**Outlook:**BAUMART HOLDINGS LIMITED assigned short-term B1 & long-term B1 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 06 Dec 2022**for (n+3 month)

**Methodology :**Active Learning (ML)

## Abstract

In modern financial market, the most crucial problem is to find essential approach to outline and visualizing the predictions in stock-markets to be made by individuals in order to attain maximum profit by investments. The stock market is a transformative, non-straight dynamical and complex system. Long term investment is one of the major investment decisions. Though, evaluating shares and calculating elementary values for companies for long term investment is difficult. In this paper we are going to present comparison of machine learning aided algorithms to evaluate the stock prices in the future to analyze market behaviour.(Kumar, D., Sarangi, P.K. and Verma, R., 2021. A systematic review of stock market prediction using machine learning and statistical techniques. Materials Today: Proceedings.)** We evaluate BAUMART HOLDINGS LIMITED prediction models with Active Learning (ML) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the BMH 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 Buy BMH stock.**

## Key Points

- What statistical methods are used to analyze data?
- Can neural networks predict stock market?
- Can stock prices be predicted?

## BMH Target Price Prediction Modeling Methodology

We consider BAUMART HOLDINGS LIMITED Decision Process with Active Learning (ML) where A is the set of discrete actions of BMH 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Active Learning (ML)) 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 BMH 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?

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

**Sample Set:**Neural Network

**Stock/Index:**BMH BAUMART HOLDINGS LIMITED

**Time series to forecast n: 06 Dec 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy BMH 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 BAUMART HOLDINGS LIMITED

- When an entity designates a financial liability as at fair value through profit or loss, it must determine whether presenting in other comprehensive income the effects of changes in the liability's credit risk would create or enlarge an accounting mismatch in profit or loss. An accounting mismatch would be created or enlarged if presenting the effects of changes in the liability's credit risk in other comprehensive income would result in a greater mismatch in profit or loss than if those amounts were presented in profit or loss
- For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.
- For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.
- Rebalancing is accounted for as a continuation of the hedging relationship in accordance with paragraphs B6.5.9–B6.5.21. On rebalancing, the hedge ineffectiveness of the hedging relationship is determined and recognised immediately before adjusting the hedging relationship.

*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

BAUMART HOLDINGS LIMITED assigned short-term B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Active Learning (ML) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the BMH 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 Buy BMH stock.**

### Financial State Forecast for BMH BAUMART HOLDINGS LIMITED Options & Futures

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

Outlook* | B1 | B1 |

Operational Risk | 72 | 76 |

Market Risk | 51 | 55 |

Technical Analysis | 53 | 75 |

Fundamental Analysis | 75 | 33 |

Risk Unsystematic | 41 | 56 |

### Prediction Confidence Score

## References

- Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
- M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
- Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
- Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
- Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
- D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]

## Frequently Asked Questions

Q: What is the prediction methodology for BMH stock?A: BMH stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Wilcoxon Sign-Rank Test

Q: Is BMH stock a buy or sell?

A: The dominant strategy among neural network is to Buy BMH Stock.

Q: Is BAUMART HOLDINGS LIMITED stock a good investment?

A: The consensus rating for BAUMART HOLDINGS LIMITED is Buy and assigned short-term B1 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of BMH stock?

A: The consensus rating for BMH is Buy.

Q: What is the prediction period for BMH stock?

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