Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading

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Year : 2024 | Volume :02 | Issue : 02 | Page : –
By
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Vikrant Arora,

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Sudhanshu Marudgan,

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Anoushka Ramankulath,

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Punya Arora,

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Aditya Kasar,

  1. Student, School of Technology Management & Engineering, SVKM’s NMIMS School of Technology and Science, Kharghar, Navi Mumbai, Maharashtra, India
  2. Student, School of Technology Management & Engineering, SVKM’s NMIMS School of Technology and Science, Kharghar, Navi Mumbai, Maharashtra, India
  3. Student, School of Technology Management & Engineering, SVKM’s NMIMS School of Technology and Science, Kharghar, Navi Mumbai, Maharashtra, India
  4. Student, School of Technology Management & Engineering, SVKM’s NMIMS School of Technology and Science, Kharghar, Navi Mumbai, Maharashtra, India
  5. Assistant Professor, School of Technology Management & Engineering, SVKM’s NMIMS School of Technology and Science, Kharghar, Navi Mumbai, Maharashtra, India

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This paper details a comparison of the overall performance of leading and lagging technical indicators used in algorithmic trading over an extended period. While much of the prior research focuses on index price forecasting and some on statistical arbitrage derived from these predictive techniques, there is a scarcity of studies that assess and evaluate trading strategies. The strategies considered for the study were tested on historical data of the fifty stocks constituting the NIFTYMIDCAP50 index, listed on the National Stock Exchange of India from January 2019 to January 2024. The study examined the Relative Strength Index (RSI), Stochastic Oscillator, Simple Moving Average (SMA), and Exponential Moving Average (EMA), representing two leading and two lagging indicators, to generate trading signals using fixed parameter sets. Over a five-year period, it was found that strategies based on leading indicators generally underperformed compared to those based on lagging indicators in longer timeframes. The mean percentage returns for strategies using lagging indicators were 37.06, while those using leading indicators were 18.67. The difference in mean returns between leading and lagging indicators across all selected stocks was statistically significant, with a p-value of less than 0.05002.

Keywords: Technical Analysis; Algorithms; Algorithmic Trading; Indian Stock Market; Technical Indicators; RSI; Stochastic Oscillator.

[This article belongs to International Journal of Algorithms Design and Analysis Review (ijadar)]

How to cite this article:
Vikrant Arora, Sudhanshu Marudgan, Anoushka Ramankulath, Punya Arora, Aditya Kasar. Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading. International Journal of Algorithms Design and Analysis Review. 2024; 02(02):-.
How to cite this URL:
Vikrant Arora, Sudhanshu Marudgan, Anoushka Ramankulath, Punya Arora, Aditya Kasar. Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading. International Journal of Algorithms Design and Analysis Review. 2024; 02(02):-. Available from: https://journals.stmjournals.com/ijadar/article=2024/view=0

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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 28/06/2024
Accepted 23/08/2024
Published 06/11/2024
Total Visits: 61

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