Modelling A.I. in Economics

OPEN Opendoor Technologies Inc Common Stock (Forecast)

Outlook: Opendoor Technologies Inc Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 06 Apr 2023 for (n+6 month)
Methodology : Modular Neural Network (DNN Layer)

Abstract

Opendoor Technologies Inc Common Stock prediction model is evaluated with Modular Neural Network (DNN Layer) and ElasticNet Regression1,2,3,4 and it is concluded that the OPEN stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

  1. Market Signals
  2. Is it better to buy and sell or hold?
  3. Is now good time to invest?

OPEN Target Price Prediction Modeling Methodology

We consider Opendoor Technologies Inc Common Stock Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of OPEN 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(ElasticNet 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 (DNN Layer)) X S(n):→ (n+6 month) i = 1 n r i

n:Time series to forecast

p:Price signals of OPEN 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?

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

Sample Set: Neural Network
Stock/Index: OPEN Opendoor Technologies Inc Common Stock
Time series to forecast n: 06 Apr 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 Opendoor Technologies Inc Common Stock

  1. Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.
  2. The characteristics of the hedged item, including how and when the hedged item affects profit or loss, also affect the period over which the forward element of a forward contract that hedges a time-period related hedged item is amortised, which is over the period to which the forward element relates. For example, if a forward contract hedges the exposure to variability in threemonth interest rates for a three-month period that starts in six months' time, the forward element is amortised during the period that spans months seven to nine.
  3. If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
  4. 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.

*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

Opendoor Technologies Inc Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Opendoor Technologies Inc Common Stock prediction model is evaluated with Modular Neural Network (DNN Layer) and ElasticNet Regression1,2,3,4 and it is concluded that the OPEN stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

OPEN Opendoor Technologies Inc Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2C
Balance SheetCC
Leverage RatiosCaa2Ba3
Cash FlowBaa2Caa2
Rates of Return and ProfitabilityCaa2Ba1

*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: 86 out of 100 with 770 signals.

References

  1. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
  2. Li L, Chen S, Kleban J, Gupta A. 2014. Counterfactual estimation and optimization of click metrics for search engines: a case study. In Proceedings of the 24th International Conference on the World Wide Web, pp. 929–34. New York: ACM
  3. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
  4. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
  5. T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
  6. Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
  7. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
Frequently Asked QuestionsQ: What is the prediction methodology for OPEN stock?
A: OPEN stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and ElasticNet Regression
Q: Is OPEN stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes OPEN Stock.
Q: Is Opendoor Technologies Inc Common Stock stock a good investment?
A: The consensus rating for Opendoor Technologies Inc Common Stock is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of OPEN stock?
A: The consensus rating for OPEN is Wait until speculative trend diminishes.
Q: What is the prediction period for OPEN stock?
A: The prediction period for OPEN is (n+6 month)

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