Outlook: MOHO RESOURCES LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 21 Mar 2023 for (n+8 weeks)
Methodology : Reinforcement Machine Learning (ML)

## Abstract

MOHO RESOURCES LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the MOH stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

## Key Points

1. Fundemental Analysis with Algorithmic Trading
2. Technical Analysis with Algorithmic Trading
3. How do you decide buy or sell a stock?

## MOH Target Price Prediction Modeling Methodology

We consider MOHO RESOURCES LIMITED Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of MOH 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(Lasso 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(Reinforcement Machine Learning (ML)) X S(n):→ (n+8 weeks) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of MOH 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?

## MOH Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: MOH MOHO RESOURCES LIMITED
Time series to forecast n: 21 Mar 2023 for (n+8 weeks)

According to price forecasts for (n+8 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 MOHO RESOURCES LIMITED

1. In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.
2. Paragraph 5.7.5 permits an entity to make an irrevocable election to present in other comprehensive income subsequent changes in the fair value of particular investments in equity instruments. Such an investment is not a monetary item. Accordingly, the gain or loss that is presented in other comprehensive income in accordance with paragraph 5.7.5 includes any related foreign exchange component.
3. A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
4. 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.

*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

MOHO RESOURCES LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. MOHO RESOURCES LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the MOH stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

### MOH MOHO RESOURCES LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Baa2
Balance SheetCCaa2
Leverage RatiosCaa2Ba1
Cash FlowB2Caa2
Rates of Return and ProfitabilityBaa2Baa2

*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

Trust metric by Neural Network: 84 out of 100 with 597 signals.

## References

1. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
2. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
3. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
4. Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
5. 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.
6. Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
7. 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.
Frequently Asked QuestionsQ: What is the prediction methodology for MOH stock?
A: MOH stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Lasso Regression
Q: Is MOH stock a buy or sell?
A: The dominant strategy among neural network is to Hold MOH Stock.
Q: Is MOHO RESOURCES LIMITED stock a good investment?
A: The consensus rating for MOHO RESOURCES LIMITED is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of MOH stock?
A: The consensus rating for MOH is Hold.
Q: What is the prediction period for MOH stock?
A: The prediction period for MOH is (n+8 weeks)