AUC Score :
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n:
Methodology : Reinforcement Machine Learning (ML)
Hypothesis Testing : Logistic Regression
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
Capital Southwest Corporation Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the CSWC stock is predictable in the short/long term. Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.5 According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell
Key Points
- Reinforcement Machine Learning (ML) for CSWC stock price prediction process.
- Logistic Regression
- Stock Rating
- Prediction Modeling
- What is statistical models in machine learning?
CSWC Stock Price Forecast
We consider Capital Southwest Corporation Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of CSWC 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: CSWC Capital Southwest Corporation Common Stock
Time series to forecast: 8 Weeks
According to price forecasts, the dominant strategy among neural network is: Sell
n:Time series to forecast
p:Price signals of CSWC stock
j:Nash equilibria (Neural Network)
k:Dominated move of CSWC stock holders
a:Best response for CSWC target price
Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.5 In statistics, logistic regression is a type of regression analysis used when the dependent variable is categorical. Logistic regression is a probability model that predicts the probability of an event occurring based on a set of independent variables. In logistic regression, the dependent variable is represented as a binary variable, such as "yes" or "no," "true" or "false," or "sick" or "healthy." The independent variables can be continuous or categorical variables.6,7
For further technical information as per how our model work we invite you to visit the article below:
CSWC 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 Reinforcement Machine Learning (ML) based CSWC Stock Prediction Model
- For the purpose of applying the requirements in paragraphs 6.4.1(c)(i) and B6.4.4–B6.4.6, an entity shall assume that the interest rate benchmark on which the hedged cash flows and/or the hedged risk (contractually or noncontractually specified) are based, or the interest rate benchmark on which the cash flows of the hedging instrument are based, is not altered as a result of interest rate benchmark reform.
- The fact that a derivative is in or out of the money when it is designated as a hedging instrument does not in itself mean that a qualitative assessment is inappropriate. It depends on the circumstances whether hedge ineffectiveness arising from that fact could have a magnitude that a qualitative assessment would not adequately capture.
- Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
- An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
*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.
CSWC Capital Southwest Corporation Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | Ba3 |
Income Statement | Caa2 | B3 |
Balance Sheet | B1 | C |
Leverage Ratios | Ba1 | Ba3 |
Cash Flow | Caa2 | Baa2 |
Rates of Return and Profitability | Baa2 | 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
- Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
- C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
- Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
- Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
- Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
- Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
Frequently Asked Questions
Q: Is CSWC stock expected to rise?A: CSWC stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Logistic Regression and it is concluded that dominant strategy for CSWC stock is Sell
Q: Is CSWC stock a buy or sell?
A: The dominant strategy among neural network is to Sell CSWC Stock.
Q: Is Capital Southwest Corporation Common Stock stock a good investment?
A: The consensus rating for Capital Southwest Corporation Common Stock is Sell and is assigned short-term B1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of CSWC stock?
A: The consensus rating for CSWC is Sell.
Q: What is the forecast for CSWC stock?
A: CSWC target price forecast: Sell