Can neural networks predict stock market? (CTSH Stock Forecast)

This study aims to predict the direction of stock prices by integrating time-varying effective transfer entropy (ETE) and various machine learning algorithms. At first, we explore that the ETE based on 3 and 6 months moving windows can be regarded as the market explanatory variable by analyzing the association between the financial crises and Granger-causal relationships among the stocks. We evaluate Cognizant prediction models with Transfer Learning (ML) and Ridge Regression1,2,3,4 and conclude that the CTSH stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Sell CTSH stock.


Keywords: CTSH, Cognizant, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. What is the use of Markov decision process?
  2. What are buy sell or hold recommendations?
  3. What is the use of Markov decision process?

CTSH Target Price Prediction Modeling Methodology

In modern financial market, the most crucial problem is to find essential approach to outline and visualizing the predictions in stock-markets to be made by individuals in order to attain maximum profit by investments. The stock market is a transformative, non-straight dynamical and complex system. Long term investment is one of the major investment decisions. Though, evaluating shares and calculating elementary values for companies for long term investment is difficult. In this paper we are going to present comparison of machine learning aided algorithms to evaluate the stock prices in the future to analyze market behaviour. We consider Cognizant Stock Decision Process with Ridge Regression where A is the set of discrete actions of CTSH 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(Ridge Regression)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(Transfer Learning (ML)) X S(n):→ (n+8 weeks) i = 1 n s i

n:Time series to forecast

p:Price signals of CTSH 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?

CTSH Stock Forecast (Buy or Sell) for (n+8 weeks)


Sample Set: Neural Network
Stock/Index: CTSH Cognizant
Time series to forecast n: 11 Nov 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Sell CTSH 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 Cognizant

  1. In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.
  2. An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
  3. Changes in market conditions that give rise to market risk include changes in a benchmark interest rate, the price of another entity's financial instrument, a commodity price, a foreign exchange rate or an index of prices or rates.
  4. Despite the requirement in paragraph 7.2.1, an entity that adopts the classification and measurement requirements of this Standard (which include the requirements related to amortised cost measurement for financial assets and impairment in Sections 5.4 and 5.5) shall provide the disclosures set out in paragraphs 42L–42O of IFRS 7 but need not restate prior periods. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application. However, if an entity restates prior periods, the restated financial statements must reflect all of the requirements in this Standard. If an entity's chosen approach to applying IFRS 9 results in more than one date of initial application for different requirements, this paragraph applies at each date of initial application (see paragraph 7.2.2). This would be the case, for example, if an entity elects to early apply only the requirements for the presentation of gains and losses on financial liabilities designated as at fair value through profit or loss in accordance with paragraph 7.1.2 before applying the other requirements in this Standard.

*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

Cognizant assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Ridge Regression1,2,3,4 and conclude that the CTSH stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Sell CTSH stock.

Financial State Forecast for CTSH Cognizant Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Operational Risk 8776
Market Risk6049
Technical Analysis6365
Fundamental Analysis4460
Risk Unsystematic6875

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 878 signals.

References

  1. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
  2. Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
  3. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
  4. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
  5. A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
  6. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
  7. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
Frequently Asked QuestionsQ: What is the prediction methodology for CTSH stock?
A: CTSH stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Ridge Regression
Q: Is CTSH stock a buy or sell?
A: The dominant strategy among neural network is to Sell CTSH Stock.
Q: Is Cognizant stock a good investment?
A: The consensus rating for Cognizant is Sell and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of CTSH stock?
A: The consensus rating for CTSH is Sell.
Q: What is the prediction period for CTSH stock?
A: The prediction period for CTSH is (n+8 weeks)

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