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

**Dominant Strategy :**SellWait until speculative trend diminishes

**Time series to forecast n: 31 Jan 2023**for (n+8 weeks)

**Methodology :**Modular Neural Network (Speculative Sentiment Analysis)

## Abstract

IMMOTION GROUP PLC prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Polynomial Regression^{1,2,3,4}and it is concluded that the LON:IMMO stock is predictable in the short/long term.

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: SellWait until speculative trend diminishes**

## Key Points

- Trading Signals
- How do you decide buy or sell a stock?
- What is neural prediction?

## LON:IMMO Target Price Prediction Modeling Methodology

We consider IMMOTION GROUP PLC Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of LON:IMMO 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+8 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:IMMO 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:IMMO Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:IMMO IMMOTION GROUP PLC

**Time series to forecast n: 31 Jan 2023**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: SellWait 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 IMMOTION GROUP PLC

- There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
- The significance of a change in the credit risk since initial recognition depends on the risk of a default occurring as at initial recognition. Thus, a given change, in absolute terms, in the risk of a default occurring will be more significant for a financial instrument with a lower initial risk of a default occurring compared to a financial instrument with a higher initial risk of a default occurring.
- If an entity measures a hybrid contract at fair value in accordance with paragraphs 4.1.2A, 4.1.4 or 4.1.5 but the fair value of the hybrid contract had not been measured in comparative reporting periods, the fair value of the hybrid contract in the comparative reporting periods shall be the sum of the fair values of the components (ie the non-derivative host and the embedded derivative) at the end of each comparative reporting period if the entity restates prior periods (see paragraph 7.2.15).
- When measuring a loss allowance for a lease receivable, the cash flows used for determining the expected credit losses should be consistent with the cash flows used in measuring the lease receivable in accordance with IFRS 16 Leases.

*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

IMMOTION GROUP PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. IMMOTION GROUP PLC prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Polynomial Regression^{1,2,3,4} and it is concluded that the LON:IMMO stock is predictable in the short/long term. ** According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: SellWait until speculative trend diminishes**

### LON:IMMO IMMOTION GROUP PLC Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | Baa2 | Baa2 |

Balance Sheet | C | Baa2 |

Leverage Ratios | B2 | Caa2 |

Cash Flow | B1 | B3 |

Rates of Return and Profitability | C | Baa2 |

*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

- Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
- M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
- Brailsford, T.J. R.W. Faff (1996), "An evaluation of volatility forecasting techniques," Journal of Banking Finance, 20, 419–438.
- Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
- M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]

## Frequently Asked Questions

Q: What is the prediction methodology for LON:IMMO stock?A: LON:IMMO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Polynomial Regression

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

A: The dominant strategy among neural network is to SellWait until speculative trend diminishes LON:IMMO Stock.

Q: Is IMMOTION GROUP PLC stock a good investment?

A: The consensus rating for IMMOTION GROUP PLC is SellWait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.

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

A: The consensus rating for LON:IMMO is SellWait until speculative trend diminishes.

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

A: The prediction period for LON:IMMO is (n+8 weeks)

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