How do you determine buy or sell? (PAYC Stock Forecast)

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.

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

Key Points

1. How useful are statistical predictions?
2. Can we predict stock market using machine learning?
3. 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(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

Trust metric by Neural Network: 82 out of 100 with 798 signals.

References

1. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
2. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
3. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
4. Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
5. 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
6. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
7. 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)