The study of financial markets has been addressed in many works during the last years. Different methods have been used in order to capture the non-linear behavior which is characteristic of these complex systems. The development of profitable strategies has been associated with the predictive character of the market movement, and special attention has been devoted to forecast the trends of financial markets. ** We evaluate Zoom prediction models with Inductive Learning (ML) and Lasso Regression ^{1,2,3,4} and conclude that the ZM 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 ZM stock.**

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

*Keywords:*## Key Points

- What are buy sell or hold recommendations?
- How do you know when a stock will go up or down?
- How accurate is machine learning in stock market?

## ZM Target Price Prediction Modeling Methodology

In this paper a Bayesian regularized artificial neural network is proposed as a novel method to forecast financial market behavior. Daily market prices and financial technical indicators are utilized as inputs to predict the one day future closing price of individual stocks. The prediction of stock price movement is generally considered to be a challenging and important task for financial time series analysis. We consider Zoom Stock Decision Process with Lasso Regression where A is the set of discrete actions of ZM 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(Lasso 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(Inductive Learning (ML)) X S(n):→ (n+1 year) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of ZM 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?

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

**Sample Set:**Neural Network

**Stock/Index:**ZM Zoom

**Time series to forecast n: 22 Oct 2022**for (n+1 year)

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

Zoom assigned short-term Ba3 & long-term B2 forecasted stock rating.** We evaluate the prediction models Inductive Learning (ML) with Lasso Regression ^{1,2,3,4} and conclude that the ZM 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 ZM stock.**

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

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

Outlook* | Ba3 | B2 |

Operational Risk | 84 | 36 |

Market Risk | 46 | 58 |

Technical Analysis | 36 | 61 |

Fundamental Analysis | 69 | 42 |

Risk Unsystematic | 84 | 63 |

### Prediction Confidence Score

## References

- Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
- G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
- Abadie A, Diamond A, Hainmueller J. 2015. Comparative politics and the synthetic control method. Am. J. Political Sci. 59:495–510
- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
- Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
- Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503

## Frequently Asked Questions

Q: What is the prediction methodology for ZM stock?A: ZM stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Lasso Regression

Q: Is ZM stock a buy or sell?

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

Q: Is Zoom stock a good investment?

A: The consensus rating for Zoom is Buy and assigned short-term Ba3 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of ZM stock?

A: The consensus rating for ZM is Buy.

Q: What is the prediction period for ZM stock?

A: The prediction period for ZM is (n+1 year)

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