Modelling A.I. in Economics

EOI Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest (Forecast)

Outlook: Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest assigned short-term B2 & long-term B2 forecasted stock rating.
Dominant Strategy : Buy
Time series to forecast n: 19 Dec 2022 for (n+3 month)
Methodology : Modular Neural Network (CNN Layer)

Abstract

In this paper, we propose a hybrid machine learning system based on Genetic Algor ithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators.(Chen, K., Zhou, Y. and Dai, F., 2015, October. A LSTM-based method for stock returns prediction: A case study of China stock market. In 2015 IEEE international conference on big data (big data) (pp. 2823-2824). IEEE.) We evaluate Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest prediction models with Modular Neural Network (CNN Layer) and Stepwise Regression1,2,3,4 and conclude that the EOI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

  1. How can neural networks improve predictions?
  2. Should I buy stocks now or wait amid such uncertainty?
  3. What is neural prediction?

EOI Target Price Prediction Modeling Methodology

We consider Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of EOI 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 (CNN Layer)) X S(n):→ (n+3 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of EOI 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?

EOI Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: EOI Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest
Time series to forecast n: 19 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

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%

Adjusted IFRS* Prediction Methods for Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest

  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. Financial assets that are held within a business model whose objective is to hold assets in order to collect contractual cash flows are managed to realise cash flows by collecting contractual payments over the life of the instrument. That is, the entity manages the assets held within the portfolio to collect those particular contractual cash flows (instead of managing the overall return on the portfolio by both holding and selling assets). In determining whether cash flows are going to be realised by collecting the financial assets' contractual cash flows, it is necessary to consider the frequency, value and timing of sales in prior periods, the reasons for those sales and expectations about future sales activity. However sales in themselves do not determine the business model and therefore cannot be considered in isolation. Instead, information about past sales and expectations about future sales provide evidence related to how the entity's stated objective for managing the financial assets is achieved and, specifically, how cash flows are realised. An entity must consider information about past sales within the context of the reasons for those sales and the conditions that existed at that time as compared to current conditions.
  3. Annual Improvements to IFRSs 2010–2012 Cycle, issued in December 2013, amended paragraphs 4.2.1 and 5.7.5 as a consequential amendment derived from the amendment to IFRS 3. An entity shall apply that amendment prospectively to business combinations to which the amendment to IFRS 3 applies.
  4. When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.

*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

Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (CNN Layer) with Stepwise Regression1,2,3,4 and conclude that the EOI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

EOI Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2B2
Operational Risk 4639
Market Risk7381
Technical Analysis4941
Fundamental Analysis6035
Risk Unsystematic4772

Financial analysis is the process of evaluating a company's financial performance and position. 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?

Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 743 signals.

References

  1. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
  2. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
  3. D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
  4. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
  5. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
  6. Athey S, Bayati M, Imbens G, Zhaonan Q. 2019. Ensemble methods for causal effects in panel data settings. NBER Work. Pap. 25675
  7. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
Frequently Asked QuestionsQ: What is the prediction methodology for EOI stock?
A: EOI stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Stepwise Regression
Q: Is EOI stock a buy or sell?
A: The dominant strategy among neural network is to Buy EOI Stock.
Q: Is Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest stock a good investment?
A: The consensus rating for Eaton Vance Enhance Equity Income Fund Eaton Vance Enhanced Equity Income Fund Shares of Beneficial Interest is Buy and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of EOI stock?
A: The consensus rating for EOI is Buy.
Q: What is the prediction period for EOI stock?
A: The prediction period for EOI is (n+3 month)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.