Modelling A.I. in Economics

TYX Stock: A Bubble Waiting to Burst

Outlook: TYRANNA RESOURCES LIMITED is assigned short-term B1 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Transductive Learning (ML)
Hypothesis Testing : Polynomial 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.

Abstract

TYRANNA RESOURCES LIMITED prediction model is evaluated with Transductive Learning (ML) and Polynomial Regression1,2,3,4 and it is concluded that the TYX stock is predictable in the short/long term. Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

Graph 29

Key Points

  1. Can neural networks predict stock market?
  2. Market Risk
  3. What is neural prediction?

TYX Target Price Prediction Modeling Methodology

We consider TYRANNA RESOURCES LIMITED Decision Process with Transductive Learning (ML) where A is the set of discrete actions of TYX 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(Polynomial Regression)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(Transductive Learning (ML)) X S(n):→ 16 Weeks R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of TYX stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Transductive Learning (ML)

Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels.

Polynomial Regression

Polynomial regression is a type of regression analysis that uses a polynomial function to model the relationship between a dependent variable and one or more independent variables. Polynomial functions are mathematical functions that have a polynomial term, which is a term that is raised to a power greater than 1. In polynomial regression, the dependent variable is modeled as a polynomial function of the independent variables. The degree of the polynomial function is determined by the researcher. The higher the degree of the polynomial function, the more complex the model will be.

 

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?

TYX Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: TYX TYRANNA RESOURCES LIMITED
Time series to forecast: 16 Weeks

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

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 Transductive Learning (ML) based TYX Stock Prediction Model

  1. The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
  2. At the date of initial application, an entity shall use reasonable and supportable information that is available without undue cost or effort to determine the credit risk at the date that a financial instrument was initially recognised (or for loan commitments and financial guarantee contracts at the date that the entity became a party to the irrevocable commitment in accordance with paragraph 5.5.6) and compare that to the credit risk at the date of initial application of this Standard.
  3. When a group of items that constitute a net position is designated as a hedged item, an entity shall designate the overall group of items that includes the items that can make up the net position. An entity is not permitted to designate a non-specific abstract amount of a net position. For example, an entity has a group of firm sale commitments in nine months' time for FC100 and a group of firm purchase commitments in 18 months' time for FC120. The entity cannot designate an abstract amount of a net position up to FC20. Instead, it must designate a gross amount of purchases and a gross amount of sales that together give rise to the hedged net position. An entity shall designate gross positions that give rise to the net position so that the entity is able to comply with the requirements for the accounting for qualifying hedging relationships.
  4. An entity shall apply Prepayment Features with Negative Compensation (Amendments to IFRS 9) retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.30–7.2.34

*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.

TYX TYRANNA RESOURCES LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Income StatementB2Caa2
Balance SheetBaa2Ba2
Leverage RatiosCBa1
Cash FlowCBaa2
Rates of Return and ProfitabilityBaa2B2

*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

TYRANNA RESOURCES LIMITED is assigned short-term B1 & long-term Ba3 estimated rating. TYRANNA RESOURCES LIMITED prediction model is evaluated with Transductive Learning (ML) and Polynomial Regression1,2,3,4 and it is concluded that the TYX stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 589 signals.

References

  1. V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
  2. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
  3. Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
  4. E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.
  5. Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
  6. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
  7. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
Frequently Asked QuestionsQ: What is the prediction methodology for TYX stock?
A: TYX stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Polynomial Regression
Q: Is TYX stock a buy or sell?
A: The dominant strategy among neural network is to Sell TYX Stock.
Q: Is TYRANNA RESOURCES LIMITED stock a good investment?
A: The consensus rating for TYRANNA RESOURCES LIMITED is Sell and is assigned short-term B1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of TYX stock?
A: The consensus rating for TYX is Sell.
Q: What is the prediction period for TYX stock?
A: The prediction period for TYX is 16 Weeks

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