## Summary

This paper proposes genetic algorithms (GAs) approach to feature discretization and the determination of connection weights for artificial neural networks (ANNs) to predict the stock price index. Previous research proposed many hybrid models of ANN and GA for the method of training the network, feature subset selection, and topology optimization.** We evaluate Hindustan Unilever Limited prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Multiple Regression ^{1,2,3,4} and conclude that the NSE HINDUNILVR 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 HINDUNILVR stock.**

## Key Points

- What are main components of Markov decision process?
- Buy, Sell and Hold Signals
- What are buy sell or hold recommendations?

## NSE HINDUNILVR Target Price Prediction Modeling Methodology

We consider Hindustan Unilever Limited Stock Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of NSE HINDUNILVR 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(Multiple 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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+1 year) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of NSE HINDUNILVR stock

j:Nash equilibria (Neural Network)

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 HINDUNILVR Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**NSE HINDUNILVR Hindustan Unilever Limited

**Time series to forecast n: 20 Nov 2022**for (n+1 year)

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

## Adjusted IFRS* Prediction Methods for Hindustan Unilever Limited

- For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.
- The purpose of estimating expected credit losses is neither to estimate a worstcase scenario nor to estimate the best-case scenario. Instead, an estimate of expected credit losses shall always reflect the possibility that a credit loss occurs and the possibility that no credit loss occurs even if the most likely outcome is no credit loss.
- If a call option right retained by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the asset continues to be measured at its fair value. The associated liability is measured at (i) the option exercise price less the time value of the option if the option is in or at the money, or (ii) the fair value of the transferred asset less the time value of the option if the option is out of the money. The adjustment to the measurement of the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the call option right. For example, if the fair value of the underlying asset is CU80, the option exercise price is CU95 and the time value of the option is CU5, the carrying amount of the associated liability is CU75 (CU80 – CU5) and the carrying amount of the transferred asset is CU80 (ie its fair value)
- An entity shall apply this Standard for annual periods beginning on or after 1 January 2018. Earlier application is permitted. If an entity elects to apply this Standard early, it must disclose that fact and apply all of the requirements in this Standard at the same time (but see also paragraphs 7.1.2, 7.2.21 and 7.3.2). It shall also, at the same time, apply the amendments in Appendix C.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Hindustan Unilever Limited assigned short-term B2 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Multiple Regression ^{1,2,3,4} and conclude that the NSE HINDUNILVR 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 HINDUNILVR stock.**

### Financial State Forecast for NSE HINDUNILVR Hindustan Unilever Limited Stock Options & Futures

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

Outlook* | B2 | Ba3 |

Operational Risk | 56 | 51 |

Market Risk | 61 | 74 |

Technical Analysis | 35 | 47 |

Fundamental Analysis | 82 | 70 |

Risk Unsystematic | 30 | 65 |

### Prediction Confidence Score

## References

- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
- Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
- 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
- H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.

## Frequently Asked Questions

Q: What is the prediction methodology for NSE HINDUNILVR stock?A: NSE HINDUNILVR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Multiple Regression

Q: Is NSE HINDUNILVR stock a buy or sell?

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

Q: Is Hindustan Unilever Limited stock a good investment?

A: The consensus rating for Hindustan Unilever Limited is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.

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

A: The consensus rating for NSE HINDUNILVR is Hold.

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

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

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