## Summary

The nature of stock market movement has always been ambiguous for investors because of various influential factors. This study aims to significantly reduce the risk of trend prediction with machine learning and deep learning algorithms.** We evaluate SET Index prediction models with Transfer Learning (ML) and ElasticNet Regression ^{1,2,3,4} and conclude that the SET Index stock is predictable in the short/long term. **

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold SET Index stock.**

## Key Points

- What statistical methods are used to analyze data?
- Is now good time to invest?
- Market Outlook

## SET Index Target Price Prediction Modeling Methodology

We consider SET Index Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of SET Index 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(ElasticNet Regression)

^{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(Transfer Learning (ML)) X S(n):→ (n+1 year) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of SET Index 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?

## SET Index Stock Forecast (Buy or Sell) for (n+1 year)

**Sample Set:**Neural Network

**Stock/Index:**SET Index SET Index

**Time series to forecast n: 27 Nov 2022**for (n+1 year)

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold SET Index 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 SET Index

- Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
- An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
- 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.
- For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, 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.

*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

SET Index assigned short-term Ba3 & long-term B2 forecasted stock rating.** We evaluate the prediction models Transfer Learning (ML) with ElasticNet Regression ^{1,2,3,4} and conclude that the SET Index stock is predictable in the short/long term.**

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold SET Index stock.**

### Financial State Forecast for SET Index SET Index Stock Options & Futures

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

Outlook* | Ba3 | B2 |

Operational Risk | 61 | 74 |

Market Risk | 57 | 65 |

Technical Analysis | 42 | 45 |

Fundamental Analysis | 85 | 42 |

Risk Unsystematic | 90 | 32 |

### Prediction Confidence Score

## References

- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- Matzkin RL. 2007. Nonparametric identification. In Handbook of Econometrics, Vol. 6B, ed. J Heckman, E Learner, pp. 5307–68. Amsterdam: Elsevier
- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
- Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
- J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell

## Frequently Asked Questions

Q: What is the prediction methodology for SET Index stock?A: SET Index stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and ElasticNet Regression

Q: Is SET Index stock a buy or sell?

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

Q: Is SET Index stock a good investment?

A: The consensus rating for SET Index is Hold and assigned short-term Ba3 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of SET Index stock?

A: The consensus rating for SET Index is Hold.

Q: What is the prediction period for SET Index stock?

A: The prediction period for SET Index is (n+1 year)

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