AC Investment Research

Can neural networks predict stock market? (VBTX Stock Forecast) Research Report

In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. We evaluate VERITEX HOLDINGS CM prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Multiple Regression1,2,3,4 and conclude that the VBTX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold VBTX stock.


Keywords: VBTX, VERITEX HOLDINGS 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 decide buy or sell a stock?
  2. Understanding Buy, Sell, and Hold Ratings
  3. Can neural networks predict stock market?

VBTX Target Price Prediction Modeling Methodology

The prediction of stock price performance is a difficult and complex problem. Multivariate analytical techniques using both quantitative and qualitative variables have repeatedly been used to help form the basis of investor stock price expectations and, hence, influence investment decision making. However, the performance of multivariate analytical techniques is often less than conclusive and needs to be improved to more accurately forecast stock price performance. A neural network method has demonstrated its capability of addressing complex problems. We consider VERITEX HOLDINGS CM Stock Decision Process with Multiple Regression where A is the set of discrete actions of VBTX 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(Multiple Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Emotional Trigger/Responses Analysis)) X S(n):→ (n+3 month) i = 1 n a i

n:Time series to forecast

p:Price signals of VBTX 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?

VBTX Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: VBTX VERITEX HOLDINGS CM
Time series to forecast n: 25 Oct 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold VBTX 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

VERITEX HOLDINGS CM assigned short-term Ba2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Multiple Regression1,2,3,4 and conclude that the VBTX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold VBTX stock.

Financial State Forecast for VBTX Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba2Ba3
Operational Risk 5369
Market Risk7886
Technical Analysis6541
Fundamental Analysis7338
Risk Unsystematic6977

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 807 signals.

References

  1. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
  2. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52
  3. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
  4. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
  5. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
  6. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
  7. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
Frequently Asked QuestionsQ: What is the prediction methodology for VBTX stock?
A: VBTX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Multiple Regression
Q: Is VBTX stock a buy or sell?
A: The dominant strategy among neural network is to Hold VBTX Stock.
Q: Is VERITEX HOLDINGS CM stock a good investment?
A: The consensus rating for VERITEX HOLDINGS CM is Hold and assigned short-term Ba2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of VBTX stock?
A: The consensus rating for VBTX is Hold.
Q: What is the prediction period for VBTX stock?
A: The prediction period for VBTX is (n+3 month)

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