Modelling A.I. in Economics

LON:XTR Stock: Set to Take Off (Forecast)

Outlook: XTRACT RESOURCES PLC is assigned short-term B1 & long-term Baa2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Speculative Sentiment Analysis)
Hypothesis Testing : Chi-Square
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

XTRACT RESOURCES PLC prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Chi-Square1,2,3,4 and it is concluded that the LON:XTR stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for speculative sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of speculative sentiment analysis, MNNs can be used to identify the sentiment of people who are speculating about the future value of an asset, such as a stock or a cryptocurrency. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

Graph 16

Key Points

  1. Game Theory
  2. How accurate is machine learning in stock market?
  3. How do you decide buy or sell a stock?

LON:XTR Target Price Prediction Modeling Methodology

We consider XTRACT RESOURCES PLC Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of LON:XTR 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(Chi-Square)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 (Speculative Sentiment Analysis)) X S(n):→ 1 Year e x rx

n:Time series to forecast

p:Price signals of LON:XTR stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Speculative Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for speculative sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of speculative sentiment analysis, MNNs can be used to identify the sentiment of people who are speculating about the future value of an asset, such as a stock or a cryptocurrency. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising.

Chi-Square

A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.

 

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?

LON:XTR Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: LON:XTR XTRACT RESOURCES PLC
Time series to forecast: 1 Year

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 (Speculative Sentiment Analysis) based LON:XTR Stock Prediction Model

  1. 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.
  2. If an entity previously accounted at cost (in accordance with IAS 39), for an investment in an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) (or for a derivative asset that is linked to and must be settled by delivery of such an equity instrument) it shall measure that instrument at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
  3. An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.
  4. If an entity has applied paragraph 7.2.6 then at the date of initial application the entity shall recognise any difference between the fair value of the entire hybrid contract at the date of initial application and the sum of the fair values of the components of the hybrid contract at the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.

*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.

LON:XTR XTRACT RESOURCES PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1Baa2
Income StatementBaa2Baa2
Balance SheetCaa2Ba1
Leverage RatiosB3Baa2
Cash FlowBa3B1
Rates of Return and ProfitabilityB1Baa2

*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

XTRACT RESOURCES PLC is assigned short-term B1 & long-term Baa2 estimated rating. XTRACT RESOURCES PLC prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Chi-Square1,2,3,4 and it is concluded that the LON:XTR stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 637 signals.

References

  1. Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
  2. Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
  3. Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
  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. Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
  6. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
  7. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
Frequently Asked QuestionsQ: What is the prediction methodology for LON:XTR stock?
A: LON:XTR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Chi-Square
Q: Is LON:XTR stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:XTR Stock.
Q: Is XTRACT RESOURCES PLC stock a good investment?
A: The consensus rating for XTRACT RESOURCES PLC is Buy and is assigned short-term B1 & long-term Baa2 estimated rating.
Q: What is the consensus rating of LON:XTR stock?
A: The consensus rating for LON:XTR is Buy.
Q: What is the prediction period for LON:XTR stock?
A: The prediction period for LON:XTR is 1 Year

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