MGF MAGELLAN GLOBAL FUND. (Forecast)

Outlook: MAGELLAN GLOBAL FUND. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 05 Feb 2023 for (n+4 weeks)
Methodology : Modular Neural Network (Social Media Sentiment Analysis)

Abstract

MAGELLAN GLOBAL FUND. prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the MGF stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Sell

Key Points

1. Technical Analysis with Algorithmic Trading
2. Stock Rating
3. What is the use of Markov decision process?

MGF Target Price Prediction Modeling Methodology

We consider MAGELLAN GLOBAL FUND. Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of MGF 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(Polynomial 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(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+4 weeks) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of MGF 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?

MGF Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: MGF MAGELLAN GLOBAL FUND.
Time series to forecast n: 05 Feb 2023 for (n+4 weeks)

According to price forecasts for (n+4 weeks) 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%

IFRS Reconciliation Adjustments for MAGELLAN GLOBAL FUND.

1. For example, an entity may use this condition to designate financial liabilities as at fair value through profit or loss if it meets the principle in paragraph 4.2.2(b) and the entity has financial assets and financial liabilities that share one or more risks and those risks are managed and evaluated on a fair value basis in accordance with a documented policy of asset and liability management. An example could be an entity that has issued 'structured products' containing multiple embedded derivatives and manages the resulting risks on a fair value basis using a mix of derivative and non-derivative financial instruments
2. If changes are made in addition to those changes required by interest rate benchmark reform to the financial asset or financial liability designated in a hedging relationship (as described in paragraphs 5.4.6–5.4.8) or to the designation of the hedging relationship (as required by paragraph 6.9.1), an entity shall first apply the applicable requirements in this Standard to determine if those additional changes result in the discontinuation of hedge accounting. If the additional changes do not result in the discontinuation of hedge accounting, an entity shall amend the formal designation of the hedging relationship as specified in paragraph 6.9.1.
3. For the avoidance of doubt, the effects of replacing the original counterparty with a clearing counterparty and making the associated changes as described in paragraph 6.5.6 shall be reflected in the measurement of the hedging instrument and therefore in the assessment of hedge effectiveness and the measurement of hedge effectiveness
4. For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).

*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

MAGELLAN GLOBAL FUND. is assigned short-term Ba1 & long-term Ba1 estimated rating. MAGELLAN GLOBAL FUND. prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the MGF stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Sell

MGF MAGELLAN GLOBAL FUND. Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba2	C
Balance Sheet	Caa2	C
Leverage Ratios	B1	Ba2
Cash Flow	B3	Baa2
Rates of Return and Profitability	B3	B3

*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: 87 out of 100 with 501 signals.

References

1. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
2. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
3. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
4. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
5. Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
6. V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
7. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71

Frequently Asked Questions

Q: What is the prediction methodology for MGF stock?
A: MGF stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression
Q: Is MGF stock a buy or sell?
A: The dominant strategy among neural network is to Sell MGF Stock.
Q: Is MAGELLAN GLOBAL FUND. stock a good investment?
A: The consensus rating for MAGELLAN GLOBAL FUND. is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of MGF stock?
A: The consensus rating for MGF is Sell.
Q: What is the prediction period for MGF stock?
A: The prediction period for MGF is (n+4 weeks)

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