The stock market is an interesting industry to study. There are various variations present in it. Many experts have been studying and researching on the various trends that the stock market goes through. One of the major studies has been the attempt to predict the stock prices of various companies based on historical data. Prediction of stock prices will greatly help people to understand where and how to invest so that the risk of losing money is minimized.** We evaluate FUTU HOLDINGS ADS prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Paired T-Test ^{1,2,3,4} and conclude that the FUTU stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FUTU stock.**

**FUTU, FUTU HOLDINGS ADS, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Technical Analysis with Algorithmic Trading
- Can stock prices be predicted?
- Market Risk

## FUTU Target Price Prediction Modeling Methodology

Impact of many factors on the stock prices makes the stock prediction a difficult and highly complicated task. In this paper, machine learning techniques have been applied for the stock price prediction in order to overcome such difficulties. In the implemented work, five models have been developed and their performances are compared in predicting the stock market trends. We consider FUTU HOLDINGS ADS Stock Decision Process with Paired T-Test where A is the set of discrete actions of FUTU 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 (Social Media Sentiment Analysis)) X S(n):→ (n+4 weeks) $\overrightarrow{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of FUTU stock

j:Nash equilibria

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?

## FUTU Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**FUTU FUTU HOLDINGS ADS

**Time series to forecast n: 13 Nov 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FUTU 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 FUTU HOLDINGS ADS

- An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
- An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.
- If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
- For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.

*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

FUTU HOLDINGS ADS assigned short-term Ba2 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Paired T-Test ^{1,2,3,4} and conclude that the FUTU stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FUTU stock.**

### Financial State Forecast for FUTU FUTU HOLDINGS ADS Stock Options & Futures

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

Outlook* | Ba2 | Ba1 |

Operational Risk | 77 | 51 |

Market Risk | 70 | 86 |

Technical Analysis | 72 | 83 |

Fundamental Analysis | 51 | 69 |

Risk Unsystematic | 77 | 70 |

### Prediction Confidence Score

## References

- 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.
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
- Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
- Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
- Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
- T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000

## Frequently Asked Questions

Q: What is the prediction methodology for FUTU stock?A: FUTU stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Paired T-Test

Q: Is FUTU stock a buy or sell?

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

Q: Is FUTU HOLDINGS ADS stock a good investment?

A: The consensus rating for FUTU HOLDINGS ADS is Hold and assigned short-term Ba2 & long-term Ba1 forecasted stock rating.

Q: What is the consensus rating of FUTU stock?

A: The consensus rating for FUTU is Hold.

Q: What is the prediction period for FUTU stock?

A: The prediction period for FUTU is (n+4 weeks)

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