Dominant Strategy : Sell
Time series to forecast n: 23 Jun 2023 for 4 Weeks
Methodology : Statistical Inference (ML)
Summary
- Core Scientific Inc. is a blockchain infrastructure and software company that provides high-performance computing solutions for the cryptocurrency mining industry.
- The company was founded in 2020 and is headquartered in Austin, Texas.
- Core Scientific operates a fleet of over 180,000 mining machines, making it one of the largest cryptocurrency miners in the world.
- In 2022, the company mined over 1.1 billion USD worth of Bitcoin.
- Core Scientific's shares are traded on the OTCQX under the ticker symbol "CORZ."
Core Scientific is a well-positioned company in the blockchain infrastructure market. The company has a large fleet of mining machines and a strong track record of mining Bitcoin. However, the company is also facing some challenges, including the recent decline in cryptocurrency prices.
- The cryptocurrency market is volatile and the price of Bitcoin could decline.
- The company could face competition from other cryptocurrency miners.
- The company could experience technical difficulties with its mining machines.
Core Scientific Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the CORZ stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Sell
Key Points
- How can neural networks improve predictions?
- What are the most successful trading algorithms?
- Market Outlook
CORZ Target Price Prediction Modeling Methodology
We consider Core Scientific Inc. Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of CORZ 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(Wilcoxon Rank-Sum Test)5,6,7= X R(Statistical Inference (ML)) X S(n):→ 4 Weeks
n:Time series to forecast
p:Price signals of CORZ stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Statistical Inference (ML)
Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.Wilcoxon Rank-Sum Test
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.
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?
CORZ Stock Forecast (Buy or Sell) for 4 Weeks
Sample Set: Neural NetworkStock/Index: CORZ Core Scientific Inc. Common Stock
Time series to forecast n: 23 Jun 2023 for 4 Weeks
According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Sell
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%
IFRS Reconciliation Adjustments for Core Scientific Inc. Common Stock
- 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).
- An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
- An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.
- Hedge effectiveness is the extent to which changes in the fair value or the cash flows of the hedging instrument offset changes in the fair value or the cash flows of the hedged item (for example, when the hedged item is a risk component, the relevant change in fair value or cash flows of an item is the one that is attributable to the hedged risk). Hedge ineffectiveness is the extent to which the changes in the fair value or the cash flows of the hedging instrument are greater or less than those on the hedged item.
*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.
Conclusions
Core Scientific Inc. Common Stock is assigned short-term B1 & long-term B1 estimated rating. Core Scientific Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the CORZ stock is predictable in the short/long term.
According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: SellCORZ Core Scientific Inc. Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B1 | B1 |
Income Statement | Ba1 | C |
Balance Sheet | Baa2 | C |
Leverage Ratios | Baa2 | Baa2 |
Cash Flow | B3 | Ba1 |
Rates of Return and Profitability | C | Baa2 |
*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?
Prediction Confidence Score
References
- J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
- S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
- Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
- O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
- Miller A. 2002. Subset Selection in Regression. New York: CRC Press
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
- Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
Frequently Asked Questions
Q: What is the prediction methodology for CORZ stock?A: CORZ stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Wilcoxon Rank-Sum Test
Q: Is CORZ stock a buy or sell?
A: The dominant strategy among neural network is to Sell CORZ Stock.
Q: Is Core Scientific Inc. Common Stock stock a good investment?
A: The consensus rating for Core Scientific Inc. Common Stock is Sell and is assigned short-term B1 & long-term B1 estimated rating.
Q: What is the consensus rating of CORZ stock?
A: The consensus rating for CORZ is Sell.
Q: What is the prediction period for CORZ stock?
A: The prediction period for CORZ is 4 Weeks
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