AUC Score :
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n:
Methodology : Modular Neural Network (Market News Sentiment Analysis)
Hypothesis Testing : Wilcoxon Sign-Rank Test
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.
Summary
Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the CFR^B 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 news feed sentiment 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.5 According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell
Key Points
- Modular Neural Network (Market News Sentiment Analysis) for CFR^B stock price prediction process.
- Wilcoxon Sign-Rank Test
- Market Outlook
- What is statistical models in machine learning?
- Stock Rating
CFR^B Stock Price Forecast
We consider Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of CFR^B 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: CFR^B Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B
Time series to forecast: 6 Month
According to price forecasts, the dominant strategy among neural network is: Sell
n:Time series to forecast
p:Price signals of CFR^B stock
j:Nash equilibria (Neural Network)
k:Dominated move of CFR^B stock holders
a:Best response for CFR^B target price
A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.5 The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.6,7
For further technical information as per how our model work we invite you to visit the article below:
CFR^B 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 (Market News Sentiment Analysis) based CFR^B Stock Prediction Model
- To calculate the change in the value of the hedged item for the purpose of measuring hedge ineffectiveness, an entity may use a derivative that would have terms that match the critical terms of the hedged item (this is commonly referred to as a 'hypothetical derivative'), and, for example for a hedge of a forecast transaction, would be calibrated using the hedged price (or rate) level. For example, if the hedge was for a two-sided risk at the current market level, the hypothetical derivative would represent a hypothetical forward contract that is calibrated to a value of nil at the time of designation of the hedging relationship. If the hedge was for example for a one-sided risk, the hypothetical derivative would represent the intrinsic value of a hypothetical option that at the time of designation of the hedging relationship is at the money if the hedged price level is the current market level, or out of the money if the hedged price level is above (or, for a hedge of a long position, below) the current market level. Using a hypothetical derivative is one possible way of calculating the change in the value of the hedged item. The hypothetical derivative replicates the hedged item and hence results in the same outcome as if that change in value was determined by a different approach. Hence, using a 'hypothetical derivative' is not a method in its own right but a mathematical expedient that can only be used to calculate the value of the hedged item. Consequently, a 'hypothetical derivative' cannot be used to include features in the value of the hedged item that only exist in the hedging instrument (but not in the hedged item). An example is debt denominated in a foreign currency (irrespective of whether it is fixed-rate or variable-rate debt). When using a hypothetical derivative to calculate the change in the value of such debt or the present value of the cumulative change in its cash flows, the hypothetical derivative cannot simply impute a charge for exchanging different currencies even though actual derivatives under which different currencies are exchanged might include such a charge (for example, cross-currency interest rate swaps).
- Adjusting the hedge ratio by decreasing the volume of the hedging instrument does not affect how the changes in the value of the hedged item are measured. The measurement of the changes in the fair value of the hedging instrument related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedging instrument was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged the price risk of a commodity using a derivative volume of 100 tonnes as the hedging instrument and reduces that volume by 10 tonnes on rebalancing, a nominal amount of 90 tonnes of the hedging instrument volume would remain (see paragraph B6.5.16 for the consequences for the derivative volume (ie the 10 tonnes) that is no longer a part of the hedging relationship).
- For the purposes of applying the requirements in paragraphs 5.7.7 and 5.7.8, an accounting mismatch is not caused solely by the measurement method that an entity uses to determine the effects of changes in a liability's credit risk. An accounting mismatch in profit or loss would arise only when the effects of changes in the liability's credit risk (as defined in IFRS 7) are expected to be offset by changes in the fair value of another financial instrument. A mismatch that arises solely as a result of the measurement method (ie because an entity does not isolate changes in a liability's credit risk from some other changes in its fair value) does not affect the determination required by paragraphs 5.7.7 and 5.7.8. For example, an entity may not isolate changes in a liability's credit risk from changes in liquidity risk. If the entity presents the combined effect of both factors in other comprehensive income, a mismatch may occur because changes in liquidity risk may be included in the fair value measurement of the entity's financial assets and the entire fair value change of those assets is presented in profit or loss. However, such a mismatch is caused by measurement imprecision, not the offsetting relationship described in paragraph B5.7.6 and, therefore, does not affect the determination required by paragraphs 5.7.7 and 5.7.8.
- For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
*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.
CFR^B Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | B2 |
Income Statement | C | Caa2 |
Balance Sheet | Ba2 | B3 |
Leverage Ratios | B1 | Baa2 |
Cash Flow | Baa2 | Caa2 |
Rates of Return and Profitability | C | C |
*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
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- Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
- Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
- Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
- G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
Frequently Asked Questions
Q: Is CFR^B stock expected to rise?A: CFR^B stock prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test and it is concluded that dominant strategy for CFR^B stock is Sell
Q: Is CFR^B stock a buy or sell?
A: The dominant strategy among neural network is to Sell CFR^B Stock.
Q: Is Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B stock a good investment?
A: The consensus rating for Cullen/Frost Bankers Inc. Depositary Shares each representing a 1/40th ownership interest in a share of 4.450% non-cumulative perpetual preferred stock Series B is Sell and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of CFR^B stock?
A: The consensus rating for CFR^B is Sell.
Q: What is the forecast for CFR^B stock?
A: CFR^B target price forecast: Sell
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