BQ Stock Forecast: A Hold For The Next 16 Weeks

Outlook: Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares is assigned short-term B2 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised :
Dominant Strategy : Hold
Time series to forecast n: for 16 Weeks
Methodology : Modular Neural Network (Market News Sentiment Analysis)
Hypothesis Testing : Wilcoxon Sign-Rank Test
Surveillance : Major exchange and OTC

Summary

Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the BQ stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. Reaction Function
2. Short/Long Term Stocks
3. Understanding Buy, Sell, and Hold Ratings

BQ Target Price Prediction Modeling Methodology

We consider Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of BQ 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(Wilcoxon Sign-Rank Test)^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(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ 16 Weeks $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of BQ stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Market News Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.

Wilcoxon Sign-Rank Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

 

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?

BQ Stock Forecast (Buy or Sell) for 16 Weeks

Sample Set: Neural Network
Stock/Index: BQ Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares
Time series to forecast: 16 Weeks

According to price forecasts for 16 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 Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares

1. When an entity discontinues measuring the financial instrument that gives rise to the credit risk, or a proportion of that financial instrument, at fair value through profit or loss, that financial instrument's fair value at the date of discontinuation becomes its new carrying amount. Subsequently, the same measurement that was used before designating the financial instrument at fair value through profit or loss shall be applied (including amortisation that results from the new carrying amount). For example, a financial asset that had originally been classified as measured at amortised cost would revert to that measurement and its effective interest rate would be recalculated based on its new gross carrying amount on the date of discontinuing measurement at fair value through profit or loss.
2. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
3. IFRS 7 defines credit risk as 'the risk that one party to a financial instrument will cause a financial loss for the other party by failing to discharge an obligation'. The requirement in paragraph 5.7.7(a) relates to the risk that the issuer will fail to perform on that particular liability. It does not necessarily relate to the creditworthiness of the issuer. For example, if an entity issues a collateralised liability and a non-collateralised liability that are otherwise identical, the credit risk of those two liabilities will be different, even though they are issued by the same entity. The credit risk on the collateralised liability will be less than the credit risk of the non-collateralised liability. The credit risk for a collateralised liability may be close to zero.
4. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.

*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

Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares is assigned short-term B2 & long-term Ba3 estimated rating. Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the BQ stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

BQ Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Ba3
Income Statement	B3	C
Balance Sheet	C	Ba3
Leverage Ratios	Ba3	Baa2
Cash Flow	Caa2	Baa2
Rates of Return and Profitability	Ba1	Ba3

*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: 81 out of 100 with 736 signals.

References

1. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
2. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
3. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
4. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
5. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
6. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
7. Athey S, Imbens G, Wager S. 2016a. Efficient inference of average treatment effects in high dimensions via approximate residual balancing. arXiv:1604.07125 [math.ST]

Frequently Asked Questions

Q: What is the prediction methodology for BQ stock?
A: BQ stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Sign-Rank Test
Q: Is BQ stock a buy or sell?
A: The dominant strategy among neural network is to Hold BQ Stock.
Q: Is Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares stock a good investment?
A: The consensus rating for Boqii Holding Limited American Depositary Shares representing Class A Ordinary Shares is Hold and is assigned short-term B2 & long-term Ba3 estimated rating.
Q: What is the consensus rating of BQ stock?
A: The consensus rating for BQ is Hold.
Q: What is the prediction period for BQ stock?
A: The prediction period for BQ is 16 Weeks

People also ask

⚐ What are the top stocks to invest in right now?
☵ What happens to stocks when they're delisted?