Recently, a lot of interesting work has been done in the area of applying Machine Learning Algorithms for analyzing price patterns and predicting stock prices and index changes. Most stock traders nowadays depend on Intelligent Trading Systems which help them in predicting prices based on various situations and conditions, thereby helping them in making instantaneous investment decisions.** We evaluate American Water Works prediction models with Reinforcement Machine Learning (ML) and Multiple Regression ^{1,2,3,4} and conclude that the AWK 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 Hold AWK stock.**

**AWK, American Water Works, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Technical Analysis with Algorithmic Trading
- Can statistics predict the future?
- What is the best way to predict stock prices?

## AWK Target Price Prediction Modeling Methodology

The search for models to predict the prices of financial markets is still a highly researched topic, despite major related challenges. The prices of financial assets are non-linear, dynamic, and chaotic; thus, they are financial time series that are difficult to predict. Among the latest techniques, machine learning models are some of the most researched, given their capabilities for recognizing complex patterns in various applications. We consider American Water Works Stock Decision Process with Multiple Regression where A is the set of discrete actions of AWK 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(Multiple Regression)

^{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(Reinforcement Machine Learning (ML)) X S(n):→ (n+4 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of AWK 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?

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

**Sample Set:**Neural Network

**Stock/Index:**AWK American Water Works

**Time series to forecast n: 21 Oct 2022**for (n+4 weeks)

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

American Water Works assigned short-term B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Reinforcement Machine Learning (ML) with Multiple Regression ^{1,2,3,4} and conclude that the AWK 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 Hold AWK stock.**

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

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

Outlook* | B1 | B1 |

Operational Risk | 79 | 68 |

Market Risk | 36 | 53 |

Technical Analysis | 63 | 74 |

Fundamental Analysis | 54 | 46 |

Risk Unsystematic | 75 | 61 |

### Prediction Confidence Score

## References

- Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
- D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
- Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
- Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
- 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
- M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
- Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer

## Frequently Asked Questions

Q: What is the prediction methodology for AWK stock?A: AWK stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Multiple Regression

Q: Is AWK stock a buy or sell?

A: The dominant strategy among neural network is to Hold AWK Stock.

Q: Is American Water Works stock a good investment?

A: The consensus rating for American Water Works is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of AWK stock?

A: The consensus rating for AWK is Hold.

Q: What is the prediction period for AWK stock?

A: The prediction period for AWK is (n+4 weeks)