Modelling A.I. in Economics

LON:IAT Stock: A Risky Bet for Investors

Outlook: INVESCO ASIA TRUST PLC is assigned short-term B1 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Reinforcement Machine Learning (ML)
Hypothesis Testing : Chi-Square
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

INVESCO ASIA TRUST PLC prediction model is evaluated with Reinforcement Machine Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the LON:IAT 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: Speculative Trend

Graph 35

Key Points

  1. How do you decide buy or sell a stock?
  2. What statistical methods are used to analyze data?
  3. Reaction Function

LON:IAT Target Price Prediction Modeling Methodology

We consider INVESCO ASIA TRUST PLC Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of LON:IAT 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(Chi-Square)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 R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of LON:IAT 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.

Chi-Square

A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.

 

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:IAT Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: LON:IAT INVESCO ASIA TRUST PLC
Time series to forecast: 4 Weeks

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

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:IAT Stock Prediction Model

  1. If a financial instrument is designated in accordance with paragraph 6.7.1 as measured at fair value through profit or loss after its initial recognition, or was previously not recognised, the difference at the time of designation between the carrying amount, if any, and the fair value shall immediately be recognised in profit or loss. For financial assets measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A, the cumulative gain or loss previously recognised in other comprehensive income shall immediately be reclassified from equity to profit or loss as a reclassification adjustment.
  2. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).
  3. The accounting for the time value of options in accordance with paragraph 6.5.15 applies only to the extent that the time value relates to the hedged item (aligned time value). The time value of an option relates to the hedged item if the critical terms of the option (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the option and the hedged item are not fully aligned, an entity shall determine the aligned time value, ie how much of the time value included in the premium (actual time value) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.15). An entity determines the aligned time value using the valuation of the option that would have critical terms that perfectly match the hedged item.
  4. IFRS 7 defines credit risk as 'the risk that one party to a financial instrument will cause a financial loss for the other party by failing to discharge an obligation'. The requirement in paragraph 5.7.7(a) relates to the risk that the issuer will fail to perform on that particular liability. It does not necessarily relate to the creditworthiness of the issuer. For example, if an entity issues a collateralised liability and a non-collateralised liability that are otherwise identical, the credit risk of those two liabilities will be different, even though they are issued by the same entity. The credit risk on the collateralised liability will be less than the credit risk of the non-collateralised liability. The credit risk for a collateralised liability may be close to zero.

*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:IAT INVESCO ASIA TRUST PLC Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1B1
Income StatementB2B1
Balance SheetB1Baa2
Leverage RatiosCaa2Baa2
Cash FlowB2C
Rates of Return and ProfitabilityBaa2C

*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

INVESCO ASIA TRUST PLC is assigned short-term B1 & long-term B1 estimated rating. INVESCO ASIA TRUST PLC prediction model is evaluated with Reinforcement Machine Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the LON:IAT stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

Prediction Confidence Score

Trust metric by Neural Network: 92 out of 100 with 826 signals.

References

  1. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
  2. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
  3. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
  4. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
  5. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, Newey W. 2017. Double/debiased/ Neyman machine learning of treatment effects. Am. Econ. Rev. 107:261–65
  6. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
  7. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:IAT stock?
A: LON:IAT stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Chi-Square
Q: Is LON:IAT stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend LON:IAT Stock.
Q: Is INVESCO ASIA TRUST PLC stock a good investment?
A: The consensus rating for INVESCO ASIA TRUST PLC is Speculative Trend and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of LON:IAT stock?
A: The consensus rating for LON:IAT is Speculative Trend.
Q: What is the prediction period for LON:IAT stock?
A: The prediction period for LON:IAT is 4 Weeks

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