Journal Press India^®

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The main aim of this paper is to apply the moving averages to know the possibility of gaining better returns in candlesticks or Heikin-Ashi charts. For the purpose of this, top five sectoral indices of Nifty are selected on the basis of market capitalization. Daily closing prices of select sectoral indices is collected for the period of five years starting from 01/12/2017 to 30/11/2022. 10 Days Simple Moving Average (DSMA) and 50 Days Simple Moving Average (DSMA) are selected for tracking the short-term trend and 100 Days Simple Moving Average (DSMA) and 200 Days Simple Moving Average (DSMA) are selected for tracking the long-term trend. The study has found that, it is possible to gain better returns in Heikinashi than compared to Candlesticks.

Keywords

Candlesticks; Heikin-Ashi; Moving Averages and Nifty Sectoral Indices

1. Anghel, D. G. (2013). How reliable is the moving average crossover rule for an investor on the Romanian Stock Market? The Review of Finance and Banking, 5(2), 89-115.
2. Azhar, A. (2010). Evaluation of technical analysis as a predictive tool: A study on Indian Stock Market. Published Thesis, University of Hyderabad, Hyderabad.
3. Jones, M., & Lee, K. (2019). Combining moving averages with Heikin-Ashi charts for trend reversal identification in stock markets. Journal of Trading Strategies, 13(1), 23-42.
4. Kim, S., & Apte, L. (2020). Identifying trend changes using moving averages on Candlesticks and Heikin-Ashi charts. International Journal of Technical Analysis, 12(4), 289-305.
5. Kolkova, A. (2018). Indicators of technical analysis on the basis of moving averages as prognostic methods in the Food Industry. Journal of Competition, 10(4), 102-119.
6. Kulshreshtha, N. (2021). Leveraging fundamental and technical analysis for predicting the stock market movements. Published Thesis, Raffles University, Neemrana.
7. Pradipbhai, N. P.  (2013). Comparison between exponential moving average based MACD with simple moving average based MACD of technical analysis. International Journal Scientific Research, 2(12), 2277-8179.
8. Satav, S. & Apte, N. (2020). The moving average crossover strategy: A study. Journal of Modern Management & Entrepreneurship (JMME), 10(3), 141–146.
9. Smith, B., & Fiore, U. (2017). Predicting price movements in forex markets: Evidence from combining exponential moving averages and Candlestick patterns. Journal of Financial Analysis, 10(2), 45-68.
10. Tan, A., & Issidore, P. H (2016). Enhancing trend pattern identification using exponential moving averages on Candlesticks and Heikin-Ashi charts. Journal of Technical Analysis, 9(1), 1-15.
11. Vaidya, R. (2020). Accuracy of moving average forecasting for NEPSE. The journal of Nepalese Business Studies, 13(1), 62-76.
12. Vaiz, J. S. & Ramaswami, M. (2016). A study on technical indicators in stock price movement prediction using decision tree algorithm. American Journal of Engineering Research (AJER), 5(12), 207-212.
13. Wang, C., & Chen, J. (2018). Moving averages for trend change identification on Candlesticks and Heikin-Ashi charts. Journal of Financial Research, 11(3), 112-129.