Consolidated Water Co. Ltd. Ordinary Shares Research Report

## Summary

Market systems are so complex that they overwhelm the ability of any individual to predict. But it is crucial for the investors to predict stock market price to generate notable profit. We have taken into factors such as Commodity Prices (crude oil, gold, silver), Market History, and Foreign exchange rate (FEX) that influence the stock trend. We evaluate Consolidated Water Co. Ltd. Ordinary Shares prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation1,2,3,4 and conclude that the CWCO 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 CWCO stock.

## Key Points

1. What is prediction model?
2. Game Theory
3. What is a prediction confidence?

## CWCO Target Price Prediction Modeling Methodology

We consider Consolidated Water Co. Ltd. Ordinary Shares Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of CWCO 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(Spearman Correlation)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Emotional Trigger/Responses Analysis)) X S(n):→ (n+4 weeks) $∑ i = 1 n a i$

n:Time series to forecast

p:Price signals of CWCO 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?

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

Sample Set: Neural Network
Stock/Index: CWCO Consolidated Water Co. Ltd. Ordinary Shares
Time series to forecast n: 04 Dec 2022 for (n+4 weeks)

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

## Adjusted IFRS* Prediction Methods for Consolidated Water Co. Ltd. Ordinary Shares

1. If any instrument in the pool does not meet the conditions in either paragraph B4.1.23 or paragraph B4.1.24, the condition in paragraph B4.1.21(b) is not met. In performing this assessment, a detailed instrument-byinstrument analysis of the pool may not be necessary. However, an entity must use judgement and perform sufficient analysis to determine whether the instruments in the pool meet the conditions in paragraphs B4.1.23–B4.1.24. (See also paragraph B4.1.18 for guidance on contractual cash flow characteristics that have only a de minimis effect.)
2. Hedge effectiveness is the extent to which changes in the fair value or the cash flows of the hedging instrument offset changes in the fair value or the cash flows of the hedged item (for example, when the hedged item is a risk component, the relevant change in fair value or cash flows of an item is the one that is attributable to the hedged risk). Hedge ineffectiveness is the extent to which the changes in the fair value or the cash flows of the hedging instrument are greater or less than those on the hedged item.
3. For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.
4. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary

*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

Consolidated Water Co. Ltd. Ordinary Shares assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Spearman Correlation1,2,3,4 and conclude that the CWCO 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 CWCO stock.

### Financial State Forecast for CWCO Consolidated Water Co. Ltd. Ordinary Shares Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B1
Operational Risk 5468
Market Risk7463
Technical Analysis6190
Fundamental Analysis7730
Risk Unsystematic3232

### Prediction Confidence Score

Trust metric by Neural Network: 90 out of 100 with 614 signals.

## References

1. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
2. Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
3. E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.
4. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
5. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
6. M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015
7. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
Frequently Asked QuestionsQ: What is the prediction methodology for CWCO stock?
A: CWCO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation
Q: Is CWCO stock a buy or sell?
A: The dominant strategy among neural network is to Hold CWCO Stock.
Q: Is Consolidated Water Co. Ltd. Ordinary Shares stock a good investment?
A: The consensus rating for Consolidated Water Co. Ltd. Ordinary Shares is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of CWCO stock?
A: The consensus rating for CWCO is Hold.
Q: What is the prediction period for CWCO stock?
A: The prediction period for CWCO is (n+4 weeks)