How Brokers Can Optimally Abuse Traders

Author Manuel Lafond



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Manuel Lafond
  • University of Sherbrooke, Canada

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Manuel Lafond. How Brokers Can Optimally Abuse Traders. In 11th International Conference on Fun with Algorithms (FUN 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 226, pp. 18:1-18:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.FUN.2022.18

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.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
Keywords
  • Algorithms
  • trading
  • graph theory

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References

  1. How crypto investors can avoid the scam that captured $2.8 billion in 2021. time.com: https://time.com/nextadvisor/investing/cryptocurrency/protect-yourself-from-crypto-pump-and-dump/. Accessed: February 17, 2022.
  2. Market makers vs. electronic communications networks. investopedia.com: https://www.investopedia.com/articles/forex/06/ecnmarketmaker.asp. Accessed: February 17, 2022.
  3. Robinhood restricts trading in gamestop, other names involved in frenzy. cnbc.com: https://www.cnbc.com/2021/01/28/robinhood-interactive-brokers-restrict-trading-in-gamestop-s.html. Accessed: February 17, 2022.
  4. Why do many forex traders lose money? here is the number 1 mistake. dailyfx.com: https://www.dailyfx.com/forex/fundamental/article/special_report/2015/06/25/what-is-the-number-one-mistake-forex-traders-make.html. Accessed: February 17, 2022.
  5. Andreas Brandstädt, Van Bang Le, and Jeremy P Spinrad. Graph classes: a survey. SIAM, 1999. Google Scholar
  6. Feodor F Dragan. Strongly orderable graphs a common generalization of strongly chordal and chordal bipartite graphs. Discrete applied mathematics, 99(1-3):427-442, 2000. Google Scholar
  7. Eugene F Fama. Efficient capital markets: A review of theory and empirical work. The journal of Finance, 25(2):383-417, 1970. Google Scholar
  8. Gianni Franceschini, Shan Muthukrishnan, and Mihai Pǎtraşcu. Radix sorting with no extra space. In European Symposium on Algorithms, pages 194-205. Springer, 2007. Google Scholar
  9. Yijie Han. Deterministic sorting in o (n log log n) time and linear space. In Proceedings of the thiry-fourth annual ACM symposium on Theory of computing, pages 602-608, 2002. Google Scholar
  10. Nicklas Larsen, Helmut Mausser, and Stanislav Uryasev. Algorithms for optimization of value-at-risk. In Financial engineering, E-commerce and supply chain, pages 19-46. Springer, 2002. Google Scholar
  11. James B Orlin. Max flows in O(nm) time, or better. In Proceedings of the forty-fifth annual ACM symposium on Theory of computing, pages 765-774, 2013. Google Scholar
  12. Mechthild Stoer and Frank Wagner. A simple min-cut algorithm. Journal of the ACM (JACM), 44(4):585-591, 1997. Google Scholar
  13. Gerold Studer. Maximum loss for measurement of market risk. PhD thesis, ETH Zurich, 1997. Google Scholar
  14. Mu Yang. Fx spot trading and risk management from a market maker’s perspective. Master’s thesis, University of Waterloo, 2011. Google Scholar
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