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Informed Trading in the Index Option Market

43 Pages Posted: 7 Jun 2017 Last revised: 25 Jul 2017

Andreas Kaeck

University of Sussex

Vincent van Kervel

Pontifical Catholic University of Chile; Tilburg Law and Economics Center (TILEC)

Norman Seeger

VU University Amsterdam

Date Written: June 5, 2017

Abstract

We estimate a structural model of informed trading in option markets. We decompose option order flow into exposures to the underlying asset (through the option delta) and its volatility (through the option vega). We then use these order flow exposures to predict changes in the underlying asset and volatility in a vector autoregressive (VAR) model. The model measures informed trading in the aggregate option market, as option order flows can be meaningfully combined across options with different strike prices and maturities. Further, the order flow aggregation increases statistical power, which is necessary to identify informed trading on the two components. The model also yields a novel price impact parameter of volatility speculation. Estimates using options on the S&P500 confirm that option trades are indeed informed about changes in both the underlying and volatility, although the magnitude of the former is substantially larger.

Keywords: Options, informed trading, price impact

Suggested Citation

Kaeck, Andreas and van Kervel, Vincent and Seeger, Norman, Informed Trading in the Index Option Market (June 5, 2017). TILEC Discussion Paper No. 2017-027. Available at SSRN: https://ssrn.com/abstract=2981332

Andreas Kaeck

University of Sussex ( email )

Sussex House
Falmer
Brighton, Sussex BNI 9RH
United Kingdom

Vincent Van Kervel

Pontifical Catholic University of Chile ( email )

Av Libertador General Bernardo O'Higgins 340
Santiago, RegiĆ³n Metropolitana 8331150
Chile

Tilburg Law and Economics Center (TILEC) ( email )

Warandelaan 2
Tilburg, 5000 LE
Netherlands

Norman Seeger (Contact Author)

VU University Amsterdam ( email )

De Boelelaan 1105
Amsterdam, 1081 HV
Netherlands
+31 20 598 1512 (Phone)

HOME PAGE: http://www.norman-seeger.com

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