Modelling A.I. in Economics

Should You Buy Now or Wait? TRTN^A Stock Forecast

Outlook: Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares is assigned short-term B1 & long-term B3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Market Volatility Analysis)
Hypothesis Testing : Independent T-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

Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Independent T-Test1,2,3,4 and it is concluded that the TRTN^A 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 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

Graph 18

Key Points

  1. What is prediction in deep learning?
  2. Understanding Buy, Sell, and Hold Ratings
  3. How do you pick a stock?

TRTN^A Target Price Prediction Modeling Methodology

We consider Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of TRTN^A 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(Independent T-Test)5,6,7= 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 (Market Volatility Analysis)) X S(n):→ 4 Weeks i = 1 n s i

n:Time series to forecast

p:Price signals of TRTN^A 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.

Independent T-Test

An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.

 

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?

TRTN^A Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: TRTN^A Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares
Time series to forecast: 4 Weeks

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

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 TRTN^A Stock Prediction Model

  1. The risk of a default occurring on financial instruments that have comparable credit risk is higher the longer the expected life of the instrument; for example, the risk of a default occurring on an AAA-rated bond with an expected life of 10 years is higher than that on an AAA-rated bond with an expected life of five years.
  2. 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.
  3. The definition of a derivative refers to non-financial variables that are not specific to a party to the contract. These include an index of earthquake losses in a particular region and an index of temperatures in a particular city. Non-financial variables specific to a party to the contract include the occurrence or non-occurrence of a fire that damages or destroys an asset of a party to the contract. A change in the fair value of a non-financial asset is specific to the owner if the fair value reflects not only changes in market prices for such assets (a financial variable) but also the condition of the specific non-financial asset held (a non-financial variable). For example, if a guarantee of the residual value of a specific car exposes the guarantor to the risk of changes in the car's physical condition, the change in that residual value is specific to the owner of the car.
  4. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.

*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.

TRTN^A Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1B3
Income StatementBaa2B3
Balance SheetBaa2Caa2
Leverage RatiosCaa2C
Cash FlowBa3Ba3
Rates of Return and ProfitabilityCC

*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

Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares is assigned short-term B1 & long-term B3 estimated rating. Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Independent T-Test1,2,3,4 and it is concluded that the TRTN^A stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 702 signals.

References

  1. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
  2. N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
  3. Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
  4. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
  5. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
  6. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
  7. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
Frequently Asked QuestionsQ: What is the prediction methodology for TRTN^A stock?
A: TRTN^A stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Independent T-Test
Q: Is TRTN^A stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend TRTN^A Stock.
Q: Is Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares stock a good investment?
A: The consensus rating for Triton International Limited 8.50% Series A Cumulative Redeemable Perpetual Preference Shares is Speculative Trend and is assigned short-term B1 & long-term B3 estimated rating.
Q: What is the consensus rating of TRTN^A stock?
A: The consensus rating for TRTN^A is Speculative Trend.
Q: What is the prediction period for TRTN^A stock?
A: The prediction period for TRTN^A is 4 Weeks

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.