AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
Methodology : Multi-Task Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum 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
ARGOSY MINERALS LIMITED prediction model is evaluated with Multi-Task Learning (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the AGY 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 8 Weeks period, the dominant strategy among neural network is: Buy
Key Points
- How do you know when a stock will go up or down?
- What is statistical models in machine learning?
- How do you pick a stock?
AGY Target Price Prediction Modeling Methodology
We consider ARGOSY MINERALS LIMITED Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of AGY 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(Wilcoxon Rank-Sum Test)5,6,7= X R(Multi-Task Learning (ML)) X S(n):→ 8 Weeks
n:Time series to forecast
p:Price signals of AGY 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.Wilcoxon Rank-Sum Test
The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that 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?
AGY Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: AGY ARGOSY MINERALS LIMITED
Time series to forecast: 8 Weeks
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 AGY Stock Prediction Model
- At the date of initial application, an entity shall assess whether a financial asset meets the condition in paragraphs 4.1.2(a) or 4.1.2A(a) on the basis of the facts and circumstances that exist at that date. The resulting classification shall be applied retrospectively irrespective of the entity's business model in prior reporting periods.
- An entity shall apply the amendments to IFRS 9 made by IFRS 17 as amended in June 2020 retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.37–7.2.42.
- An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
- Lifetime expected credit losses are generally expected to be recognised before a financial instrument becomes past due. Typically, credit risk increases significantly before a financial instrument becomes past due or other lagging borrower-specific factors (for example, a modification or restructuring) are observed. Consequently when reasonable and supportable information that is more forward-looking than past due information is available without undue cost or effort, it must be used to assess changes in credit risk.
*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.
AGY ARGOSY MINERALS LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | B1 |
Income Statement | Caa2 | B3 |
Balance Sheet | Baa2 | Baa2 |
Leverage Ratios | B1 | Caa2 |
Cash Flow | B2 | Ba1 |
Rates of Return and Profitability | B2 | Caa2 |
*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
ARGOSY MINERALS LIMITED is assigned short-term B1 & long-term B1 estimated rating. ARGOSY MINERALS LIMITED prediction model is evaluated with Multi-Task Learning (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the AGY stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Buy
Prediction Confidence Score
References
- Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
- Schapire RE, Freund Y. 2012. Boosting: Foundations and Algorithms. Cambridge, MA: MIT Press
- B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
- Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
- Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
- Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
- Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
Frequently Asked Questions
Q: What is the prediction methodology for AGY stock?A: AGY stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is AGY stock a buy or sell?
A: The dominant strategy among neural network is to Buy AGY Stock.
Q: Is ARGOSY MINERALS LIMITED stock a good investment?
A: The consensus rating for ARGOSY MINERALS LIMITED is Buy and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of AGY stock?
A: The consensus rating for AGY is Buy.
Q: What is the prediction period for AGY stock?
A: The prediction period for AGY is 8 Weeks
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