nep-mst New Economics Papers
on Market Microstructure
Issue of 2020‒08‒24
four papers chosen by
Thanos Verousis

  1. A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data By Lam, Clifford; Feng, Phoenix
  2. Multivariate General Compound Point Processes in Limit Order Books By Qi Guo; Bruno Remillard; Anatoliy Swishchuk
  3. Principal Trading Firm Activity in Treasury Cash Markets By James Collin Harkrader; Michael Puglia
  4. Optimal semi-static hedging in illiquid markets By Teemu Pennanen; Udomsak Rakwongwan

  1. By: Lam, Clifford; Feng, Phoenix
    Abstract: In high-frequency data analysis, the extreme eigenvalues of a realized covariance matrix are biased when its dimension p is large relative to the sample size n. Furthermore, with non-synchronous trading and contamination of microstructure noise, we propose a nonparametrically eigenvalue-regularized integrated covariance matrix estimator (NERIVE) which does not assume specific structures for the underlying integrated covariance matrix. We show that NERIVE is positive definite in probability, with extreme eigenvalues shrunk nonlinearly under the high dimensional framework p=n ! c > 0. We also prove that in portfolio allocation, the minimum variance optimal weight vector constructed using NERIVE has maximum exposure and actual risk upper bounds of order p. Incidentally, the same maximum exposure bound is also satisfied by the theoretical minimum variance portfolio weights. All these results hold true also under a jump-diffusion model for the log-price processes with jumps removed using the wavelet method proposed in Fan and Wang (2007). They are further extended to accommodate the existence of pervasive factors such as a market factor under the setting p3=2=n ! c > 0. The practical performance of NERIVE is illustrated by comparing to the usual two-scale realized covariance matrix as well as some other nonparametric alternatives using different simulation settings and a real data set.
    Keywords: High frequency data; Microstructure noise; Non-synchronous trading; Integrated covariance matrix; Minimum variance portfolio; Nonlinear shrinkage
    JEL: C13 C14 C5
    Date: 2018–09–01
  2. By: Qi Guo; Bruno Remillard; Anatoliy Swishchuk
    Abstract: In this paper, we focus on a new generalization of multivariate general compound Hawkes process (MGCHP), which we referred to as the multivariate general compound point process (MGCPP). Namely, we applied a multivariate point process to model the order flow instead of the Hawkes process. Law of large numbers (LLN) and two functional central limit theorems (FCLTs) for the MGCPP were proved in this work. Applications of the MGCPP in the limit order market were also considered. We provided numerical simulations and comparisons for the MGCPP and MGCHP by applying Google, Apple, Microsoft, Amazon, and Intel trading data.
    Date: 2020–07
  3. By: James Collin Harkrader; Michael Puglia
    Abstract: This FEDS Note aims to share insights on Treasury cash transactions reported in the Financial Industry Regulatory Authority (FINRA)'s Trade Reporting and Compliance Engine (TRACE). Following earlier joint FEDS Notes and Liberty Street Economics blog posts that examined aggregate trading volume in the Treasury cash market across venues and security types, this post sheds light on the trading activity of Principal Trade Firms (PTFs) and other market participants that are not registered broker-dealer members of FINRA.
    Date: 2020–08–04
  4. By: Teemu Pennanen; Udomsak Rakwongwan
    Abstract: We study indifference pricing of exotic derivatives by using hedging strategies that take static positions in quoted derivatives but trade the underlying and cash dynamically over time. We use real quotes that come with bid-ask spreads and finite quantities. Galerkin method and integration quadratures are used to approximate the hedging problem by a finite dimensional convex optimization problem which is solved by an interior point method. The techniques are extended also to situations where the underlying is subject to bid-ask spreads. As an illustration, we compute indifference prices of path-dependent options written on S&P500 index. Semi-static hedging improves considerably on the purely static options strategy as well as dynamic trading without options. The indifference prices make good economic sense even in the presence of arbitrage opportunities that are found when the underlying is assumed perfectly liquid. When transaction costs are introduced, the arbitrage opportunities vanish but the indifference prices remain almost unchanged.
    Date: 2020–08

This nep-mst issue is ©2020 by Thanos Verousis. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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