CRD CONRAD ASIA ENERGY LTD.

Outlook: CONRAD ASIA ENERGY LTD. assigned short-term B3 & long-term Baa2 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 12 Dec 2022 for (n+16 weeks)
Methodology : Multi-Instance Learning (ML)

Abstract

This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysis. To study the influence of market characteristics on stock prices, traditional neural network algorithms may incorrectly predict the stock market, since the initial weight of the random selection problem can be easily prone to incorrect predictions. (Parray, I.R., Khurana, S.S., Kumar, M. and Altalbe, A.A., 2020. Time series data analysis of stock price movement using machine learning techniques. Soft Computing, 24(21), pp.16509-16517.) We evaluate CONRAD ASIA ENERGY LTD. prediction models with Multi-Instance Learning (ML) and Wilcoxon Sign-Rank Test^1,2,3,4 and conclude that the CRD stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

Key Points

1. Is now good time to invest?
2. Probability Distribution
3. Should I buy stocks now or wait amid such uncertainty?

CRD Target Price Prediction Modeling Methodology

We consider CONRAD ASIA ENERGY LTD. Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of CRD 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(Wilcoxon Sign-Rank Test)^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(Multi-Instance Learning (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of CRD 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?

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

Sample Set: Neural Network
Stock/Index: CRD CONRAD ASIA ENERGY LTD.
Time series to forecast n: 12 Dec 2022 for (n+16 weeks)

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

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 (Grey to Black): *Technical Analysis%

Adjusted IFRS* Prediction Methods for CONRAD ASIA ENERGY LTD.

1. A regular way purchase or sale gives rise to a fixed price commitment between trade date and settlement date that meets the definition of a derivative. However, because of the short duration of the commitment it is not recognised as a derivative financial instrument. Instead, this Standard provides for special accounting for such regular way contracts (see paragraphs 3.1.2 and B3.1.3–B3.1.6).
2. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.
3. 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.)
4. The accounting for the forward element of forward contracts in accordance with paragraph 6.5.16 applies only to the extent that the forward element relates to the hedged item (aligned forward element). The forward element of a forward contract relates to the hedged item if the critical terms of the forward contract (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the forward contract and the hedged item are not fully aligned, an entity shall determine the aligned forward element, ie how much of the forward element included in the forward contract (actual forward element) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.16). An entity determines the aligned forward element using the valuation of the forward contract that would have critical terms that perfectly match the hedged item.

*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

CONRAD ASIA ENERGY LTD. assigned short-term B3 & long-term Baa2 forecasted stock rating. We evaluate the prediction models Multi-Instance Learning (ML) with Wilcoxon Sign-Rank Test^1,2,3,4 and conclude that the CRD stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

Financial State Forecast for CRD CONRAD ASIA ENERGY LTD. Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B3	Baa2
Operational Risk	72	72
Market Risk	55	78
Technical Analysis	39	79
Fundamental Analysis	37	59
Risk Unsystematic	32	82

Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 834 signals.

References

1. Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
2. 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.
3. Athey S, Mobius MM, Pál J. 2017c. The impact of aggregators on internet news consumption. Unpublished manuscript, Grad. School Bus., Stanford Univ., Stanford, CA
4. Athey S, Mobius MM, Pál J. 2017c. The impact of aggregators on internet news consumption. Unpublished manuscript, Grad. School Bus., Stanford Univ., Stanford, CA
5. Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
6. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
7. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer

Frequently Asked Questions

Q: What is the prediction methodology for CRD stock?
A: CRD stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is CRD stock a buy or sell?
A: The dominant strategy among neural network is to Sell CRD Stock.
Q: Is CONRAD ASIA ENERGY LTD. stock a good investment?
A: The consensus rating for CONRAD ASIA ENERGY LTD. is Sell and assigned short-term B3 & long-term Baa2 forecasted stock rating.
Q: What is the consensus rating of CRD stock?
A: The consensus rating for CRD is Sell.
Q: What is the prediction period for CRD stock?
A: The prediction period for CRD is (n+16 weeks)

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