Dominant Strategy : Buy
Time series to forecast n: 06 Jun 2023 for 8 Weeks
Methodology : Multi-Task Learning (ML)
Abstract
Alnylam Pharmaceuticals Inc. Common Stock prediction model is evaluated with Multi-Task Learning (ML) and Spearman Correlation1,2,3,4 and it is concluded that the ALNY stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: BuyKey Points
- Can we predict stock market using machine learning?
- Market Risk
- What are the most successful trading algorithms?
ALNY Target Price Prediction Modeling Methodology
We consider Alnylam Pharmaceuticals Inc. Common Stock Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of ALNY 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(Spearman Correlation)5,6,7= X R(Multi-Task Learning (ML)) X S(n):→ 8 Weeks
n:Time series to forecast
p:Price signals of ALNY 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?
ALNY Stock Forecast (Buy or Sell) for 8 Weeks
Sample Set: Neural NetworkStock/Index: ALNY Alnylam Pharmaceuticals Inc. Common Stock
Time series to forecast n: 06 Jun 2023 for 8 Weeks
According to price forecasts for 8 Weeks 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 Alnylam Pharmaceuticals Inc. Common Stock
- When defining default for the purposes of determining the risk of a default occurring, an entity shall apply a default definition that is consistent with the definition used for internal credit risk management purposes for the relevant financial instrument and consider qualitative indicators (for example, financial covenants) when appropriate. However, there is a rebuttable presumption that default does not occur later than when a financial asset is 90 days past due unless an entity has reasonable and supportable information to demonstrate that a more lagging default criterion is more appropriate. The definition of default used for these purposes shall be applied consistently to all financial instruments unless information becomes available that demonstrates that another default definition is more appropriate for a particular financial instrument.
- At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.
- Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.
- An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.
*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
Alnylam Pharmaceuticals Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Alnylam Pharmaceuticals Inc. Common Stock prediction model is evaluated with Multi-Task Learning (ML) and Spearman Correlation1,2,3,4 and it is concluded that the ALNY stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Buy
ALNY Alnylam Pharmaceuticals Inc. Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Ba1 |
Balance Sheet | Caa2 | Baa2 |
Leverage Ratios | Baa2 | C |
Cash Flow | B3 | B1 |
Rates of Return and Profitability | B1 | C |
*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

References
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- Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
- Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
- T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
- P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
- Firth JR. 1957. A synopsis of linguistic theory 1930–1955. In Studies in Linguistic Analysis (Special Volume of the Philological Society), ed. JR Firth, pp. 1–32. Oxford, UK: Blackwell
- 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.
Frequently Asked Questions
Q: What is the prediction methodology for ALNY stock?A: ALNY stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Spearman Correlation
Q: Is ALNY stock a buy or sell?
A: The dominant strategy among neural network is to Buy ALNY Stock.
Q: Is Alnylam Pharmaceuticals Inc. Common Stock stock a good investment?
A: The consensus rating for Alnylam Pharmaceuticals Inc. Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ALNY stock?
A: The consensus rating for ALNY is Buy.
Q: What is the prediction period for ALNY stock?
A: The prediction period for ALNY is 8 Weeks
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