AC Investment Research

PEB^F Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest Research Report

Outlook: Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 07 Jan 2023 for (n+6 month)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Ridge Regression1,2,3,4 and it is concluded that the PEB^F stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

Key Points

  1. How do predictive algorithms actually work?
  2. Stock Rating
  3. What statistical methods are used to analyze data?

PEB^F Target Price Prediction Modeling Methodology

We consider Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of PEB^F 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(Ridge Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+6 month) i = 1 n a i

n:Time series to forecast

p:Price signals of PEB^F 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?

PEB^F Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: PEB^F Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest
Time series to forecast n: 07 Jan 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

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 Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest

  1. When measuring hedge ineffectiveness, an entity shall consider the time value of money. Consequently, the entity determines the value of the hedged item on a present value basis and therefore the change in the value of the hedged item also includes the effect of the time value of money.
  2. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).
  3. If a put option obligation written by an entity or call option right held by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at amortised cost, the associated liability is measured at its cost (ie the consideration received) adjusted for the amortisation of any difference between that cost and the gross carrying amount of the transferred asset at the expiration date of the option. For example, assume that the gross carrying amount of the asset on the date of the transfer is CU98 and that the consideration received is CU95. The gross carrying amount of the asset on the option exercise date will be CU100. The initial carrying amount of the associated liability is CU95 and the difference between CU95 and CU100 is recognised in profit or loss using the effective interest method. If the option is exercised, any difference between the carrying amount of the associated liability and the exercise price is recognised in profit or loss.
  4. For the purposes of applying the requirements in paragraphs 5.7.7 and 5.7.8, an accounting mismatch is not caused solely by the measurement method that an entity uses to determine the effects of changes in a liability's credit risk. An accounting mismatch in profit or loss would arise only when the effects of changes in the liability's credit risk (as defined in IFRS 7) are expected to be offset by changes in the fair value of another financial instrument. A mismatch that arises solely as a result of the measurement method (ie because an entity does not isolate changes in a liability's credit risk from some other changes in its fair value) does not affect the determination required by paragraphs 5.7.7 and 5.7.8. For example, an entity may not isolate changes in a liability's credit risk from changes in liquidity risk. If the entity presents the combined effect of both factors in other comprehensive income, a mismatch may occur because changes in liquidity risk may be included in the fair value measurement of the entity's financial assets and the entire fair value change of those assets is presented in profit or loss. However, such a mismatch is caused by measurement imprecision, not the offsetting relationship described in paragraph B5.7.6 and, therefore, does not affect the determination required by paragraphs 5.7.7 and 5.7.8.

*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

Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest is assigned short-term Ba1 & long-term Ba1 estimated rating. Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Ridge Regression1,2,3,4 and it is concluded that the PEB^F stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

PEB^F Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Baa2
Balance SheetCB3
Leverage RatiosBa1Ba3
Cash FlowB2Caa2
Rates of Return and ProfitabilityB2B1

*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: 84 out of 100 with 729 signals.

References

  1. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
  2. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
  3. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
  4. 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).
  5. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
  6. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
  7. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
Frequently Asked QuestionsQ: What is the prediction methodology for PEB^F stock?
A: PEB^F stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Ridge Regression
Q: Is PEB^F stock a buy or sell?
A: The dominant strategy among neural network is to Buy PEB^F Stock.
Q: Is Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest stock a good investment?
A: The consensus rating for Pebblebrook Hotel Trust 6.3% Series F Cumulative Redeemable Preferred Shares of Beneficial Interest is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PEB^F stock?
A: The consensus rating for PEB^F is Buy.
Q: What is the prediction period for PEB^F stock?
A: The prediction period for PEB^F is (n+6 month)

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