Stock market trading is an activity in which investors need fast and accurate information to make effective decisions. Since many stocks are traded on a stock exchange, numerous factors influence the decision-making process. Moreover, the behaviour of stock prices is uncertain and hard to predict. For these reasons, stock price prediction is an important process and a challenging one. We evaluate Avenue Supermarts Limited prediction models with Modular Neural Network (Market Direction Analysis) and Beta1,2,3,4 and conclude that the NSE DMART stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy NSE DMART stock.

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

## Key Points

1. Can neural networks predict stock market?
2. What is the use of Markov decision process?
3. What is a prediction confidence? ## NSE DMART Target Price Prediction Modeling Methodology

Data mining and machine learning approaches can be incorporated into business intelligence (BI) systems to help users for decision support in many real-life applications. Here, in this paper, we propose a machine learning approach for BI applications. Specifically, we apply structural support vector machines (SSVMs) to perform classification on complex inputs such as the nodes of a graph structure. We consider Avenue Supermarts Limited Stock Decision Process with Beta where A is the set of discrete actions of NSE DMART 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(Beta)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+16 weeks) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of NSE DMART 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 DMART Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: NSE DMART Avenue Supermarts Limited
Time series to forecast n: 29 Sep 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy NSE DMART 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

Avenue Supermarts Limited assigned short-term B1 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Beta1,2,3,4 and conclude that the NSE DMART stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy NSE DMART stock.

### Financial State Forecast for NSE DMART Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B3
Operational Risk 8154
Market Risk6131
Technical Analysis3633
Fundamental Analysis7559
Risk Unsystematic6049

### Prediction Confidence Score

Trust metric by Neural Network: 87 out of 100 with 547 signals.

## References

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3. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
4. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
5. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
6. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
7. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
Frequently Asked QuestionsQ: What is the prediction methodology for NSE DMART stock?
A: NSE DMART stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Beta
Q: Is NSE DMART stock a buy or sell?
A: The dominant strategy among neural network is to Buy NSE DMART Stock.
Q: Is Avenue Supermarts Limited stock a good investment?
A: The consensus rating for Avenue Supermarts Limited is Buy and assigned short-term B1 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of NSE DMART stock?
A: The consensus rating for NSE DMART is Buy.
Q: What is the prediction period for NSE DMART stock?
A: The prediction period for NSE DMART is (n+16 weeks)