Modelling A.I. in Economics

KKO KINETIKO ENERGY LTD (Forecast)

KINETIKO ENERGY LTD Research Report

Abstract

Outlook: KINETIKO ENERGY LTD assigned short-term B1 & long-term Caa1 forecasted stock rating.
Signal: Buy
Time series to forecast n: 05 Dec 2022 for (n+6 month)

In today's economy, there is a profound impact of the stock market or equity market. Prediction of stock prices is extremely complex, chaotic, and the presence of a dynamic environment makes it a great challenge. Behavioural finance suggests that decision-making process of investors is to a very great extent influenced by the emotions and sentiments in response to a particular news. Thus, to support the decisions of the investors, we have presented an approach combining two distinct fields for analysis of stock exchange. (Dase, R.K. and Pawar, D.D., 2010. Application of Artificial Neural Network for stock market predictions: A review of literature. International Journal of Machine Intelligence, 2(2), pp.14-17.) We evaluate KINETIKO ENERGY LTD prediction models with Ensemble Learning (ML) and Paired T-Test1,2,3,4 and conclude that the KKO 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 Buy KKO stock.

Key Points

  1. How accurate is machine learning in stock market?
  2. Market Outlook
  3. Nash Equilibria

KKO Target Price Prediction Modeling Methodology

We consider KINETIKO ENERGY LTD Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of KKO 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(Paired T-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(Ensemble Learning (ML)) X S(n):→ (n+6 month) r s rs

n:Time series to forecast

p:Price signals of KKO 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?

KKO Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: KKO KINETIKO ENERGY LTD
Time series to forecast n: 05 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy KKO 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 KINETIKO ENERGY LTD

  1. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
  2. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.
  3. For the purpose of applying paragraphs B4.1.11(b) and B4.1.12(b), irrespective of the event or circumstance that causes the early termination of the contract, a party may pay or receive reasonable compensation for that early termination. For example, a party may pay or receive reasonable compensation when it chooses to terminate the contract early (or otherwise causes the early termination to occur).
  4. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).

*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

KINETIKO ENERGY LTD assigned short-term B1 & long-term Caa1 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Paired T-Test1,2,3,4 and conclude that the KKO 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 Buy KKO stock.

Financial State Forecast for KKO KINETIKO ENERGY LTD Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Caa1
Operational Risk 6536
Market Risk5830
Technical Analysis6138
Fundamental Analysis6044
Risk Unsystematic4730

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 570 signals.

References

  1. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
  2. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
  3. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
  4. A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
  5. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
  6. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
  7. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
Frequently Asked QuestionsQ: What is the prediction methodology for KKO stock?
A: KKO stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Paired T-Test
Q: Is KKO stock a buy or sell?
A: The dominant strategy among neural network is to Buy KKO Stock.
Q: Is KINETIKO ENERGY LTD stock a good investment?
A: The consensus rating for KINETIKO ENERGY LTD is Buy and assigned short-term B1 & long-term Caa1 forecasted stock rating.
Q: What is the consensus rating of KKO stock?
A: The consensus rating for KKO is Buy.
Q: What is the prediction period for KKO stock?
A: The prediction period for KKO is (n+6 month)

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