This paper surveys machine learning techniques for stock market prediction. The prediction of stock markets is regarded as a challenging task of financial time series prediction.** We evaluate NMI HOLDINGS CMN A prediction models with Modular Neural Network (Social Media Sentiment Analysis) and ElasticNet Regression ^{1,2,3,4} and conclude that the NMIH stock is predictable in the short/long term. **

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NMIH stock.**

**NMIH, NMI HOLDINGS CMN A, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Technical Analysis with Algorithmic Trading
- Prediction Modeling
- Prediction Modeling

## NMIH Target Price Prediction Modeling Methodology

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. We consider NMI HOLDINGS CMN A Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of NMIH 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 Î³ ∈ [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(Modular Neural Network (Social Media Sentiment Analysis)) 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 NMIH 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?

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

**Sample Set:**Neural Network

**Stock/Index:**NMIH NMI HOLDINGS CMN A

**Time series to forecast n: 22 Sep 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NMIH 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

NMI HOLDINGS CMN A assigned short-term Ba3 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with ElasticNet Regression ^{1,2,3,4} and conclude that the NMIH stock is predictable in the short/long term.**

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NMIH stock.**

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

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

Outlook* | Ba3 | Ba3 |

Operational Risk | 78 | 68 |

Market Risk | 57 | 66 |

Technical Analysis | 40 | 73 |

Fundamental Analysis | 87 | 84 |

Risk Unsystematic | 53 | 36 |

### Prediction Confidence Score

## References

- Miller A. 2002. Subset Selection in Regression. New York: CRC Press
- Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
- Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
- P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
- E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
- Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
- 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 NMIH stock?A: NMIH stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and ElasticNet Regression

Q: Is NMIH stock a buy or sell?

A: The dominant strategy among neural network is to Hold NMIH Stock.

Q: Is NMI HOLDINGS CMN A stock a good investment?

A: The consensus rating for NMI HOLDINGS CMN A is Hold and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.

Q: What is the consensus rating of NMIH stock?

A: The consensus rating for NMIH is Hold.

Q: What is the prediction period for NMIH stock?

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