FR Stock Forecast: A Hold For The Next 3 Month

Name: FR Stock Forecast: A Hold For The Next 3 Month
Uploaded: Sunday, November 19, 2023
Duration: 37 min 14 s
Description: FR Stock Forecast: A Hold For The Next 3 Month

Outlook: First Industrial Realty Trust Inc. Common Stock is assigned short-term B1 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (Market Volatility Analysis)
Hypothesis Testing : Chi-Square
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

First Industrial Realty Trust Inc. Common Stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Chi-Square^1,2,3,4 and it is concluded that the FR stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.⁵ According to price forecasts for 3 Month period, the dominant strategy among neural network is: Hold

Key Points

Modular Neural Network (Market Volatility Analysis) for FR stock price prediction process.
Chi-Square
Can we predict stock market using machine learning?
Can stock prices be predicted?
Trading Signals

FR Stock Price Forecast

We consider First Industrial Realty Trust Inc. Common Stock Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of FR 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: FR First Industrial Realty Trust Inc. Common Stock
Time series to forecast: 3 Month

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

F(Chi-Square)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Modular Neural Network (Market Volatility Analysis)) X S(n):→ 3 Month

\begin{array}{l} \int e^{x} rx \end{array}

n:Time series to forecast

p:Price signals of FR stock

j:Nash equilibria (Neural Network)

k:Dominated move of FR stock holders

a:Best response for FR target price

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.⁵ A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.^6,7

For further technical information as per how our model work we invite you to visit the article below:

How do Predictive A.I. algorithms actually work?

FR 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 Modular Neural Network (Market Volatility Analysis) based FR Stock Prediction Model

IFRS 16, issued in January 2016, amended paragraphs 2.1, 5.5.15, B4.3.8, B5.5.34 and B5.5.46. An entity shall apply those amendments when it applies IFRS 16.
Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
Adjusting the hedge ratio by decreasing the volume of the hedged item does not affect how the changes in the fair value of the hedging instrument are measured. The measurement of the changes in the value of the hedged item related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedged item was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged a volume of 100 tonnes of a commodity at a forward price of CU80 and reduces that volume by 10 tonnes on rebalancing, the hedged item after rebalancing would be 90 tonnes hedged at CU80. The 10 tonnes of the hedged item that are no longer part of the hedging relationship would be accounted for in accordance with the requirements for the discontinuation of hedge accounting (see paragraphs 6.5.6–6.5.7 and B6.5.22–B6.5.28).
For example, an entity hedges an exposure to Foreign Currency A using a currency derivative that references Foreign Currency B and Foreign Currencies A and B are pegged (ie their exchange rate is maintained within a band or at an exchange rate set by a central bank or other authority). If the exchange rate between Foreign Currency A and Foreign Currency B were changed (ie a new band or rate was set), rebalancing the hedging relationship to reflect the new exchange rate would ensure that the hedging relationship would continue to meet the hedge effectiveness requirement for the hedge ratio in the new circumstances. In contrast, if there was a default on the currency derivative, changing the hedge ratio could not ensure that the hedging relationship would continue to meet that hedge effectiveness requirement. Hence, rebalancing does not facilitate the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item changes in a way that cannot be compensated for by adjusting the hedge ratio

*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.

FR First Industrial Realty Trust Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B1	B1
Income Statement	Caa2	B1
Balance Sheet	Baa2	Caa2
Leverage Ratios	Baa2	Ba3
Cash Flow	C	Baa2
Rates of Return and Profitability	B1	C

*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

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).
Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Google's Stock Price Set to Soar in the Next 3 Months. AC Investment Research Journal, 220(44).
Brailsford, T.J. R.W. Faff (1996), "An evaluation of volatility forecasting techniques," Journal of Banking Finance, 20, 419–438.
Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51

Frequently Asked Questions

Q: Is FR stock expected to rise?
A: FR stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Chi-Square and it is concluded that dominant strategy for FR stock is Hold
Q: Is FR stock a buy or sell?
A: The dominant strategy among neural network is to Hold FR Stock.
Q: Is First Industrial Realty Trust Inc. Common Stock stock a good investment?
A: The consensus rating for First Industrial Realty Trust Inc. Common Stock is Hold and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of FR stock?
A: The consensus rating for FR is Hold.
Q: What is the forecast for FR stock?
A: FR target price forecast: Hold

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