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Low Frequency Algorithmic Trading

This special issue belongs to the section “Mathematics and Finance“.

Special Issue Information

Dear Colleagues,

Algorithmic trading accounts for over 80% (and growing) of all trades and over 90% of trades by professionals. Much of this work is focused on short-term trading (down to microseconds), also called high-frequency trading, suitable for machine trading by professionals. These algorithms often take advantage of arbitrage opportunities that exist only on very short time scales. Little attention is paid to low-frequency trading—trading that is based on minutes, hours, and days. Such trading methods can be suitable for very long-term performance (e.g., over decades) and can apply to both professionals and small investors alike. This Special Issue aims to remedy this gap, as the majority of those who invest are in fact small investors who seek long-term performance. This puts severe constraints on the complexity and frequency of trades; we suggest limiting trades to once per day and on average less than once per week. Importantly, performance measures specifically suitable to this application space are encouraged as standard measures such as the Sharpe ratio may not be as suitable. 

Dr. Pankaj Topiwala
Guest Editor

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Keywords

  • algorithmic trading suitable for small investors
  • index and stock (and bond) trading at relaxed pace
  • long-term investment performance
  • novel investment performance measures
  • quantitative analysis of performance

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J. Risk Financial Manag. - ISSN 1911-8074