Trading Signals (WTS Stock Forecast)

Abstract

We evaluate Watts Water Technologies prediction models with Adaptive Moving Average and Logistic Regression^1,2,3,4 and conclude that the WTS 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 WTS stock.

Keywords: WTS, Watts Water Technologies, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. What statistical methods are used to analyze data?
2. Can statistics predict the future?
3. Stock Forecast Based On a Predictive Algorithm

WTS Target Price Prediction Modeling Methodology

We consider Watts Water Technologies Stock Decision Process with Logistic Regression where A is the set of discrete actions of WTS 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(Logistic Regression)^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(Adaptive Moving Average) X S(n):→ (n+4 weeks) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of WTS 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?

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

Sample Set: Neural Network
Stock/Index: WTS Watts Water Technologies
Time series to forecast n: 01 Sep 2022 for (n+4 weeks)

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

Watts Water Technologies assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Adaptive Moving Average with Logistic Regression^1,2,3,4 and conclude that the WTS 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 WTS stock.

Financial State Forecast for WTS Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B1	Ba3
Operational Risk	72	84
Market Risk	35	35
Technical Analysis	61	86
Fundamental Analysis	74	52
Risk Unsystematic	48	55

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 543 signals.

References

1. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
2. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
3. Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
4. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
5. 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.
6. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
7. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.

Frequently Asked Questions

Q: What is the prediction methodology for WTS stock?
A: WTS stock prediction methodology: We evaluate the prediction models Adaptive Moving Average and Logistic Regression
Q: Is WTS stock a buy or sell?
A: The dominant strategy among neural network is to Sell WTS Stock.
Q: Is Watts Water Technologies stock a good investment?
A: The consensus rating for Watts Water Technologies is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of WTS stock?
A: The consensus rating for WTS is Sell.
Q: What is the prediction period for WTS stock?
A: The prediction period for WTS is (n+4 weeks)

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