Modelling A.I. in Economics

LON:DGI9 DIGITAL 9 INFRASTRUCTURE PLC

Outlook: DIGITAL 9 INFRASTRUCTURE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 24 Apr 2023 for (n+6 month)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

DIGITAL 9 INFRASTRUCTURE PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Factor1,2,3,4 and it is concluded that the LON:DGI9 stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

Key Points

  1. Buy, Sell and Hold Signals
  2. Should I buy stocks now or wait amid such uncertainty?
  3. Can statistics predict the future?

LON:DGI9 Target Price Prediction Modeling Methodology

We consider DIGITAL 9 INFRASTRUCTURE PLC Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:DGI9 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(Factor)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 (Market Volatility Analysis)) X S(n):→ (n+6 month) R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of LON:DGI9 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?

LON:DGI9 Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:DGI9 DIGITAL 9 INFRASTRUCTURE PLC
Time series to forecast n: 24 Apr 2023 for (n+6 month)

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

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 DIGITAL 9 INFRASTRUCTURE PLC

  1. At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.
  2. Rebalancing does not apply if the risk management objective for a hedging relationship has changed. Instead, hedge accounting for that hedging relationship shall be discontinued (despite that an entity might designate a new hedging relationship that involves the hedging instrument or hedged item of the previous hedging relationship as described in paragraph B6.5.28).
  3. 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).
  4. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary

*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

DIGITAL 9 INFRASTRUCTURE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. DIGITAL 9 INFRASTRUCTURE PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Factor1,2,3,4 and it is concluded that the LON:DGI9 stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

LON:DGI9 DIGITAL 9 INFRASTRUCTURE PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2B1
Balance SheetCCaa2
Leverage RatiosBaa2C
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBa1Ba3

*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: 91 out of 100 with 535 signals.

References

  1. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
  2. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
  3. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
  4. J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
  5. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
  6. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
  7. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
Frequently Asked QuestionsQ: What is the prediction methodology for LON:DGI9 stock?
A: LON:DGI9 stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Factor
Q: Is LON:DGI9 stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:DGI9 Stock.
Q: Is DIGITAL 9 INFRASTRUCTURE PLC stock a good investment?
A: The consensus rating for DIGITAL 9 INFRASTRUCTURE PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:DGI9 stock?
A: The consensus rating for LON:DGI9 is Hold.
Q: What is the prediction period for LON:DGI9 stock?
A: The prediction period for LON:DGI9 is (n+6 month)



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