Modelling A.I. in Economics

Buy, Sell, or Hold? (LYV Stock Forecast)

In today's economy, there is a profound impact of the stock market or equity market. Prediction of stock prices is extremely complex, chaotic, and the presence of a dynamic environment makes it a great challenge. Behavioural finance suggests that decision-making process of investors is to a very great extent influenced by the emotions and sentiments in response to a particular news. Thus, to support the decisions of the investors, we have presented an approach combining two distinct fields for analysis of stock exchange. We evaluate Live Nation Entertainment prediction models with Multi-Task Learning (ML) and Logistic Regression1,2,3,4 and conclude that the LYV 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 LYV stock.


Keywords: LYV, Live Nation Entertainment, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How do predictive algorithms actually work?
  2. Market Outlook
  3. Buy, Sell and Hold Signals

LYV Target Price Prediction Modeling Methodology

Market systems are so complex that they overwhelm the ability of any individual to predict. But it is crucial for the investors to predict stock market price to generate notable profit. We have taken into factors such as Commodity Prices (crude oil, gold, silver), Market History, and Foreign exchange rate (FEX) that influence the stock trend. We consider Live Nation Entertainment Stock Decision Process with Logistic Regression where A is the set of discrete actions of LYV 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(Logistic 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(Multi-Task Learning (ML)) X S(n):→ (n+1 year) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of LYV 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?

LYV Stock Forecast (Buy or Sell) for (n+1 year)


Sample Set: Neural Network
Stock/Index: LYV Live Nation Entertainment
Time series to forecast n: 08 Nov 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LYV 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 Live Nation Entertainment

  1. 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.
  2. The rebuttable presumption in paragraph 5.5.11 is not an absolute indicator that lifetime expected credit losses should be recognised, but is presumed to be the latest point at which lifetime expected credit losses should be recognised even when using forward-looking information (including macroeconomic factors on a portfolio level).
  3. 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.
  4. Credit risk analysis is a multifactor and holistic analysis; whether a specific factor is relevant, and its weight compared to other factors, will depend on the type of product, characteristics of the financial instruments and the borrower as well as the geographical region. An entity shall consider reasonable and supportable information that is available without undue cost or effort and that is relevant for the particular financial instrument being assessed. However, some factors or indicators may not be identifiable on an individual financial instrument level. In such a case, the factors or indicators should be assessed for appropriate portfolios, groups of portfolios or portions of a portfolio of financial instruments to determine whether the requirement in paragraph 5.5.3 for the recognition of lifetime expected credit losses has been met.

*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

Live Nation Entertainment assigned short-term B3 & long-term Ba1 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Logistic Regression1,2,3,4 and conclude that the LYV 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 LYV stock.

Financial State Forecast for LYV Live Nation Entertainment Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3Ba1
Operational Risk 4275
Market Risk7451
Technical Analysis3368
Fundamental Analysis4778
Risk Unsystematic4481

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 688 signals.

References

  1. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
  2. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
  3. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
  4. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  5. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
  6. Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
  7. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
Frequently Asked QuestionsQ: What is the prediction methodology for LYV stock?
A: LYV stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Logistic Regression
Q: Is LYV stock a buy or sell?
A: The dominant strategy among neural network is to Hold LYV Stock.
Q: Is Live Nation Entertainment stock a good investment?
A: The consensus rating for Live Nation Entertainment is Hold and assigned short-term B3 & long-term Ba1 forecasted stock rating.
Q: What is the consensus rating of LYV stock?
A: The consensus rating for LYV is Hold.
Q: What is the prediction period for LYV stock?
A: The prediction period for LYV is (n+1 year)



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