**Outlook:**RANK GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 03 Mar 2023**for (n+4 weeks)

**Methodology :**Statistical Inference (ML)

## Abstract

RANK GROUP PLC prediction model is evaluated with Statistical Inference (ML) and Beta^{1,2,3,4}and it is concluded that the LON:RNK 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

- What is prediction model?
- How useful are statistical predictions?
- What is neural prediction?

## LON:RNK Target Price Prediction Modeling Methodology

We consider RANK GROUP PLC Decision Process with Statistical Inference (ML) where A is the set of discrete actions of LON:RNK 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Statistical Inference (ML)) X S(n):→ (n+4 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of LON:RNK 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:RNK Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:RNK RANK GROUP PLC

**Time series to forecast n: 03 Mar 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 RANK GROUP PLC

- The risk of a default occurring on financial instruments that have comparable credit risk is higher the longer the expected life of the instrument; for example, the risk of a default occurring on an AAA-rated bond with an expected life of 10 years is higher than that on an AAA-rated bond with an expected life of five years.
- An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.
- For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).
- If a guarantee provided by an entity to pay for default losses on a transferred asset prevents the transferred asset from being derecognised to the extent of the continuing involvement, the transferred asset at the date of the transfer is measured at the lower of (i) the carrying amount of the asset and (ii) the maximum amount of the consideration received in the transfer that the entity could be required to repay ('the guarantee amount'). The associated liability is initially measured at the guarantee amount plus the fair value of the guarantee (which is normally the consideration received for the guarantee). Subsequently, the initial fair value of the guarantee is recognised in profit or loss when (or as) the obligation is satisfied (in accordance with the principles of IFRS 15) and the carrying value of the asset is reduced by any loss allowance.

*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

RANK GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. RANK GROUP PLC prediction model is evaluated with Statistical Inference (ML) and Beta^{1,2,3,4} and it is concluded that the LON:RNK 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**

### LON:RNK RANK GROUP PLC Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Income Statement | Ba3 | B2 |

Balance Sheet | Baa2 | Baa2 |

Leverage Ratios | Caa2 | C |

Cash Flow | Caa2 | Baa2 |

Rates of Return and Profitability | B1 | 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

## References

- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
- Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
- Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
- R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
- Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
- Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106

## Frequently Asked Questions

Q: What is the prediction methodology for LON:RNK stock?A: LON:RNK stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Beta

Q: Is LON:RNK stock a buy or sell?

A: The dominant strategy among neural network is to Sell LON:RNK Stock.

Q: Is RANK GROUP PLC stock a good investment?

A: The consensus rating for RANK GROUP PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of LON:RNK stock?

A: The consensus rating for LON:RNK is Sell.

Q: What is the prediction period for LON:RNK stock?

A: The prediction period for LON:RNK is (n+4 weeks)