AUC Score :
Short-Term Revised1 :
Dominant Strategy : Hold
Time series to forecast n:
Methodology : Modular Neural Network (DNN Layer)
Hypothesis Testing : Pearson Correlation
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
NIMY RESOURCES LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Pearson Correlation1,2,3,4 and it is concluded that the NIM stock is predictable in the short/long term. In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold
Key Points
- Which neural network is best for prediction?
- Fundemental Analysis with Algorithmic Trading
- Can statistics predict the future?
NIM Target Price Prediction Modeling Methodology
We consider NIMY RESOURCES LIMITED Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of NIM 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(Pearson Correlation)5,6,7= X R(Modular Neural Network (DNN Layer)) X S(n):→ 6 Month
n:Time series to forecast
p:Price signals of NIM stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Modular Neural Network (DNN Layer)
In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another.Pearson Correlation
Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.
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?
NIM Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: NIM NIMY RESOURCES LIMITED
Time series to forecast: 6 Month
According to price forecasts, the dominant strategy among neural network is: Hold
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 (DNN Layer) based NIM Stock Prediction Model
- 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.
- Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
- In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.
- Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
*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.
NIM NIMY RESOURCES LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Caa2 | B1 |
Income Statement | C | Baa2 |
Balance Sheet | Caa2 | Baa2 |
Leverage Ratios | C | Caa2 |
Cash Flow | C | Caa2 |
Rates of Return and Profitability | Caa2 | 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
NIMY RESOURCES LIMITED is assigned short-term Caa2 & long-term B1 estimated rating. NIMY RESOURCES LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Pearson Correlation1,2,3,4 and it is concluded that the NIM stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold
Prediction Confidence Score
References
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- Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
- V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
- Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
Frequently Asked Questions
Q: What is the prediction methodology for NIM stock?A: NIM stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Pearson Correlation
Q: Is NIM stock a buy or sell?
A: The dominant strategy among neural network is to Hold NIM Stock.
Q: Is NIMY RESOURCES LIMITED stock a good investment?
A: The consensus rating for NIMY RESOURCES LIMITED is Hold and is assigned short-term Caa2 & long-term B1 estimated rating.
Q: What is the consensus rating of NIM stock?
A: The consensus rating for NIM is Hold.
Q: What is the prediction period for NIM stock?
A: The prediction period for NIM is 6 Month
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