## Abstract

**We evaluate Cleveland-Cliffs prediction models with Ensemble Learning (ML) and ElasticNet Regression ^{1,2,3,4} and conclude that the CLF 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 CLF stock.**

**CLF, Cleveland-Cliffs, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What are the most successful trading algorithms?
- What is the use of Markov decision process?
- Is now good time to invest?

## CLF Target Price Prediction Modeling Methodology

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

n:Time series to forecast

p:Price signals of CLF 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?

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

**Sample Set:**Neural Network

**Stock/Index:**CLF Cleveland-Cliffs

**Time series to forecast n: 05 Sep 2022**for (n+4 weeks)

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

Cleveland-Cliffs assigned short-term B1 & long-term B2 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with ElasticNet Regression ^{1,2,3,4} and conclude that the CLF 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 CLF stock.**

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

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B1 | B2 |

Operational Risk | 83 | 65 |

Market Risk | 32 | 50 |

Technical Analysis | 70 | 52 |

Fundamental Analysis | 44 | 58 |

Risk Unsystematic | 71 | 30 |

### Prediction Confidence Score

## References

- Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
- G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
- Friedman JH. 2002. Stochastic gradient boosting. Comput. Stat. Data Anal. 38:367–78
- Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
- V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
- Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
- Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press

## Frequently Asked Questions

Q: What is the prediction methodology for CLF stock?A: CLF stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and ElasticNet Regression

Q: Is CLF stock a buy or sell?

A: The dominant strategy among neural network is to Buy CLF Stock.

Q: Is Cleveland-Cliffs stock a good investment?

A: The consensus rating for Cleveland-Cliffs is Buy and assigned short-term B1 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of CLF stock?

A: The consensus rating for CLF is Buy.

Q: What is the prediction period for CLF stock?

A: The prediction period for CLF is (n+4 weeks)