AUC Score :
Short-Term Revised1 :
Dominant Strategy : BuySpeculative Trend
Time series to forecast n:
Methodology : Statistical Inference (ML)
Hypothesis Testing : Factor
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.
Summary
Gaming and Leisure Properties Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Factor1,2,3,4 and it is concluded that the GLPI stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: BuySpeculative Trend
Key Points
- What is the best way to predict stock prices?
- How do you decide buy or sell a stock?
- Stock Rating
GLPI Target Price Prediction Modeling Methodology
We consider Gaming and Leisure Properties Inc. Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of GLPI 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(Factor)5,6,7= X R(Statistical Inference (ML)) X S(n):→ 8 Weeks
n:Time series to forecast
p:Price signals of GLPI stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Statistical Inference (ML)
Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.Factor
In statistics, a factor is a variable that can influence the value of another variable. Factors can be categorical or continuous. Categorical factors have a limited number of possible values, such as gender (male or female) or blood type (A, B, AB, or O). Continuous factors can have an infinite number of possible values, such as height or weight. Factors can be used to explain the variation in a dependent variable. For example, a study might find that there is a relationship between gender and height. In this case, gender would be the independent variable, height would be the dependent variable, and the factor would be gender.
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?
GLPI Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: GLPI Gaming and Leisure Properties Inc. Common Stock
Time series to forecast: 8 Weeks
According to price forecasts, the dominant strategy among neural network is: BuySpeculative 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 Statistical Inference (ML) based GLPI Stock Prediction Model
- An example of a fair value hedge is a hedge of exposure to changes in the fair value of a fixed-rate debt instrument arising from changes in interest rates. Such a hedge could be entered into by the issuer or by the holder.
- If a financial asset contains a contractual term that could change the timing or amount of contractual cash flows (for example, if the asset can be prepaid before maturity or its term can be extended), the entity must determine whether the contractual cash flows that could arise over the life of the instrument due to that contractual term are solely payments of principal and interest on the principal amount outstanding. To make this determination, the entity must assess the contractual cash flows that could arise both before, and after, the change in contractual cash flows. The entity may also need to assess the nature of any contingent event (ie the trigger) that would change the timing or amount of the contractual cash flows. While the nature of the contingent event in itself is not a determinative factor in assessing whether the contractual cash flows are solely payments of principal and interest, it may be an indicator. For example, compare a financial instrument with an interest rate that is reset to a higher rate if the debtor misses a particular number of payments to a financial instrument with an interest rate that is reset to a higher rate if a specified equity index reaches a particular level. It is more likely in the former case that the contractual cash flows over the life of the instrument will be solely payments of principal and interest on the principal amount outstanding because of the relationship between missed payments and an increase in credit risk. (See also paragraph B4.1.18.)
- An entity's business model refers to how an entity manages its financial assets in order to generate cash flows. That is, the entity's business model determines whether cash flows will result from collecting contractual cash flows, selling financial assets or both. Consequently, this assessment is not performed on the basis of scenarios that the entity does not reasonably expect to occur, such as so-called 'worst case' or 'stress case' scenarios. For example, if an entity expects that it will sell a particular portfolio of financial assets only in a stress case scenario, that scenario would not affect the entity's assessment of the business model for those assets if the entity reasonably expects that such a scenario will not occur. If cash flows are realised in a way that is different from the entity's expectations at the date that the entity assessed the business model (for example, if the entity sells more or fewer financial assets than it expected when it classified the assets), that does not give rise to a prior period error in the entity's financial statements (see IAS 8 Accounting Policies, Changes in Accounting Estimates and Errors) nor does it change the classification of the remaining financial assets held in that business model (ie those assets that the entity recognised in prior periods and still holds) as long as the entity considered all relevant information that was available at the time that it made the business model assessment.
- An entity shall apply this Standard retrospectively, in accordance with IAS 8 Accounting Policies, Changes in Accounting Estimates and Errors, except as specified in paragraphs 7.2.4–7.2.26 and 7.2.28. This Standard shall not be applied to items that have already been derecognised at the date of initial application.
*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.
GLPI Gaming and Leisure Properties Inc. Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba3 | B1 |
Income Statement | Ba3 | Baa2 |
Balance Sheet | Baa2 | Baa2 |
Leverage Ratios | Baa2 | C |
Cash Flow | Caa2 | B3 |
Rates of Return and Profitability | B1 | C |
*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
Gaming and Leisure Properties Inc. Common Stock is assigned short-term Ba3 & long-term B1 estimated rating. Gaming and Leisure Properties Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Factor1,2,3,4 and it is concluded that the GLPI stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: BuySpeculative Trend
Prediction Confidence Score
References
- Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
- Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
- Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
- G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
- Harris ZS. 1954. Distributional structure. Word 10:146–62
Frequently Asked Questions
Q: What is the prediction methodology for GLPI stock?A: GLPI stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Factor
Q: Is GLPI stock a buy or sell?
A: The dominant strategy among neural network is to BuySpeculative Trend GLPI Stock.
Q: Is Gaming and Leisure Properties Inc. Common Stock stock a good investment?
A: The consensus rating for Gaming and Leisure Properties Inc. Common Stock is BuySpeculative Trend and is assigned short-term Ba3 & long-term B1 estimated rating.
Q: What is the consensus rating of GLPI stock?
A: The consensus rating for GLPI is BuySpeculative Trend.
Q: What is the prediction period for GLPI stock?
A: The prediction period for GLPI is 8 Weeks