Buy, sell or hold: NSE OIL Stock Forecast

Prediction of future movement of stock prices has been a subject matter of many research work. In this work, we propose a hybrid approach for stock price prediction using machine learning and deep learning-based methods. We evaluate Oil India Limited prediction models with Ensemble Learning (ML) and Paired T-Test^1,2,3,4 and conclude that the NSE OIL stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE OIL stock.

Keywords: NSE OIL, Oil India Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. What is prediction in deep learning?
2. Is now good time to invest?
3. What statistical methods are used to analyze data?

NSE OIL Target Price Prediction Modeling Methodology

The stock market prediction has attracted much attention from academia as well as business. Due to the non-linear, volatile and complex nature of the market, it is quite difficult to predict. As the stock markets grow bigger, more investors pay attention to develop a systematic approach to predict the stock market. We consider Oil India Limited Stock Decision Process with Paired T-Test where A is the set of discrete actions of NSE OIL stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.^1,2,3,4

F(Paired T-Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Ensemble Learning (ML)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of NSE OIL stock

j:Nash equilibria

k:Dominated move

a:Best response for target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do AC Investment Research machine learning (predictive) algorithms actually work?

NSE OIL Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: NSE OIL Oil India Limited
Time series to forecast n: 27 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE OIL stock.

X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)

Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)

Z axis (Yellow to Green): *Technical Analysis%

Conclusions

Oil India Limited assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Paired T-Test^1,2,3,4 and conclude that the NSE OIL stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE OIL stock.

Financial State Forecast for NSE OIL Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Ba3
Operational Risk	41	49
Market Risk	32	73
Technical Analysis	66	48
Fundamental Analysis	83	76
Risk Unsystematic	38	85

Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 679 signals.

References

1. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
2. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
3. Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
4. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
5. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
6. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
7. Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67

Frequently Asked Questions

Q: What is the prediction methodology for NSE OIL stock?
A: NSE OIL stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Paired T-Test
Q: Is NSE OIL stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE OIL Stock.
Q: Is Oil India Limited stock a good investment?
A: The consensus rating for Oil India Limited is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE OIL stock?
A: The consensus rating for NSE OIL is Hold.
Q: What is the prediction period for NSE OIL stock?
A: The prediction period for NSE OIL is (n+6 month)

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