Machine Learning stock prediction: AFL Stock Prediction


Abstract

We evaluate Aflac prediction models with Transfer Learning (ML) and Lasso Regression1,2,3,4 and conclude that the AFL stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy AFL stock.


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

Key Points

  1. What are the most successful trading algorithms?
  2. Short/Long Term Stocks
  3. Prediction Modeling

AFL Target Price Prediction Modeling Methodology

We consider Aflac Stock Decision Process with Lasso Regression where A is the set of discrete actions of AFL 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(Lasso 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(Transfer Learning (ML)) X S(n):→ (n+3 month) r s rs

n:Time series to forecast

p:Price signals of AFL 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?

AFL Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: AFL Aflac
Time series to forecast n: 07 Sep 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy AFL 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

Aflac assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Lasso Regression1,2,3,4 and conclude that the AFL stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy AFL stock.

Financial State Forecast for AFL Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Operational Risk 5871
Market Risk7754
Technical Analysis7282
Fundamental Analysis7431
Risk Unsystematic5266

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 690 signals.

References

  1. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
  2. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
  3. N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
  4. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
  5. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  6. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
  7. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
Frequently Asked QuestionsQ: What is the prediction methodology for AFL stock?
A: AFL stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Lasso Regression
Q: Is AFL stock a buy or sell?
A: The dominant strategy among neural network is to Buy AFL Stock.
Q: Is Aflac stock a good investment?
A: The consensus rating for Aflac is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of AFL stock?
A: The consensus rating for AFL is Buy.
Q: What is the prediction period for AFL stock?
A: The prediction period for AFL is (n+3 month)

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