Modelling A.I. in Economics

FBRT^E Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock (Forecast)

Outlook: Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 23 Mar 2023 for (n+3 month)
Methodology : Ensemble Learning (ML)

Abstract

Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock prediction model is evaluated with Ensemble Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the FBRT^E stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

  1. Can we predict stock market using machine learning?
  2. Prediction Modeling
  3. How can neural networks improve predictions?

FBRT^E Target Price Prediction Modeling Methodology

We consider Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of FBRT^E 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(Linear 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(Ensemble Learning (ML)) X S(n):→ (n+3 month) e x rx

n:Time series to forecast

p:Price signals of FBRT^E 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?

FBRT^E Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: FBRT^E Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock
Time series to forecast n: 23 Mar 2023 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

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 Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock

  1. An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
  2. As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.
  3. Leverage is a contractual cash flow characteristic of some financial assets. Leverage increases the variability of the contractual cash flows with the result that they do not have the economic characteristics of interest. Stand-alone option, forward and swap contracts are examples of financial assets that include such leverage. Thus, such contracts do not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and cannot be subsequently measured at amortised cost or fair value through other comprehensive income.
  4. 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

*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

Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock prediction model is evaluated with Ensemble Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the FBRT^E stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

FBRT^E Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2B2
Balance SheetCaa2Caa2
Leverage RatiosB3C
Cash FlowBaa2C
Rates of Return and ProfitabilityBaa2C

*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: 86 out of 100 with 551 signals.

References

  1. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
  2. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
  3. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
  4. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
  5. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  6. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
  7. Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
Frequently Asked QuestionsQ: What is the prediction methodology for FBRT^E stock?
A: FBRT^E stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Linear Regression
Q: Is FBRT^E stock a buy or sell?
A: The dominant strategy among neural network is to Sell FBRT^E Stock.
Q: Is Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock stock a good investment?
A: The consensus rating for Franklin BSP Realty Trust Inc. 7.50% Series E Cumulative Redeemable Preferred Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of FBRT^E stock?
A: The consensus rating for FBRT^E is Sell.
Q: What is the prediction period for FBRT^E stock?
A: The prediction period for FBRT^E is (n+3 month)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.