**Outlook:**Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 assigned short-term B2 & long-term B2 forecasted stock rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 19 Dec 2022**for (n+6 month)

**Methodology :**Ensemble Learning (ML)

## Abstract

The prediction of a stock market direction may serve as an early recommendation system for short-term investors and as an early financial distress warning system for long-term shareholders. (Yuan, X., Yuan, J., Jiang, T. and Ain, Q.U., 2020. Integrated long-term stock selection models based on feature selection and machine learning algorithms for China stock market. IEEE Access, 8, pp.22672-22685.)** We evaluate Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 prediction models with Ensemble Learning (ML) and Pearson Correlation ^{1,2,3,4} and conclude that the EICA stock is predictable in the short/long term. **

**According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell**

## Key Points

- Trading Interaction
- Understanding Buy, Sell, and Hold Ratings
- What are the most successful trading algorithms?

## EICA Target Price Prediction Modeling Methodology

We consider Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of EICA 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(Pearson Correlation)

^{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+6 month) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of EICA stock

j:Nash equilibria (Neural Network)

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?

## EICA Stock Forecast (Buy or Sell) for (n+6 month)

**Sample Set:**Neural Network

**Stock/Index:**EICA Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026

**Time series to forecast n: 19 Dec 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell**

**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 (Grey to Black): *Technical Analysis%**

## Adjusted IFRS* Prediction Methods for Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026

- If the underlyings are not the same but are economically related, there can be situations in which the values of the hedging instrument and the hedged item move in the same direction, for example, because the price differential between the two related underlyings changes while the underlyings themselves do not move significantly. That is still consistent with an economic relationship between the hedging instrument and the hedged item if the values of the hedging instrument and the hedged item are still expected to typically move in the opposite direction when the underlyings move.
- A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
- The fact that a derivative is in or out of the money when it is designated as a hedging instrument does not in itself mean that a qualitative assessment is inappropriate. It depends on the circumstances whether hedge ineffectiveness arising from that fact could have a magnitude that a qualitative assessment would not adequately capture.
- There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 assigned short-term B2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with Pearson Correlation ^{1,2,3,4} and conclude that the EICA stock is predictable in the short/long term.**

**According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell**

### Financial State Forecast for EICA Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 Options & Futures

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

Outlook* | B2 | B2 |

Operational Risk | 37 | 51 |

Market Risk | 84 | 36 |

Technical Analysis | 42 | 61 |

Fundamental Analysis | 46 | 57 |

Risk Unsystematic | 74 | 70 |

### Prediction Confidence Score

## References

- Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
- J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
- Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
- Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
- Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.

## Frequently Asked Questions

Q: What is the prediction methodology for EICA stock?A: EICA stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Pearson Correlation

Q: Is EICA stock a buy or sell?

A: The dominant strategy among neural network is to Sell EICA Stock.

Q: Is Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 stock a good investment?

A: The consensus rating for Eagle Point Income Company Inc. 5.00% Series A Term Preferred Stock due 2026 is Sell and assigned short-term B2 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of EICA stock?

A: The consensus rating for EICA is Sell.

Q: What is the prediction period for EICA stock?

A: The prediction period for EICA is (n+6 month)