Asian Hotels (East) Limited Stock Forecast, Price & Rating (NSE AHLEAST)

Prediction of future movement of stock prices has been a subject matter of many research work. There is a gamut of literature of technical analysis of stock prices where the objective is to identify patterns in stock price movements and derive profit from it. Improving the prediction accuracy remains the single most challenge in this area of research. We propose a hybrid approach for stock price movement prediction using machine learning, deep learning, and natural language processing. We evaluate Asian Hotels (East) Limited prediction models with Modular Neural Network (Market Direction Analysis) and Logistic Regression^1,2,3,4 and conclude that the NSE AHLEAST 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 Hold NSE AHLEAST stock.

Keywords: NSE AHLEAST, Asian Hotels (East) Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Can statistics predict the future?
2. How do you know when a stock will go up or down?
3. Understanding Buy, Sell, and Hold Ratings

NSE AHLEAST Target Price Prediction Modeling Methodology

Impact of many factors on the stock prices makes the stock prediction a difficult and highly complicated task. In this paper, machine learning techniques have been applied for the stock price prediction in order to overcome such difficulties. In the implemented work, five models have been developed and their performances are compared in predicting the stock market trends. We consider Asian Hotels (East) Limited Stock Decision Process with Logistic Regression where A is the set of discrete actions of NSE AHLEAST 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(Logistic Regression)^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(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: NSE AHLEAST Asian Hotels (East) Limited
Time series to forecast n: 02 Oct 2022 for (n+16 weeks)

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

Asian Hotels (East) Limited assigned short-term Ba3 & long-term Ba1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Logistic Regression^1,2,3,4 and conclude that the NSE AHLEAST 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 Hold NSE AHLEAST stock.

Financial State Forecast for NSE AHLEAST Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	Ba1
Operational Risk	74	62
Market Risk	65	88
Technical Analysis	52	60
Fundamental Analysis	53	67
Risk Unsystematic	72	73

Prediction Confidence Score

Trust metric by Neural Network: 91 out of 100 with 530 signals.

References

1. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
2. N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
3. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
4. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
5. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
6. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
7. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99

Frequently Asked Questions

Q: What is the prediction methodology for NSE AHLEAST stock?
A: NSE AHLEAST stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Logistic Regression
Q: Is NSE AHLEAST stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE AHLEAST Stock.
Q: Is Asian Hotels (East) Limited stock a good investment?
A: The consensus rating for Asian Hotels (East) Limited is Hold and assigned short-term Ba3 & long-term Ba1 forecasted stock rating.
Q: What is the consensus rating of NSE AHLEAST stock?
A: The consensus rating for NSE AHLEAST is Hold.
Q: What is the prediction period for NSE AHLEAST stock?
A: The prediction period for NSE AHLEAST is (n+16 weeks)

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