WDI Western Asset Diversified Income Fund Common Shares of Beneficial Interest

Outlook: Western Asset Diversified Income Fund Common Shares of Beneficial Interest assigned short-term B2 & long-term B1 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 17 Dec 2022 for (n+3 month)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

This paper examines the theory and practice of regression techniques for prediction of stock price trend by using a transformed data set in ordinal data format. The original pretransformed data source contains data of heterogeneous data types used for handling of currency values and financial ratios. The data formats in currency values and financial ratios provide a process for computation of stock prices. The transformed data set contains only a standardized ordinal data type which provides a process to measure rankings of stock price trends.(Singh, S., Madan, T.K., Kumar, J. and Singh, A.K., 2019, July. Stock market forecasting using machine learning: Today and tomorrow. In 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) (Vol. 1, pp. 738-745). IEEE.) We evaluate Western Asset Diversified Income Fund Common Shares of Beneficial Interest prediction models with Modular Neural Network (Market Direction Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the WDI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

1. What is prediction model?
2. Trust metric by Neural Network
3. Trust metric by Neural Network

WDI Target Price Prediction Modeling Methodology

We consider Western Asset Diversified Income Fund Common Shares of Beneficial Interest Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of WDI 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(Wilcoxon Rank-Sum Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of WDI 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?

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

Sample Set: Neural Network
Stock/Index: WDI Western Asset Diversified Income Fund Common Shares of Beneficial Interest
Time series to forecast n: 17 Dec 2022 for (n+3 month)

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

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 Western Asset Diversified Income Fund Common Shares of Beneficial Interest

1. To calculate the change in the value of the hedged item for the purpose of measuring hedge ineffectiveness, an entity may use a derivative that would have terms that match the critical terms of the hedged item (this is commonly referred to as a 'hypothetical derivative'), and, for example for a hedge of a forecast transaction, would be calibrated using the hedged price (or rate) level. For example, if the hedge was for a two-sided risk at the current market level, the hypothetical derivative would represent a hypothetical forward contract that is calibrated to a value of nil at the time of designation of the hedging relationship. If the hedge was for example for a one-sided risk, the hypothetical derivative would represent the intrinsic value of a hypothetical option that at the time of designation of the hedging relationship is at the money if the hedged price level is the current market level, or out of the money if the hedged price level is above (or, for a hedge of a long position, below) the current market level. Using a hypothetical derivative is one possible way of calculating the change in the value of the hedged item. The hypothetical derivative replicates the hedged item and hence results in the same outcome as if that change in value was determined by a different approach. Hence, using a 'hypothetical derivative' is not a method in its own right but a mathematical expedient that can only be used to calculate the value of the hedged item. Consequently, a 'hypothetical derivative' cannot be used to include features in the value of the hedged item that only exist in the hedging instrument (but not in the hedged item). An example is debt denominated in a foreign currency (irrespective of whether it is fixed-rate or variable-rate debt). When using a hypothetical derivative to calculate the change in the value of such debt or the present value of the cumulative change in its cash flows, the hypothetical derivative cannot simply impute a charge for exchanging different currencies even though actual derivatives under which different currencies are exchanged might include such a charge (for example, cross-currency interest rate swaps).
2. If an entity prepares interim financial reports in accordance with IAS 34 Interim Financial Reporting the entity need not apply the requirements in this Standard to interim periods prior to the date of initial application if it is impracticable (as defined in IAS 8).
3. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
4. A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.

*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

Western Asset Diversified Income Fund Common Shares of Beneficial Interest assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the WDI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Financial State Forecast for WDI Western Asset Diversified Income Fund Common Shares of Beneficial Interest Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B1
Operational Risk	40	80
Market Risk	33	62
Technical Analysis	82	72
Fundamental Analysis	78	48
Risk Unsystematic	54	38

Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 795 signals.

References

1. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
2. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
3. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
4. Andrews, D. W. K. (1993), "Tests for parameter instability and structural change with unknown change point," Econometrica, 61, 821–856.
5. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
6. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
7. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.

Frequently Asked Questions

Q: What is the prediction methodology for WDI stock?
A: WDI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Wilcoxon Rank-Sum Test
Q: Is WDI stock a buy or sell?
A: The dominant strategy among neural network is to Sell WDI Stock.
Q: Is Western Asset Diversified Income Fund Common Shares of Beneficial Interest stock a good investment?
A: The consensus rating for Western Asset Diversified Income Fund Common Shares of Beneficial Interest is Sell and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of WDI stock?
A: The consensus rating for WDI is Sell.
Q: What is the prediction period for WDI stock?
A: The prediction period for WDI 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