AC Investment Research

ABUS Arbutus Biopharma Corporation Common Stock Research Report

Outlook: Arbutus Biopharma Corporation Common Stock assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 23 Dec 2022 for (n+4 weeks)
Methodology : Multi-Task Learning (ML)

Abstract

Stock prediction with data mining techniques is one of the most important issues in finance being investigated by researchers across the globe. Data mining techniques can be used extensively in the financial markets to help investors make qualitative decision. One of the techniques is artificial neural network (ANN). However, in the application of ANN for predicting the financial market the use of technical analysis variables for stock prediction is predominant. In this paper, we present a hybridized approach which combines the use of the variables of technical and fundamental analysis of stock market indicators for prediction of future price of stock in order to improve on the existing approaches. (Vachhani, H., Obiadat, M.S., Thakkar, A., Shah, V., Sojitra, R., Bhatia, J. and Tanwar, S., 2020. Machine learning based stock market analysis: A short survey. In International Conference on Innovative Data Communication Technologies and Application (pp. 12-26). Springer, Cham.) We evaluate Arbutus Biopharma Corporation Common Stock prediction models with Multi-Task Learning (ML) and Independent T-Test1,2,3,4 and conclude that the ABUS 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. How do predictive algorithms actually work?
  2. Trust metric by Neural Network
  3. Can statistics predict the future?

ABUS Target Price Prediction Modeling Methodology

We consider Arbutus Biopharma Corporation Common Stock Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of ABUS 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(Independent T-Test)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(Multi-Task Learning (ML)) X S(n):→ (n+4 weeks) e x rx

n:Time series to forecast

p:Price signals of ABUS 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?

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

Sample Set: Neural Network
Stock/Index: ABUS Arbutus Biopharma Corporation Common Stock
Time series to forecast n: 23 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 Arbutus Biopharma Corporation Common Stock

  1. In the reporting period that includes the date of initial application of these amendments, an entity is not required to present the quantitative information required by paragraph 28(f) of IAS 8.
  2. If a guarantee provided by an entity to pay for default losses on a transferred asset prevents the transferred asset from being derecognised to the extent of the continuing involvement, the transferred asset at the date of the transfer is measured at the lower of (i) the carrying amount of the asset and (ii) the maximum amount of the consideration received in the transfer that the entity could be required to repay ('the guarantee amount'). The associated liability is initially measured at the guarantee amount plus the fair value of the guarantee (which is normally the consideration received for the guarantee). Subsequently, the initial fair value of the guarantee is recognised in profit or loss when (or as) the obligation is satisfied (in accordance with the principles of IFRS 15) and the carrying value of the asset is reduced by any loss allowance.
  3. Paragraph 4.1.1(b) requires an entity to classify a financial asset on the basis of its contractual cash flow characteristics if the financial asset is held within a business model whose objective is to hold assets to collect contractual cash flows or within a business model whose objective is achieved by both collecting contractual cash flows and selling financial assets, unless paragraph 4.1.5 applies. To do so, the condition in paragraphs 4.1.2(b) and 4.1.2A(b) requires an entity to determine whether the asset's contractual cash flows are solely payments of principal and interest on the principal amount outstanding.
  4. 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.

*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

Arbutus Biopharma Corporation Common Stock assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Multi-Task Learning (ML) with Independent T-Test1,2,3,4 and conclude that the ABUS 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

ABUS Arbutus Biopharma Corporation Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3C
Balance SheetBaa2B2
Leverage RatiosBa2Baa2
Cash FlowBaa2B3
Rates of Return and ProfitabilityBaa2Ba2

*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: 92 out of 100 with 569 signals.

References

  1. Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
  2. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
  3. Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701
  4. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
  5. K. Boda and J. Filar. Time consistent dynamic risk measures. Mathematical Methods of Operations Research, 63(1):169–186, 2006
  6. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
  7. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
Frequently Asked QuestionsQ: What is the prediction methodology for ABUS stock?
A: ABUS stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Independent T-Test
Q: Is ABUS stock a buy or sell?
A: The dominant strategy among neural network is to Hold ABUS Stock.
Q: Is Arbutus Biopharma Corporation Common Stock stock a good investment?
A: The consensus rating for Arbutus Biopharma Corporation Common Stock is Hold and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ABUS stock?
A: The consensus rating for ABUS is Hold.
Q: What is the prediction period for ABUS stock?
A: The prediction period for ABUS is (n+4 weeks)

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