Outlook: TRxADE HEALTH Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 05 Feb 2023 for (n+6 month)
Methodology : Transductive Learning (ML)

## Abstract

TRxADE HEALTH Inc. Common Stock prediction model is evaluated with Transductive Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the MEDS stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

## Key Points

1. How do you know when a stock will go up or down?
2. Stock Forecast Based On a Predictive Algorithm
3. Probability Distribution

## MEDS Target Price Prediction Modeling Methodology

We consider TRxADE HEALTH Inc. Common Stock Decision Process with Transductive Learning (ML) where A is the set of discrete actions of MEDS 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(ElasticNet 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(Transductive Learning (ML)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of MEDS 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?

## MEDS Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: MEDS TRxADE HEALTH Inc. Common Stock
Time series to forecast n: 05 Feb 2023 for (n+6 month)

According to price forecasts for (n+6 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%

1. If an entity measures a hybrid contract at fair value in accordance with paragraphs 4.1.2A, 4.1.4 or 4.1.5 but the fair value of the hybrid contract had not been measured in comparative reporting periods, the fair value of the hybrid contract in the comparative reporting periods shall be the sum of the fair values of the components (ie the non-derivative host and the embedded derivative) at the end of each comparative reporting period if the entity restates prior periods (see paragraph 7.2.15).
2. When assessing a modified time value of money element, an entity must consider factors that could affect future contractual cash flows. For example, if an entity is assessing a bond with a five-year term and the variable interest rate is reset every six months to a five-year rate, the entity cannot conclude that the contractual cash flows are solely payments of principal and interest on the principal amount outstanding simply because the interest rate curve at the time of the assessment is such that the difference between a five-year interest rate and a six-month interest rate is not significant. Instead, the entity must also consider whether the relationship between the five-year interest rate and the six-month interest rate could change over the life of the instrument such that the contractual (undiscounted) cash flows over the life of the instrument could be significantly different from the (undiscounted) benchmark cash flows. However, an entity must consider only reasonably possible scenarios instead of every possible scenario. If an entity concludes that the contractual (undiscounted) cash flows could be significantly different from the (undiscounted) benchmark cash flows, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and therefore cannot be measured at amortised cost or fair value through other comprehensive income.
3. The following example describes a situation in which an accounting mismatch would be created in profit or loss if the effects of changes in the credit risk of the liability were presented in other comprehensive income. A mortgage bank provides loans to customers and funds those loans by selling bonds with matching characteristics (eg amount outstanding, repayment profile, term and currency) in the market. The contractual terms of the loan permit the mortgage customer to prepay its loan (ie satisfy its obligation to the bank) by buying the corresponding bond at fair value in the market and delivering that bond to the mortgage bank. As a result of that contractual prepayment right, if the credit quality of the bond worsens (and, thus, the fair value of the mortgage bank's liability decreases), the fair value of the mortgage bank's loan asset also decreases. The change in the fair value of the asset reflects the mortgage customer's contractual right to prepay the mortgage loan by buying the underlying bond at fair value (which, in this example, has decreased) and delivering the bond to the mortgage bank. Consequently, the effects of changes in the credit risk of the liability (the bond) will be offset in profit or loss by a corresponding change in the fair value of a financial asset (the loan). If the effects of changes in the liability's credit risk were presented in other comprehensive income there would be an accounting mismatch in profit or loss. Consequently, the mortgage bank is required to present all changes in fair value of the liability (including the effects of changes in the liability's credit risk) in profit or loss.
4. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.

*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

TRxADE HEALTH Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. TRxADE HEALTH Inc. Common Stock prediction model is evaluated with Transductive Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the MEDS stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

### MEDS TRxADE HEALTH Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2B3
Balance SheetBa3B3
Leverage RatiosBaa2Baa2
Cash FlowBa3C
Rates of Return and ProfitabilityBaa2Baa2

*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: 88 out of 100 with 877 signals.

## References

1. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
2. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
3. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
4. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
5. Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
6. J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.
7. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
Frequently Asked QuestionsQ: What is the prediction methodology for MEDS stock?
A: MEDS stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and ElasticNet Regression
Q: Is MEDS stock a buy or sell?
A: The dominant strategy among neural network is to Sell MEDS Stock.
Q: Is TRxADE HEALTH Inc. Common Stock stock a good investment?
A: The consensus rating for TRxADE HEALTH Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of MEDS stock?
A: The consensus rating for MEDS is Sell.
Q: What is the prediction period for MEDS stock?
A: The prediction period for MEDS is (n+6 month)