Modelling A.I. in Economics

PKX Stock: A Cautionary Tale (Forecast)

Outlook: POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) is assigned short-term Ba2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Multi-Instance Learning (ML)
Hypothesis Testing : Logistic 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

POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) prediction model is evaluated with Multi-Instance Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the PKX stock is predictable in the short/long term. Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance.5 According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Speculative Trend

Graph 47

Key Points

  1. Multi-Instance Learning (ML) for PKX stock price prediction process.
  2. Logistic Regression
  3. Stock Rating
  4. Fundemental Analysis with Algorithmic Trading
  5. What are the most successful trading algorithms?

PKX Stock Price Forecast

We consider POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of PKX 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: PKX POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock)
Time series to forecast: 16 Weeks

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


F(Logistic 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(Multi-Instance Learning (ML)) X S(n):→ 16 Weeks e x rx

n:Time series to forecast

p:Price signals of PKX stock

j:Nash equilibria (Neural Network)

k:Dominated move of PKX stock holders

a:Best response for PKX target price


Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance.5 In statistics, logistic regression is a type of regression analysis used when the dependent variable is categorical. Logistic regression is a probability model that predicts the probability of an event occurring based on a set of independent variables. In logistic regression, the dependent variable is represented as a binary variable, such as "yes" or "no," "true" or "false," or "sick" or "healthy." The independent variables can be continuous or categorical variables.6,7

 

For further technical information as per how our model work we invite you to visit the article below: 

How do PredictiveAI algorithms actually work?

PKX 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 Multi-Instance Learning (ML) based PKX Stock Prediction Model

  1. The purpose of estimating expected credit losses is neither to estimate a worstcase scenario nor to estimate the best-case scenario. Instead, an estimate of expected credit losses shall always reflect the possibility that a credit loss occurs and the possibility that no credit loss occurs even if the most likely outcome is no credit loss.
  2. A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
  3. The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
  4. The risk of a default occurring on financial instruments that have comparable credit risk is higher the longer the expected life of the instrument; for example, the risk of a default occurring on an AAA-rated bond with an expected life of 10 years is higher than that on an AAA-rated bond with an expected life of five years.

*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.

PKX POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba2B1
Income StatementBaa2Baa2
Balance SheetCB2
Leverage RatiosBaa2C
Cash FlowBaa2B3
Rates of Return and ProfitabilityB1Ba3

*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. Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
  2. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
  3. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
  4. G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
  5. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
  6. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Google's Stock Price Set to Soar in the Next 3 Months. AC Investment Research Journal, 220(44).
  7. Harris ZS. 1954. Distributional structure. Word 10:146–62
Frequently Asked QuestionsQ: Is PKX stock expected to rise?
A: PKX stock prediction model is evaluated with Multi-Instance Learning (ML) and Logistic Regression and it is concluded that dominant strategy for PKX stock is Speculative Trend
Q: Is PKX stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend PKX Stock.
Q: Is POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) stock a good investment?
A: The consensus rating for POSCO Holdings Inc. American Depositary Shares (Each representing 1/4th of a share of Common Stock) is Speculative Trend and is assigned short-term Ba2 & long-term B1 estimated rating.
Q: What is the consensus rating of PKX stock?
A: The consensus rating for PKX is Speculative Trend.
Q: What is the forecast for PKX stock?
A: PKX target price forecast: Speculative Trend

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.