks have good explanatory power for the stocks of interest. I identify an “EV” factor as the first principal component of the idiosyncratic returns and find it has relatively good explanatory power for EV and battery stocks, often exceeding that of the tech factor. There is also evidence for a lithium factor that plays an important role in the returns of lithium companies.

Suggested Citation

  • Michael D. Plante, 2023. "Investing in the Batteries and Vehicles of the Future: A View Through the Stock Market," Working Papers 2314, Federal Reserve Bank of Dallas, revised 25 Mar 2024.
    • Handle: RePEc:fip:feddwp:96951
    DOI: 10.24149/wp2314r1
    as

    Download full text from publisher

    File URL: https://www.dallasfed.org/-/media/documents/research/papers/2023/wp2314r1.pdf
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.24149/wp2314r1?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
    ---><---

    References listed on IDEAS

    as
    1. Trzcinka, Charles A, 1986. "On the Number of Factors in the Arbitrage Pricing Model," Journal of Finance, American Finance Association, vol. 41(2), pages 347-368, June.
    2. Sadorsky, Perry, 2012. "Modeling renewable energy company risk," Energy Policy, Elsevier, vol. 40(C), pages 39-48.
    3. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    4. Bolton, Patrick & Kacperczyk, Marcin, 2021. "Do investors care about carbon risk?," Journal of Financial Economics, Elsevier, vol. 142(2), pages 517-549.
    5. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2022. "Dissecting green returns," Journal of Financial Economics, Elsevier, vol. 146(2), pages 403-424.
    6. Henriques, Irene & Sadorsky, Perry, 2008. "Oil prices and the stock prices of alternative energy companies," Energy Economics, Elsevier, vol. 30(3), pages 998-1010, May.
    7. Yacine Aït-Sahalia & Jean Jacod, 2014. "High-Frequency Financial Econometrics," Economics Books, Princeton University Press, edition 1, number 10261.
    8. Bohl, Martin T. & Kaufmann, Philipp & Stephan, Patrick M., 2013. "From hero to zero: Evidence of performance reversal and speculative bubbles in German renewable energy stocks," Energy Economics, Elsevier, vol. 37(C), pages 40-51.
    9. Eraker, Bjørn & Ready, Mark, 2015. "Do investors overpay for stocks with lottery-like payoffs? An examination of the returns of OTC stocks," Journal of Financial Economics, Elsevier, vol. 115(3), pages 486-504.
    10. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    11. Christine L. Dobridge & Rebecca John & Berardino Palazzo, 2022. "The post-COVID stock listing boom," FEDS Notes 2022-06-17-1, Board of Governors of the Federal Reserve System (U.S.).
    12. Aït-Sahalia, Yacine & Xiu, Dacheng, 2019. "A Hausman test for the presence of market microstructure noise in high frequency data," Journal of Econometrics, Elsevier, vol. 211(1), pages 176-205.
    13. Alessi, Lucia & Ossola, Elisa & Panzica, Roberto, 2021. "What greenium matters in the stock market? The role of greenhouse gas emissions and environmental disclosures," Journal of Financial Stability, Elsevier, vol. 54(C).
    14. Roy, Preeti & Ahmad, Wasim & Sadorsky, Perry & Phani, B.V., 2022. "What do we know about the idiosyncratic risk of clean energy equities?," Energy Economics, Elsevier, vol. 112(C).
    15. Connor, Gregory & Korajczyk, Robert A, 1993. "A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
    16. Pham, Linh & Hao, Wei & Truong, Ha & Trinh, Hai Hong, 2023. "The impact of climate policy on U.S. environmentally friendly firms: A firm-level examination of stock return, volatility, volume, and connectedness," Energy Economics, Elsevier, vol. 119(C).
    17. Pelger, Markus, 2019. "Large-dimensional factor modeling based on high-frequency observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 23-42.
    Full references (including those not matched with items on IDEAS)

    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. Sun, Yucheng & Xu, Wen & Zhang, Chuanhai, 2023. "Identifying latent factors based on high-frequency data," Journal of Econometrics, Elsevier, vol. 233(1), pages 251-270.
    2. Nuno Cassola & Claudio Morana & Elisa Ossola, 2023. "Green risk in Europe," Working Papers 526, University of Milano-Bicocca, Department of Economics.
    3. Bu, Ruijun & Hizmeri, Rodrigo & Izzeldin, Marwan & Murphy, Anthony & Tsionas, Mike, 2023. "The contribution of jump signs and activity to forecasting stock price volatility," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 144-164.
    4. Roy, Preeti & Ahmad, Wasim & Sadorsky, Perry & Phani, B.V., 2022. "What do we know about the idiosyncratic risk of clean energy equities?," Energy Economics, Elsevier, vol. 112(C).
    5. Ugolini, Andrea & Reboredo, Juan C. & Ojea-Ferreiro, Javier, 2024. "Is climate transition risk priced into corporate credit risk? Evidence from credit default swaps," Research in International Business and Finance, Elsevier, vol. 70(PB).
    6. Zhou, Wei & Gu, Qinen & Chen, Jin, 2021. "From volatility spillover to risk spread: An empirical study focuses on renewable energy markets," Renewable Energy, Elsevier, vol. 180(C), pages 329-342.
    7. Bohl, Martin T. & Kaufmann, Philipp & Siklos, Pierre L., 2015. "What drove the mid-2000s explosiveness in alternative energy stock prices? Evidence from U.S., European and global indices," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 194-206.
    8. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    9. Roy Kouwenberg & Chenglong Zheng, 2023. "A Review of the Global Climate Finance Literature," Sustainability, MDPI, vol. 15(2), pages 1-32, January.
    10. Sadorsky, Perry, 2022. "Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    11. Perry Sadorsky, 2021. "A Random Forests Approach to Predicting Clean Energy Stock Prices," JRFM, MDPI, vol. 14(2), pages 1-20, January.
    12. Reboredo, Juan C., 2015. "Is there dependence and systemic risk between oil and renewable energy stock prices?," Energy Economics, Elsevier, vol. 48(C), pages 32-45.
    13. Cortez, Maria Céu & Andrade, Nuno & Silva, Florinda, 2022. "The environmental and financial performance of green energy investments: European evidence," Ecological Economics, Elsevier, vol. 197(C).
    14. Alain-Philippe Fortin & Patrick Gagliardini & O. Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Swiss Finance Institute Research Paper Series 22-81, Swiss Finance Institute.
    15. Shen, Yiran & Liu, Chang & Sun, Xiaolei & Guo, Kun, 2023. "Investor sentiment and the Chinese new energy stock market: A risk–return perspective," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 395-408.
    16. Ferriani, Fabrizio, 2023. "Issuing bonds during the Covid-19 pandemic: Was there an ESG premium?," International Review of Financial Analysis, Elsevier, vol. 88(C).
    17. Dunbar, Kwamie & Treku, Daniel & Sarnie, Robert & Hoover, Jack, 2023. "What does ESG risk premia tell us about mutual fund sustainability levels: A difference-in-differences analysis," Finance Research Letters, Elsevier, vol. 57(C).
    18. Goyal, Amit & Pérignon, Christophe & Villa, Christophe, 2008. "How common are common return factors across the NYSE and Nasdaq?," Journal of Financial Economics, Elsevier, vol. 90(3), pages 252-271, December.
    19. Benjamin Dennis, 2022. "Climate Change and Financial Policy: A Literature Review," Finance and Economics Discussion Series 2022-048, Board of Governors of the Federal Reserve System (U.S.).
    20. Lars Winkelmann & Wenying Yao, 2024. "Tests for Jumps in Yield Spreads," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 946-957, July.

    More about this item

    Keywords

    stock returns; principal components; electric vehicles; batteries; high-frequency data;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:fip:feddwp:96951. 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: Amy Chapman (email available below). General contact details of provider: https://edirc.repec.org/data/frbdaus.html .

    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.