Modelling A.I. in Economics

LON:VNH Stock: Where should i invest $1000 right now?

Outlook: VIETNAM HOLDING LIMITED is assigned short-term Ba3 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n: for Weeks2
Methodology : Reinforcement Machine Learning (ML)
Hypothesis Testing : Lasso Regression
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.

Abstract

VIETNAM HOLDING LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the LON:VNH stock is predictable in the short/long term. Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Buy

Graph 49

Key Points

  1. What is a prediction confidence?
  2. Is it better to buy and sell or hold?
  3. Trading Interaction

LON:VNH Target Price Prediction Modeling Methodology

We consider VIETNAM HOLDING LIMITED Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of LON:VNH 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(Lasso Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Reinforcement Machine Learning (ML)) X S(n):→ 4 Weeks i = 1 n r i

n:Time series to forecast

p:Price signals of LON:VNH stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Reinforcement Machine Learning (ML)

Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.

Lasso Regression

Lasso regression, also known as L1 regularization, is a type of regression analysis that adds a penalty to the least squares objective function in order to reduce the variance of the estimates and to induce sparsity in the model. This is done by adding a term to the objective function that is proportional to the sum of the absolute values of the coefficients. The penalty term is called the "lasso" penalty, and it is controlled by a parameter called the "lasso constant". Lasso regression can be used to address the problem of multicollinearity in linear regression, as well as the problem of overfitting. Multicollinearity occurs when two or more independent variables are highly correlated. This can cause the standard errors of the coefficients to be large, and it can also cause the coefficients to be unstable. Overfitting occurs when a model is too closely fit to the training data, and as a result, it does not generalize well to new data.

 

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:VNH Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: LON:VNH VIETNAM HOLDING LIMITED
Time series to forecast: 4 Weeks

According to price forecasts, the dominant strategy among neural network is: Buy

Strategic Interaction Table Legend:

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 (Grey to Black): *Technical Analysis%

Financial Data Adjustments for Reinforcement Machine Learning (ML) based LON:VNH Stock Prediction Model

  1. An entity shall assess whether contractual cash flows are solely payments of principal and interest on the principal amount outstanding for the currency in which the financial asset is denominated.
  2. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
  3. 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.
  4. Paragraph 6.3.4 permits an entity to designate as hedged items aggregated exposures that are a combination of an exposure and a derivative. When designating such a hedged item, an entity assesses whether the aggregated exposure combines an exposure with a derivative so that it creates a different aggregated exposure that is managed as one exposure for a particular risk (or risks). In that case, the entity may designate the hedged item on the basis of the aggregated exposure

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

LON:VNH VIETNAM HOLDING LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Income StatementCC
Balance SheetBaa2Baa2
Leverage RatiosBaa2B3
Cash FlowBaa2B3
Rates of Return and ProfitabilityCBa3

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Conclusions

VIETNAM HOLDING LIMITED is assigned short-term Ba3 & long-term B1 estimated rating. VIETNAM HOLDING LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and Lasso Regression1,2,3,4 and it is concluded that the LON:VNH stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Buy

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 733 signals.

References

  1. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
  2. Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
  3. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
  4. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
  5. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
  6. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
  7. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
Frequently Asked QuestionsQ: What is the prediction methodology for LON:VNH stock?
A: LON:VNH stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Lasso Regression
Q: Is LON:VNH stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:VNH Stock.
Q: Is VIETNAM HOLDING LIMITED stock a good investment?
A: The consensus rating for VIETNAM HOLDING LIMITED is Buy and is assigned short-term Ba3 & long-term B1 estimated rating.
Q: What is the consensus rating of LON:VNH stock?
A: The consensus rating for LON:VNH is Buy.
Q: What is the prediction period for LON:VNH stock?
A: The prediction period for LON:VNH is 4 Weeks

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