Modelling A.I. in Economics

What is NSE TATACONSUM stock prediction? (Forecast)

It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. We evaluate TATA CONSUMER PRODUCTS LIMITED prediction models with Multi-Task Learning (ML) and Sign Test1,2,3,4 and conclude that the NSE TATACONSUM 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 TATACONSUM stock.


Keywords: NSE TATACONSUM, TATA CONSUMER PRODUCTS LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Market Outlook
  2. What is Markov decision process in reinforcement learning?
  3. What is the best way to predict stock prices?

NSE TATACONSUM Target Price Prediction Modeling Methodology

As stock data is characterized by highly noisy and non-stationary, stock price prediction is regarded as a knotty problem. In this paper, we propose new two-stage ensemble models by combining empirical mode decomposition (EMD) (or variational mode decomposition (VMD)), extreme learning machine (ELM) and improved harmony search (IHS) algorithm for stock price prediction, which are respectively named EMD–ELM–IHS and VMD–ELM–IHS. We consider TATA CONSUMER PRODUCTS LIMITED Stock Decision Process with Sign Test where A is the set of discrete actions of NSE TATACONSUM 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(Sign Test)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Multi-Task Learning (ML)) X S(n):→ (n+6 month) r s rs

n:Time series to forecast

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


Sample Set: Neural Network
Stock/Index: NSE TATACONSUM TATA CONSUMER PRODUCTS LIMITED
Time series to forecast n: 09 Nov 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE TATACONSUM 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 TATA CONSUMER PRODUCTS LIMITED

  1. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
  2. The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
  3. If a financial instrument that was previously recognised as a financial asset is measured at fair value through profit or loss and its fair value decreases below zero, it is a financial liability measured in accordance with paragraph 4.2.1. However, hybrid contracts with hosts that are assets within the scope of this Standard are always measured in accordance with paragraph 4.3.2.
  4. An entity must look through until it can identify the underlying pool of instruments that are creating (instead of passing through) the cash flows. This is the underlying pool of financial instruments.

*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

TATA CONSUMER PRODUCTS LIMITED assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Sign Test1,2,3,4 and conclude that the NSE TATACONSUM 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 TATACONSUM stock.

Financial State Forecast for NSE TATACONSUM TATA CONSUMER PRODUCTS LIMITED Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B1
Operational Risk 3671
Market Risk7849
Technical Analysis7459
Fundamental Analysis8571
Risk Unsystematic3345

Prediction Confidence Score

Trust metric by Neural Network: 92 out of 100 with 577 signals.

References

  1. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
  2. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
  3. Abadie A, Diamond A, Hainmueller J. 2015. Comparative politics and the synthetic control method. Am. J. Political Sci. 59:495–510
  4. Mnih A, Teh YW. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pp. 419–26. La Jolla, CA: Int. Mach. Learn. Soc.
  5. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  6. 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.
  7. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
Frequently Asked QuestionsQ: What is the prediction methodology for NSE TATACONSUM stock?
A: NSE TATACONSUM stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Sign Test
Q: Is NSE TATACONSUM stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE TATACONSUM Stock.
Q: Is TATA CONSUMER PRODUCTS LIMITED stock a good investment?
A: The consensus rating for TATA CONSUMER PRODUCTS LIMITED is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of NSE TATACONSUM stock?
A: The consensus rating for NSE TATACONSUM is Hold.
Q: What is the prediction period for NSE TATACONSUM stock?
A: The prediction period for NSE TATACONSUM is (n+6 month)

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