Dominant Strategy : Buy
Time series to forecast n: 13 Mar 2023 for (n+6 month)
Methodology : Active Learning (ML)
Abstract
FinVolution Group American Depositary Shares prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the FINV stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: BuyKey Points
- What is the best way to predict stock prices?
- What are the most successful trading algorithms?
- Technical Analysis with Algorithmic Trading
FINV Target Price Prediction Modeling Methodology
We consider FinVolution Group American Depositary Shares Decision Process with Active Learning (ML) where A is the set of discrete actions of FINV 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(Linear Regression)5,6,7= X R(Active Learning (ML)) X S(n):→ (n+6 month)
n:Time series to forecast
p:Price signals of FINV 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?
FINV Stock Forecast (Buy or Sell) for (n+6 month)
Sample Set: Neural NetworkStock/Index: FINV FinVolution Group American Depositary Shares
Time series to forecast n: 13 Mar 2023 for (n+6 month)
According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy
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 FinVolution Group American Depositary Shares
- An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
- Changes in market conditions that give rise to market risk include changes in a benchmark interest rate, the price of another entity's financial instrument, a commodity price, a foreign exchange rate or an index of prices or rates.
- If, in applying paragraph 7.2.44, an entity reinstates a discontinued hedging relationship, the entity shall read references in paragraphs 6.9.11 and 6.9.12 to the date the alternative benchmark rate is designated as a noncontractually specified risk component for the first time as referring to the date of initial application of these amendments (ie the 24-month period for that alternative benchmark rate designated as a non-contractually specified risk component begins from the date of initial application of these amendments).
- An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
*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
FinVolution Group American Depositary Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. FinVolution Group American Depositary Shares prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the FINV stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy
FINV FinVolution Group American Depositary Shares Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Caa2 | B2 |
Balance Sheet | B2 | B3 |
Leverage Ratios | Baa2 | C |
Cash Flow | B1 | B2 |
Rates of Return and Profitability | Baa2 | B3 |
*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

References
- F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
- Abadie A, Imbens GW. 2011. Bias-corrected matching estimators for average treatment effects. J. Bus. Econ. Stat. 29:1–11
- Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
Frequently Asked Questions
Q: What is the prediction methodology for FINV stock?A: FINV stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Linear Regression
Q: Is FINV stock a buy or sell?
A: The dominant strategy among neural network is to Buy FINV Stock.
Q: Is FinVolution Group American Depositary Shares stock a good investment?
A: The consensus rating for FinVolution Group American Depositary Shares is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of FINV stock?
A: The consensus rating for FINV is Buy.
Q: What is the prediction period for FINV stock?
A: The prediction period for FINV is (n+6 month)
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