It has never been easy to invest in a set of assets, the abnormally of financial market does not allow simple models to predict future asset values with higher accuracy. Machine learning, which consist of making computers perform tasks that normally requiring human intelligence is currently the dominant trend in scientific research. This article aims to build a model using Recurrent Neural Networks (RNN) and especially Long-Short Term Memory model (LSTM) to predict future stock market values. We evaluate BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY prediction models with Multi-Task Learning (ML) and Sign Test1,2,3,4 and conclude that the LON:BOCH 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 LON:BOCH stock.

Keywords: LON:BOCH, BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Stock Rating
2. Nash Equilibria
3. What is statistical models in machine learning?

## LON:BOCH Target Price Prediction Modeling Methodology

This study presents financial network indicators that can be applied to global stock market investment strategies. We propose to design both undirected and directed volatility networks of global stock market based on simple pair-wise correlation and system-wide connectedness of stock date using a vector auto-regressive model. We consider BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY Stock Decision Process with Sign Test where A is the set of discrete actions of LON:BOCH 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(Sign 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(Multi-Task Learning (ML)) X S(n):→ (n+1 year) $∑ i = 1 n a i$

n:Time series to forecast

p:Price signals of LON:BOCH 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:BOCH Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: LON:BOCH BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY
Time series to forecast n: 31 Oct 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:BOCH 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 BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY

1. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
2. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
3. At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.
4. An entity need not undertake an exhaustive search for information but shall consider all reasonable and supportable information that is available without undue cost or effort and that is relevant to the estimate of expected credit losses, including the effect of expected prepayments. The information used shall include factors that are specific to the borrower, general economic conditions and an assessment of both the current as well as the forecast direction of conditions at the reporting date. An entity may use various sources of data, that may be both internal (entity-specific) and external. Possible data sources include internal historical credit loss experience, internal ratings, credit loss experience of other entities and external ratings, reports and statistics. Entities that have no, or insufficient, sources of entityspecific data may use peer group experience for the comparable financial instrument (or groups of financial instruments).

*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

BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY assigned short-term Ba1 & long-term B1 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Sign Test1,2,3,4 and conclude that the LON:BOCH 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 LON:BOCH stock.

### Financial State Forecast for LON:BOCH BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba1B1
Operational Risk 6583
Market Risk8350
Technical Analysis6558
Fundamental Analysis6768
Risk Unsystematic7431

### Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 837 signals.

## References

1. Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
2. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
3. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.
4. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
5. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
6. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
7. 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
Frequently Asked QuestionsQ: What is the prediction methodology for LON:BOCH stock?
A: LON:BOCH stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Sign Test
Q: Is LON:BOCH stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:BOCH Stock.
Q: Is BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY stock a good investment?
A: The consensus rating for BANK OF CYPRUS HOLDINGS PUBLIC LIMITED COMPANY is Hold and assigned short-term Ba1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:BOCH stock?
A: The consensus rating for LON:BOCH is Hold.
Q: What is the prediction period for LON:BOCH stock?
A: The prediction period for LON:BOCH is (n+1 year)