What are the most successful trading algorithms? (PGR Stock Forecast)


Abstract

We evaluate Progressive Corporation prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Pearson Correlation1,2,3,4 and conclude that the PGR 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 Hold PGR stock.


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

Key Points

  1. Fundemental Analysis with Algorithmic Trading
  2. Why do we need predictive models?
  3. How do you decide buy or sell a stock?

PGR Target Price Prediction Modeling Methodology

We consider Progressive Corporation Stock Decision Process with Pearson Correlation where A is the set of discrete actions of PGR 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(Pearson Correlation)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(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ (n+8 weeks) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of PGR 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?

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

Sample Set: Neural Network
Stock/Index: PGR Progressive Corporation
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 Hold PGR 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

Progressive Corporation assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Pearson Correlation1,2,3,4 and conclude that the PGR 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 Hold PGR stock.

Financial State Forecast for PGR Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B2
Operational Risk 6874
Market Risk4154
Technical Analysis6345
Fundamental Analysis4338
Risk Unsystematic6862

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 639 signals.

References

  1. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
  2. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
  3. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
  4. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
  5. Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
  6. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
  7. Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678
Frequently Asked QuestionsQ: What is the prediction methodology for PGR stock?
A: PGR stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Pearson Correlation
Q: Is PGR stock a buy or sell?
A: The dominant strategy among neural network is to Hold PGR Stock.
Q: Is Progressive Corporation stock a good investment?
A: The consensus rating for Progressive Corporation is Hold and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of PGR stock?
A: The consensus rating for PGR is Hold.
Q: What is the prediction period for PGR stock?
A: The prediction period for PGR is (n+8 weeks)

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