Where Will ACR^D Stock Be in 3 Month?

Outlook: ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock is assigned short-term B1 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Multi-Instance Learning (ML)
Hypothesis Testing : Wilcoxon Rank-Sum Test
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.

Abstract

ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock prediction model is evaluated with Multi-Instance Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the ACR^D stock is predictable in the short/long term. Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Hold

Key Points

1. What is prediction in deep learning?
2. Short/Long Term Stocks
3. Can stock prices be predicted?

ACR^D Target Price Prediction Modeling Methodology

We consider ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of ACR^D 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(Multi-Instance Learning (ML)) X S(n):→ 3 Month $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of ACR^D stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Multi-Instance Learning (ML)

Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance.

Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

 

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?

ACR^D Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: ACR^D ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock
Time series to forecast: 3 Month

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

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 Multi-Instance Learning (ML) based ACR^D Stock Prediction Model

1. 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.
2. An entity shall amend a hedging relationship as required in paragraph 6.9.1 by the end of the reporting period during which a change required by interest rate benchmark reform is made to the hedged risk, hedged item or hedging instrument. For the avoidance of doubt, such an amendment to the formal designation of a hedging relationship constitutes neither the discontinuation of the hedging relationship nor the designation of a new hedging relationship.
3. Time value of money is the element of interest that provides consideration for only the passage of time. That is, the time value of money element does not provide consideration for other risks or costs associated with holding the financial asset. In order to assess whether the element provides consideration for only the passage of time, an entity applies judgement and considers relevant factors such as the currency in which the financial asset is denominated and the period for which the interest rate is set.
4. To be eligible for designation as a hedged item, a risk component must be a separately identifiable component of the financial or the non-financial item, and the changes in the cash flows or the fair value of the item attributable to changes in that risk component must be reliably measurable.

*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.

ACR^D ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B1	Ba2
Income Statement	B2	B2
Balance Sheet	B2	C
Leverage Ratios	Baa2	Baa2
Cash Flow	B1	Ba3
Rates of Return and Profitability	C	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?

Conclusions

ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock is assigned short-term B1 & long-term Ba2 estimated rating. ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock prediction model is evaluated with Multi-Instance Learning (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the ACR^D stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Hold

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 662 signals.

References

1. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
2. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
3. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
4. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market?. AC Investment Research Journal, 220(44).
5. Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
6. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
7. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99

Frequently Asked Questions

Q: What is the prediction methodology for ACR^D stock?
A: ACR^D stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is ACR^D stock a buy or sell?
A: The dominant strategy among neural network is to Hold ACR^D Stock.
Q: Is ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock stock a good investment?
A: The consensus rating for ACRES Commercial Realty Corp. 7.875% Series D Cumulative Redeemable Preferred Stock is Hold and is assigned short-term B1 & long-term Ba2 estimated rating.
Q: What is the consensus rating of ACR^D stock?
A: The consensus rating for ACR^D is Hold.
Q: What is the prediction period for ACR^D stock?
A: The prediction period for ACR^D is 3 Month