Modelling A.I. in Economics

IDA Stock: Maximize your return (Forecast)

Outlook: IDACORP Inc. Common Stock is assigned short-term B2 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n: for Weeks2
Methodology : Statistical Inference (ML)
Hypothesis Testing : Paired T-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.


IDACORP Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Paired T-Test1,2,3,4 and it is concluded that the IDA 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. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy

Graph 16

Key Points

  1. Technical Analysis with Algorithmic Trading
  2. Short/Long Term Stocks
  3. How accurate is machine learning in stock market?

IDA Target Price Prediction Modeling Methodology

We consider IDACORP Inc. Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of IDA 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(Paired T-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(Statistical Inference (ML)) X S(n):→ 3 Month e x rx

n:Time series to forecast

p:Price signals of IDA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Statistical Inference (ML)

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.

Paired T-Test

A paired t-test is a statistical test that compares the means of two paired samples. In a paired t-test, 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 paired t-test is a parametric test, which means that it assumes that the data is normally distributed. The paired t-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?

IDA Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: IDA IDACORP Inc. Common Stock
Time series to forecast: 3 Month

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

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 IDA Stock Prediction Model

  1. In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.
  2. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.
  3. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
  4. Rebalancing is accounted for as a continuation of the hedging relationship in accordance with paragraphs B6.5.9–B6.5.21. On rebalancing, the hedge ineffectiveness of the hedging relationship is determined and recognised immediately before adjusting the hedging relationship.

*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.

IDA IDACORP Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2B2
Income StatementB3B1
Balance SheetCC
Leverage RatiosBaa2C
Cash FlowBa3B2
Rates of Return and ProfitabilityB1B1

*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. Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
  2. Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
  3. Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
  4. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
  5. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
  6. Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
  7. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
Frequently Asked QuestionsQ: What is the prediction methodology for IDA stock?
A: IDA stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Paired T-Test
Q: Is IDA stock a buy or sell?
A: The dominant strategy among neural network is to Buy IDA Stock.
Q: Is IDACORP Inc. Common Stock stock a good investment?
A: The consensus rating for IDACORP Inc. Common Stock is Buy and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of IDA stock?
A: The consensus rating for IDA is Buy.
Q: What is the prediction period for IDA stock?
A: The prediction period for IDA is 3 Month

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