Outlook: ABRDN EUROPEAN LOGISTICS INCOME PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 10 Feb 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market Volatility Analysis)

## Abstract

ABRDN EUROPEAN LOGISTICS INCOME PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Sign Test1,2,3,4 and it is concluded that the LON:ASLI stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

## Key Points

1. Market Signals
2. How accurate is machine learning in stock market?
3. How useful are statistical predictions?

## LON:ASLI Target Price Prediction Modeling Methodology

We consider ABRDN EUROPEAN LOGISTICS INCOME PLC Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:ASLI 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(Sign 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 (Market Volatility Analysis)) X S(n):→ (n+8 weeks) $∑ i = 1 n a i$

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: LON:ASLI ABRDN EUROPEAN LOGISTICS INCOME PLC
Time series to forecast n: 10 Feb 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 ABRDN EUROPEAN LOGISTICS INCOME PLC

1. When an entity first applies this Standard, it may choose as its accounting policy to continue to apply the hedge accounting requirements of IAS 39 instead of the requirements in Chapter 6 of this Standard. An entity shall apply that policy to all of its hedging relationships. An entity that chooses that policy shall also apply IFRIC 16 Hedges of a Net Investment in a Foreign Operation without the amendments that conform that Interpretation to the requirements in Chapter 6 of this Standard.
2. When designating a group of items as the hedged item, or a combination of financial instruments as the hedging instrument, an entity shall prospectively cease applying paragraphs 6.8.4–6.8.6 to an individual item or financial instrument in accordance with paragraphs 6.8.9, 6.8.10, or 6.8.11, as relevant, when the uncertainty arising from interest rate benchmark reform is no longer present with respect to the hedged risk and/or the timing and the amount of the interest rate benchmark-based cash flows of that item or financial instrument.
3. When an entity separates the foreign currency basis spread from a financial instrument and excludes it from the designation of that financial instrument as the hedging instrument (see paragraph 6.2.4(b)), the application guidance in paragraphs B6.5.34–B6.5.38 applies to the foreign currency basis spread in the same manner as it is applied to the forward element of a forward contract.
4. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.

*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

ABRDN EUROPEAN LOGISTICS INCOME PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. ABRDN EUROPEAN LOGISTICS INCOME PLC prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Sign Test1,2,3,4 and it is concluded that the LON:ASLI stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

### LON:ASLI ABRDN EUROPEAN LOGISTICS INCOME PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Baa2
Balance SheetB2C
Leverage RatiosB2Baa2
Cash FlowBaa2C
Rates of Return and ProfitabilityCaa2C

*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: 72 out of 100 with 716 signals.

## References

1. Matzkin RL. 2007. Nonparametric identification. In Handbook of Econometrics, Vol. 6B, ed. J Heckman, E Learner, pp. 5307–68. Amsterdam: Elsevier
2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold AQN Stock. AC Investment Research Journal, 101(3).
3. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
4. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
5. G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
6. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
7. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:ASLI stock?
A: LON:ASLI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Sign Test
Q: Is LON:ASLI stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:ASLI Stock.
Q: Is ABRDN EUROPEAN LOGISTICS INCOME PLC stock a good investment?
A: The consensus rating for ABRDN EUROPEAN LOGISTICS INCOME PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:ASLI stock?
A: The consensus rating for LON:ASLI is Hold.
Q: What is the prediction period for LON:ASLI stock?
A: The prediction period for LON:ASLI is (n+8 weeks)