Estimating I-Star Market Impact Model Parameters

2021 ◽  
pp. 233-267
Author(s):  
Robert L. Kissell

In this paper we revisit techniques from “Creating Dynamic Pre-Trade Models: Beyond the Black Box” (Kissell, 2011) which was awarded The Journal of Trading’s Best Paper of the Year Award in 2011. We provide investors a pre-trade of pre-trade modeling technique that can be used to decipher broker and vendor models, and to calibrate a customized investor specific market impact model. We also provide a suite of Excel TCA Add-In functions that can incorporate investor specific market impact parameters and allow investors to perform TCA analysis on their own desktops within Excel, and with the added level of security and comfort that their investment decision process will not be reverse engineered because they do not need to upload or transmit any of their proprietary information and valuable trade information to a third-party website or API for analysis. Techniques in this paper enable investors to create their own customized TCA analyses within Excel to assist with both trading decisions and portfolio analysis and optimization.


2015 ◽  
Vol 01 (02) ◽  
pp. 1550007 ◽  
Author(s):  
X. Brokmann ◽  
E. Sérié ◽  
J. Kockelkoren ◽  
J.-P. Bouchaud

Using a proprietary dataset of meta-orders and prediction signals, and assuming a quasi-linear impact model, we deconvolve market impact from past correlated trades and a predictable return component to elicit the temporal dependence of the market impact of a single daily meta-order, over a 10-day horizon in various equity markets. We find that the impact of single meta-orders is to a first approximation universal and slowly decays to zero (or to a small value), possibly as a power-law. We show that autocorrelated order-flows and trade information contents fully accounts for the apparent plateau observed in the raw data. We discuss the possible bias introduced by the quasi-linear assumption.


2018 ◽  
Vol 27 (Suppl 1) ◽  
pp. s82-s86 ◽  
Author(s):  
Wendy B Max ◽  
Hai-Yen Sung ◽  
James Lightwood ◽  
Yingning Wang ◽  
Tingting Yao

ObjectivesWe review the Population Health Impact Model (PHIM) developed by Philip Morris International and used in its application to the US Food and Drug Administration (FDA) to market its heated tobacco product (HTP), IQOS, as a modified-risk tobacco product (MRTP). We assess the model against FDA guidelines for MRTP applications and consider more general criteria for evaluating reduced-risk tobacco products.MethodsIn assessing the PHIM against FDA guidelines, we consider two key components of the model: the assumptions implicit in the model (outcomes included, relative harm of the new product vs cigarettes, tobacco-related diseases considered, whether dual or polyuse of the new product is modelled, and what other tobacco products are included) and data used to estimate and validate model parameters (transition rates between non-smoking, cigarette-only smoking, dual use of cigarettes and MRTP, and MRTP-only use; and starting tobacco use prevalence).ResultsThe PHIM is a dynamic state transition model which models the impact of cigarette and MRTP use on mortality from four tobacco-attributable diseases. The PHIM excludes morbidity, underestimates mortality, excludes tobacco products other than cigarettes, does not include FDA-recommended impacts on non-users and underestimates the impact on other population groups.ConclusionThe PHIM underestimates the health impact of HTP products and cannot be used to justify an MRTP claim. An assessment of the impact of a potential MRTP on population health should include a comprehensive measure of health impacts, consideration of all groups impacted, and documented and justifiable assumptions regarding model parameters.


2017 ◽  
Vol 24 (5) ◽  
pp. 417-450 ◽  
Author(s):  
Florian Klöck ◽  
Alexander Schied ◽  
Yuemeng Sun

Author(s):  
Florian Klöck ◽  
Alexander Schied ◽  
Yuemeng Sunny Sun

2021 ◽  
Vol 6 (3) ◽  
pp. 237
Author(s):  
Samuel Drapeau ◽  
Peng Luo ◽  
Alexander Schied ◽  
Dewen Xiong

<p style='text-indent:20px;'>In this study, we have analyzed a market impact game between <i>n</i> risk-averse agents who compete for liquidity in a market impact model with a permanent price impact and additional slippage. Most market parameters, including volatility and drift, are allowed to vary stochastically. Our first main result characterizes the Nash equilibrium in terms of a fully coupled system of forward-backward stochastic differential equations (FBSDEs). Our second main result provides conditions under which this system of FBSDEs has a unique solution, resulting in a unique Nash equilibrium. </p>


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