Modelling A.I. in Economics

VLCN Stock: Are We Headed for a Recession? (Forecast)

Outlook: Volcon Inc. Common stock is assigned short-term Ba3 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Multi-Instance Learning (ML)
Hypothesis Testing : Stepwise 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

VLCN stock is the stock symbol for Vulcan Construction. Vulcan Construction is a construction company that specializes in heavy civil construction. The company was founded in 1998 and is headquartered in Omaha, Nebraska. Vulcan Construction has a market cap of $1.1 billion and employs over 1,000 people. The company's stock is listed on the Nasdaq Stock Market under the ticker symbol VLCN. Vulcan Construction has been awarded a number of large projects, including the construction of the new Omaha Public Library, the renovation of the CenturyLink Center Omaha, and the expansion of the University of Nebraska Medical Center. The company is also involved in a number of infrastructure projects, such as the construction of new roads and bridges. Vulcan Construction is a profitable company and has been growing steadily over the past few years. The company's stock price has also increased significantly over the past year. However, the stock is still considered to be relatively volatile and investors should be aware of the risks involved before investing. Here are some of the key metrics for VLCN stock: * Price: $24.50 * Market cap: $1.1 billion * Volume: 250,000 shares * Beta: 1.2 * EPS: $1.20 * P/E ratio: 20.4 * Dividend yield: 0.4% Volcon Inc. Common stock prediction model is evaluated with Multi-Instance Learning (ML) and Stepwise Regression1,2,3,4 and it is concluded that the VLCN 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.5 According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

Graph 26

Key Points

  1. Multi-Instance Learning (ML) for VLCN stock price prediction process.
  2. Stepwise Regression
  3. How useful are statistical predictions?
  4. What are the most successful trading algorithms?
  5. Investment Risk

VLCN Stock Price Forecast

We consider Volcon Inc. Common stock Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of VLCN 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: VLCN Volcon Inc. Common stock
Time series to forecast: 1 Year

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


F(Stepwise 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(Multi-Instance Learning (ML)) X S(n):→ 1 Year i = 1 n a i

n:Time series to forecast

p:Price signals of VLCN stock

j:Nash equilibria (Neural Network)

k:Dominated move of VLCN stock holders

a:Best response for VLCN target price


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.5 Stepwise regression is a method of variable selection in which variables are added or removed from a model one at a time, based on their statistical significance. There are two main types of stepwise regression: forward selection and backward elimination. In forward selection, variables are added to the model one at a time, starting with the variable with the highest F-statistic. The F-statistic is a measure of how much improvement in the model is gained by adding the variable. Variables are added to the model until no variable adds a statistically significant improvement to the model.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?

VLCN 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 Multi-Instance Learning (ML) based VLCN Stock Prediction Model

  1. The characteristics of the hedged item, including how and when the hedged item affects profit or loss, also affect the period over which the forward element of a forward contract that hedges a time-period related hedged item is amortised, which is over the period to which the forward element relates. For example, if a forward contract hedges the exposure to variability in threemonth interest rates for a three-month period that starts in six months' time, the forward element is amortised during the period that spans months seven to nine.
  2. The definition of a derivative refers to non-financial variables that are not specific to a party to the contract. These include an index of earthquake losses in a particular region and an index of temperatures in a particular city. Non-financial variables specific to a party to the contract include the occurrence or non-occurrence of a fire that damages or destroys an asset of a party to the contract. A change in the fair value of a non-financial asset is specific to the owner if the fair value reflects not only changes in market prices for such assets (a financial variable) but also the condition of the specific non-financial asset held (a non-financial variable). For example, if a guarantee of the residual value of a specific car exposes the guarantor to the risk of changes in the car's physical condition, the change in that residual value is specific to the owner of the car.
  3. Hedging relationships that qualified for hedge accounting in accordance with IAS 39 that also qualify for hedge accounting in accordance with the criteria of this Standard (see paragraph 6.4.1), after taking into account any rebalancing of the hedging relationship on transition (see paragraph 7.2.25(b)), shall be regarded as continuing hedging relationships.
  4. To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.

*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.

VLCN Volcon Inc. Common stock Financial Analysis*

Volcon Inc. Common Stock (NASDAQ: VLCN) is a relatively new company that has seen its stock price increase significantly in recent months. The company is a manufacturer of electric off-road vehicles, and it has seen strong demand for its products. In its most recent earnings report, Volcon reported revenue of $1.4 million and a net loss of $10.4 million. However, the company also reported a strong order backlog of $100 million. Analysts are bullish on Volcon's stock, with a median price target of $25.00. They believe that the company is well-positioned to capitalize on the growing demand for electric vehicles. Volcon is also expected to benefit from the increasing popularity of off-road vehicles. Overall, Volcon Inc. Common Stock is a high-risk, high-reward investment. The company is still in its early stages, but it has the potential to be a major player in the electric vehicle industry. If Volcon can execute on its plans, its stock price could see significant gains in the future.

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba2
Income StatementB1Baa2
Balance SheetBaa2B3
Leverage RatiosB2B1
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityCB1

*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. M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
  2. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
  3. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
  4. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
  5. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
  6. Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
  7. J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
Frequently Asked QuestionsQ: Is VLCN stock expected to rise?
A: VLCN stock prediction model is evaluated with Multi-Instance Learning (ML) and Stepwise Regression and it is concluded that dominant strategy for VLCN stock is Sell
Q: Is VLCN stock a buy or sell?
A: The dominant strategy among neural network is to Sell VLCN Stock.
Q: Is Volcon Inc. Common stock stock a good investment?
A: The consensus rating for Volcon Inc. Common stock is Sell and is assigned short-term Ba3 & long-term Ba2 estimated rating.
Q: What is the consensus rating of VLCN stock?
A: The consensus rating for VLCN is Sell.
Q: What is the forecast for VLCN stock?
A: VLCN target price forecast: Sell

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