License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.FUN.2022.18
URN: urn:nbn:de:0030-drops-159882
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/15988/
Go to the corresponding LIPIcs Volume Portal

Lafond, Manuel

How Brokers Can Optimally Abuse Traders

pdf-format:
LIPIcs-FUN-2022-18.pdf (0.9 MB)

Abstract

Traders buy and sell financial instruments in hopes of making profit, and brokers are responsible for the transaction. There are several hypotheses and conspiracy theories arguing that in some situations, brokers want their traders to lose money. For instance, a broker may want to protect the positions of a privileged customer. Another example is that some brokers take positions opposite to their traders', in which case they make money whenever their traders lose money. These are reasons for which brokers might manipulate prices in order to maximize the losses of their traders.
In this paper, our goal is to perform this shady task optimally - or at least to check whether this can actually be done algorithmically. Assuming total control over the price of an asset (ignoring the usual aspects of finance such as market conditions, external influence or stochasticity), we show how in quadratic time, given a set of trades specified by a stop-loss and a take-profit price, a broker can find a maximum loss price movement. We also look at an online trade model where broker and trader exchange turns, each trying to make a profit. We show in which condition either side can make a profit, and that the best option for the trader is to never trade.

BibTeX - Entry

@InProceedings{lafond:LIPIcs.FUN.2022.18,
  author =	{Lafond, Manuel},
  title =	{{How Brokers Can Optimally Abuse Traders}},
  booktitle =	{11th International Conference on Fun with Algorithms (FUN 2022)},
  pages =	{18:1--18:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-232-7},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{226},
  editor =	{Fraigniaud, Pierre and Uno, Yushi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/15988},
  URN =		{urn:nbn:de:0030-drops-159882},
  doi =		{10.4230/LIPIcs.FUN.2022.18},
  annote =	{Keywords: Algorithms, trading, graph theory}
}

Keywords: Algorithms, trading, graph theory
Collection: 11th International Conference on Fun with Algorithms (FUN 2022)
Issue Date: 2022
Date of publication: 23.05.2022

DROPS-Home | Fulltext Search | Imprint | Privacy Published by LZI