SMWB Similarweb Ltd. Ordinary Shares

Outlook: Similarweb Ltd. Ordinary Shares assigned short-term B2 & long-term Ba2 forecasted stock rating.
Dominant Strategy : Buy
Time series to forecast n: 07 Dec 2022 for (n+6 month)
Methodology : Multi-Task Learning (ML)

Abstract

Prediction of the Stock Market is a challenging task in predicting the stock prices in the future. Due to the fluctuating nature of the stock, the stock market is too difficult to predict. Stock prices are constantly changing every day. Estimating of the stock market has a high demand for stock customers. Applying all extracted rules at any time is a major challenge to estimate the future stock price with high accuracy. The latest prediction techniques adopted for the stock market such as Artificial Neural Network, Neuro-Fuzzy System, Time Series Linear Models (TSLM), Recurrent Neural Network (RNN).(Devadoss, A.V. and Ligori, T.A.A., 2013. Stock prediction using artificial neural networks. International Journal of Data Mining Techniques and Applications, 2(1), pp.283-291.) We evaluate Similarweb Ltd. Ordinary Shares prediction models with Multi-Task Learning (ML) and Stepwise Regression^1,2,3,4 and conclude that the SMWB stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy SMWB stock.

Key Points

1. How accurate is machine learning in stock market?
2. Game Theory
3. Decision Making

SMWB Target Price Prediction Modeling Methodology

We consider Similarweb Ltd. Ordinary Shares Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of SMWB 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(Stepwise Regression)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Multi-Task Learning (ML)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of SMWB 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?

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

Sample Set: Neural Network
Stock/Index: SMWB Similarweb Ltd. Ordinary Shares
Time series to forecast n: 07 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy SMWB stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Similarweb Ltd. Ordinary Shares

1. If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
2. If an entity previously accounted for a derivative liability that is linked to, and must be settled by, delivery of an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) at cost in accordance with IAS 39, it shall measure that derivative liability at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings of the reporting period that includes the date of initial application.
3. In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.
4. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Similarweb Ltd. Ordinary Shares assigned short-term B2 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Stepwise Regression^1,2,3,4 and conclude that the SMWB stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy SMWB stock.

Financial State Forecast for SMWB Similarweb Ltd. Ordinary Shares Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Ba2
Operational Risk	31	36
Market Risk	88	84
Technical Analysis	70	50
Fundamental Analysis	46	82
Risk Unsystematic	53	85

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 618 signals.

References

1. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
2. Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
3. Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
4. Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
5. Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
6. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
7. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008

Frequently Asked Questions

Q: What is the prediction methodology for SMWB stock?
A: SMWB stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Stepwise Regression
Q: Is SMWB stock a buy or sell?
A: The dominant strategy among neural network is to Buy SMWB Stock.
Q: Is Similarweb Ltd. Ordinary Shares stock a good investment?
A: The consensus rating for Similarweb Ltd. Ordinary Shares is Buy and assigned short-term B2 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of SMWB stock?
A: The consensus rating for SMWB is Buy.
Q: What is the prediction period for SMWB stock?
A: The prediction period for SMWB is (n+6 month)

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