OMF Stock Price Prediction


This paper proposes genetic algorithms (GAs) approach to feature discretization and the determination of connection weights for artificial neural networks (ANNs) to predict the stock price index. Previous research proposed many hybrid models of ANN and GA for the method of training the network, feature subset selection, and topology optimization. We evaluate OneMain Financial prediction models with Inductive Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and conclude that the OMF stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold OMF stock.


Keywords: OMF, OneMain Financial, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Is Target price a good indicator?
  2. What are the most successful trading algorithms?
  3. Nash Equilibria

OMF Target Price Prediction Modeling Methodology

Social media comments have in the past had an instantaneous effect on stock markets. This paper investigates the sentiments expressed on the social media platform Twitter and their pr edictive impact on the Stock Market. We consider OneMain Financial Stock Decision Process with Wilcoxon Sign-Rank Test where A is the set of discrete actions of OMF 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(Wilcoxon Sign-Rank Test)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(Inductive Learning (ML)) X S(n):→ (n+16 weeks) i = 1 n s i

n:Time series to forecast

p:Price signals of OMF stock

j:Nash equilibria

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?

OMF Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: OMF OneMain Financial
Time series to forecast n: 13 Sep 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold OMF stock.

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 (Yellow to Green): *Technical Analysis%


Conclusions

OneMain Financial assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Inductive Learning (ML) with Wilcoxon Sign-Rank Test1,2,3,4 and conclude that the OMF stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold OMF stock.

Financial State Forecast for OMF Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B2
Operational Risk 8444
Market Risk7442
Technical Analysis4074
Fundamental Analysis8736
Risk Unsystematic4461

Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 467 signals.

References

  1. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
  2. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
  3. Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
  4. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
  5. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
  6. Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
  7. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
Frequently Asked QuestionsQ: What is the prediction methodology for OMF stock?
A: OMF stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is OMF stock a buy or sell?
A: The dominant strategy among neural network is to Hold OMF Stock.
Q: Is OneMain Financial stock a good investment?
A: The consensus rating for OneMain Financial is Hold and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of OMF stock?
A: The consensus rating for OMF is Hold.
Q: What is the prediction period for OMF stock?
A: The prediction period for OMF is (n+16 weeks)

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