AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
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
Employers Holdings Inc Common Stock prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the EIG 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 16 Weeks period, the dominant strategy among neural network is: Buy
Key Points
- Active Learning (ML) for EIG stock price prediction process.
- Linear Regression
- Technical Analysis with Algorithmic Trading
- How can neural networks improve predictions?
- Which neural network is best for prediction?
EIG Stock Price Forecast
We consider Employers Holdings Inc Common Stock Decision Process with Active Learning (ML) where A is the set of discrete actions of EIG 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: EIG Employers Holdings Inc Common Stock
Time series to forecast: 16 Weeks
According to price forecasts, the dominant strategy among neural network is: Buy
n:Time series to forecast
p:Price signals of EIG stock
j:Nash equilibria (Neural Network)
k:Dominated move of EIG stock holders
a:Best response for EIG 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:
EIG 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 EIG Stock Prediction Model
- An entity must look through until it can identify the underlying pool of instruments that are creating (instead of passing through) the cash flows. This is the underlying pool of financial instruments.
- For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.
- As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.
- An entity must look through until it can identify the underlying pool of instruments that are creating (instead of passing through) the cash flows. This is the underlying pool of financial instruments.
*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.
EIG Employers Holdings Inc Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | B2 |
Income Statement | Baa2 | Caa2 |
Balance Sheet | B2 | C |
Leverage Ratios | B1 | Baa2 |
Cash Flow | Caa2 | Caa2 |
Rates of Return and Profitability | B1 | Baa2 |
*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
- Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
- Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
- Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
- A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
- Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
- Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
- Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
Frequently Asked Questions
Q: Is EIG stock expected to rise?A: EIG stock prediction model is evaluated with Active Learning (ML) and Linear Regression and it is concluded that dominant strategy for EIG stock is Buy
Q: Is EIG stock a buy or sell?
A: The dominant strategy among neural network is to Buy EIG Stock.
Q: Is Employers Holdings Inc Common Stock stock a good investment?
A: The consensus rating for Employers Holdings Inc Common Stock is Buy and is assigned short-term B1 & long-term B2 estimated rating.
Q: What is the consensus rating of EIG stock?
A: The consensus rating for EIG is Buy.
Q: What is the forecast for EIG stock?
A: EIG target price forecast: Buy