Is REXR Stock Buy or Sell? (Stock Forecast)

Abstract

We evaluate Rexford Industrial Realty prediction models with Modular Neural Network (DNN Layer) and Ridge Regression^1,2,3,4 and conclude that the REXR stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell REXR stock.

Keywords: REXR, Rexford Industrial Realty, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Investment Risk
2. Market Signals
3. Prediction Modeling

REXR Target Price Prediction Modeling Methodology

We consider Rexford Industrial Realty Stock Decision Process with Ridge Regression where A is the set of discrete actions of REXR 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(Ridge Regression)^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 (DNN Layer)) X S(n):→ (n+1 year) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of REXR stock

j:Nash equilibria

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?

REXR Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: REXR Rexford Industrial Realty
Time series to forecast n: 02 Sep 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell REXR stock.

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 (Yellow to Green): *Technical Analysis%

Conclusions

Rexford Industrial Realty assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (DNN Layer) with Ridge Regression^1,2,3,4 and conclude that the REXR stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell REXR stock.

Financial State Forecast for REXR Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B2
Operational Risk	62	35
Market Risk	33	80
Technical Analysis	69	36
Fundamental Analysis	60	36
Risk Unsystematic	43	62

Prediction Confidence Score

Trust metric by Neural Network: 82 out of 100 with 845 signals.

References

1. V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.
2. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
3. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
4. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
5. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
6. V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 02 2015.
7. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765

Frequently Asked Questions

Q: What is the prediction methodology for REXR stock?
A: REXR stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Ridge Regression
Q: Is REXR stock a buy or sell?
A: The dominant strategy among neural network is to Sell REXR Stock.
Q: Is Rexford Industrial Realty stock a good investment?
A: The consensus rating for Rexford Industrial Realty is Sell and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of REXR stock?
A: The consensus rating for REXR is Sell.
Q: What is the prediction period for REXR stock?
A: The prediction period for REXR is (n+1 year)

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