**Outlook:**DUXTON WATER LIMITED assigned short-term B2 & long-term B2 forecasted stock rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 09 Dec 2022**for (n+16 weeks)

**Methodology :**Reinforcement Machine Learning (ML)

## Abstract

Stock prediction is a very hot topic in our life. However, in the early time, because of some reasons and the limitation of the device, only a few people had the access to the study. Thanks to the rapid development of science and technology, in recent years more and more people are devoted to the study of the prediction and it becomes easier and easier for us to make stock prediction by using different ways now, including machine learning, deep learning and so on. (Siew, H.L. and Nordin, M.J., 2012, September. Regression techniques for the prediction of stock price trend. In 2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE) (pp. 1-5). IEEE.)** We evaluate DUXTON WATER LIMITED prediction models with Reinforcement Machine Learning (ML) and Ridge Regression ^{1,2,3,4} and conclude that the D2O stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold**

## Key Points

- Prediction Modeling
- Prediction Modeling
- Why do we need predictive models?

## D2O Target Price Prediction Modeling Methodology

We consider DUXTON WATER LIMITED Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of D2O 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(Ridge 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+16 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of D2O stock

j:Nash equilibria (Neural Network)

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?

## D2O Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**D2O DUXTON WATER LIMITED

**Time series to forecast n: 09 Dec 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold**

**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%**

## Adjusted IFRS* Prediction Methods for DUXTON WATER LIMITED

- This Standard does not specify a method for assessing whether a hedging relationship meets the hedge effectiveness requirements. However, an entity shall use a method that captures the relevant characteristics of the hedging relationship including the sources of hedge ineffectiveness. Depending on those factors, the method can be a qualitative or a quantitative assessment.
- Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
- At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.
- To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

DUXTON WATER LIMITED assigned short-term B2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Reinforcement Machine Learning (ML) with Ridge Regression ^{1,2,3,4} and conclude that the D2O stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold**

### Financial State Forecast for D2O DUXTON WATER LIMITED Options & Futures

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

Outlook* | B2 | B2 |

Operational Risk | 43 | 67 |

Market Risk | 51 | 54 |

Technical Analysis | 87 | 34 |

Fundamental Analysis | 39 | 50 |

Risk Unsystematic | 67 | 47 |

### Prediction Confidence Score

## References

- Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
- K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
- Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
- Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
- 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
- O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
- J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.

## Frequently Asked Questions

Q: What is the prediction methodology for D2O stock?A: D2O stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Ridge Regression

Q: Is D2O stock a buy or sell?

A: The dominant strategy among neural network is to Hold D2O Stock.

Q: Is DUXTON WATER LIMITED stock a good investment?

A: The consensus rating for DUXTON WATER LIMITED is Hold and assigned short-term B2 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of D2O stock?

A: The consensus rating for D2O is Hold.

Q: What is the prediction period for D2O stock?

A: The prediction period for D2O is (n+16 weeks)

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