Title: Leveraging technical analysis and artificial intelligence - optimisation of global portfolio management through world indices

Authors: Nitin Kulshrestha; Vishal Kamra; Shalini Aggarwal

Addresses: Chandigarh University, NH-95, Ludhiana-Chandigarh State Highway, Punjab – 140413, India ' Amity University, Sec. 125, Amity University Campus, Noida – UP – 201313, India ' Chandigarh University, NH-95, Ludhiana-Chandigarh State Highway, Punjab – 140413, India

Abstract: The motivation of this research is to analyse portfolio optimisation through technical analysis and artificial intelligence through stock indices of the world market. The technical report includes RSI, MACD, moving average and other indicators. The present research is based on technical analysis, more precisely, exponential moving average crossover on three world indices, i.e., Nifty (India), Dow Jones (USA), Nikkei (Japan) from 2016 to 2019, with the help of Ami-broker software to develop investing and trading model through AFL code language 6.20 version. After comparing technical analysis (AI) and buy and hold results, our results show, technical trading strategy, along with AI, outperforms the results. All the selected indices generate more returns and less Risk to compare with buy and hold strategy.

Keywords: artificial intelligence; technical analysis; indicators; backtest; EMA crossover; Nifty Index; Portfolio; Nifty; Dow Jones; Nikkei.

DOI: 10.1504/IJPSPM.2023.133588

International Journal of Public Sector Performance Management, 2023 Vol.12 No.3, pp.445 - 461

Received: 16 Mar 2020
Accepted: 05 Sep 2020
Published online: 22 Sep 2023 *

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