Modelling A.I. in Economics

EEX Emerald Holding Inc. Common Stock

Outlook: Emerald Holding Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 05 Mar 2023 for (n+6 month)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Emerald Holding Inc. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the EEX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

Key Points

  1. Trading Interaction
  2. Can stock prices be predicted?
  3. Market Outlook

EEX Target Price Prediction Modeling Methodology

We consider Emerald Holding Inc. Common Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of EEX 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(Statistical Hypothesis Testing)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(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+6 month) e x rx

n:Time series to forecast

p:Price signals of EEX 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?

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

Sample Set: Neural Network
Stock/Index: EEX Emerald Holding Inc. Common Stock
Time series to forecast n: 05 Mar 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

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 (Grey to Black): *Technical Analysis%

IFRS Reconciliation Adjustments for Emerald Holding Inc. Common Stock

  1. Paragraph 6.3.6 states that in consolidated financial statements the foreign currency risk of a highly probable forecast intragroup transaction may qualify as a hedged item in a cash flow hedge, provided that the transaction is denominated in a currency other than the functional currency of the entity entering into that transaction and that the foreign currency risk will affect consolidated profit or loss. For this purpose an entity can be a parent, subsidiary, associate, joint arrangement or branch. If the foreign currency risk of a forecast intragroup transaction does not affect consolidated profit or loss, the intragroup transaction cannot qualify as a hedged item. This is usually the case for royalty payments, interest payments or management charges between members of the same group, unless there is a related external transaction. However, when the foreign currency risk of a forecast intragroup transaction will affect consolidated profit or loss, the intragroup transaction can qualify as a hedged item. An example is forecast sales or purchases of inventories between members of the same group if there is an onward sale of the inventory to a party external to the group. Similarly, a forecast intragroup sale of plant and equipment from the group entity that manufactured it to a group entity that will use the plant and equipment in its operations may affect consolidated profit or loss. This could occur, for example, because the plant and equipment will be depreciated by the purchasing entity and the amount initially recognised for the plant and equipment may change if the forecast intragroup transaction is denominated in a currency other than the functional currency of the purchasing entity.
  2. If the holder cannot assess the conditions in paragraph B4.1.21 at initial recognition, the tranche must be measured at fair value through profit or loss. If the underlying pool of instruments can change after initial recognition in such a way that the pool may not meet the conditions in paragraphs B4.1.23–B4.1.24, the tranche does not meet the conditions in paragraph B4.1.21 and must be measured at fair value through profit or loss. However, if the underlying pool includes instruments that are collateralised by assets that do not meet the conditions in paragraphs B4.1.23–B4.1.24, the ability to take possession of such assets shall be disregarded for the purposes of applying this paragraph unless the entity acquired the tranche with the intention of controlling the collateral.
  3. As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.
  4. An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

Conclusions

Emerald Holding Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Emerald Holding Inc. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the EEX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

EEX Emerald Holding Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa1Baa2
Balance SheetB2B2
Leverage RatiosBaa2Ba3
Cash FlowB1C
Rates of Return and ProfitabilityBa1C

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 821 signals.

References

  1. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
  2. Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
  3. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
  4. Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
  5. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
  6. S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
  7. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
Frequently Asked QuestionsQ: What is the prediction methodology for EEX stock?
A: EEX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Statistical Hypothesis Testing
Q: Is EEX stock a buy or sell?
A: The dominant strategy among neural network is to Sell EEX Stock.
Q: Is Emerald Holding Inc. Common Stock stock a good investment?
A: The consensus rating for Emerald Holding Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of EEX stock?
A: The consensus rating for EEX is Sell.
Q: What is the prediction period for EEX stock?
A: The prediction period for EEX is (n+6 month)

Premium

  • 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)

Login
This project is licensed under the license; additional terms may apply.