Modelling A.I. in Economics

LON:LDSG LEEDS GROUP PLC (Forecast)

LEEDS GROUP PLC Research Report

Summary

Recently, numerous investigations for stock price prediction and portfolio management using machine learning have been trying to develop efficient mechanical trading systems. But these systems have a limitation in that they are mainly based on the supervised learning which is not so adequate for learning problems with long-term goals and delayed rewards. This paper proposes a method of applying reinforcement learning, suitable for modeling and learning various kinds of interactions in real situations, to the problem of stock price prediction. We evaluate LEEDS GROUP PLC prediction models with Modular Neural Network (Market Direction Analysis) and Stepwise Regression1,2,3,4 and conclude that the LON:LDSG stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:LDSG stock.

Key Points

  1. Short/Long Term Stocks
  2. Can stock prices be predicted?
  3. Why do we need predictive models?

LON:LDSG Target Price Prediction Modeling Methodology

We consider LEEDS GROUP PLC Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LON:LDSG 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(Stepwise 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(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+16 weeks) e x rx

n:Time series to forecast

p:Price signals of LON:LDSG 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?

LON:LDSG Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: LON:LDSG LEEDS GROUP PLC
Time series to forecast n: 29 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:LDSG 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 LEEDS GROUP PLC

  1. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.
  2. For the purpose of applying the requirements in paragraphs 6.4.1(c)(i) and B6.4.4–B6.4.6, an entity shall assume that the interest rate benchmark on which the hedged cash flows and/or the hedged risk (contractually or noncontractually specified) are based, or the interest rate benchmark on which the cash flows of the hedging instrument are based, is not altered as a result of interest rate benchmark reform.
  3. An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.
  4. In cases such as those described in the preceding paragraph, to designate, at initial recognition, the financial assets and financial liabilities not otherwise so measured as at fair value through profit or loss may eliminate or significantly reduce the measurement or recognition inconsistency and produce more relevant information. For practical purposes, the entity need not enter into all of the assets and liabilities giving rise to the measurement or recognition inconsistency at exactly the same time. A reasonable delay is permitted provided that each transaction is designated as at fair value through profit or loss at its initial recognition and, at that time, any remaining transactions are expected to occur.

*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

LEEDS GROUP PLC assigned short-term B2 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Stepwise Regression1,2,3,4 and conclude that the LON:LDSG stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:LDSG stock.

Financial State Forecast for LON:LDSG LEEDS GROUP PLC Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2Ba2
Operational Risk 4983
Market Risk3167
Technical Analysis6267
Fundamental Analysis6245
Risk Unsystematic7571

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 782 signals.

References

  1. Athey S, Imbens G, Wager S. 2016a. Efficient inference of average treatment effects in high dimensions via approximate residual balancing. arXiv:1604.07125 [math.ST]
  2. Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
  3. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
  4. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
  5. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
  6. Harris ZS. 1954. Distributional structure. Word 10:146–62
  7. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
Frequently Asked QuestionsQ: What is the prediction methodology for LON:LDSG stock?
A: LON:LDSG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Stepwise Regression
Q: Is LON:LDSG stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:LDSG Stock.
Q: Is LEEDS GROUP PLC stock a good investment?
A: The consensus rating for LEEDS GROUP PLC is Hold and assigned short-term B2 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of LON:LDSG stock?
A: The consensus rating for LON:LDSG is Hold.
Q: What is the prediction period for LON:LDSG stock?
A: The prediction period for LON:LDSG is (n+16 weeks)

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