**Outlook:**INTELLIHR LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 21 Mar 2023**for (n+16 weeks)

**Methodology :**Modular Neural Network (Market Volatility Analysis)

## Abstract

INTELLIHR LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Paired T-Test^{1,2,3,4}and it is concluded that the IHR 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

- Can neural networks predict stock market?
- Trading Interaction
- What is the use of Markov decision process?

## IHR Target Price Prediction Modeling Methodology

We consider INTELLIHR LIMITED Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of IHR 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(Paired T-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 Volatility Analysis)) X S(n):→ (n+16 weeks) $\overrightarrow{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of IHR 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?

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

**Sample Set:**Neural Network

**Stock/Index:**IHR INTELLIHR LIMITED

**Time series to forecast n: 21 Mar 2023**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 (Grey to Black): *Technical Analysis%**

## IFRS Reconciliation Adjustments for INTELLIHR LIMITED

- The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
- The characteristics of the hedged item, including how and when the hedged item affects profit or loss, also affect the period over which the forward element of a forward contract that hedges a time-period related hedged item is amortised, which is over the period to which the forward element relates. For example, if a forward contract hedges the exposure to variability in threemonth interest rates for a three-month period that starts in six months' time, the forward element is amortised during the period that spans months seven to nine.
- An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
- Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

## Conclusions

INTELLIHR LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. INTELLIHR LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Paired T-Test^{1,2,3,4} and it is concluded that the IHR 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**

### IHR INTELLIHR LIMITED Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | Caa2 | C |

Balance Sheet | Baa2 | Caa2 |

Leverage Ratios | Baa2 | Ba3 |

Cash Flow | B3 | C |

Rates of Return and Profitability | C | C |

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.

How does neural network examine financial reports and understand financial state of the company?

### Prediction Confidence Score

## References

- J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
- Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
- E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
- R. Rockafellar and S. Uryasev. Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7):1443 – 1471, 2002
- Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
- Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
- S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010

## Frequently Asked Questions

Q: What is the prediction methodology for IHR stock?A: IHR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Paired T-Test

Q: Is IHR stock a buy or sell?

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

Q: Is INTELLIHR LIMITED stock a good investment?

A: The consensus rating for INTELLIHR LIMITED is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of IHR stock?

A: The consensus rating for IHR is Hold.

Q: What is the prediction period for IHR stock?

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