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Exploring Classic Quantitative Strategies

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  • 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
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    File URL: http://arxiv.org/pdf/2202.11309
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    References listed on IDEAS

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    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.
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    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.

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