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 evaluate Indiabulls Real Estate Limited prediction models with Modular Neural Network (Market News Sentiment Analysis) and Lasso Regression ^{1,2,3,4} and conclude that the NSE IBREALEST 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 IBREALEST stock.**

**NSE IBREALEST, Indiabulls Real Estate Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Market Risk
- What is neural prediction?
- What is the use of Markov decision process?

## NSE IBREALEST Target Price Prediction Modeling Methodology

Stock market investment strategies are complex and rely on an evaluation of vast amounts of data. In recent years, machine learning techniques have increasingly been examined to assess whether they can improve market forecasting when compared with traditional approaches. The objective for this study is to identify directions for future machine learning stock market prediction research based upon a review of current literature. We consider Indiabulls Real Estate Limited Stock Decision Process with Lasso Regression where A is the set of discrete actions of NSE IBREALEST 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(Lasso Regression)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of NSE IBREALEST 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 IBREALEST Stock Forecast (Buy or Sell) for (n+6 month)

**Sample Set:**Neural Network

**Stock/Index:**NSE IBREALEST Indiabulls Real Estate Limited

**Time series to forecast n: 30 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 IBREALEST 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

Indiabulls Real Estate Limited assigned short-term Baa2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Lasso Regression ^{1,2,3,4} and conclude that the NSE IBREALEST 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 IBREALEST stock.**

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

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Baa2 | B2 |

Operational Risk | 72 | 75 |

Market Risk | 81 | 82 |

Technical Analysis | 73 | 41 |

Fundamental Analysis | 89 | 33 |

Risk Unsystematic | 56 | 42 |

### Prediction Confidence Score

## References

- Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
- G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
- Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
- Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
- R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
- Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66

## Frequently Asked Questions

Q: What is the prediction methodology for NSE IBREALEST stock?A: NSE IBREALEST stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Lasso Regression

Q: Is NSE IBREALEST stock a buy or sell?

A: The dominant strategy among neural network is to Hold NSE IBREALEST Stock.

Q: Is Indiabulls Real Estate Limited stock a good investment?

A: The consensus rating for Indiabulls Real Estate Limited is Hold and assigned short-term Baa2 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of NSE IBREALEST stock?

A: The consensus rating for NSE IBREALEST is Hold.

Q: What is the prediction period for NSE IBREALEST stock?

A: The prediction period for NSE IBREALEST is (n+6 month)