## Abstract

Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. (Leung, C.K.S., MacKinnon, R.K. and Wang, Y., 2014, July. A machine learning approach for stock price prediction. In Proceedings of the 18th International Database Engineering & Applications Symposium (pp. 274-277).)** We evaluate Stran & Company Inc. Warrant prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Factor ^{1,2,3,4} and conclude that the STRNW stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy STRNW stock.**

## Key Points

- Decision Making
- What are buy sell or hold recommendations?
- What is the use of Markov decision process?

## STRNW Target Price Prediction Modeling Methodology

We consider Stran & Company Inc. Warrant Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of STRNW 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(Factor)

^{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 (Emotional Trigger/Responses 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 STRNW 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?

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

**Sample Set:**Neural Network

**Stock/Index:**STRNW Stran & Company Inc. Warrant

**Time series to forecast n: 05 Dec 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy STRNW 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 Stran & Company Inc. Warrant

- If such a mismatch would be created or enlarged, the entity is required to present all changes in fair value (including the effects of changes in the credit risk of the liability) in profit or loss. If such a mismatch would not be created or enlarged, the entity is required to present the effects of changes in the liability's credit risk in other comprehensive income.
- For the purpose of applying the requirement in paragraph 6.5.12 in order to determine whether the hedged future cash flows are expected to occur, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
- Leverage is a contractual cash flow characteristic of some financial assets. Leverage increases the variability of the contractual cash flows with the result that they do not have the economic characteristics of interest. Stand-alone option, forward and swap contracts are examples of financial assets that include such leverage. Thus, such contracts do not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and cannot be subsequently measured at amortised cost or fair value through other comprehensive income.
- An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.

*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

Stran & Company Inc. Warrant assigned short-term Ba3 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Factor ^{1,2,3,4} and conclude that the STRNW stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy STRNW stock.**

### Financial State Forecast for STRNW Stran & Company Inc. Warrant Options & Futures

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

Outlook* | Ba3 | B1 |

Operational Risk | 84 | 72 |

Market Risk | 59 | 35 |

Technical Analysis | 47 | 71 |

Fundamental Analysis | 84 | 72 |

Risk Unsystematic | 60 | 41 |

### Prediction Confidence Score

## References

- Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
- Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
- Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
- H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
- G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
- 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 STRNW stock?A: STRNW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Factor

Q: Is STRNW stock a buy or sell?

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

Q: Is Stran & Company Inc. Warrant stock a good investment?

A: The consensus rating for Stran & Company Inc. Warrant is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of STRNW stock?

A: The consensus rating for STRNW is Buy.

Q: What is the prediction period for STRNW stock?

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