**Outlook:**Imperial Oil Limited Common Stock assigned short-term Ba3 & long-term B2 forecasted stock rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 09 Dec 2022**for (n+3 month)

**Methodology :**Modular Neural Network (Market News Sentiment Analysis)

## Abstract

A speculator on a Stock Market, aside from having money to spare, needs at least one other thing — a means of producing accurate and understandable predictions ahead of others in the Market, so that a tactical and price advantage can be gained. This work demonstrates that it is possible to predict one such Market to a high degree of accuracy. (Strader, T.J., Rozycki, J.J., Root, T.H. and Huang, Y.H.J., 2020. Machine learning stock market prediction studies: Review and research directions. Journal of International Technology and Information Management, 28(4), pp.63-83.)** We evaluate Imperial Oil Limited Common Stock prediction models with Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the IMO stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell**

## Key Points

- Which neural network is best for prediction?
- What is the use of Markov decision process?
- Buy, Sell and Hold Signals

## IMO Target Price Prediction Modeling Methodology

We consider Imperial Oil Limited Common Stock Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of IMO 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 Rank-Sum Test)

^{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(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^{n}\left({s}_{i}\right)$

n:Time series to forecast

p:Price signals of IMO 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?

## IMO Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**IMO Imperial Oil Limited Common Stock

**Time series to forecast n: 09 Dec 2022**for (n+3 month)

**According to price forecasts for (n+3 month) 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 Imperial Oil Limited Common Stock

- All investments in equity instruments and contracts on those instruments must be measured at fair value. However, in limited circumstances, cost may be an appropriate estimate of fair value. That may be the case if insufficient more recent information is available to measure fair value, or if there is a wide range of possible fair value measurements and cost represents the best estimate of fair value within that range.
- When measuring hedge ineffectiveness, an entity shall consider the time value of money. Consequently, the entity determines the value of the hedged item on a present value basis and therefore the change in the value of the hedged item also includes the effect of the time value of money.
- Paragraph 6.3.4 permits an entity to designate as hedged items aggregated exposures that are a combination of an exposure and a derivative. When designating such a hedged item, an entity assesses whether the aggregated exposure combines an exposure with a derivative so that it creates a different aggregated exposure that is managed as one exposure for a particular risk (or risks). In that case, the entity may designate the hedged item on the basis of the aggregated exposure
- An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.

*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

Imperial Oil Limited Common Stock assigned short-term Ba3 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the IMO stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell**

### Financial State Forecast for IMO Imperial Oil Limited Common Stock Options & Futures

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

Outlook* | Ba3 | B2 |

Operational Risk | 52 | 57 |

Market Risk | 45 | 52 |

Technical Analysis | 78 | 44 |

Fundamental Analysis | 87 | 33 |

Risk Unsystematic | 57 | 63 |

### Prediction Confidence Score

## References

- Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
- A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
- Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
- Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
- Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93

## Frequently Asked Questions

Q: What is the prediction methodology for IMO stock?A: IMO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Wilcoxon Rank-Sum Test

Q: Is IMO stock a buy or sell?

A: The dominant strategy among neural network is to Sell IMO Stock.

Q: Is Imperial Oil Limited Common Stock stock a good investment?

A: The consensus rating for Imperial Oil Limited Common Stock is Sell and assigned short-term Ba3 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of IMO stock?

A: The consensus rating for IMO is Sell.

Q: What is the prediction period for IMO stock?

A: The prediction period for IMO is (n+3 month)