Outlook: Bruush Oral Care Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 07 Jan 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Market News Sentiment Analysis)

## Abstract

Bruush Oral Care Inc. Common Stock prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the BRSH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

## Key Points

1. Reaction Function
2. What is prediction in deep learning?
3. Prediction Modeling

## BRSH Target Price Prediction Modeling Methodology

We consider Bruush Oral Care Inc. Common Stock Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of BRSH 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(Pearson Correlation)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of BRSH 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?

## BRSH Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: BRSH Bruush Oral Care Inc. Common Stock
Time series to forecast n: 07 Jan 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) 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%

## IFRS Reconciliation Adjustments for Bruush Oral Care Inc. Common Stock

1. Conversely, if the critical terms of the hedging instrument and the hedged item are not closely aligned, there is an increased level of uncertainty about the extent of offset. Consequently, the hedge effectiveness during the term of the hedging relationship is more difficult to predict. In such a situation it might only be possible for an entity to conclude on the basis of a quantitative assessment that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6). In some situations a quantitative assessment might also be needed to assess whether the hedge ratio used for designating the hedging relationship meets the hedge effectiveness requirements (see paragraphs B6.4.9–B6.4.11). An entity can use the same or different methods for those two different purposes.
2. A similar example of a non-financial item is a specific type of crude oil from a particular oil field that is priced off the relevant benchmark crude oil. If an entity sells that crude oil under a contract using a contractual pricing formula that sets the price per barrel at the benchmark crude oil price minus CU10 with a floor of CU15, the entity can designate as the hedged item the entire cash flow variability under the sales contract that is attributable to the change in the benchmark crude oil price. However, the entity cannot designate a component that is equal to the full change in the benchmark crude oil price. Hence, as long as the forward price (for each delivery) does not fall below CU25, the hedged item has the same cash flow variability as a crude oil sale at the benchmark crude oil price (or with a positive spread). However, if the forward price for any delivery falls below CU25, the hedged item has a lower cash flow variability than a crude oil sale at the benchmark crude oil price (or with a positive spread).
3. In some circumstances an entity does not have reasonable and supportable information that is available without undue cost or effort to measure lifetime expected credit losses on an individual instrument basis. In that case, lifetime expected credit losses shall be recognised on a collective basis that considers comprehensive credit risk information. This comprehensive credit risk information must incorporate not only past due information but also all relevant credit information, including forward-looking macroeconomic information, in order to approximate the result of recognising lifetime expected credit losses when there has been a significant increase in credit risk since initial recognition on an individual instrument level.
4. For example, an entity may use this condition to designate financial liabilities as at fair value through profit or loss if it meets the principle in paragraph 4.2.2(b) and the entity has financial assets and financial liabilities that share one or more risks and those risks are managed and evaluated on a fair value basis in accordance with a documented policy of asset and liability management. An example could be an entity that has issued 'structured products' containing multiple embedded derivatives and manages the resulting risks on a fair value basis using a mix of derivative and non-derivative financial instruments

*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

Bruush Oral Care Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Bruush Oral Care Inc. Common Stock prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the BRSH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

### BRSH Bruush Oral Care Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3C
Balance SheetB3B2
Leverage RatiosCB3
Cash FlowCBaa2
Rates of Return and ProfitabilityCBa3

*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: 79 out of 100 with 880 signals.

## References

1. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can neural networks predict stock market?(ATVI Stock Forecast). AC Investment Research Journal, 101(3).
2. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
3. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
4. 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
5. D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.
6. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., What are buy sell or hold recommendations?(AIRC Stock Forecast). AC Investment Research Journal, 101(3).
7. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
Frequently Asked QuestionsQ: What is the prediction methodology for BRSH stock?
A: BRSH stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation
Q: Is BRSH stock a buy or sell?
A: The dominant strategy among neural network is to Sell BRSH Stock.
Q: Is Bruush Oral Care Inc. Common Stock stock a good investment?
A: The consensus rating for Bruush Oral Care Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BRSH stock?
A: The consensus rating for BRSH is Sell.
Q: What is the prediction period for BRSH stock?
A: The prediction period for BRSH is (n+16 weeks)