How accurate is machine learning in stock market? (HRB Stock Forecast)


Abstract

We evaluate H&R Block prediction models with Exponential Moving Average (EMA) and ElasticNet Regression1,2,3,4 and conclude that the HRB stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell HRB stock.


Keywords: HRB, H&R Block, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Investment Risk
  2. How useful are statistical predictions?
  3. What is the use of Markov decision process?

HRB Target Price Prediction Modeling Methodology

We consider H&R Block Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of HRB 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(Exponential Moving Average (EMA)) X S(n):→ (n+1 year) i = 1 n a i

n:Time series to forecast

p:Price signals of HRB 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?

HRB Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: HRB H&R Block
Time series to forecast n: 01 Sep 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell HRB 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

H&R Block assigned short-term Ba1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Exponential Moving Average (EMA) with ElasticNet Regression1,2,3,4 and conclude that the HRB stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell HRB stock.

Financial State Forecast for HRB Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba3
Operational Risk 8765
Market Risk3268
Technical Analysis7355
Fundamental Analysis8271
Risk Unsystematic8464

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 754 signals.

References

  1. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
  2. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
  3. Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
  4. 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.
  5. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
  6. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
  7. K. Boda, J. Filar, Y. Lin, and L. Spanjers. Stochastic target hitting time and the problem of early retirement. Automatic Control, IEEE Transactions on, 49(3):409–419, 2004
Frequently Asked QuestionsQ: What is the prediction methodology for HRB stock?
A: HRB stock prediction methodology: We evaluate the prediction models Exponential Moving Average (EMA) and ElasticNet Regression
Q: Is HRB stock a buy or sell?
A: The dominant strategy among neural network is to Sell HRB Stock.
Q: Is H&R Block stock a good investment?
A: The consensus rating for H&R Block is Sell and assigned short-term Ba1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of HRB stock?
A: The consensus rating for HRB is Sell.
Q: What is the prediction period for HRB stock?
A: The prediction period for HRB is (n+1 year)

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