Modelling A.I. in Economics

BRSP Stock Price Prediction

Outlook: BrightSpire Capital Inc. Class A Common Stock is assigned short-term B1 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Statistical Inference (ML)
Hypothesis Testing : Pearson Correlation
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.


BrightSpire Capital Inc. Class A Common Stock prediction model is evaluated with Statistical Inference (ML) and Pearson Correlation1,2,3,4 and it is concluded that the BRSP stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

Graph 11

Key Points

  1. Market Outlook
  2. Technical Analysis with Algorithmic Trading
  3. What is neural prediction?

BRSP Stock Price Forecast

We consider BrightSpire Capital Inc. Class A Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of BRSP 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: BRSP BrightSpire Capital Inc. Class A Common Stock
Time series to forecast: 1 Year

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


F(Pearson Correlation)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(Statistical Inference (ML)) X S(n):→ 1 Year r s rs

n:Time series to forecast

p:Price signals of BRSP stock

j:Nash equilibria (Neural Network)

k:Dominated move of BRSP stock holders

a:Best response for BRSP target price


Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.6,7

 

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?

BRSP 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 Statistical Inference (ML) based BRSP Stock Prediction Model

  1. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
  2. Annual Improvements to IFRSs 2010–2012 Cycle, issued in December 2013, amended paragraphs 4.2.1 and 5.7.5 as a consequential amendment derived from the amendment to IFRS 3. An entity shall apply that amendment prospectively to business combinations to which the amendment to IFRS 3 applies.
  3. When an entity discontinues measuring the financial instrument that gives rise to the credit risk, or a proportion of that financial instrument, at fair value through profit or loss, that financial instrument's fair value at the date of discontinuation becomes its new carrying amount. Subsequently, the same measurement that was used before designating the financial instrument at fair value through profit or loss shall be applied (including amortisation that results from the new carrying amount). For example, a financial asset that had originally been classified as measured at amortised cost would revert to that measurement and its effective interest rate would be recalculated based on its new gross carrying amount on the date of discontinuing measurement at fair value through profit or loss.
  4. 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.

*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.

BRSP BrightSpire Capital Inc. Class A Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1B2
Income StatementB2C
Balance SheetB3Caa2
Leverage RatiosBa3Baa2
Cash FlowBaa2C
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. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
  2. Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
  3. Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99
  4. Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
  5. Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
  6. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
  7. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
Frequently Asked QuestionsQ: What is the prediction methodology for BRSP stock?
A: BRSP stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Pearson Correlation
Q: Is BRSP stock a buy or sell?
A: The dominant strategy among neural network is to Sell BRSP Stock.
Q: Is BrightSpire Capital Inc. Class A Common Stock stock a good investment?
A: The consensus rating for BrightSpire Capital Inc. Class A Common Stock is Sell and is assigned short-term B1 & long-term B2 estimated rating.
Q: What is the consensus rating of BRSP stock?
A: The consensus rating for BRSP is Sell.
Q: What is the prediction period for BRSP stock?
A: The prediction period for BRSP is 1 Year



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