Modelling A.I. in Economics

LON:RESI RESIDENTIAL SECURE INCOME PLC (Forecast)

Outlook: RESIDENTIAL SECURE INCOME PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 22 Apr 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

RESIDENTIAL SECURE INCOME PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Multiple Regression1,2,3,4 and it is concluded that the LON:RESI stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

Key Points

  1. Market Signals
  2. How do you decide buy or sell a stock?
  3. Understanding Buy, Sell, and Hold Ratings

LON:RESI Target Price Prediction Modeling Methodology

We consider RESIDENTIAL SECURE INCOME PLC Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:RESI 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(Multiple 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(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+8 weeks) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of LON:RESI 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:RESI Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: LON:RESI RESIDENTIAL SECURE INCOME PLC
Time series to forecast n: 22 Apr 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

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 RESIDENTIAL SECURE INCOME PLC

  1. When an entity, consistent with its hedge documentation, frequently resets (ie discontinues and restarts) a hedging relationship because both the hedging instrument and the hedged item frequently change (ie the entity uses a dynamic process in which both the hedged items and the hedging instruments used to manage that exposure do not remain the same for long), the entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component is separately identifiable—only when it initially designates a hedged item in that hedging relationship. A hedged item that has been assessed at the time of its initial designation in the hedging relationship, whether it was at the time of the hedge inception or subsequently, is not reassessed at any subsequent redesignation in the same hedging relationship.
  2. In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.
  3. The fact that a derivative is in or out of the money when it is designated as a hedging instrument does not in itself mean that a qualitative assessment is inappropriate. It depends on the circumstances whether hedge ineffectiveness arising from that fact could have a magnitude that a qualitative assessment would not adequately capture.
  4. If the group of items does have offsetting risk positions (for example, a group of sales and expenses denominated in a foreign currency hedged together for foreign currency risk) then an entity shall present the hedging gains or losses in a separate line item in the statement of profit or loss and other comprehensive income. Consider, for example, a hedge of the foreign currency risk of a net position of foreign currency sales of FC100 and foreign currency expenses of FC80 using a forward exchange contract for FC20. The gain or loss on the forward exchange contract that is reclassified from the cash flow hedge reserve to profit or loss (when the net position affects profit or loss) shall be presented in a separate line item from the hedged sales and expenses. Moreover, if the sales occur in an earlier period than the expenses, the sales revenue is still measured at the spot exchange rate in accordance with IAS 21. The related hedging gain or loss is presented in a separate line item, so that profit or loss reflects the effect of hedging the net position, with a corresponding adjustment to the cash flow hedge reserve. When the hedged expenses affect profit or loss in a later period, the hedging gain or loss previously recognised in the cash flow hedge reserve on the sales is reclassified to profit or loss and presented as a separate line item from those that include the hedged expenses, which are measured at the spot exchange rate in accordance with IAS 21.

*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

RESIDENTIAL SECURE INCOME PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. RESIDENTIAL SECURE INCOME PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Multiple Regression1,2,3,4 and it is concluded that the LON:RESI stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

LON:RESI RESIDENTIAL SECURE INCOME PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2C
Balance SheetBa1C
Leverage RatiosBaa2Caa2
Cash FlowB3B3
Rates of Return and ProfitabilityB3C

*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: 74 out of 100 with 741 signals.

References

  1. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
  2. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. The Dow Jones Industrial Average (No. Stock Analysis). AC Investment Research.
  3. Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
  4. Harris ZS. 1954. Distributional structure. Word 10:146–62
  5. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
  6. Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
  7. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
Frequently Asked QuestionsQ: What is the prediction methodology for LON:RESI stock?
A: LON:RESI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Multiple Regression
Q: Is LON:RESI stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:RESI Stock.
Q: Is RESIDENTIAL SECURE INCOME PLC stock a good investment?
A: The consensus rating for RESIDENTIAL SECURE INCOME PLC is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:RESI stock?
A: The consensus rating for LON:RESI is Buy.
Q: What is the prediction period for LON:RESI stock?
A: The prediction period for LON:RESI is (n+8 weeks)

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