Modelling A.I. in Economics

NYCB Stock: A Risky Investment, But One with a lot of Potential (Forecast)

Outlook: New York Community Bancorp Inc. Common Stock is assigned short-term Ba3 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (CNN Layer)
Hypothesis Testing : Multiple Regression
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.


New York Community Bancorp Inc. Common Stock prediction model is evaluated with Modular Neural Network (CNN Layer) and Multiple Regression1,2,3,4 and it is concluded that the NYCB stock is predictable in the short/long term. CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

Graph 41

Key Points

  1. Buy, Sell and Hold Signals
  2. Stock Rating
  3. Should I buy stocks now or wait amid such uncertainty?

NYCB Target Price Prediction Modeling Methodology

We consider New York Community Bancorp Inc. Common Stock Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of NYCB 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 (CNN Layer)) X S(n):→ 1 Year R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of NYCB stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (CNN Layer)

CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications.

Multiple Regression

Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in the model.

 

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?

NYCB Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: NYCB New York Community Bancorp Inc. Common Stock
Time series to forecast: 1 Year

According to price forecasts, the dominant strategy among neural network is: Sell

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Modular Neural Network (CNN Layer) based NYCB Stock Prediction Model

  1. When an entity separates the foreign currency basis spread from a financial instrument and excludes it from the designation of that financial instrument as the hedging instrument (see paragraph 6.2.4(b)), the application guidance in paragraphs B6.5.34–B6.5.38 applies to the foreign currency basis spread in the same manner as it is applied to the forward element of a forward contract.
  2. An example of a fair value hedge is a hedge of exposure to changes in the fair value of a fixed-rate debt instrument arising from changes in interest rates. Such a hedge could be entered into by the issuer or by the holder.
  3. 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
  4. If an entity prepares interim financial reports in accordance with IAS 34 Interim Financial Reporting the entity need not apply the requirements in this Standard to interim periods prior to the date of initial application if it is impracticable (as defined in IAS 8).

*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.

NYCB New York Community Bancorp Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba3B2
Income StatementB2Caa2
Balance SheetBaa2C
Leverage RatiosBaa2B1
Cash FlowCaa2Baa2
Rates of Return and ProfitabilityB1Ba3

*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?

References

  1. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
  2. Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
  3. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
  4. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
  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. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
  7. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
Frequently Asked QuestionsQ: What is the prediction methodology for NYCB stock?
A: NYCB stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Multiple Regression
Q: Is NYCB stock a buy or sell?
A: The dominant strategy among neural network is to Sell NYCB Stock.
Q: Is New York Community Bancorp Inc. Common Stock stock a good investment?
A: The consensus rating for New York Community Bancorp Inc. Common Stock is Sell and is assigned short-term Ba3 & long-term B2 estimated rating.
Q: What is the consensus rating of NYCB stock?
A: The consensus rating for NYCB is Sell.
Q: What is the prediction period for NYCB stock?
A: The prediction period for NYCB is 1 Year

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