Modelling A.I. in Economics

CADIZ Inc. Common Stock is assigned short-term Ba3 & long-term Ba3 estimated rating.

Outlook: CADIZ Inc. Common Stock is assigned short-term Ba3 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Financial Sentiment Analysis)
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.


Summary

CDZI stock (Cadiz Inc.) is a small cap stock that has been on the rise in recent months. The company is a water resource development company that owns and operates water rights in California. CDZI stock is currently trading at around $10 per share, up from around $5 per share at the beginning of the year. There are a few reasons why CDZI stock has been gaining traction recently. First, the company has been making some strategic acquisitions that are expected to increase its revenue and profitability. In February, CDZI acquired the water rights to the Kern River Water District for $110 million. This acquisition gives the company access to a significant source of water in California, which is a state that is facing a severe drought. Second, CDZI stock has been getting some positive attention from analysts. In a recent report, Oppenheimer analyst Jason Greenwald upgraded CDZI stock to "outperform" and set a price target of $15 per share. Greenwald believes that the company's water rights are undervalued and that the company is poised for growth. Finally, CDZI stock has been getting some attention from retail investors. The stock is trading on the OTCQX market, which is a popular destination for retail investors looking for small cap stocks with high potential. Overall, CDZI stock is a speculative investment that could potentially provide significant returns. However, investors should be aware of the risks involved, including the fact that the company is still in the early stages of development and that its financial results are volatile. CADIZ Inc. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the CDZI stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising.5 According to price forecasts for 6 Month period, the dominant strategy among neural network is: Speculative Trend

Graph 44

Key Points

  1. Modular Neural Network (Financial Sentiment Analysis) for CDZI stock price prediction process.
  2. Wilcoxon Rank-Sum Test
  3. Can stock prices be predicted?
  4. Probability Distribution
  5. How useful are statistical predictions?

CDZI Stock Price Forecast

We consider CADIZ Inc. Common Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of CDZI 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: CDZI CADIZ Inc. Common Stock
Time series to forecast: 6 Month

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


F(Wilcoxon Rank-Sum Test)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 (Financial Sentiment Analysis)) X S(n):→ 6 Month R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of CDZI stock

j:Nash equilibria (Neural Network)

k:Dominated move of CDZI stock holders

a:Best response for CDZI target price


Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising.5 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.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?

CDZI 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 (Financial Sentiment Analysis) based CDZI Stock Prediction Model

  1. An entity shall apply Prepayment Features with Negative Compensation (Amendments to IFRS 9) retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.30–7.2.34
  2. However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
  3. Amounts presented in other comprehensive income shall not be subsequently transferred to profit or loss. However, the entity may transfer the cumulative gain or loss within equity.
  4. An entity that first applies IFRS 17 as amended in June 2020 after it first applies this Standard shall apply paragraphs 7.2.39–7.2.42. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).

*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.

CDZI CADIZ Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Income StatementBaa2C
Balance SheetBaa2Baa2
Leverage RatiosB3Ba1
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityCaa2Caa2

*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. S. J. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA, pages 656–663, 2003.
  2. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
  3. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
  4. Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
  5. Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
  6. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
  7. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
Frequently Asked QuestionsQ: Is CDZI stock expected to rise?
A: CDZI stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Rank-Sum Test and it is concluded that dominant strategy for CDZI stock is Speculative Trend
Q: Is CDZI stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend CDZI Stock.
Q: Is CADIZ Inc. Common Stock stock a good investment?
A: The consensus rating for CADIZ Inc. Common Stock is Speculative Trend and is assigned short-term Ba3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of CDZI stock?
A: The consensus rating for CDZI is Speculative Trend.
Q: What is the forecast for CDZI stock?
A: CDZI target price forecast: Speculative Trend

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