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Semi-parametric dynamic contextual pricing

Author

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  • Virag Shah
  • Jose Blanchet
  • Ramesh Johari

Abstract

Motivated by the application of real-time pricing in e-commerce platforms, we consider the problem of revenue-maximization in a setting where the seller can leverage contextual information describing the customer's history and the product's type to predict her valuation of the product. However, her true valuation is unobservable to the seller, only binary outcome in the form of success-failure of a transaction is observed. Unlike in usual contextual bandit settings, the optimal price/arm given a covariate in our setting is sensitive to the detailed characteristics of the residual uncertainty distribution. We develop a semi-parametric model in which the residual distribution is non-parametric and provide the first algorithm which learns both regression parameters and residual distribution with $\tilde O(\sqrt{n})$ regret. We empirically test a scalable implementation of our algorithm and observe good performance.

Suggested Citation

  • Virag Shah & Jose Blanchet & Ramesh Johari, 2019. "Semi-parametric dynamic contextual pricing," Papers 1901.02045, arXiv.org, revised Aug 2019.
    • Handle: RePEc:arx:papers:1901.02045
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    References listed on IDEAS

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    1. N. Bora Keskin & Assaf Zeevi, 2014. "Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies," Operations Research, INFORMS, vol. 62(5), pages 1142-1167, October.
    2. Arnoud V. den Boer, 2014. "Dynamic Pricing with Multiple Products and Partially Specified Demand Distribution," Mathematics of Operations Research, INFORMS, vol. 39(3), pages 863-888, August.
    3. Josef Broder & Paat Rusmevichientong, 2012. "Dynamic Pricing Under a General Parametric Choice Model," Operations Research, INFORMS, vol. 60(4), pages 965-980, August.
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    Cited by:

    1. Jianqing Fan & Yongyi Guo & Mengxin Yu, 2021. "Policy Optimization Using Semi-parametric Models for Dynamic Pricing," Papers 2109.06368, arXiv.org, revised May 2022.
    2. Akshay Krishnamurthy & Thodoris Lykouris & Chara Podimata & Robert Schapire, 2020. "Contextual Search in the Presence of Adversarial Corruptions," Papers 2002.11650, arXiv.org, revised Aug 2022.

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