Dominant Strategy : Sell
Time series to forecast n: 02 Jun 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Financial Sentiment Analysis)
Abstract
Credicorp Ltd. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test1,2,3,4 and it is concluded that the BAP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: SellKey Points
- Prediction Modeling
- Is Target price a good indicator?
- What are buy sell or hold recommendations?
BAP Target Price Prediction Modeling Methodology
We consider Credicorp Ltd. Common Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of BAP 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(Independent T-Test)5,6,7= X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of BAP 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?
BAP Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: BAP Credicorp Ltd. Common Stock
Time series to forecast n: 02 Jun 2023 for (n+16 weeks)
According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell
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 Credicorp Ltd. Common Stock
- If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
- If an entity measures a hybrid contract at fair value in accordance with paragraphs 4.1.2A, 4.1.4 or 4.1.5 but the fair value of the hybrid contract had not been measured in comparative reporting periods, the fair value of the hybrid contract in the comparative reporting periods shall be the sum of the fair values of the components (ie the non-derivative host and the embedded derivative) at the end of each comparative reporting period if the entity restates prior periods (see paragraph 7.2.15).
- The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
- In some cases, the qualitative and non-statistical quantitative information available may be sufficient to determine that a financial instrument has met the criterion for the recognition of a loss allowance at an amount equal to lifetime expected credit losses. That is, the information does not need to flow through a statistical model or credit ratings process in order to determine whether there has been a significant increase in the credit risk of the financial instrument. In other cases, an entity may need to consider other information, including information from its statistical models or credit ratings processes.
*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
Credicorp Ltd. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Credicorp Ltd. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test1,2,3,4 and it is concluded that the BAP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell
BAP Credicorp Ltd. Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | C | B2 |
Balance Sheet | Caa2 | B3 |
Leverage Ratios | Caa2 | Baa2 |
Cash Flow | C | B3 |
Rates of Return and Profitability | B2 | B1 |
*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

References
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- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.
Frequently Asked Questions
Q: What is the prediction methodology for BAP stock?A: BAP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test
Q: Is BAP stock a buy or sell?
A: The dominant strategy among neural network is to Sell BAP Stock.
Q: Is Credicorp Ltd. Common Stock stock a good investment?
A: The consensus rating for Credicorp Ltd. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BAP stock?
A: The consensus rating for BAP is Sell.
Q: What is the prediction period for BAP stock?
A: The prediction period for BAP is (n+16 weeks)