## Abstract

**We evaluate Paycom prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the PAYC stock is predictable in the short/long term. **

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Buy PAYC stock.**

**PAYC, Paycom, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- How useful are statistical predictions?
- Can we predict stock market using machine learning?
- How do you decide buy or sell a stock?

## PAYC Target Price Prediction Modeling Methodology

We consider Paycom Stock Decision Process with Wilcoxon Rank-Sum Test where A is the set of discrete actions of PAYC 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(Wilcoxon Rank-Sum 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(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+8 weeks) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of PAYC 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?

## PAYC Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**PAYC Paycom

**Time series to forecast n: 06 Sep 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Buy PAYC 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

Paycom assigned short-term Caa2 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the PAYC stock is predictable in the short/long term.**

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Buy PAYC stock.**

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

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

Outlook* | Caa2 | Ba1 |

Operational Risk | 38 | 80 |

Market Risk | 50 | 42 |

Technical Analysis | 42 | 83 |

Fundamental Analysis | 34 | 75 |

Risk Unsystematic | 55 | 69 |

### Prediction Confidence Score

## References

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- A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
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- V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.

## Frequently Asked Questions

Q: What is the prediction methodology for PAYC stock?A: PAYC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Wilcoxon Rank-Sum Test

Q: Is PAYC stock a buy or sell?

A: The dominant strategy among neural network is to Buy PAYC Stock.

Q: Is Paycom stock a good investment?

A: The consensus rating for Paycom is Buy and assigned short-term Caa2 & long-term Ba1 forecasted stock rating.

Q: What is the consensus rating of PAYC stock?

A: The consensus rating for PAYC is Buy.

Q: What is the prediction period for PAYC stock?

A: The prediction period for PAYC is (n+8 weeks)

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