AUC Score :
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n:
Methodology : Transfer Learning (ML)
Hypothesis Testing : Independent T-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.
RADIOPHARM THERANOSTICS LIMITED prediction model is evaluated with Transfer Learning (ML) and Independent T-Test1,2,3,4 and it is concluded that the RAD stock is predictable in the short/long term. Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.5 According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

Key Points
- Fundemental Analysis with Algorithmic Trading
- Probability Distribution
- Nash Equilibria
RAD Stock Price Forecast
We consider RADIOPHARM THERANOSTICS LIMITED Decision Process with Transfer Learning (ML) where A is the set of discrete actions of RAD 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
Sample Set: Neural Network
Stock/Index: RAD RADIOPHARM THERANOSTICS LIMITED
Time series to forecast: 3 Month
According to price forecasts, the dominant strategy among neural network is: Sell
n:Time series to forecast
p:Price signals of RAD stock
j:Nash equilibria (Neural Network)
k:Dominated move of RAD stock holders
a:Best response for RAD target price
Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.5 An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.6,7
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?
RAD Stock Forecast (Buy or Sell) Strategic Interaction Table
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 Transfer Learning (ML) based RAD Stock Prediction Model
- A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
- If items are hedged together as a group in a cash flow hedge, they might affect different line items in the statement of profit or loss and other comprehensive income. The presentation of hedging gains or losses in that statement depends on the group of items
- A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
- 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
*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.
RAD RADIOPHARM THERANOSTICS LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | B1 |
Income Statement | B3 | B3 |
Balance Sheet | B2 | C |
Leverage Ratios | C | Ba2 |
Cash Flow | B1 | Ba3 |
Rates of Return and Profitability | Baa2 | B1 |
*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?
References
- Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
- Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
- Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
- V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
- F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
Frequently Asked Questions
Q: What is the prediction methodology for RAD stock?A: RAD stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Independent T-Test
Q: Is RAD stock a buy or sell?
A: The dominant strategy among neural network is to Sell RAD Stock.
Q: Is RADIOPHARM THERANOSTICS LIMITED stock a good investment?
A: The consensus rating for RADIOPHARM THERANOSTICS LIMITED is Sell and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of RAD stock?
A: The consensus rating for RAD is Sell.
Q: What is the prediction period for RAD stock?
A: The prediction period for RAD is 3 Month
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