Recently, a lot of interesting work has been done in the area of applying Machine Learning Algorithms for analyzing price patterns and predicting stock prices and index changes. Most stock traders nowadays depend on Intelligent Trading Systems which help them in predicting prices based on various situations and conditions, thereby helping them in making instantaneous investment decisions. We evaluate GRAND VISION MEDIA HOLDINGS PLC prediction models with Supervised Machine Learning (ML) and Independent T-Test1,2,3,4 and conclude that the LON:GVMH stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:GVMH stock.

Keywords: LON:GVMH, GRAND VISION MEDIA HOLDINGS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Technical Analysis with Algorithmic Trading
2. Market Outlook
3. What is Markov decision process in reinforcement learning?

## LON:GVMH Target Price Prediction Modeling Methodology

With the advent of machine learning, numerous approaches have been proposed to forecast stock prices. Various models have been developed to date such as Recurrent Neural Networks, Long Short-Term Memory, Convolutional Neural Network sliding window, etc., but were not accurate enough. Here, the aim is to predict the price of a stock and compare the results obtained using three major algorithms namely Kalman filters, XGBoost and ARIMA. We consider GRAND VISION MEDIA HOLDINGS PLC Stock Decision Process with Independent T-Test where A is the set of discrete actions of LON:GVMH 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(Independent T-Test)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(Supervised Machine Learning (ML)) X S(n):→ (n+6 month) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of LON:GVMH 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?

## LON:GVMH Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:GVMH GRAND VISION MEDIA HOLDINGS PLC
Time series to forecast n: 05 Nov 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:GVMH 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 GRAND VISION MEDIA HOLDINGS PLC

1. When an entity first applies this Standard, it may choose as its accounting policy to continue to apply the hedge accounting requirements of IAS 39 instead of the requirements in Chapter 6 of this Standard. An entity shall apply that policy to all of its hedging relationships. An entity that chooses that policy shall also apply IFRIC 16 Hedges of a Net Investment in a Foreign Operation without the amendments that conform that Interpretation to the requirements in Chapter 6 of this Standard.
2. IFRS 17, issued in May 2017, amended paragraphs 2.1, B2.1, B2.4, B2.5 and B4.1.30, and added paragraph 3.3.5. Amendments to IFRS 17, issued in June 2020, further amended paragraph 2.1 and added paragraphs 7.2.36‒7.2.42. An entity shall apply those amendments when it applies IFRS 17.
3. An entity that first applies these amendments at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.31–7.2.34.
4. At the date of initial application, an entity is permitted to make the designation in paragraph 2.5 for contracts that already exist on the date but only if it designates all similar contracts. The change in the net assets resulting from such designations shall be recognised in retained earnings at the date of initial application.

*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

GRAND VISION MEDIA HOLDINGS PLC assigned short-term Baa2 & long-term B1 forecasted stock rating. We evaluate the prediction models Supervised Machine Learning (ML) with Independent T-Test1,2,3,4 and conclude that the LON:GVMH stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:GVMH stock.

### Financial State Forecast for LON:GVMH GRAND VISION MEDIA HOLDINGS PLC Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Baa2B1
Operational Risk 5864
Market Risk6230
Technical Analysis8647
Fundamental Analysis7464
Risk Unsystematic8777

### Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 725 signals.

## References

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3. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
4. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
5. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
6. V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
7. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:GVMH stock?
A: LON:GVMH stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Independent T-Test
Q: Is LON:GVMH stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:GVMH Stock.
Q: Is GRAND VISION MEDIA HOLDINGS PLC stock a good investment?
A: The consensus rating for GRAND VISION MEDIA HOLDINGS PLC is Hold and assigned short-term Baa2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:GVMH stock?
A: The consensus rating for LON:GVMH is Hold.
Q: What is the prediction period for LON:GVMH stock?
A: The prediction period for LON:GVMH is (n+6 month)