What are the most successful trading algorithms? (CMCM Stock Forecast)

Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares Research Report

Summary

Prediction of future movement of stock prices has been a subject matter of many research work. In this work, we propose a hybrid approach for stock price prediction using machine learning and deep learning-based methods. We evaluate Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares prediction models with Inductive Learning (ML) and ElasticNet Regression1,2,3,4 and conclude that the CMCM stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold CMCM stock.

Key Points

  1. Is it better to buy and sell or hold?
  2. What are buy sell or hold recommendations?
  3. Can machine learning predict?

CMCM Target Price Prediction Modeling Methodology

We consider Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares Stock Decision Process with Inductive Learning (ML) where A is the set of discrete actions of CMCM 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= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Inductive Learning (ML)) X S(n):→ (n+3 month) i = 1 n s i

n:Time series to forecast

p:Price signals of CMCM 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?

CMCM Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: CMCM Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares
Time series to forecast n: 24 Nov 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold CMCM stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares

  1. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
  2. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
  3. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
  4. 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.

*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

Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Inductive Learning (ML) with ElasticNet Regression1,2,3,4 and conclude that the CMCM stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold CMCM stock.

Financial State Forecast for CMCM Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B1
Operational Risk 4990
Market Risk6963
Technical Analysis6441
Fundamental Analysis5678
Risk Unsystematic4930

Prediction Confidence Score

Trust metric by Neural Network: 86 out of 100 with 671 signals.

References

  1. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
  2. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  3. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
  4. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
  5. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
  6. Harris ZS. 1954. Distributional structure. Word 10:146–62
  7. R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
Frequently Asked QuestionsQ: What is the prediction methodology for CMCM stock?
A: CMCM stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and ElasticNet Regression
Q: Is CMCM stock a buy or sell?
A: The dominant strategy among neural network is to Hold CMCM Stock.
Q: Is Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares stock a good investment?
A: The consensus rating for Cheetah Mobile Inc. American Depositary Shares each representing fifty (50) Class A Ordinary Shares is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of CMCM stock?
A: The consensus rating for CMCM is Hold.
Q: What is the prediction period for CMCM stock?
A: The prediction period for CMCM is (n+3 month)

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