Journal of Open Innovation: Technology, Market and Complexity (Sep 2024)

Synergizing quantitative finance models and market microstructure analysis for enhanced algorithmic trading strategies

  • Om Mengshetti,
  • Kanishk Gupta,
  • Nilima Zade,
  • Ketan Kotecha,
  • Siddhanth Mutha,
  • Gayatri Joshi

Journal volume & issue
Vol. 10, no. 3
p. 100334

Abstract

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In today’s complex financial markets, “Algorithmic Trading” has become very important. The study delves into the amalgamation of four pivotal indicators - Relative Strength Index (RSI), Exponential Moving Average (EMA), Volume-Weighted Average Price (VWAP), and Moving Average Convergence/Divergence (MACD) Relative Strength Index (RSI), Exponential Moving Average (EMA), Volume-Weighted Average Price (VWAP), and Moving Average Convergence/Divergence (MACD) to create and develop a potent trading strategy. Through intensive backtesting and parameter tuning, our study demonstrates 60.63 % profitable trades on the National Stock Exchange (NSE), India, surpassing the standalone indicators. The Weapon Candle Strategy created using the four indicators presents its efficiency as it was able to achieve a profit factor of 1.882. This suggests that when these four technical indicators combined to make a strategy, it can provide significantly more accurate and reliable trading signals compared to using a combination of two or three indicators. Algorithmic traders should use a multi-indicator approach to achieve a more comprehensive understanding of the market and make informed trading decisions.

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