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 India Tourism Development Corporation Limited prediction models with Inductive Learning (ML) and Beta ^{1,2,3,4} and conclude that the NSE ITDC stock is predictable in the short/long term. **

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold NSE ITDC stock.**

**NSE ITDC, India Tourism Development Corporation Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Probability Distribution
- Can statistics predict the future?
- Short/Long Term Stocks

## NSE ITDC Target Price Prediction Modeling Methodology

Stock market forecasting is considered to be a challenging topic among time series forecasting. This study proposes a novel two-stage ensemble machine learning model named SVR-ENANFIS for stock price prediction by combining features of support vector regression (SVR) and ensemble adaptive neuro fuzzy inference system (ENANFIS). We consider India Tourism Development Corporation Limited Stock Decision Process with Beta where A is the set of discrete actions of NSE ITDC 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Inductive Learning (ML)) X S(n):→ (n+1 year) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of NSE ITDC 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 ITDC Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**NSE ITDC India Tourism Development Corporation Limited

**Time series to forecast n: 02 Oct 2022**for (n+1 year)

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold NSE ITDC 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

India Tourism Development Corporation Limited assigned short-term Ba2 & long-term Baa2 forecasted stock rating.** We evaluate the prediction models Inductive Learning (ML) with Beta ^{1,2,3,4} and conclude that the NSE ITDC stock is predictable in the short/long term.**

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold NSE ITDC stock.**

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

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

Outlook* | Ba2 | Baa2 |

Operational Risk | 90 | 78 |

Market Risk | 57 | 76 |

Technical Analysis | 69 | 84 |

Fundamental Analysis | 69 | 65 |

Risk Unsystematic | 55 | 80 |

### Prediction Confidence Score

## References

- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
- L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
- Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
- Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
- Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016

## Frequently Asked Questions

Q: What is the prediction methodology for NSE ITDC stock?A: NSE ITDC stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Beta

Q: Is NSE ITDC stock a buy or sell?

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

Q: Is India Tourism Development Corporation Limited stock a good investment?

A: The consensus rating for India Tourism Development Corporation Limited is Hold and assigned short-term Ba2 & long-term Baa2 forecasted stock rating.

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

A: The consensus rating for NSE ITDC is Hold.

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

A: The prediction period for NSE ITDC is (n+1 year)

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