## Abstract

We evaluate Meta Platforms prediction models with Transfer Learning (ML) and Factor1,2,3,4 and conclude that the META 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 Buy META stock.

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

## Key Points

1. Can neural networks predict stock market?
2. How do you know when a stock will go up or down?
3. What is neural prediction?

## META Target Price Prediction Modeling Methodology

We consider Meta Platforms Stock Decision Process with Factor where A is the set of discrete actions of META 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(Factor)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ (n+1 year) $∑ i = 1 n a i$

n:Time series to forecast

p:Price signals of META 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?

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

Sample Set: Neural Network
Stock/Index: META Meta Platforms
Time series to forecast n: 03 Sep 2022 for (n+1 year)

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

Meta Platforms assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Factor1,2,3,4 and conclude that the META 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 Buy META stock.

### Financial State Forecast for META Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Operational Risk 7684
Market Risk4337
Technical Analysis5669
Fundamental Analysis8550
Risk Unsystematic7262

### Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 779 signals.

## References

1. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
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3. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
4. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
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7. Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
Frequently Asked QuestionsQ: What is the prediction methodology for META stock?
A: META stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Factor
Q: Is META stock a buy or sell?
A: The dominant strategy among neural network is to Buy META Stock.
Q: Is Meta Platforms stock a good investment?
A: The consensus rating for Meta Platforms is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of META stock?
A: The consensus rating for META is Buy.
Q: What is the prediction period for META stock?
A: The prediction period for META is (n+1 year)