Outlook: Absolute Software Corporation is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 10 Mar 2023 for (n+3 month)
Methodology : Active Learning (ML)

Abstract

Absolute Software Corporation prediction model is evaluated with Active Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the ABST:TSX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

1. Which neural network is best for prediction?
2. Short/Long Term Stocks
3. What is the use of Markov decision process?

ABST:TSX Target Price Prediction Modeling Methodology

We consider Absolute Software Corporation Decision Process with Active Learning (ML) where A is the set of discrete actions of ABST:TSX 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(Logistic Regression)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(Active Learning (ML)) X S(n):→ (n+3 month) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of ABST:TSX 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?

ABST:TSX Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: ABST:TSX Absolute Software Corporation
Time series to forecast n: 10 Mar 2023 for (n+3 month)

According to price forecasts for (n+3 month) 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 Absolute Software Corporation

1. Leverage is a contractual cash flow characteristic of some financial assets. Leverage increases the variability of the contractual cash flows with the result that they do not have the economic characteristics of interest. Stand-alone option, forward and swap contracts are examples of financial assets that include such leverage. Thus, such contracts do not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and cannot be subsequently measured at amortised cost or fair value through other comprehensive income.
2. Amounts presented in other comprehensive income shall not be subsequently transferred to profit or loss. However, the entity may transfer the cumulative gain or loss within equity.
3. The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
4. 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.

*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

Absolute Software Corporation is assigned short-term Ba1 & long-term Ba1 estimated rating. Absolute Software Corporation prediction model is evaluated with Active Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the ABST:TSX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

ABST:TSX Absolute Software Corporation Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3B1
Balance SheetBaa2Baa2
Leverage RatiosBa2Ba3
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityB2Baa2

*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: 78 out of 100 with 682 signals.

References

1. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
2. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
3. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
4. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
5. Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
6. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
7. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
Frequently Asked QuestionsQ: What is the prediction methodology for ABST:TSX stock?
A: ABST:TSX stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Logistic Regression
Q: Is ABST:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell ABST:TSX Stock.
Q: Is Absolute Software Corporation stock a good investment?
A: The consensus rating for Absolute Software Corporation is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ABST:TSX stock?
A: The consensus rating for ABST:TSX is Sell.
Q: What is the prediction period for ABST:TSX stock?
A: The prediction period for ABST:TSX is (n+3 month)