HCM HUTCHMED (China) Limited American Depositary Shares

Outlook: HUTCHMED (China) Limited American Depositary Shares assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 20 Dec 2022 for (n+4 weeks)
Methodology : Multi-Task Learning (ML)

Abstract

Predicting stock market prices is crucial subject at the present economy. Hence, the tendency of researchers towards new opportunities to predict the stock market has been increased. Researchers have found that, historical stock data and Search Engine Queries, social mood from user generated content in sources like Twitter, Web News has a predictive relationship to the future stock prices. Lack of information such as social mood was there in past studies and in this research, we discuss an effective method to analyze multiple information sources to fill the information gap and predict an accurate future value.(Parray, I.R., Khurana, S.S., Kumar, M. and Altalbe, A.A., 2020. Time series data analysis of stock price movement using machine learning techniques. Soft Computing, 24(21), pp.16509-16517.) We evaluate HUTCHMED (China) Limited American Depositary Shares prediction models with Multi-Task Learning (ML) and Multiple Regression^1,2,3,4 and conclude that the HCM stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

Key Points

1. Is now good time to invest?
2. Market Risk
3. What is prediction model?

HCM Target Price Prediction Modeling Methodology

We consider HUTCHMED (China) Limited American Depositary Shares Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of HCM 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(Multiple 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(Multi-Task Learning (ML)) X S(n):→ (n+4 weeks) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of HCM 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?

HCM Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: HCM HUTCHMED (China) Limited American Depositary Shares
Time series to forecast n: 20 Dec 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

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%

IFRS Reconciliation Adjustments for HUTCHMED (China) Limited American Depositary Shares

1. There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
2. An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.
3. 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.
4. If such a mismatch would be created or enlarged, the entity is required to present all changes in fair value (including the effects of changes in the credit risk of the liability) in profit or loss. If such a mismatch would not be created or enlarged, the entity is required to present the effects of changes in the liability's credit risk in other comprehensive income.

*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.

Conclusions

HUTCHMED (China) Limited American Depositary Shares assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Multi-Task Learning (ML) with Multiple Regression^1,2,3,4 and conclude that the HCM stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

HCM HUTCHMED (China) Limited American Depositary Shares Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	C	B3
Balance Sheet	C	Ba3
Leverage Ratios	Baa2	Caa2
Cash Flow	Caa2	B3
Rates of Return and Profitability	Baa2	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?

Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 814 signals.

References

1. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
2. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
3. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
4. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
5. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
6. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
7. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52

Frequently Asked Questions

Q: What is the prediction methodology for HCM stock?
A: HCM stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Multiple Regression
Q: Is HCM stock a buy or sell?
A: The dominant strategy among neural network is to Hold HCM Stock.
Q: Is HUTCHMED (China) Limited American Depositary Shares stock a good investment?
A: The consensus rating for HUTCHMED (China) Limited American Depositary Shares is Hold and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of HCM stock?
A: The consensus rating for HCM is Hold.
Q: What is the prediction period for HCM stock?
A: The prediction period for HCM is (n+4 weeks)

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