AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
Methodology : Modular Neural Network (Market Volatility Analysis)
Hypothesis Testing : Factor
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.
Abstract
Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Factor1,2,3,4 and it is concluded that the DSX^B stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy
Key Points
- What is prediction in deep learning?
- Market Outlook
- Market Risk
DSX^B Target Price Prediction Modeling Methodology
We consider Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of DSX^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
F(Factor)5,6,7= X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ 3 Month
n:Time series to forecast
p:Price signals of DSX^B stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Modular Neural Network (Market Volatility Analysis)
Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.Factor
In statistics, a factor is a variable that can influence the value of another variable. Factors can be categorical or continuous. Categorical factors have a limited number of possible values, such as gender (male or female) or blood type (A, B, AB, or O). Continuous factors can have an infinite number of possible values, such as height or weight. Factors can be used to explain the variation in a dependent variable. For example, a study might find that there is a relationship between gender and height. In this case, gender would be the independent variable, height would be the dependent variable, and the factor would be gender.
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?
DSX^B Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: DSX^B Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands)
Time series to forecast: 3 Month
According to price forecasts, the dominant strategy among neural network is: Buy
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 Volatility Analysis) based DSX^B Stock Prediction Model
- 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).
- Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
- In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.
- Credit risk analysis is a multifactor and holistic analysis; whether a specific factor is relevant, and its weight compared to other factors, will depend on the type of product, characteristics of the financial instruments and the borrower as well as the geographical region. An entity shall consider reasonable and supportable information that is available without undue cost or effort and that is relevant for the particular financial instrument being assessed. However, some factors or indicators may not be identifiable on an individual financial instrument level. In such a case, the factors or indicators should be assessed for appropriate portfolios, groups of portfolios or portions of a portfolio of financial instruments to determine whether the requirement in paragraph 5.5.3 for the recognition of lifetime expected credit losses has been met.
*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.
DSX^B Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B3 | Ba3 |
Income Statement | B3 | C |
Balance Sheet | Caa2 | Ba1 |
Leverage Ratios | Caa2 | Baa2 |
Cash Flow | C | Baa2 |
Rates of Return and Profitability | B3 | Caa2 |
*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?
Conclusions
Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) is assigned short-term B3 & long-term Ba3 estimated rating. Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Factor1,2,3,4 and it is concluded that the DSX^B stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy
Prediction Confidence Score
References
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- Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
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- Sutton RS, Barto AG. 1998. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press
Frequently Asked Questions
Q: What is the prediction methodology for DSX^B stock?A: DSX^B stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Factor
Q: Is DSX^B stock a buy or sell?
A: The dominant strategy among neural network is to Buy DSX^B Stock.
Q: Is Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) stock a good investment?
A: The consensus rating for Diana Shipping Inc. Perpetual Preferred Shares Series B (Marshall Islands) is Buy and is assigned short-term B3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of DSX^B stock?
A: The consensus rating for DSX^B is Buy.
Q: What is the prediction period for DSX^B stock?
A: The prediction period for DSX^B is 3 Month
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