Modelling A.I. in Economics

DLR Stock: A Risky Investment

Outlook: Digital Realty Trust Inc. Common Stock is assigned short-term B1 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Active Learning (ML)
Hypothesis Testing : Linear 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.


Summary

Digital Realty Trust Inc. Common Stock prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the DLR stock is predictable in the short/long term. Active learning (AL) is a machine learning (ML) method in which the model actively queries the user for labels on data points. This allows the model to learn more efficiently, as it is only learning about the data points that are most informative.5 According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend

Graph 38

Key Points

  1. Active Learning (ML) for DLR stock price prediction process.
  2. Linear Regression
  3. What is Markov decision process in reinforcement learning?
  4. Short/Long Term Stocks
  5. What are main components of Markov decision process?

DLR Stock Price Forecast

We consider Digital Realty Trust Inc. Common Stock Decision Process with Active Learning (ML) where A is the set of discrete actions of DLR 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


Sample Set: Neural Network
Stock/Index: DLR Digital Realty Trust Inc. Common Stock
Time series to forecast: 8 Weeks

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


F(Linear Regression)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(Active Learning (ML)) X S(n):→ 8 Weeks e x rx

n:Time series to forecast

p:Price signals of DLR stock

j:Nash equilibria (Neural Network)

k:Dominated move of DLR stock holders

a:Best response for DLR target price


Active learning (AL) is a machine learning (ML) method in which the model actively queries the user for labels on data points. This allows the model to learn more efficiently, as it is only learning about the data points that are most informative.5 In statistics, linear regression is a method for estimating the relationship between a dependent variable and one or more independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Linear regression assumes that the relationship between the dependent variable and the independent variables is linear. This means that the dependent variable can be represented as a straight line function of the independent variables.6,7

 

For further technical information as per how our model work we invite you to visit the article below: 

How do PredictiveAI algorithms actually work?

DLR Stock Forecast (Buy or Sell) Strategic Interaction Table

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 Active Learning (ML) based DLR Stock Prediction Model

  1. Accordingly the date of the modification shall be treated as the date of initial recognition of that financial asset when applying the impairment requirements to the modified financial asset. This typically means measuring the loss allowance at an amount equal to 12-month expected credit losses until the requirements for the recognition of lifetime expected credit losses in paragraph 5.5.3 are met. However, in some unusual circumstances following a modification that results in derecognition of the original financial asset, there may be evidence that the modified financial asset is credit-impaired at initial recognition, and thus, the financial asset should be recognised as an originated credit-impaired financial asset. This might occur, for example, in a situation in which there was a substantial modification of a distressed asset that resulted in the derecognition of the original financial asset. In such a case, it may be possible for the modification to result in a new financial asset which is credit-impaired at initial recognition.
  2. Adjusting the hedge ratio by decreasing the volume of the hedging instrument does not affect how the changes in the value of the hedged item are measured. The measurement of the changes in the fair value of the hedging instrument related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedging instrument was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged the price risk of a commodity using a derivative volume of 100 tonnes as the hedging instrument and reduces that volume by 10 tonnes on rebalancing, a nominal amount of 90 tonnes of the hedging instrument volume would remain (see paragraph B6.5.16 for the consequences for the derivative volume (ie the 10 tonnes) that is no longer a part of the hedging relationship).
  3. For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
  4. Changes in market conditions that give rise to market risk include changes in a benchmark interest rate, the price of another entity's financial instrument, a commodity price, a foreign exchange rate or an index of prices or rates.

*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.

DLR Digital Realty Trust Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1Ba2
Income StatementCBaa2
Balance SheetB3Caa2
Leverage RatiosCaa2Baa2
Cash FlowBaa2Caa2
Rates of Return and ProfitabilityBaa2Baa2

*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?

References

  1. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
  2. 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.
  3. Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
  4. K. Boda, J. Filar, Y. Lin, and L. Spanjers. Stochastic target hitting time and the problem of early retirement. Automatic Control, IEEE Transactions on, 49(3):409–419, 2004
  5. White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
  6. Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
  7. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
Frequently Asked QuestionsQ: Is DLR stock expected to rise?
A: DLR stock prediction model is evaluated with Active Learning (ML) and Linear Regression and it is concluded that dominant strategy for DLR stock is Speculative Trend
Q: Is DLR stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend DLR Stock.
Q: Is Digital Realty Trust Inc. Common Stock stock a good investment?
A: The consensus rating for Digital Realty Trust Inc. Common Stock is Speculative Trend and is assigned short-term B1 & long-term Ba2 estimated rating.
Q: What is the consensus rating of DLR stock?
A: The consensus rating for DLR is Speculative Trend.
Q: What is the forecast for DLR stock?
A: DLR target price forecast: Speculative Trend

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