Modelling A.I. in Economics

COLIW Colicity Inc. Warrant

Outlook: Colicity Inc. Warrant is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 08 May 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Colicity Inc. Warrant prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Ridge Regression1,2,3,4 and it is concluded that the COLIW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

Key Points

  1. What is the best way to predict stock prices?
  2. Should I buy stocks now or wait amid such uncertainty?
  3. Technical Analysis with Algorithmic Trading

COLIW Target Price Prediction Modeling Methodology

We consider Colicity Inc. Warrant Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of COLIW 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 (Financial Sentiment Analysis)) X S(n):→ (n+16 weeks) e x rx

n:Time series to forecast

p:Price signals of COLIW 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?

COLIW Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: COLIW Colicity Inc. Warrant
Time series to forecast n: 08 May 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) 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 Colicity Inc. Warrant

  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. If a guarantee provided by an entity to pay for default losses on a transferred asset prevents the transferred asset from being derecognised to the extent of the continuing involvement, the transferred asset at the date of the transfer is measured at the lower of (i) the carrying amount of the asset and (ii) the maximum amount of the consideration received in the transfer that the entity could be required to repay ('the guarantee amount'). The associated liability is initially measured at the guarantee amount plus the fair value of the guarantee (which is normally the consideration received for the guarantee). Subsequently, the initial fair value of the guarantee is recognised in profit or loss when (or as) the obligation is satisfied (in accordance with the principles of IFRS 15) and the carrying value of the asset is reduced by any loss allowance.
  3. For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.
  4. Paragraph 4.1.1(a) requires an entity to classify financial assets on the basis of the entity's business model for managing the financial assets, unless paragraph 4.1.5 applies. An entity assesses whether its financial assets meet the condition in paragraph 4.1.2(a) or the condition in paragraph 4.1.2A(a) on the basis of the business model as determined by the entity's key management personnel (as defined in IAS 24 Related Party Disclosures).

*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

Colicity Inc. Warrant is assigned short-term Ba1 & long-term Ba1 estimated rating. Colicity Inc. Warrant prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Ridge Regression1,2,3,4 and it is concluded that the COLIW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

COLIW Colicity Inc. Warrant Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa3Ba3
Balance SheetBa3C
Leverage RatiosCaa2Caa2
Cash FlowBa2Caa2
Rates of Return and ProfitabilityB3B1

*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: 75 out of 100 with 476 signals.

References

  1. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
  2. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
  3. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
  4. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
  5. Athey S, Bayati M, Imbens G, Zhaonan Q. 2019. Ensemble methods for causal effects in panel data settings. NBER Work. Pap. 25675
  6. Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
  7. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
Frequently Asked QuestionsQ: What is the prediction methodology for COLIW stock?
A: COLIW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Ridge Regression
Q: Is COLIW stock a buy or sell?
A: The dominant strategy among neural network is to Buy COLIW Stock.
Q: Is Colicity Inc. Warrant stock a good investment?
A: The consensus rating for Colicity Inc. Warrant is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of COLIW stock?
A: The consensus rating for COLIW is Buy.
Q: What is the prediction period for COLIW stock?
A: The prediction period for COLIW is (n+16 weeks)

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