FIRST AU LIMITED Research Report

## Summary

Stock markets are affected by many uncertainties and interrelated economic and political factors at both local and global levels. The key to successful stock market forecasting is achieving best results with minimum required input data. To determine the set of relevant factors for making accurate predictions is a complicated task and so regular stock market analysis is very essential. More specifically, the stock market's movements are analyzed and predicted in order to retrieve knowledge that could guide investors on when to buy and sell. We evaluate FIRST AU LIMITED prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Logistic Regression1,2,3,4 and conclude that the FAU stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold FAU stock.

## Key Points

1. Market Outlook
2. Which neural network is best for prediction?
3. What is the best way to predict stock prices?

## FAU Target Price Prediction Modeling Methodology

We consider FIRST AU LIMITED Stock Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of FAU 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(Logistic Regression)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+3 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of FAU 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?

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

Sample Set: Neural Network
Stock/Index: FAU FIRST AU LIMITED
Time series to forecast n: 24 Nov 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold FAU 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 FIRST AU LIMITED

1. For example, an entity hedges an exposure to Foreign Currency A using a currency derivative that references Foreign Currency B and Foreign Currencies A and B are pegged (ie their exchange rate is maintained within a band or at an exchange rate set by a central bank or other authority). If the exchange rate between Foreign Currency A and Foreign Currency B were changed (ie a new band or rate was set), rebalancing the hedging relationship to reflect the new exchange rate would ensure that the hedging relationship would continue to meet the hedge effectiveness requirement for the hedge ratio in the new circumstances. In contrast, if there was a default on the currency derivative, changing the hedge ratio could not ensure that the hedging relationship would continue to meet that hedge effectiveness requirement. Hence, rebalancing does not facilitate the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item changes in a way that cannot be compensated for by adjusting the hedge ratio
2. Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
3. Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.
4. 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.

*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

FIRST AU LIMITED assigned short-term Ba3 & long-term Baa2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Logistic Regression1,2,3,4 and conclude that the FAU stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold FAU stock.

### Financial State Forecast for FAU FIRST AU LIMITED Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Baa2
Operational Risk 8081
Market Risk4663
Technical Analysis6352
Fundamental Analysis8989
Risk Unsystematic4185

### Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 640 signals.

## References

1. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
2. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
3. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
4. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
5. F. A. Oliehoek, M. T. J. Spaan, and N. A. Vlassis. Optimal and approximate q-value functions for decentralized pomdps. J. Artif. Intell. Res. (JAIR), 32:289–353, 2008
6. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
7. S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
Frequently Asked QuestionsQ: What is the prediction methodology for FAU stock?
A: FAU stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Logistic Regression
Q: Is FAU stock a buy or sell?
A: The dominant strategy among neural network is to Hold FAU Stock.
Q: Is FIRST AU LIMITED stock a good investment?
A: The consensus rating for FIRST AU LIMITED is Hold and assigned short-term Ba3 & long-term Baa2 forecasted stock rating.
Q: What is the consensus rating of FAU stock?
A: The consensus rating for FAU is Hold.
Q: What is the prediction period for FAU stock?
A: The prediction period for FAU is (n+3 month)