Short-term trading is a difficult task due to fluctuating demand and supply in the stock market. These demands and supply are reflected in stock prices. The stock prices may be predicted using technical indicators. Most of the existing literature considered the limited technical indicators to measure short-term prices. We have considered 82 different combinations of technical indicators to predict the stock prices. ** We evaluate Bandhan Bank Limited prediction models with Modular Neural Network (Market Direction Analysis) and Beta ^{1,2,3,4} and conclude that the NSE BANDHANBNK stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE BANDHANBNK stock.**

**NSE BANDHANBNK, Bandhan Bank Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Which neural network is best for prediction?
- How do you decide buy or sell a stock?
- What is statistical models in machine learning?

## NSE BANDHANBNK Target Price Prediction Modeling Methodology

In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. We consider Bandhan Bank Limited Stock Decision Process with Beta where A is the set of discrete actions of NSE BANDHANBNK 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(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+3 month) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of NSE BANDHANBNK 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 BANDHANBNK Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**NSE BANDHANBNK Bandhan Bank Limited

**Time series to forecast n: 03 Oct 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE BANDHANBNK 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

Bandhan Bank Limited assigned short-term Ba3 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Beta ^{1,2,3,4} and conclude that the NSE BANDHANBNK stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE BANDHANBNK stock.**

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

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

Outlook* | Ba3 | Ba1 |

Operational Risk | 77 | 70 |

Market Risk | 80 | 87 |

Technical Analysis | 31 | 68 |

Fundamental Analysis | 53 | 54 |

Risk Unsystematic | 83 | 69 |

### Prediction Confidence Score

## References

- G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
- Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
- Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
- Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
- V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.

## Frequently Asked Questions

Q: What is the prediction methodology for NSE BANDHANBNK stock?A: NSE BANDHANBNK stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Beta

Q: Is NSE BANDHANBNK stock a buy or sell?

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

Q: Is Bandhan Bank Limited stock a good investment?

A: The consensus rating for Bandhan Bank Limited is Hold and assigned short-term Ba3 & long-term Ba1 forecasted stock rating.

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

A: The consensus rating for NSE BANDHANBNK is Hold.

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

A: The prediction period for NSE BANDHANBNK is (n+3 month)

- Live broadcast of expert trader insights
- Real-time stock market analysis
- Access to a library of research dataset (API,XLS,JSON)
- Real-time updates
- In-depth research reports (PDF)