Industrial Logistics Properties Trust Common Shares of Beneficial Interest Research Report

## Summary

In this paper we investigate ways to use prior knowledge and neural networks to improve multivariate prediction ability. Daily stock prices are predicted as a complicated real-world problem, taking non-numerical factors such as political and international events are into account. We have studied types of prior knowledge which are difficult to insert into initial network structures or to represent in the form of error measurements. We evaluate Industrial Logistics Properties Trust Common Shares of Beneficial Interest prediction models with Deductive Inference (ML) and Sign Test1,2,3,4 and conclude that the ILPT stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy ILPT stock.

## Key Points

2. What is neural prediction?
3. Is now good time to invest?

## ILPT Target Price Prediction Modeling Methodology

We consider Industrial Logistics Properties Trust Common Shares of Beneficial Interest Stock Decision Process with Deductive Inference (ML) where A is the set of discrete actions of ILPT 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(Deductive Inference (ML)) X S(n):→ (n+16 weeks) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of ILPT 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?

## ILPT Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: ILPT Industrial Logistics Properties Trust Common Shares of Beneficial Interest
Time series to forecast n: 24 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy ILPT stock.

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 (Yellow to Green): *Technical Analysis%

## Adjusted IFRS* Prediction Methods for Industrial Logistics Properties Trust Common Shares of Beneficial Interest

1. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.
2. An entity may retain the right to a part of the interest payments on transferred assets as compensation for servicing those assets. The part of the interest payments that the entity would give up upon termination or transfer of the servicing contract is allocated to the servicing asset or servicing liability. The part of the interest payments that the entity would not give up is an interest-only strip receivable. For example, if the entity would not give up any interest upon termination or transfer of the servicing contract, the entire interest spread is an interest-only strip receivable. For the purposes of applying paragraph 3.2.13, the fair values of the servicing asset and interest-only strip receivable are used to allocate the carrying amount of the receivable between the part of the asset that is derecognised and the part that continues to be recognised. If there is no servicing fee specified or the fee to be received is not expected to compensate the entity adequately for performing the servicing, a liability for the servicing obligation is recognised at fair value.
3. The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
4. In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.

*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

Industrial Logistics Properties Trust Common Shares of Beneficial Interest assigned short-term Ba1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Sign Test1,2,3,4 and conclude that the ILPT stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy ILPT stock.

### Financial State Forecast for ILPT Industrial Logistics Properties Trust Common Shares of Beneficial Interest Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba3
Operational Risk 6564
Market Risk7184
Technical Analysis8777
Fundamental Analysis5073
Risk Unsystematic7930

### Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 764 signals.

## References

1. Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
2. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
3. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
4. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
5. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
6. Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
7. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
Frequently Asked QuestionsQ: What is the prediction methodology for ILPT stock?
A: ILPT stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Sign Test
Q: Is ILPT stock a buy or sell?
A: The dominant strategy among neural network is to Buy ILPT Stock.
Q: Is Industrial Logistics Properties Trust Common Shares of Beneficial Interest stock a good investment?
A: The consensus rating for Industrial Logistics Properties Trust Common Shares of Beneficial Interest is Buy and assigned short-term Ba1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of ILPT stock?
A: The consensus rating for ILPT is Buy.
Q: What is the prediction period for ILPT stock?
A: The prediction period for ILPT is (n+16 weeks)