## Abstract

**We evaluate American Electric Power prediction models with Trend and Paired T-Test ^{1,2,3,4} and conclude that the AEP stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell AEP stock.**

**AEP, American Electric Power, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What is Markov decision process in reinforcement learning?
- How do you pick a stock?
- What is the best way to predict stock prices?

## AEP Target Price Prediction Modeling Methodology

We consider American Electric Power Stock Decision Process with Paired T-Test where A is the set of discrete actions of AEP 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 Î³ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Paired T-Test)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Trend) X S(n):→ (n+4 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of AEP 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?

## AEP Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**AEP American Electric Power

**Time series to forecast n: 31 Aug 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell AEP 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%**

## Conclusions

American Electric Power assigned short-term Ba3 & long-term B2 forecasted stock rating.** We evaluate the prediction models Trend with Paired T-Test ^{1,2,3,4} and conclude that the AEP stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell AEP stock.**

### Financial State Forecast for AEP Stock Options & Futures

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba3 | B2 |

Operational Risk | 82 | 43 |

Market Risk | 76 | 40 |

Technical Analysis | 63 | 62 |

Fundamental Analysis | 37 | 70 |

Risk Unsystematic | 70 | 50 |

### Prediction Confidence Score

## References

- Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
- Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
- S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
- Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
- Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
- Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
- J. G. Schneider, W. Wong, A. W. Moore, and M. A. Riedmiller. Distributed value functions. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 371–378, 1999.

## Frequently Asked Questions

Q: What is the prediction methodology for AEP stock?A: AEP stock prediction methodology: We evaluate the prediction models Trend and Paired T-Test

Q: Is AEP stock a buy or sell?

A: The dominant strategy among neural network is to Sell AEP Stock.

Q: Is American Electric Power stock a good investment?

A: The consensus rating for American Electric Power is Sell and assigned short-term Ba3 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of AEP stock?

A: The consensus rating for AEP is Sell.

Q: What is the prediction period for AEP stock?

A: The prediction period for AEP is (n+4 weeks)