Machine Learning stock prediction: COIN Stock Prediction

Abstract

We evaluate COINBASE GLB CL A CM prediction models with Transfer Learning (ML) and ElasticNet Regression^1,2,3,4 and conclude that the COIN stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy COIN stock.

Keywords: COIN, COINBASE GLB CL A CM, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. How do you know when a stock will go up or down?
2. Should I buy stocks now or wait amid such uncertainty?
3. Reaction Function

COIN Target Price Prediction Modeling Methodology

We consider COINBASE GLB CL A CM Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of COIN 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ (n+4 weeks) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of COIN 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?

COIN Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: COIN COINBASE GLB CL A CM
Time series to forecast n: 03 Sep 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy COIN 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

COINBASE GLB CL A CM assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with ElasticNet Regression^1,2,3,4 and conclude that the COIN stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy COIN stock.

Financial State Forecast for COIN Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B2
Operational Risk	72	62
Market Risk	79	60
Technical Analysis	77	38
Fundamental Analysis	49	33
Risk Unsystematic	38	61

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 840 signals.

References

1. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
2. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
3. D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
4. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
5. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
6. Athey S, Bayati M, Imbens G, Zhaonan Q. 2019. Ensemble methods for causal effects in panel data settings. NBER Work. Pap. 25675
7. A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.

Frequently Asked Questions

Q: What is the prediction methodology for COIN stock?
A: COIN stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and ElasticNet Regression
Q: Is COIN stock a buy or sell?
A: The dominant strategy among neural network is to Buy COIN Stock.
Q: Is COINBASE GLB CL A CM stock a good investment?
A: The consensus rating for COINBASE GLB CL A CM is Buy and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of COIN stock?
A: The consensus rating for COIN is Buy.
Q: What is the prediction period for COIN stock?
A: The prediction period for COIN is (n+4 weeks)

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