AUC Score :
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n:
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)
Hypothesis Testing : Spearman Correlation
Surveillance : Major exchange and OTC
1The accuracy of the model is being monitored on a regular basis.(15-minute period)
2Time series is updated based on short-term trends.
ZoomInfo Technologies Inc Common Stock prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the ZI stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for emotional trigger/responses analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences.5 According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

Key Points
- What statistical methods are used to analyze data?
- Decision Making
- Prediction Modeling
ZI Stock Price Forecast
We consider ZoomInfo Technologies Inc Common Stock Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of ZI 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
Sample Set: Neural Network
Stock/Index: ZI ZoomInfo Technologies Inc Common Stock
Time series to forecast: 1 Year
According to price forecasts, the dominant strategy among neural network is: Sell
n:Time series to forecast
p:Price signals of ZI stock
j:Nash equilibria (Neural Network)
k:Dominated move of ZI stock holders
a:Best response for ZI target price
A modular neural network (MNN) is a type of artificial neural network that can be used for emotional trigger/responses analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences.5 Spearman correlation is a nonparametric measure of the strength and direction of association between two variables. It is a rank-based correlation, which means that it does not assume that the data is normally distributed. Spearman correlation is calculated by first ranking the data for each variable, and then calculating the Pearson correlation between the ranks.6,7
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?
ZI Stock Forecast (Buy or Sell) Strategic Interaction Table
Strategic Interaction Table Legend:
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%
Financial Data Adjustments for Modular Neural Network (Emotional Trigger/Responses Analysis) based ZI Stock Prediction Model
- If the contractual cash flows on a financial asset have been renegotiated or otherwise modified, but the financial asset is not derecognised, that financial asset is not automatically considered to have lower credit risk. An entity shall assess whether there has been a significant increase in credit risk since initial recognition on the basis of all reasonable and supportable information that is available without undue cost or effort. This includes historical and forwardlooking information and an assessment of the credit risk over the expected life of the financial asset, which includes information about the circumstances that led to the modification. Evidence that the criteria for the recognition of lifetime expected credit losses are no longer met may include a history of up-to-date and timely payment performance against the modified contractual terms. Typically a customer would need to demonstrate consistently good payment behaviour over a period of time before the credit risk is considered to have decreased.
- An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
- When identifying what risk components qualify for designation as a hedged item, an entity assesses such risk components within the context of the particular market structure to which the risk or risks relate and in which the hedging activity takes place. Such a determination requires an evaluation of the relevant facts and circumstances, which differ by risk and market.
- A portfolio of financial assets that is managed and whose performance is evaluated on a fair value basis (as described in paragraph 4.2.2(b)) is neither held to collect contractual cash flows nor held both to collect contractual cash flows and to sell financial assets. The entity is primarily focused on fair value information and uses that information to assess the assets' performance and to make decisions. In addition, a portfolio of financial assets that meets the definition of held for trading is not held to collect contractual cash flows or held both to collect contractual cash flows and to sell financial assets. For such portfolios, the collection of contractual cash flows is only incidental to achieving the business model's objective. Consequently, such portfolios of financial assets must be measured at fair value through profit or loss.
*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.
ZI ZoomInfo Technologies Inc Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | B1 |
Income Statement | C | Caa2 |
Balance Sheet | Baa2 | B1 |
Leverage Ratios | C | Caa2 |
Cash Flow | Ba1 | B2 |
Rates of Return and Profitability | Ba3 | Baa2 |
*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?
References
- Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
- A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
- Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
- A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
Frequently Asked Questions
Q: What is the prediction methodology for ZI stock?A: ZI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation
Q: Is ZI stock a buy or sell?
A: The dominant strategy among neural network is to Sell ZI Stock.
Q: Is ZoomInfo Technologies Inc Common Stock stock a good investment?
A: The consensus rating for ZoomInfo Technologies Inc Common Stock is Sell and is assigned short-term B2 & long-term B1 estimated rating.
Q: What is the consensus rating of ZI stock?
A: The consensus rating for ZI is Sell.
Q: What is the prediction period for ZI stock?
A: The prediction period for ZI is 1 Year
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