Outlook: Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 30 Jan 2023 for (n+3 month)
Methodology : Modular Neural Network (Speculative Sentiment Analysis)

Abstract

Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and ElasticNet Regression1,2,3,4 and it is concluded that the PEI^D stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Key Points

1. Probability Distribution
2. Which neural network is best for prediction?
3. Probability Distribution

PEI^D Target Price Prediction Modeling Methodology

We consider Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of PEI^D 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(ElasticNet Regression)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 (Speculative Sentiment Analysis)) X S(n):→ (n+3 month) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of PEI^D 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?

PEI^D Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: PEI^D Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares
Time series to forecast n: 30 Jan 2023 for (n+3 month)

According to price forecasts for (n+3 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%

IFRS Reconciliation Adjustments for Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares

1. Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.
2. If items are hedged together as a group in a cash flow hedge, they might affect different line items in the statement of profit or loss and other comprehensive income. The presentation of hedging gains or losses in that statement depends on the group of items
3. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
4. 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.

*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

Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and ElasticNet Regression1,2,3,4 and it is concluded that the PEI^D stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

PEI^D Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa3C
Balance SheetBaa2C
Leverage RatiosBaa2B3
Cash FlowCBaa2
Rates of Return and ProfitabilityBaa2Baa2

*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: 89 out of 100 with 552 signals.

References

1. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52
2. J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
3. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
4. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
5. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
6. P. Marbach. Simulated-Based Methods for Markov Decision Processes. PhD thesis, Massachusetts Institute of Technology, 1998
7. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
Frequently Asked QuestionsQ: What is the prediction methodology for PEI^D stock?
A: PEI^D stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and ElasticNet Regression
Q: Is PEI^D stock a buy or sell?
A: The dominant strategy among neural network is to Hold PEI^D Stock.
Q: Is Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares stock a good investment?
A: The consensus rating for Pennsylvania Real Estate Investment Trust 6.875% Series D Cumulative Redeemable Perpetual Preferred Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PEI^D stock?
A: The consensus rating for PEI^D is Hold.
Q: What is the prediction period for PEI^D stock?
A: The prediction period for PEI^D is (n+3 month)