LON:SDY SPEEDY HIRE PLC

Outlook: SPEEDY HIRE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 25 Mar 2023 for (n+3 month)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

SPEEDY HIRE PLC prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Beta^1,2,3,4 and it is concluded that the LON:SDY stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Key Points

1. Technical Analysis with Algorithmic Trading
2. Short/Long Term Stocks
3. Buy, Sell and Hold Signals

LON:SDY Target Price Prediction Modeling Methodology

We consider SPEEDY HIRE PLC Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of LON:SDY 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(Beta)^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 (Financial Sentiment Analysis)) X S(n):→ (n+3 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:SDY 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:SDY Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:SDY SPEEDY HIRE PLC
Time series to forecast n: 25 Mar 2023 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

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 SPEEDY HIRE PLC

1. The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
2. 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.
3. A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
4. An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.

*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

SPEEDY HIRE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. SPEEDY HIRE PLC prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Beta^1,2,3,4 and it is concluded that the LON:SDY stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

LON:SDY SPEEDY HIRE PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba3	C
Balance Sheet	C	Baa2
Leverage Ratios	C	B1
Cash Flow	Ba3	C
Rates of Return and Profitability	Baa2	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: 87 out of 100 with 787 signals.

References

1. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
2. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
3. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
4. Li L, Chen S, Kleban J, Gupta A. 2014. Counterfactual estimation and optimization of click metrics for search engines: a case study. In Proceedings of the 24th International Conference on the World Wide Web, pp. 929–34. New York: ACM
5. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
6. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
7. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42

Frequently Asked Questions

Q: What is the prediction methodology for LON:SDY stock?
A: LON:SDY stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Beta
Q: Is LON:SDY stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:SDY Stock.
Q: Is SPEEDY HIRE PLC stock a good investment?
A: The consensus rating for SPEEDY HIRE PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:SDY stock?
A: The consensus rating for LON:SDY is Hold.
Q: What is the prediction period for LON:SDY stock?
A: The prediction period for LON:SDY is (n+3 month)

Premium

• Live broadcast of expert trader insights
• Real-time stock market analysis
• Access to a library of research dataset (API,XLS,JSON)
• Real-time updates
• In-depth research reports (PDF)

Login