LON:FRES FRESNILLO PLC

Outlook: FRESNILLO PLC assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 22 Dec 2022 for (n+6 month)
Methodology : Modular Neural Network (News Feed Sentiment Analysis)

Abstract

The study of financial markets has been addressed in many works during the last years. Different methods have been used in order to capture the non-linear behavior which is characteristic of these complex systems. The development of profitable strategies has been associated with the predictive character of the market movement, and special attention has been devoted to forecast the trends of financial markets. (Rao, P.S., Srinivas, K. and Mohan, A.K., 2020. A survey on stock market prediction using machine learning techniques. In ICDSMLA 2019 (pp. 923-931). Springer, Singapore.) We evaluate FRESNILLO PLC prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Statistical Hypothesis Testing^1,2,3,4 and conclude that the LON:FRES stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. How do you decide buy or sell a stock?
2. Can machine learning predict?
3. Technical Analysis with Algorithmic Trading

LON:FRES Target Price Prediction Modeling Methodology

We consider FRESNILLO PLC Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of LON:FRES 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(Statistical Hypothesis Testing)^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 (News Feed Sentiment Analysis)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of LON:FRES 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?

LON:FRES Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:FRES FRESNILLO PLC
Time series to forecast n: 22 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 FRESNILLO PLC

1. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
2. 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.
3. When an entity separates the foreign currency basis spread from a financial instrument and excludes it from the designation of that financial instrument as the hedging instrument (see paragraph 6.2.4(b)), the application guidance in paragraphs B6.5.34–B6.5.38 applies to the foreign currency basis spread in the same manner as it is applied to the forward element of a forward contract.
4. The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding

*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

FRESNILLO PLC assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Statistical Hypothesis Testing^1,2,3,4 and conclude that the LON:FRES stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

LON:FRES FRESNILLO PLC Financial Analysis*

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

*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: 80 out of 100 with 483 signals.

References

1. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
2. Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
3. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
4. Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
5. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
6. Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67
7. 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

Frequently Asked Questions

Q: What is the prediction methodology for LON:FRES stock?
A: LON:FRES stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Statistical Hypothesis Testing
Q: Is LON:FRES stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes LON:FRES Stock.
Q: Is FRESNILLO PLC stock a good investment?
A: The consensus rating for FRESNILLO PLC is Wait until speculative trend diminishes and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:FRES stock?
A: The consensus rating for LON:FRES is Wait until speculative trend diminishes.
Q: What is the prediction period for LON:FRES stock?
A: The prediction period for LON:FRES is (n+6 month)

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