The target audience for the line of research to be described in this tutorial paper is control system researchers with an interest in algorithmic stock trading but without a substantial background in finance and economics. To this end, we focus our attention on just a few hand-picked problem areas to illustrate how algorithmic trading research might be carried out from a control-theoretic perspective and refer the reader to a number of references where extensive survey-style material can be found. The paper begins with the exposition of some basics associated with opening a brokerage account and mathematical modelling of common order types. Subsequently, we consider a number of trading scenarios involving feedback control design, optimization problems arising in portfolio man- agement, the theory of Kelly Betting in a stock trading context and interaction with the Limit Order Book which is crucial for smooth market operation. Given the control-theoretic point of view taken in this paper, many of our basic tools come into play; e.g., standard results from areas such as convex optimization, discrete probability theory and Markov processes, to name a few. One of the salient features of this tutorial is our use of idealizing assumptions and simplistic models whenever convenient for pedagogical and motivational purposes. In the conclusion section, we mention some challenging new research opportunities involving more general models and relaxation some of our simplifying assumptions.

A Jump Start to Stock Trading Research for the Uninitiated Control Scientist: A Tutorial / Barmish, B. Ross; Formentin, Simone; Hsieh, Chung-Han; Proskurnikov, Anton V.; Warnick, Sean. - (2024), pp. 7441-7457. (Intervento presentato al convegno IEEE 63rd Conference on Decision and Control tenutosi a Milano (Ita) nel 16-19 December 2024) [10.1109/cdc56724.2024.10886117].

A Jump Start to Stock Trading Research for the Uninitiated Control Scientist: A Tutorial

Formentin, Simone;Proskurnikov, Anton V.;
2024

Abstract

The target audience for the line of research to be described in this tutorial paper is control system researchers with an interest in algorithmic stock trading but without a substantial background in finance and economics. To this end, we focus our attention on just a few hand-picked problem areas to illustrate how algorithmic trading research might be carried out from a control-theoretic perspective and refer the reader to a number of references where extensive survey-style material can be found. The paper begins with the exposition of some basics associated with opening a brokerage account and mathematical modelling of common order types. Subsequently, we consider a number of trading scenarios involving feedback control design, optimization problems arising in portfolio man- agement, the theory of Kelly Betting in a stock trading context and interaction with the Limit Order Book which is crucial for smooth market operation. Given the control-theoretic point of view taken in this paper, many of our basic tools come into play; e.g., standard results from areas such as convex optimization, discrete probability theory and Markov processes, to name a few. One of the salient features of this tutorial is our use of idealizing assumptions and simplistic models whenever convenient for pedagogical and motivational purposes. In the conclusion section, we mention some challenging new research opportunities involving more general models and relaxation some of our simplifying assumptions.
2024
979-8-3503-1633-9
File in questo prodotto:
File Dimensione Formato  
CDC24_2560_FI.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Pubblico - Tutti i diritti riservati
Dimensione 1.14 MB
Formato Adobe PDF
1.14 MB Adobe PDF Visualizza/Apri
A_Jump_Start_to_Stock_Trading_Research_for_the_Uninitiated_Control_Scientist_A_Tutorial.pdf

accesso riservato

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 1.22 MB
Formato Adobe PDF
1.22 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2998302