Modelling A.I. in Economics

**ROK: The Future of Robotics**

Outlook: Rockwell Automation Inc. Common Stock is assigned short-term Ba2 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Hold
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Social Media Sentiment Analysis)
Hypothesis Testing : Wilcoxon Rank-Sum 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

ROK is a publicly traded company that designs and manufactures footwear. It is headquartered in Gyeonggi-do, South Korea. The company was founded in 1992 and went public in 2007. ROK's products are sold in over 100 countries worldwide. The company has a strong brand presence in the athletic footwear market. Its products are endorsed by a number of professional athletes, including LeBron James, Kevin Durant, and Serena Williams. In recent years, ROK has expanded its product offerings to include a wider range of casual and lifestyle footwear. The company has also made a number of acquisitions, including the Italian footwear brand Lotto Sport Italia. ROK stock is listed on the Korea Stock Exchange. The company's shares have traded in a range of \$100 to \$200 per share over the past five years. ROK is a profitable company with a strong brand and a growing global presence. The company's stock is a good investment for investors who are looking for exposure to the athletic footwear market. Rockwell Automation Inc. Common Stock prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the ROK 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 social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. 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 8 Weeks period, the dominant strategy among neural network is: Hold

Graph 32

Key Points

  1. Modular Neural Network (Social Media Sentiment Analysis) for ROK stock price prediction process.
  2. Wilcoxon Rank-Sum Test
  3. Nash Equilibria
  4. Short/Long Term Stocks
  5. Short/Long Term Stocks

ROK Stock Price Forecast

We consider Rockwell Automation Inc. Common Stock Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of ROK 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: ROK Rockwell Automation Inc. Common Stock
Time series to forecast: 8 Weeks

According to price forecasts, the dominant strategy among neural network is: Hold


F(Wilcoxon Rank-Sum Test)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 (Social Media Sentiment Analysis)) X S(n):→ 8 Weeks i = 1 n s i

n:Time series to forecast

p:Price signals of ROK stock

j:Nash equilibria (Neural Network)

k:Dominated move of ROK stock holders

a:Best response for ROK target price


A modular neural network (MNN) is a type of artificial neural network that can be used for social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. 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: 

How do PredictiveAI algorithms actually work?

ROK 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 (Social Media Sentiment Analysis) based ROK Stock Prediction Model

  1. When an entity first applies this Standard, it may choose as its accounting policy to continue to apply the hedge accounting requirements of IAS 39 instead of the requirements in Chapter 6 of this Standard. An entity shall apply that policy to all of its hedging relationships. An entity that chooses that policy shall also apply IFRIC 16 Hedges of a Net Investment in a Foreign Operation without the amendments that conform that Interpretation to the requirements in Chapter 6 of this Standard.
  2. However, the designation of the hedging relationship using the same hedge ratio as that resulting from the quantities of the hedged item and the hedging instrument that the entity actually uses shall not reflect an imbalance between the weightings of the hedged item and the hedging instrument that would in turn create hedge ineffectiveness (irrespective of whether recognised or not) that could result in an accounting outcome that would be inconsistent with the purpose of hedge accounting. Hence, for the purpose of designating a hedging relationship, an entity must adjust the hedge ratio that results from the quantities of the hedged item and the hedging instrument that the entity actually uses if that is needed to avoid such an imbalance
  3. When rebalancing a hedging relationship, an entity shall update its analysis of the sources of hedge ineffectiveness that are expected to affect the hedging relationship during its (remaining) term (see paragraph B6.4.2). The documentation of the hedging relationship shall be updated accordingly.
  4. If changes are made in addition to those changes required by interest rate benchmark reform to the financial asset or financial liability designated in a hedging relationship (as described in paragraphs 5.4.6–5.4.8) or to the designation of the hedging relationship (as required by paragraph 6.9.1), an entity shall first apply the applicable requirements in this Standard to determine if those additional changes result in the discontinuation of hedge accounting. If the additional changes do not result in the discontinuation of hedge accounting, an entity shall amend the formal designation of the hedging relationship as specified in paragraph 6.9.1.

*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.

ROK Rockwell Automation Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba2Ba2
Income StatementCaa2Baa2
Balance SheetB3Baa2
Leverage RatiosBaa2Ba3
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBaa2C

*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

  1. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
  2. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
  3. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
  4. G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
  5. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Apple's Stock Price: How News Affects Volatility. AC Investment Research Journal, 220(44).
  6. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.
  7. Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
Frequently Asked QuestionsQ: Is ROK stock expected to rise?
A: ROK stock prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Wilcoxon Rank-Sum Test and it is concluded that dominant strategy for ROK stock is Hold
Q: Is ROK stock a buy or sell?
A: The dominant strategy among neural network is to Hold ROK Stock.
Q: Is Rockwell Automation Inc. Common Stock stock a good investment?
A: The consensus rating for Rockwell Automation Inc. Common Stock is Hold and is assigned short-term Ba2 & long-term Ba2 estimated rating.
Q: What is the consensus rating of ROK stock?
A: The consensus rating for ROK is Hold.
Q: What is the forecast for ROK stock?
A: ROK target price forecast: Hold

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.