Trade Cost: <i>Handicapping on PAR</i>

Rashkovich, Vlad; Verma, Arun

doi:10.3905/jot.2012.7.4.047

Cited by 10 publications

(3 citation statements)

References 6 publications

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“…Thus, an improvement in tactical and SOR levels doesn't necessarily translate linearly into better performance vs. benchmarks like IS or VWAP. Order level TCA was studied in a different approach in [Rashkovich and Verma, 2012]. In this paper, we study and calibrate models using placement level data.…”

Section: Execution Benchmarksmentioning

confidence: 99%

Bayesian Trading Cost Analysis and Ranking of Broker Algorithms

Марков¹

2019

Preprint

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We present a formulation of transaction cost analysis (TCA) in the Bayesian framework for the primary purpose of comparing broker algorithms using standardized benchmarks. Our formulation allows effective calculation of the expected value of trading benchmarks with only a finite sample of data relevant to practical applications. We discuss the nature of distribution of implementation shortfall, volume-weighted average price, participation-weighted price and short-term reversion benchmarks. Our model takes into account fat tails, skewness of the distributions and heteroscedasticity of benchmarks. The proposed framework allows the use of hierarchical models to transfer approximate knowledge from a large aggregated sample of observations to a smaller sample of a particular algorithm.

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Section: Execution Benchmarksmentioning

confidence: 99%

Bayesian Trading Cost Analysis and Ranking of Broker Algorithms

Марков¹

2019

Preprint

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“…Portfolio managers are aware that incorrect future volume estimation leads to excessive transaction costs and poses serious constraints on capacity of an alpha-model. Efficient implementation of pre-trade TCA relies on volume prediction as well (Rashkovich & Verma (2012)).…”

Section: Introductionmentioning

confidence: 99%

Quintet Volume Projection

Марков¹,

Vilenskaia²,

Rashkovich³

2017

JOT

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We consider the problem of finding a strategy that tracks the volume weighted average price (VWAP) of a stock, a key measure of execution quality for large orders used by institutional investors. We obtain the optimal, dynamic, VWAP tracking strategy in closed form in a model without trading costs with general price and volume dynamics. We build a model of intraday volume using the Trade and Quote dataset to empirically test the strategy, both without trading costs and when trading has temporary and permanent effects, and find that the implementation cost is lower than the cost charged by brokerage houses.JEL classification: G12, G29, C61

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“…These models are typically estimated through large scale cross-sectional regressions based on the realized costs of a proprietary set of algorithmically executed trades. Almgren et al (2005) describe an econometric approach for that problem, while Rashkovich and Verma (2012) provide important insights that improve the estimation procedure, and allow for more accurate de-trending of the trade data. Moallemi et al (2014) extend the above approach to include a short term alpha fixed effect associated with the identity of the trader.…”

Section: Introductionmentioning

confidence: 99%