LON:53GW FULLER, SMITH & TURNER PLC (Forecast)

Outlook: FULLER, SMITH & TURNER PLC assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 24 Dec 2022 for (n+16 weeks)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

The stock market is an interesting industry to study. There are various variations present in it. Many experts have been studying and researching on the various trends that the stock market goes through. One of the major studies has been the attempt to predict the stock prices of various companies based on historical data. Prediction of stock prices will greatly help people to understand where and how to invest so that the risk of losing money is minimized.(Kohara, K., Ishikawa, T., Fukuhara, Y. and Nakamura, Y., 1997. Stock price prediction using prior knowledge and neural networks. Intelligent Systems in Accounting, Finance & Management, 6(1), pp.11-22.) We evaluate FULLER, SMITH & TURNER PLC prediction models with Modular Neural Network (Market Volatility Analysis) and Paired T-Test^1,2,3,4 and conclude that the LON:53GW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

Key Points

1. Stock Forecast Based On a Predictive Algorithm
2. Fundemental Analysis with Algorithmic Trading
3. How do you pick a stock?

LON:53GW Target Price Prediction Modeling Methodology

We consider FULLER, SMITH & TURNER PLC Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:53GW 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(Paired T-Test)^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 (Market Volatility Analysis)) X S(n):→ (n+16 weeks) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of LON:53GW 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:53GW Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: LON:53GW FULLER, SMITH & TURNER PLC
Time series to forecast n: 24 Dec 2022 for (n+16 weeks)

According to price forecasts for (n+16 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 FULLER, SMITH & TURNER PLC

1. Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
2. When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
3. Such designation may be used whether paragraph 4.3.3 requires the embedded derivatives to be separated from the host contract or prohibits such separation. However, paragraph 4.3.5 would not justify designating the hybrid contract as at fair value through profit or loss in the cases set out in paragraph 4.3.5(a) and (b) because doing so would not reduce complexity or increase reliability.
4. Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.

*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

FULLER, SMITH & TURNER PLC assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Paired T-Test^1,2,3,4 and conclude that the LON:53GW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

LON:53GW FULLER, SMITH & TURNER PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B1	C
Balance Sheet	Caa2	C
Leverage Ratios	Caa2	Baa2
Cash Flow	Ba3	Baa2
Rates of Return and Profitability	C	Caa2

*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: 85 out of 100 with 662 signals.

References

1. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can neural networks predict stock market?(ATVI Stock Forecast). AC Investment Research Journal, 101(3).
3. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
4. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
5. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
6. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
7. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.

Frequently Asked Questions

Q: What is the prediction methodology for LON:53GW stock?
A: LON:53GW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Paired T-Test
Q: Is LON:53GW stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:53GW Stock.
Q: Is FULLER, SMITH & TURNER PLC stock a good investment?
A: The consensus rating for FULLER, SMITH & TURNER PLC is Sell and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:53GW stock?
A: The consensus rating for LON:53GW is Sell.
Q: What is the prediction period for LON:53GW stock?
A: The prediction period for LON:53GW is (n+16 weeks)

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