SATS EchoStar Corporation Common Stock (Forecast)

Outlook: EchoStar Corporation Common Stock assigned short-term B3 & long-term Ba2 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 17 Dec 2022 for (n+1 year)
Methodology : Multi-Task Learning (ML)

Abstract

Different machine learning algorithms are discussed in this literature review. These algorithms can be used for predicting the stock market. The prediction of the stock market is one of the challenging tasks that must have to be handled. In this paper, it is discussed how the machine learning algorithms can be used for predicting the stock value.(Anand, C., 2021. Comparison of stock price prediction models using pre-trained neural networks. Journal of Ubiquitous Computing and Communication Technologies (UCCT), 3(02), pp.122-134.) We evaluate EchoStar Corporation Common Stock prediction models with Multi-Task Learning (ML) and Factor^1,2,3,4 and conclude that the SATS stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

Key Points

1. What is the use of Markov decision process?
2. Stock Rating
3. Stock Forecast Based On a Predictive Algorithm

SATS Target Price Prediction Modeling Methodology

We consider EchoStar Corporation Common Stock Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of SATS 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(Factor)^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+1 year) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of SATS 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?

SATS Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: SATS EchoStar Corporation Common Stock
Time series to forecast n: 17 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) 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%

Adjusted IFRS* Prediction Methods for EchoStar Corporation Common Stock

1. 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.
2. A layer component that includes a prepayment option is not eligible to be designated as a hedged item in a fair value hedge if the prepayment option's fair value is affected by changes in the hedged risk, unless the designated layer includes the effect of the related prepayment option when determining the change in the fair value of the hedged item.
3. However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
4. To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.

*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

EchoStar Corporation Common Stock assigned short-term B3 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Factor^1,2,3,4 and conclude that the SATS stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

Financial State Forecast for SATS EchoStar Corporation Common Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B3	Ba2
Operational Risk	36	65
Market Risk	39	37
Technical Analysis	35	86
Fundamental Analysis	51	62
Risk Unsystematic	70	89

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 876 signals.

References

1. F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
2. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
3. Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
4. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
5. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
6. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
7. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994

Frequently Asked Questions

Q: What is the prediction methodology for SATS stock?
A: SATS stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Factor
Q: Is SATS stock a buy or sell?
A: The dominant strategy among neural network is to Sell SATS Stock.
Q: Is EchoStar Corporation Common Stock stock a good investment?
A: The consensus rating for EchoStar Corporation Common Stock is Sell and assigned short-term B3 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of SATS stock?
A: The consensus rating for SATS is Sell.
Q: What is the prediction period for SATS stock?
A: The prediction period for SATS is (n+1 year)

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