Modelling A.I. in Economics

PepsiCo assigned short-term B1 & long-term Ba3 forecasted stock rating.

Efficient Market Hypothesis (EMH) is the cornerstone of the modern financial theory and it states that it is impossible to predict the price of any stock using any trend, fundamental or technical analysis. Stock trading is one of the most important activities in the world of finance. Stock price prediction has been an age-old problem and many researchers from academia and business have tried to solve it using many techniques ranging from basic statistics to machine learning using relevant information such as news sentiment and historical prices. We evaluate PepsiCo prediction models with Multi-Instance Learning (ML) and Beta1,2,3,4 and conclude that the PEP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell PEP stock.


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

Key Points

  1. How do you decide buy or sell a stock?
  2. What is prediction model?
  3. Trading Signals

PEP Target Price Prediction Modeling Methodology

The presented paper modeled and predicted stock returns using LSTM. The historical data of stock market were transformed into 30-days-long sequences with 10 learning features and 7-day earning rate labeling. The model was fitted by training on 1200000 sequences and tested using the other 350000 sequences. We consider PepsiCo Stock Decision Process with Beta where A is the set of discrete actions of PEP 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(Beta)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Multi-Instance Learning (ML)) X S(n):→ (n+3 month) i = 1 n s i

n:Time series to forecast

p:Price signals of PEP 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?

PEP Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: PEP PepsiCo
Time series to forecast n: 07 Oct 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell PEP 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

PepsiCo assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Multi-Instance Learning (ML) with Beta1,2,3,4 and conclude that the PEP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell PEP stock.

Financial State Forecast for PEP Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 4552
Market Risk5765
Technical Analysis7465
Fundamental Analysis4343
Risk Unsystematic7481

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 737 signals.

References

  1. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
  2. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
  3. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
  4. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
  5. K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
  6. Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
  7. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
Frequently Asked QuestionsQ: What is the prediction methodology for PEP stock?
A: PEP stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and Beta
Q: Is PEP stock a buy or sell?
A: The dominant strategy among neural network is to Sell PEP Stock.
Q: Is PepsiCo stock a good investment?
A: The consensus rating for PepsiCo is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of PEP stock?
A: The consensus rating for PEP is Sell.
Q: What is the prediction period for PEP stock?
A: The prediction period for PEP is (n+3 month)



Stop Guessing, Start Winning.
Get Today's AI-Driven Picks.

Click here to see what the AI recommends.




Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.