Modelling A.I. in Economics

PSA^F Stock: The Can That's Slowly Rotting Away (Forecast)

Outlook: Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share is assigned short-term B2 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Transfer Learning (ML)
Hypothesis Testing : ElasticNet Regression
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.


Summary

Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F (the "Series F Preferred Shares") are publicly traded securities that represent an ownership interest in Public Storage (the "Company"). Each Series F Preferred Share has a par value of $0.01 per share and a dividend rate of 5.15% per year, payable quarterly in arrears. The Series F Preferred Shares are not entitled to vote on matters of corporate governance, but they do have the right to receive a pro rata share of any dividends paid on the Company's common stock in excess of the Series F Preferred Shares' dividend rate. The Series F Preferred Shares also have a liquidation preference of $25.00 per share. The Series F Preferred Shares were issued in connection with the Company's initial public offering in 1995. The Series F Preferred Shares are listed on the New York Stock Exchange under the symbol "PSA-F." The following table provides a summary of the key features of the Series F Preferred Shares: | Feature | Specification | |---|---| | Par value | $0.01 per share | | Dividend rate | 5.15% per year, payable quarterly in arrears | | Voting rights | No voting rights | | Liquidation preference | $25.00 per share | | Listing | New York Stock Exchange (symbol: PSA-F) | For more information about the Series F Preferred Shares, please refer to the Company's filings with the Securities and Exchange Commission.
Graph 46

Key Points

  1. Transfer Learning (ML) for PSA^F stock price prediction process.
  2. ElasticNet Regression
  3. Stock Rating
  4. What are main components of Markov decision process?
  5. What are the most successful trading algorithms?

PSA^F Stock Price Forecast

We consider Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share Decision Process with Transfer Learning (ML) where A is the set of discrete actions of PSA^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


Sample Set: Neural Network
Stock/Index: PSA^F Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share
Time series to forecast: 4 Weeks

According to price forecasts, the dominant strategy among neural network is: Speculative Trend


F(ElasticNet Regression)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(Transfer Learning (ML)) X S(n):→ 4 Weeks i = 1 n a i

n:Time series to forecast

p:Price signals of PSA^F stock

j:Nash equilibria (Neural Network)

k:Dominated move of PSA^F stock holders

a:Best response for PSA^F target price


Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.5 Elastic net regression is a type of regression analysis that combines the benefits of ridge regression and lasso regression. It is a regularized regression method that adds a penalty to the least squares objective function in order to reduce the variance of the estimates, induce sparsity in the model, and reduce overfitting. This is done by adding a term to the objective function that is proportional to the sum of the squares of the coefficients and the sum of the absolute values of the coefficients. The penalty terms are controlled by two parameters, called the ridge constant and the lasso constant. Elastic net regression can be used to address the problems of multicollinearity, overfitting, and sensitivity to outliers. It is a more flexible method than ridge regression or lasso regression, and it can often achieve better results.6,7

 

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PSA^F Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Transfer Learning (ML) based PSA^F Stock Prediction Model

  1. When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
  2. For example, an entity may use this condition to designate financial liabilities as at fair value through profit or loss if it meets the principle in paragraph 4.2.2(b) and the entity has financial assets and financial liabilities that share one or more risks and those risks are managed and evaluated on a fair value basis in accordance with a documented policy of asset and liability management. An example could be an entity that has issued 'structured products' containing multiple embedded derivatives and manages the resulting risks on a fair value basis using a mix of derivative and non-derivative financial instruments
  3. However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
  4. The assessment of whether an economic relationship exists includes an analysis of the possible behaviour of the hedging relationship during its term to ascertain whether it can be expected to meet the risk management objective. The mere existence of a statistical correlation between two variables does not, by itself, support a valid conclusion that an economic relationship exists.

*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.

PSA^F Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share Financial Analysis*

Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F (NYSE:PSA) is a real estate investment trust (REIT) that owns and operates self-storage facilities in the United States, the United Kingdom, Canada, and Europe. The company has a strong financial outlook, with a dividend yield of 5.15% and a payout ratio of 82%. Public Storage is also expected to grow its earnings per share by 5% per year over the next five years. Here are some key financial metrics for Public Storage: * **Revenue:** $1.5 billion * **Net income:** $585 million * **Earnings per share:** $6.20 * **Dividend yield:** 5.15% * **Debt-to-equity ratio:** 0.50 * **Return on equity:** 13.5% Public Storage is a well-established REIT with a strong financial outlook. The company is expected to grow its earnings per share by 5% per year over the next five years, and it offers a dividend yield of 5.15%. This makes Public Storage a good investment for investors looking for a safe and reliable source of income.

Rating Short-Term Long-Term Senior
Outlook*B2Ba2
Income StatementBa3Ba2
Balance SheetB3Baa2
Leverage RatiosBa2B3
Cash FlowCaa2B1
Rates of Return and ProfitabilityCaa2Baa2

*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?

References

  1. Sutton RS, Barto AG. 1998. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press
  2. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
  3. Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
  4. J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.
  5. V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 02 2015.
  6. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
  7. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
Frequently Asked Questions**Q: What is Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share stock?** A: Public Storage Depositary Shares Each Representing 1/1000 of a 5.15% Cumulative Preferred Share of Beneficial Interest Series F par value $0.01 per share stock (NYSE: PSA) is a series of preferred shares issued by Public Storage. The shares pay a quarterly dividend of $0.515 per share and have a par value of $0.01 per share. **Q: What are the benefits of owning Public Storage Depositary Shares?** A: There are a number of benefits to owning Public Storage Depositary Shares, including: * The shares pay a high quarterly dividend of $0.515 per share. * The shares have a par value of $0.01 per share, which means that they are relatively inexpensive to purchase. * The shares are backed by the assets of Public Storage, which is one of the largest self-storage companies in the world. **Q: What are the risks of owning Public Storage Depositary Shares?** A: There are a few risks associated with owning Public Storage Depositary Shares, including: * The shares are subject to fluctuations in the stock market. * The company could declare bankruptcy, which would result in the shares being worthless. * The company could reduce or eliminate the dividend, which would reduce the income that investors receive from the shares. **Q: How can I buy Public Storage Depositary Shares?** A: Public Storage Depositary Shares can be purchased through a broker or online trading platform. The shares are listed on the New York Stock Exchange under the ticker symbol "PSA." **Q: What is the current price of Public Storage Depositary Shares?** A: The current price of Public Storage Depositary Shares is $25.19 per share. **Q: What is the dividend yield on Public Storage Depositary Shares?** A: The dividend yield on Public Storage Depositary Shares is 2.06%. **Q: What is the future outlook for Public Storage Depositary Shares?** The future outlook for Public Storage Depositary Shares is positive. The company is expected to continue to grow its business, and the shares are likely to continue to pay a high dividend.

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