IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2202.11309.html
   My bibliography  Save this paper

Exploring Classic Quantitative Strategies

Author

Listed:
  • Jun Lu

Abstract

The goal of this paper is to debunk and dispel the magic behind the black-box quantitative strategies. It aims to build a solid foundation on how and why the techniques work. This manuscript crystallizes this knowledge by deriving from simple intuitions, the mathematics behind the strategies. This tutorial doesn't shy away from addressing both the formal and informal aspects of quantitative strategies. By doing so, it hopes to provide readers with a deeper understanding of these techniques as well as the when, the how and the why of applying these techniques. The strategies are presented in terms of both S\&P500 and SH510300 data sets. However, the results from the tests are just examples of how the methods work; no claim is made on the suggestion of real market positions.

Suggested Citation

  • Jun Lu, 2022. "Exploring Classic Quantitative Strategies," Papers 2202.11309, arXiv.org.
    • Handle: RePEc:arx:papers:2202.11309
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2202.11309
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Joseph Man-Joe Leung & Terence Tai-Leung Chong, 2003. "An empirical comparison of moving average envelopes and Bollinger Bands," Applied Economics Letters, Taylor & Francis Journals, vol. 10(6), pages 339-341.
    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. Jun Lu & Shao Yi, 2022. "Reducing Overestimating and Underestimating Volatility via the Augmented Blending-ARCH Model," Applied Economics and Finance, Redfame publishing, vol. 9(2), pages 48-59, May.
    2. Jun Lu & Minhui Wu, 2022. "A note on VIX for postprocessing quantitative strategies," Papers 2207.04887, arXiv.org.

    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. Wong, Wing-Keung & Du, Jun & Chong, Terence Tai-Leung, 2005. "Do the technical indicators reward chartists? A study on the stock markets of China, Hong Kong and Taiwan," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-23.
    2. Michael McAleer & John Suen & Wing Keung Wong, 2016. "Profiteering from the Dot-Com Bubble, Subprime Crisis and Asian Financial Crisis," The Japanese Economic Review, Japanese Economic Association, vol. 67(3), pages 257-279, September.
    3. Pick-Soon Ling & Ruzita Abdul-Rahim, 2017. "Market Efficiency Based on Unconventional Technical Trading Strategies in Malaysian Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 88-96.
    4. Hung-Cheng Lai & Tseng-Chan Tseng & Sz-Chi Huang, 2016. "Combining value averaging and Bollinger Band for an ETF trading strategy," Applied Economics, Taylor & Francis Journals, vol. 48(37), pages 3550-3557, August.
    5. Gerritsen, Dirk F., 2016. "Are chartists artists? The determinants and profitability of recommendations based on technical analysis," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 179-196.
    6. Wong, Wing-Keung & Du, Jun & Chong, Terence Tai-Leung, 2005. "Do the technical indicators reward chartists? A study on the stock markets of China, Hong Kong and Taiwan," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 1(2), pages 1-23.
    7. Stefanescu, Răzvan & Dumitriu, Ramona, 2015. "Buy and sell signals on Bucharest Stock Exchange," MPRA Paper 89014, University Library of Munich, Germany, revised 05 Jan 2016.
    8. Ken Chung & Anthony Bellotti, 2021. "Evidence and Behaviour of Support and Resistance Levels in Financial Time Series," Papers 2101.07410, arXiv.org.
    9. Day, Min-Yuh & Ni, Yensen, 2023. "Do clean energy indices outperform using contrarian strategies based on contrarian trading rules?," Energy, Elsevier, vol. 272(C).
    10. Ramnarayan, Padmanabhan & Ray, Samiran & Peters, Mark J., 2018. "Development and implementation of a real time statistical control method to identify the start and end of the winter surge in demand for paediatric intensive careAuthor-Name: Pagel, Christina," European Journal of Operational Research, Elsevier, vol. 264(3), pages 847-858.
    11. Ni, Yensen & Day, Min-Yuh & Huang, Paoyu & Yu, Shang-Ru, 2020. "The profitability of Bollinger Bands: Evidence from the constituent stocks of Taiwan 50," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    12. Hsien-Ming Chou, 2024. "Analyzing the Impact of COVID-19 on Short-Term Investment Behavior through Stochastic Oscillator Indicators," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(5), pages 1-6.
    13. Nijolė MAKNICKIENĖ & Jelena STANKEVIČIENĖ & Algirdas MAKNICKAS, 2020. "Comparison of Forex Market Forecasting Tools Based on Evolino Ensemble and Technical Analysis Indicators," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 134-148, September.
    14. Lubnau, Thorben, 2014. "Spread trading strategies in the crude oil futures market," Discussion Papers 353, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    15. Hsien-Ming Chou, 2023. "Using Bull and Bear Index of Deep Learning to Improve the Indicator Model on Extremely Short-term Futures Trading," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 13(6), pages 1-6.
    16. Senol Emir & Hasan Dincer & Umit Hacioglu & Serhat Yuksel, 2016. "Random Regression Forest Model using Technical Analysis Variables: An application on Turkish Banking Sector in Borsa Istanbul (BIST)," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 5(3), pages 85-102, April.
    17. Lubnau, Thorben & Todorova, Neda, 2015. "Trading on mean-reversion in energy futures markets," Energy Economics, Elsevier, vol. 51(C), pages 312-319.
    18. Strobel, Marcus & Auer, Benjamin R., 2018. "Does the predictive power of variable moving average rules vanish over time and can we explain such tendencies?," International Review of Economics & Finance, Elsevier, vol. 53(C), pages 168-184.

    More about this item

    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:arx:papers:2202.11309. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.