Artificial intelligence-based indicators for ALGO trading strategy on the NSE derivatives
Article No.: 38, Pages 1 - 6
Abstract
Machine learning and ALGO trading processes have resulted in a worldwide change in corporate practices. As a result of these technical advancements, traders may now lower their susceptibility to loss while improving their possibilities of earning from their investments. The buy-or-write method is often used for a single asset or a marketable product. A buy-and-sell maximization study design is a type of research design used to form an opinion. This research design establishes a position by optimizing an exponential moving average (EMA), a relative strength index (RSI), and an average true range (ATR). When the buy and sell signals of the proposed approach are engaged, it also generates signals for a stop-loss order and target price for the position. Additionally, gains and losses for a specific period are represented.
References
[1]
A. K. Singh, J. Patra, M. Chakraborty, and S. Gupta, “Prediction of Indian government stakeholder oil stock prices using hyper parameterized LSTM models,” 2022 Int. Conf. Intell. Controll. Comput. Smart Power, ICICCSP 2022, pp. 1–6, 2022.
[2]
P. Mukherjee, “Monitoring, Recognition and Attendance Automation in Online Class: Combination of Image Processing, Cryptography in IoT Security,” in Proceedings of International Conference on Network Security and Blockchain Technology., Singapore: Springer, 2022, pp. 18–27.
[3]
A. Vashishtha and S. Kumar, “Development of financial derivatives market in India - A case study,” Int. Res. J. Financ. Econ., vol. 37, no. September, pp. 15–29, 2010.
[4]
R. Soujanya, P. Akshith Goud, A. Bhandwalkar, and G. Anil Kumar, “Evaluating future stock value asset using machine learning,” Mater. Today Proc., vol. 33, no. xxxx, pp. 4808–4813, 2020.
[5]
H. M. Maniar, R. Bhatt, and D. M. Maniyar, “‘Expiration hour effect of futures and options markets on stock market’ - A case study on NSE (National Stock Exchange of India),” Int. Rev. Econ. Financ., vol. 18, no. 3, pp. 381–391, 2009.
[6]
Avinash and T. Mallikarjunappa, “Testing the informativeness of non-price variables with MIDAS touch: Informativeness of options open interest and volume,” IIMB Manag. Rev., vol. 32, no. 2, pp. 189–207, 2020.
[7]
A. Gupta and P. Rajib, “Do VaR exceptions have seasonality? An empirical study on Indian commodity spot prices,” IIMB Manag. Rev., vol. 30, no. 4, pp. 369–384, 2018.
[8]
M. S. Abdulla, “SR-BLITS: Sharpe ratio's backward-looking improvement as a trading strategy,” IIMB Manag. Rev., vol. 31, no. 4, pp. 368–373, 2019.
[9]
S. A. Monfared and D. Enke, “Volatility forecasting using a hybrid GJR-GARCH neural network model,” Procedia Comput. Sci., vol. 36, no. C, pp. 246–253, 2014.
[10]
A. Nemeti and B. Denkena, “Stock-market related price determination in consideration of time dynamic cost factors,” Procedia CIRP, vol. 33, pp. 593–598, 2015.
[11]
L. L. Albu, R. Lupu, and A. C. Călin, “Stock Market Asymmetric Volatility and Macroeconomic Dynamics in Central and Eastern Europe,” Procedia Econ. Financ., vol. 22, no. November 2014, pp. 560–567, 2015.
[12]
A. Nayak, M. M. M. Pai, and R. M. Pai, “Prediction Models for Indian Stock Market,” Procedia Comput. Sci., vol. 89, pp. 441–449, 2016.
[13]
M. Saliba, F.Kaddari, A. Elachqar, et E. Elhassouny, and J. Chahwan, “Comparative Study of the IT Teaching/Learning in School Contexts: Lebanese and Moroccan,” Procedia - Soc. Behav. Sci., vol. 116, pp. 4650–4653, 2014.
[14]
V. Singh, S. S. Chen, M. Singhania, B. Nanavati, A. kumar kar, and A. Gupta, “How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda,” Int. J. Inf. Manag. Data Insights, vol. 2, no. 2, p. 100094, 2022.
[15]
B. O. Osu, E. O. Eze, and C. N. Obi, “The impact of stochastic volatility process on the values of assets,” Sci. African, vol. 9, 2020.
[16]
G. Buyukkara, C. C. Kucukozmen, and E. T. Uysal, “Optimal hedge ratios and hedging effectiveness: An analysis of the Turkish futures market,” Borsa Istanbul Rev., vol. 22, no. 1, pp. 92–102, 2022.
[17]
T. Tripathy and L. A. Gil-Alana, “Modelling time-varying volatility in the Indian stock returns: Some empirical evidence,” Rev. Dev. Financ., vol. 5, no. 2, pp. 91–97, 2015.
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Published In
December 2022
749 pages
ISBN:9781450399937
DOI:10.1145/3590837
Copyright © 2022 ACM.
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Published: 30 May 2023
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ICIMMI 2022
ICIMMI 2022: International Conference on Information Management & Machine Intelligence
December 23 - 24, 2022
Jaipur, India
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