Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN). We evaluate Capital One prediction models with Statistical Inference (ML) and Factor1,2,3,4 and conclude that the COF stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy COF stock.

Keywords: COF, Capital One, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Can statistics predict the future?
2. How accurate is machine learning in stock market?
3. How do you pick a stock?

## COF Target Price Prediction Modeling Methodology

In the finance world stock trading is one of the most important activities. Stock market prediction is an act of trying to determine the future value of a stock other financial instrument traded on a financial exchange. This paper explains the prediction of a stock using Machine Learning. The technical and fundamental or the time series analysis is used by the most of the stockbrokers while making the stock predictions. We consider Capital One Stock Decision Process with Factor where A is the set of discrete actions of COF 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(Factor)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Statistical Inference (ML)) X S(n):→ (n+6 month) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of COF stock

j:Nash equilibria

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?

## COF Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: COF Capital One
Time series to forecast n: 30 Oct 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy COF stock.

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 (Yellow to Green): *Technical Analysis%

## Adjusted IFRS* Prediction Methods for Capital One

1. When an entity first applies this Standard, it may choose as its accounting policy to continue to apply the hedge accounting requirements of IAS 39 instead of the requirements in Chapter 6 of this Standard. An entity shall apply that policy to all of its hedging relationships. An entity that chooses that policy shall also apply IFRIC 16 Hedges of a Net Investment in a Foreign Operation without the amendments that conform that Interpretation to the requirements in Chapter 6 of this Standard.
2. An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
3. Credit risk analysis is a multifactor and holistic analysis; whether a specific factor is relevant, and its weight compared to other factors, will depend on the type of product, characteristics of the financial instruments and the borrower as well as the geographical region. An entity shall consider reasonable and supportable information that is available without undue cost or effort and that is relevant for the particular financial instrument being assessed. However, some factors or indicators may not be identifiable on an individual financial instrument level. In such a case, the factors or indicators should be assessed for appropriate portfolios, groups of portfolios or portions of a portfolio of financial instruments to determine whether the requirement in paragraph 5.5.3 for the recognition of lifetime expected credit losses has been met.
4. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Capital One assigned short-term Ba2 & long-term B1 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Factor1,2,3,4 and conclude that the COF stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy COF stock.

### Financial State Forecast for COF Capital One Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba2B1
Operational Risk 4864
Market Risk8344
Technical Analysis8649
Fundamental Analysis8156
Risk Unsystematic4988

### Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 741 signals.

## References

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Frequently Asked QuestionsQ: What is the prediction methodology for COF stock?
A: COF stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Factor
Q: Is COF stock a buy or sell?
A: The dominant strategy among neural network is to Buy COF Stock.
Q: Is Capital One stock a good investment?
A: The consensus rating for Capital One is Buy and assigned short-term Ba2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of COF stock?
A: The consensus rating for COF is Buy.
Q: What is the prediction period for COF stock?
A: The prediction period for COF is (n+6 month)