NA Nano Labs Ltd American Depositary Shares

Outlook: Nano Labs Ltd American Depositary Shares assigned short-term B2 & long-term B2 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 19 Dec 2022 for (n+1 year)
Methodology : Ensemble Learning (ML)

Abstract

This paper examines the theory and practice of regression techniques for prediction of stock price trend by using a transformed data set in ordinal data format. The original pretransformed data source contains data of heterogeneous data types used for handling of currency values and financial ratios. The data formats in currency values and financial ratios provide a process for computation of stock prices. The transformed data set contains only a standardized ordinal data type which provides a process to measure rankings of stock price trends.(Morris, K.J., Egan, S.D., Linsangan, J.L., Leung, C.K., Cuzzocrea, A. and Hoi, C.S., 2018, December. Token-based adaptive time-series prediction by ensembling linear and non-linear estimators: a machine learning approach for predictive analytics on big stock data. In 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 1486-1491). IEEE.) We evaluate Nano Labs Ltd American Depositary Shares prediction models with Ensemble Learning (ML) and ElasticNet Regression^1,2,3,4 and conclude that the NA stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

Key Points

1. What is Markov decision process in reinforcement learning?
2. Fundemental Analysis with Algorithmic Trading
3. Operational Risk

NA Target Price Prediction Modeling Methodology

We consider Nano Labs Ltd American Depositary Shares Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of NA 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(ElasticNet Regression)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Ensemble Learning (ML)) X S(n):→ (n+1 year) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of NA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

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?

NA Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: NA Nano Labs Ltd American Depositary Shares
Time series to forecast n: 19 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

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%

Adjusted IFRS* Prediction Methods for Nano Labs Ltd American Depositary Shares

1. To make that determination, an entity must assess whether it expects that the effects of changes in the liability's credit risk will be offset in profit or loss by a change in the fair value of another financial instrument measured at fair value through profit or loss. Such an expectation must be based on an economic relationship between the characteristics of the liability and the characteristics of the other financial instrument.
2. The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
3. Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
4. An entity must look through until it can identify the underlying pool of instruments that are creating (instead of passing through) the cash flows. This is the underlying pool of financial instruments.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Nano Labs Ltd American Depositary Shares assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with ElasticNet Regression^1,2,3,4 and conclude that the NA stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

Financial State Forecast for NA Nano Labs Ltd American Depositary Shares Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B2
Operational Risk	39	33
Market Risk	72	52
Technical Analysis	33	41
Fundamental Analysis	74	61
Risk Unsystematic	58	77

Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 665 signals.

References

1. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
2. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
3. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
4. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
5. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
6. Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
7. Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.

Frequently Asked Questions

Q: What is the prediction methodology for NA stock?
A: NA stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and ElasticNet Regression
Q: Is NA stock a buy or sell?
A: The dominant strategy among neural network is to Sell NA Stock.
Q: Is Nano Labs Ltd American Depositary Shares stock a good investment?
A: The consensus rating for Nano Labs Ltd American Depositary Shares is Sell and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of NA stock?
A: The consensus rating for NA is Sell.
Q: What is the prediction period for NA stock?
A: The prediction period for NA is (n+1 year)

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