Modelling A.I. in Economics

NVCN Neovasc Inc. Common Shares (Forecast)

Outlook: Neovasc Inc. Common Shares assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 21 Dec 2022 for (n+3 month)
Methodology : Ensemble Learning (ML)

Abstract

Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person's interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).(Rouf, N., Malik, M.B., Arif, T., Sharma, S., Singh, S., Aich, S. and Kim, H.C., 2021. Stock market prediction using machine learning techniques: a decade survey on methodologies, recent developments, and future directions. Electronics, 10(21), p.2717.) We evaluate Neovasc Inc. Common Shares prediction models with Ensemble Learning (ML) and Chi-Square1,2,3,4 and conclude that the NVCN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

  1. Can we predict stock market using machine learning?
  2. How useful are statistical predictions?
  3. Is it better to buy and sell or hold?

NVCN Target Price Prediction Modeling Methodology

We consider Neovasc Inc. Common Shares Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of NVCN 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(Chi-Square)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(Ensemble Learning (ML)) X S(n):→ (n+3 month) i = 1 n s i

n:Time series to forecast

p:Price signals of NVCN 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?

NVCN Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: NVCN Neovasc Inc. Common Shares
Time series to forecast n: 21 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

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 Neovasc Inc. Common Shares

  1. A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
  2. If a financial asset contains a contractual term that could change the timing or amount of contractual cash flows (for example, if the asset can be prepaid before maturity or its term can be extended), the entity must determine whether the contractual cash flows that could arise over the life of the instrument due to that contractual term are solely payments of principal and interest on the principal amount outstanding. To make this determination, the entity must assess the contractual cash flows that could arise both before, and after, the change in contractual cash flows. The entity may also need to assess the nature of any contingent event (ie the trigger) that would change the timing or amount of the contractual cash flows. While the nature of the contingent event in itself is not a determinative factor in assessing whether the contractual cash flows are solely payments of principal and interest, it may be an indicator. For example, compare a financial instrument with an interest rate that is reset to a higher rate if the debtor misses a particular number of payments to a financial instrument with an interest rate that is reset to a higher rate if a specified equity index reaches a particular level. It is more likely in the former case that the contractual cash flows over the life of the instrument will be solely payments of principal and interest on the principal amount outstanding because of the relationship between missed payments and an increase in credit risk. (See also paragraph B4.1.18.)
  3. For the purpose of applying the requirement in paragraph 6.5.12 in order to determine whether the hedged future cash flows are expected to occur, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
  4. Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.

*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

Neovasc Inc. Common Shares assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Ensemble Learning (ML) with Chi-Square1,2,3,4 and conclude that the NVCN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

NVCN Neovasc Inc. Common Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Caa2
Balance SheetBa3Caa2
Leverage RatiosCaa2C
Cash FlowBaa2Ba2
Rates of Return and ProfitabilityBaa2C

*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: 77 out of 100 with 491 signals.

References

  1. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
  2. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
  3. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
  4. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
  5. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
  6. Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
  7. 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
Frequently Asked QuestionsQ: What is the prediction methodology for NVCN stock?
A: NVCN stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Chi-Square
Q: Is NVCN stock a buy or sell?
A: The dominant strategy among neural network is to Buy NVCN Stock.
Q: Is Neovasc Inc. Common Shares stock a good investment?
A: The consensus rating for Neovasc Inc. Common Shares is Buy and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of NVCN stock?
A: The consensus rating for NVCN is Buy.
Q: What is the prediction period for NVCN stock?
A: The prediction period for NVCN is (n+3 month)

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