An Incremental Algorithm for Estimating Extreme Quantiles

Joseph, AG and Bhatnagar, S (2019) An Incremental Algorithm for Estimating Extreme Quantiles. In: 2019 Sixth Indian Control Conference (ICC)Proceedings, 18-20 Dec. 2019, Hyderabad, India, pp. 286-291.

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Abstract

Extreme quantile is a very influential and powerful performance measure in high risk environments like financial markets, targeted advertising and high frequency trading. Extreme quantiles are defined as the threshold in the range of the performance values of the system being monitored beyond which the probability is extremely low. Unfortunately, the estimation of extreme quantiles is usually accompanied by high variance. We provide an incremental, single pass and adaptive variance reduction technique to estimate extreme quantiles. We further provide additional theoretical and empirical analysis pertaining to the effectiveness of our approach. Our experiments show considerable performance improvement over other widely popular algorithms. © 2019 IEEE.

Item Type:	Conference Paper
Publication:	2019 6th Indian Control Conference, ICC 2019 - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	cited By 0; Conference of 6th Indian Control Conference, ICC 2019 ; Conference Date: 18 December 2019 Through 20 December 2019; Conference Code:161423
Keywords:	Commerce; Risk assessment, Empirical analysis; High risk environment; High-frequency trading; Incremental algorithm; Performance measure; Performance value; Targeted advertising; Variance reduction techniques, Electronic trading
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation Division of Interdisciplinary Sciences > Robert Bosch Centre for Cyber Physical Systems
Date Deposited:	08 Oct 2020 09:47
Last Modified:	08 Oct 2020 09:47
URI:	http://eprints.iisc.ac.in/id/eprint/66129

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