Modelling A.I. in Economics

ANALYZING SBBA STOCK: A COMPREHENSIVE EVALUATION OF GROWTH POTENTIAL AND INVESTMENT OPPORTUNITIES

Outlook: Scorpio Tankers Inc. 7.00% Senior Notes due 2025 is assigned short-term B2 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n: for Weeks2
Methodology : Multi-Task Learning (ML)
Hypothesis Testing : Sign 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.

Abstract

Scorpio Tankers Inc. 7.00% Senior Notes due 2025 prediction model is evaluated with Multi-Task Learning (ML) and Sign Test1,2,3,4 and it is concluded that the SBBA stock is predictable in the short/long term. Multi-task learning (MTL) is a machine learning (ML) method in which multiple related tasks are learned simultaneously. This can be done by sharing features and weights between the tasks. MTL has been shown to improve the performance of each task, compared to learning each task independently. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Buy

Graph 4

Key Points

  1. Can we predict stock market using machine learning?
  2. What is prediction model?
  3. What is a prediction confidence?

SBBA Target Price Prediction Modeling Methodology

We consider Scorpio Tankers Inc. 7.00% Senior Notes due 2025 Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of SBBA 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(Sign 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(Multi-Task Learning (ML)) X S(n):→ 6 Month R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of SBBA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Multi-Task Learning (ML)

Multi-task learning (MTL) is a machine learning (ML) method in which multiple related tasks are learned simultaneously. This can be done by sharing features and weights between the tasks. MTL has been shown to improve the performance of each task, compared to learning each task independently.

Sign Test

The sign test is a non-parametric hypothesis test that is used to compare two paired samples. In a paired sample, each data point in one sample is paired with a data point in the other sample. The pairs are typically related in some way, such as before and after measurements, or measurements from the same subject under different conditions. The sign test is a non-parametric test, which means that it does not assume that the data is normally distributed. The sign test is also a dependent samples test, which means that the data points in each pair are correlated.

 

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?

SBBA Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: SBBA Scorpio Tankers Inc. 7.00% Senior Notes due 2025
Time series to forecast: 6 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 Multi-Task Learning (ML) based SBBA Stock Prediction Model

  1. 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.
  2. The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
  3. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary
  4. The change in the value of the hedged item determined using a hypothetical derivative may also be used for the purpose of assessing whether a hedging relationship meets the hedge effectiveness requirements.

*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.

SBBA Scorpio Tankers Inc. 7.00% Senior Notes due 2025 Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2Ba3
Income StatementCB2
Balance SheetCaa2C
Leverage RatiosBa1Baa2
Cash FlowBa1Baa2
Rates of Return and ProfitabilityCaa2Ba3

*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

Scorpio Tankers Inc. 7.00% Senior Notes due 2025 is assigned short-term B2 & long-term Ba3 estimated rating. Scorpio Tankers Inc. 7.00% Senior Notes due 2025 prediction model is evaluated with Multi-Task Learning (ML) and Sign Test1,2,3,4 and it is concluded that the SBBA stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Buy

Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 742 signals.

References

  1. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
  2. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
  3. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
  4. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
  5. White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
  6. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
  7. D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
Frequently Asked QuestionsQ: What is the prediction methodology for SBBA stock?
A: SBBA stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Sign Test
Q: Is SBBA stock a buy or sell?
A: The dominant strategy among neural network is to Buy SBBA Stock.
Q: Is Scorpio Tankers Inc. 7.00% Senior Notes due 2025 stock a good investment?
A: The consensus rating for Scorpio Tankers Inc. 7.00% Senior Notes due 2025 is Buy and is assigned short-term B2 & long-term Ba3 estimated rating.
Q: What is the consensus rating of SBBA stock?
A: The consensus rating for SBBA is Buy.
Q: What is the prediction period for SBBA stock?
A: The prediction period for SBBA is 6 Month

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