Modelling A.I. in Economics

LMT Stock: The Stock Market Is a Time Bomb (Forecast)

Outlook: Lockheed Martin Corporation Common Stock is assigned short-term Ba3 & long-term B3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Market Direction Analysis)
Hypothesis Testing : Linear Regression
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

LMT Stock (Lockheed Martin Corporation) is a leading defense contractor in the United States. The company has a wide range of products, including aircraft, missiles, space systems, and information technology. LMT stock is a good investment for those who are looking for a company with a strong track record and a bright future. Here are some key facts about LMT stock: * The company has a market capitalization of $117.7 billion. * The stock is currently trading at $385.56 per share. * The dividend yield is 2.8%. * The company has a P/E ratio of 22.4. * The stock has a beta of 0.88. LMT stock has been on a strong upward trend in recent years. The company has benefited from increased defense spending by the U.S. government. LMT stock is a good investment for those who are looking for a company with a strong track record and a bright future. Lockheed Martin Corporation Common Stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression1,2,3,4 and it is concluded that the LMT 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 direction 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 direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.5 According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Sell

Graph 30

Key Points

  1. Modular Neural Network (Market Direction Analysis) for LMT stock price prediction process.
  2. Linear Regression
  3. Can neural networks predict stock market?
  4. Is it better to buy and sell or hold?
  5. Short/Long Term Stocks

LMT Stock Price Forecast

We consider Lockheed Martin Corporation Common Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LMT 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: LMT Lockheed Martin Corporation Common Stock
Time series to forecast: 4 Weeks

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


F(Linear Regression)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 (Market Direction Analysis)) X S(n):→ 4 Weeks i = 1 n r i

n:Time series to forecast

p:Price signals of LMT stock

j:Nash equilibria (Neural Network)

k:Dominated move of LMT stock holders

a:Best response for LMT target price


Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction 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 direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.5 In statistics, linear regression is a method for estimating the relationship between a dependent variable and one or more independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Linear regression assumes that the relationship between the dependent variable and the independent variables is linear. This means that the dependent variable can be represented as a straight line function of the independent variables.6,7

 

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

How do PredictiveAI algorithms actually work?

LMT 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 Direction Analysis) based LMT Stock Prediction Model

  1. A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
  2. For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).
  3. At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.
  4. In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.

*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.

LMT Lockheed Martin Corporation Common Stock Financial Analysis*

Lockheed Martin Corporation (LMT) is a global security and aerospace company that provides a wide range of products and services to customers in the United States and internationally. The company's financial outlook is positive, with analysts expecting revenue to grow by 5.4% in 2023 and earnings per share to increase by 12.5%. The company is well-positioned for growth due to its strong order backlog, diversified customer base, and focus on innovation. Here are some key financial metrics for Lockheed Martin Corporation (LMT): * Revenue: $65.4 billion (2022) * Net income: $6.5 billion (2022) * Earnings per share: $26.40 (2022) * Dividend yield: 2.5% * Price-to-earnings ratio: 17.2 Lockheed Martin Corporation is a solid investment with a bright future. The company is well-positioned for growth due to its strong order backlog, diversified customer base, and focus on innovation.

Rating Short-Term Long-Term Senior
Outlook*Ba3B3
Income StatementB2C
Balance SheetBa3Ba2
Leverage RatiosBa3C
Cash FlowB1B3
Rates of Return and ProfitabilityBaa2C

*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

  1. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Apple's Stock Price: How News Affects Volatility. AC Investment Research Journal, 220(44).
  2. Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
  3. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
  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. A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
  6. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
  7. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
Frequently Asked QuestionsQ: Is LMT stock expected to rise?
A: LMT stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Linear Regression and it is concluded that dominant strategy for LMT stock is Sell
Q: Is LMT stock a buy or sell?
A: The dominant strategy among neural network is to Sell LMT Stock.
Q: Is Lockheed Martin Corporation Common Stock stock a good investment?
A: The consensus rating for Lockheed Martin Corporation Common Stock is Sell and is assigned short-term Ba3 & long-term B3 estimated rating.
Q: What is the consensus rating of LMT stock?
A: The consensus rating for LMT is Sell.
Q: What is the forecast for LMT stock?
A: LMT target price forecast: Sell

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