Outlook: X2M CONNECT LIMITED assigned short-term B1 & long-term Ba3 forecasted stock rating.
Dominant Strategy : Hold
Time series to forecast n: 18 Dec 2022 for (n+6 month)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

## Abstract

In recent years there has been a significant growth of interest in the incorporation of historical series of variables related to stock prediction into mathematical models or computational algorithms in order to generate predictions or indications about expected price movements.(Xia, Y., Liu, Y. and Chen, Z., 2013, November. Support Vector Regression for prediction of stock trend. In 2013 6th international conference on information management, innovation management and industrial engineering (Vol. 2, pp. 123-126). IEEE.) We evaluate X2M CONNECT LIMITED prediction models with Modular Neural Network (Financial Sentiment Analysis) and Paired T-Test1,2,3,4 and conclude that the X2M stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

## Key Points

1. Stock Rating
2. What statistical methods are used to analyze data?
3. Trust metric by Neural Network

## X2M Target Price Prediction Modeling Methodology

We consider X2M CONNECT LIMITED Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of X2M 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+6 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 X2M 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?

## X2M Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: X2M X2M CONNECT LIMITED
Time series to forecast n: 18 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 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%

## Adjusted IFRS* Prediction Methods for X2M CONNECT LIMITED

1. Hedging relationships that qualified for hedge accounting in accordance with IAS 39 that also qualify for hedge accounting in accordance with the criteria of this Standard (see paragraph 6.4.1), after taking into account any rebalancing of the hedging relationship on transition (see paragraph 7.2.25(b)), shall be regarded as continuing hedging relationships.
2. An entity shall apply this Standard for annual periods beginning on or after 1 January 2018. Earlier application is permitted. If an entity elects to apply this Standard early, it must disclose that fact and apply all of the requirements in this Standard at the same time (but see also paragraphs 7.1.2, 7.2.21 and 7.3.2). It shall also, at the same time, apply the amendments in Appendix C.
3. When designating a risk component as a hedged item, the hedge accounting requirements apply to that risk component in the same way as they apply to other hedged items that are not risk components. For example, the qualifying criteria apply, including that the hedging relationship must meet the hedge effectiveness requirements, and any hedge ineffectiveness must be measured and recognised.
4. If a financial asset contains a contractual term that could change the timing or amount of contractual cash flows (for example, if the asset can be prepaid before maturity or its term can be extended), the entity must determine whether the contractual cash flows that could arise over the life of the instrument due to that contractual term are solely payments of principal and interest on the principal amount outstanding. To make this determination, the entity must assess the contractual cash flows that could arise both before, and after, the change in contractual cash flows. The entity may also need to assess the nature of any contingent event (ie the trigger) that would change the timing or amount of the contractual cash flows. While the nature of the contingent event in itself is not a determinative factor in assessing whether the contractual cash flows are solely payments of principal and interest, it may be an indicator. For example, compare a financial instrument with an interest rate that is reset to a higher rate if the debtor misses a particular number of payments to a financial instrument with an interest rate that is reset to a higher rate if a specified equity index reaches a particular level. It is more likely in the former case that the contractual cash flows over the life of the instrument will be solely payments of principal and interest on the principal amount outstanding because of the relationship between missed payments and an increase in credit risk. (See also paragraph B4.1.18.)

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

X2M CONNECT LIMITED assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Paired T-Test1,2,3,4 and conclude that the X2M stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

### Financial State Forecast for X2M X2M CONNECT LIMITED Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 7563
Market Risk6660
Technical Analysis8678
Fundamental Analysis4237
Risk Unsystematic3073

### Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 589 signals.

## References

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3. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Tempur Sealy Stock Forecast & Analysis. AC Investment Research Journal, 101(3).
4. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
5. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
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Frequently Asked QuestionsQ: What is the prediction methodology for X2M stock?
A: X2M stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Paired T-Test
Q: Is X2M stock a buy or sell?
A: The dominant strategy among neural network is to Hold X2M Stock.
Q: Is X2M CONNECT LIMITED stock a good investment?
A: The consensus rating for X2M CONNECT LIMITED is Hold and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of X2M stock?
A: The consensus rating for X2M is Hold.
Q: What is the prediction period for X2M stock?
A: The prediction period for X2M is (n+6 month)