How do you predict if a stock will go up or down? (JKHY Stock Prediction) (Forecast)

It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. We evaluate Jack Henry & Associates prediction models with Deductive Inference (ML) and Paired T-Test^1,2,3,4 and conclude that the JKHY 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 Buy JKHY stock.

Keywords: JKHY, Jack Henry & Associates, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Buy, Sell and Hold Signals
2. Reaction Function
3. Buy, Sell and Hold Signals

JKHY Target Price Prediction Modeling Methodology

The presented paper modeled and predicted stock returns using LSTM. The historical data of stock market were transformed into 30-days-long sequences with 10 learning features and 7-day earning rate labeling. The model was fitted by training on 1200000 sequences and tested using the other 350000 sequences. We consider Jack Henry & Associates Stock Decision Process with Paired T-Test where A is the set of discrete actions of JKHY 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(Paired T-Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Deductive Inference (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of JKHY 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?

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

Sample Set: Neural Network
Stock/Index: JKHY Jack Henry & Associates
Time series to forecast n: 14 Oct 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy JKHY 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

Jack Henry & Associates assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Paired T-Test^1,2,3,4 and conclude that the JKHY 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 Buy JKHY stock.

Financial State Forecast for JKHY Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B2
Operational Risk	68	47
Market Risk	32	39
Technical Analysis	33	41
Fundamental Analysis	61	89
Risk Unsystematic	66	33

Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 579 signals.

References

1. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
2. Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
3. Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
4. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
5. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
6. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
7. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99

Frequently Asked Questions

Q: What is the prediction methodology for JKHY stock?
A: JKHY stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Paired T-Test
Q: Is JKHY stock a buy or sell?
A: The dominant strategy among neural network is to Buy JKHY Stock.
Q: Is Jack Henry & Associates stock a good investment?
A: The consensus rating for Jack Henry & Associates is Buy and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of JKHY stock?
A: The consensus rating for JKHY is Buy.
Q: What is the prediction period for JKHY stock?
A: The prediction period for JKHY is (n+16 weeks)

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