Modelling A.I. in Economics

BUR Stock: A Sinking Ship?

Outlook: Burford Capital Limited Ordinary Shares is assigned short-term B2 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (CNN Layer)
Hypothesis Testing : Sign Test
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.


Burford Capital Limited Ordinary Shares prediction model is evaluated with Modular Neural Network (CNN Layer) and Sign Test1,2,3,4 and it is concluded that the BUR stock is predictable in the short/long term. CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Sell

Graph 45

Key Points

  1. Dominated Move
  2. Can neural networks predict stock market?
  3. Can machine learning predict?

BUR Target Price Prediction Modeling Methodology

We consider Burford Capital Limited Ordinary Shares Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of BUR 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(Sign Test)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 (CNN Layer)) X S(n):→ 4 Weeks R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of BUR stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (CNN Layer)

CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications.

Sign Test

The sign test is a non-parametric hypothesis test that is used to compare two paired samples. In a paired sample, each data point in one sample is paired with a data point in the other sample. The pairs are typically related in some way, such as before and after measurements, or measurements from the same subject under different conditions. The sign test is a non-parametric test, which means that it does not assume that the data is normally distributed. The sign test is also a dependent samples test, which means that the data points in each pair are correlated.

 

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?

BUR Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: BUR Burford Capital Limited Ordinary Shares
Time series to forecast: 4 Weeks

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

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 Modular Neural Network (CNN Layer) based BUR Stock Prediction Model

  1. However, the fact that a financial asset is non-recourse does not in itself necessarily preclude the financial asset from meeting the condition in paragraphs 4.1.2(b) and 4.1.2A(b). In such situations, the creditor is required to assess ('look through to') the particular underlying assets or cash flows to determine whether the contractual cash flows of the financial asset being classified are payments of principal and interest on the principal amount outstanding. If the terms of the financial asset give rise to any other cash flows or limit the cash flows in a manner inconsistent with payments representing principal and interest, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b). Whether the underlying assets are financial assets or non-financial assets does not in itself affect this assessment.
  2. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
  3. Expected credit losses shall be discounted to the reporting date, not to the expected default or some other date, using the effective interest rate determined at initial recognition or an approximation thereof. If a financial instrument has a variable interest rate, expected credit losses shall be discounted using the current effective interest rate determined in accordance with paragraph B5.4.5.
  4. IFRS 17, issued in May 2017, amended paragraphs 2.1, B2.1, B2.4, B2.5 and B4.1.30, and added paragraph 3.3.5. Amendments to IFRS 17, issued in June 2020, further amended paragraph 2.1 and added paragraphs 7.2.36‒7.2.42. An entity shall apply those amendments when it applies IFRS 17.

*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.

BUR Burford Capital Limited Ordinary Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2Ba1
Income StatementBaa2B1
Balance SheetCaa2Baa2
Leverage RatiosCBaa2
Cash FlowB1Baa2
Rates of Return and ProfitabilityCaa2B2

*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. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
  2. M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
  3. Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
  4. Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
  5. Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
  6. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
  7. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
Frequently Asked QuestionsQ: What is the prediction methodology for BUR stock?
A: BUR stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Sign Test
Q: Is BUR stock a buy or sell?
A: The dominant strategy among neural network is to Sell BUR Stock.
Q: Is Burford Capital Limited Ordinary Shares stock a good investment?
A: The consensus rating for Burford Capital Limited Ordinary Shares is Sell and is assigned short-term B2 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BUR stock?
A: The consensus rating for BUR is Sell.
Q: What is the prediction period for BUR stock?
A: The prediction period for BUR is 4 Weeks

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