AUC Score :
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n:
Methodology : Deductive Inference (ML)
Hypothesis Testing : Statistical Hypothesis Testing
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
Barrick Gold Corporation prediction model is evaluated with Deductive Inference (ML) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the ABX:TSX stock is predictable in the short/long term. Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend
Key Points
- Can statistics predict the future?
- How accurate is machine learning in stock market?
- Is Target price a good indicator?
ABX:TSX Target Price Prediction Modeling Methodology
We consider Barrick Gold Corporation Decision Process with Deductive Inference (ML) where A is the set of discrete actions of ABX:TSX 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(Statistical Hypothesis Testing)5,6,7= X R(Deductive Inference (ML)) X S(n):→ 8 Weeks
n:Time series to forecast
p:Price signals of ABX:TSX stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Deductive Inference (ML)
Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses.Statistical Hypothesis Testing
Statistical hypothesis testing is a process used to determine whether there is enough evidence to support a claim about a population based on a sample. The process involves making two hypotheses, a null hypothesis and an alternative hypothesis, and then collecting data and using statistical tests to determine which hypothesis is more likely to be true. The null hypothesis is the statement that there is no difference between the population and the sample. The alternative hypothesis is the statement that there is a difference between the population and the sample. The statistical test is used to calculate a p-value, which is the probability of obtaining the observed data or more extreme data if the null hypothesis is true. A p-value of less than 0.05 is typically considered to be statistically significant, which means that there is less than a 5% chance of obtaining the observed data or more extreme data if the null hypothesis is true.
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?
ABX:TSX Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: ABX:TSX Barrick Gold Corporation
Time series to forecast: 8 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 Deductive Inference (ML) based ABX:TSX Stock Prediction Model
- To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.
- If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
- In applying the effective interest method, an entity identifies fees that are an integral part of the effective interest rate of a financial instrument. The description of fees for financial services may not be indicative of the nature and substance of the services provided. Fees that are an integral part of the effective interest rate of a financial instrument are treated as an adjustment to the effective interest rate, unless the financial instrument is measured at fair value, with the change in fair value being recognised in profit or loss. In those cases, the fees are recognised as revenue or expense when the instrument is initially recognised.
- In applying the effective interest method, an entity identifies fees that are an integral part of the effective interest rate of a financial instrument. The description of fees for financial services may not be indicative of the nature and substance of the services provided. Fees that are an integral part of the effective interest rate of a financial instrument are treated as an adjustment to the effective interest rate, unless the financial instrument is measured at fair value, with the change in fair value being recognised in profit or loss. In those cases, the fees are recognised as revenue or expense when the instrument is initially recognised.
*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.
ABX:TSX Barrick Gold Corporation Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | Caa1 |
Income Statement | Caa2 | C |
Balance Sheet | Baa2 | B2 |
Leverage Ratios | Ba2 | C |
Cash Flow | Caa2 | C |
Rates of Return and Profitability | Ba1 | B3 |
*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
Barrick Gold Corporation is assigned short-term B1 & long-term Caa1 estimated rating. Barrick Gold Corporation prediction model is evaluated with Deductive Inference (ML) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the ABX:TSX stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend
Prediction Confidence Score
References
- Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
- Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
- Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market?. AC Investment Research Journal, 220(44).
- Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
- Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
- P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
- R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
Frequently Asked Questions
Q: What is the prediction methodology for ABX:TSX stock?A: ABX:TSX stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Statistical Hypothesis Testing
Q: Is ABX:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend ABX:TSX Stock.
Q: Is Barrick Gold Corporation stock a good investment?
A: The consensus rating for Barrick Gold Corporation is Speculative Trend and is assigned short-term B1 & long-term Caa1 estimated rating.
Q: What is the consensus rating of ABX:TSX stock?
A: The consensus rating for ABX:TSX is Speculative Trend.
Q: What is the prediction period for ABX:TSX stock?
A: The prediction period for ABX:TSX is 8 Weeks