NKLA Stock Forecast: A Hold For The Next 16 Weeks

Outlook: Nikola Corporation Common Stock is assigned short-term Ba3 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised* :
Dominant Strategy : Hold
Time series to forecast n: for 16 Weeks
Methodology : Multi-Instance Learning (ML)
Hypothesis Testing : Independent T-Test
Surveillance : Major exchange and OTC

Summary

Nikola Corporation Common Stock prediction model is evaluated with Multi-Instance Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the NKLA 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. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

*Revision

We revised our short-term strategy to .(Based on stock rating surveillance.) We also affirmed our outlook and Nikola Corporation Common Stock is assigned short-term Ba3 & long-term B1 estimated rating.

Key Points

1. What is prediction model?
2. Reaction Function
3. Buy, Sell and Hold Signals

NKLA Target Price Prediction Modeling Methodology

We consider Nikola Corporation Common Stock Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of NKLA 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(Independent T-Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Multi-Instance Learning (ML)) X S(n):→ 16 Weeks $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of NKLA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Multi-Instance Learning (ML)

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.

Independent T-Test

An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.

 

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?

NKLA Stock Forecast (Buy or Sell) for 16 Weeks

Sample Set: Neural Network
Stock/Index: NKLA Nikola Corporation Common Stock
Time series to forecast: 16 Weeks

According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

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 Nikola Corporation Common Stock

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. For the purpose of applying the requirements in paragraphs 6.4.1(c)(i) and B6.4.4–B6.4.6, an entity shall assume that the interest rate benchmark on which the hedged cash flows and/or the hedged risk (contractually or noncontractually specified) are based, or the interest rate benchmark on which the cash flows of the hedging instrument are based, is not altered as a result of interest rate benchmark reform.
3. 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).
4. Subject to the conditions in paragraphs 4.1.5 and 4.2.2, this Standard allows an entity to designate a financial asset, a financial liability, or a group of financial instruments (financial assets, financial liabilities or both) as at fair value through profit or loss provided that doing so results in more relevant information.

*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

Nikola Corporation Common Stock is assigned short-term Ba3 & long-term B1 estimated rating. Nikola Corporation Common Stock prediction model is evaluated with Multi-Instance Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the NKLA stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

NKLA Nikola Corporation Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B1
Income Statement	Caa2	Baa2
Balance Sheet	B3	Caa2
Leverage Ratios	B3	Baa2
Cash Flow	Baa2	C
Rates of Return and Profitability	Baa2	Ba3

*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

Trust metric by Neural Network: 77 out of 100 with 869 signals.

References

1. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
2. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
3. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. How is the price of gold determined? (No. Stock Analysis). AC Investment Research.
4. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
5. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
6. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
7. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011

Frequently Asked Questions

Q: What is the prediction methodology for NKLA stock?
A: NKLA stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and Independent T-Test
Q: Is NKLA stock a buy or sell?
A: The dominant strategy among neural network is to Hold NKLA Stock.
Q: Is Nikola Corporation Common Stock stock a good investment?
A: The consensus rating for Nikola Corporation Common Stock is Hold and is assigned short-term Ba3 & long-term B1 estimated rating.
Q: What is the consensus rating of NKLA stock?
A: The consensus rating for NKLA is Hold.
Q: What is the prediction period for NKLA stock?
A: The prediction period for NKLA is 16 Weeks

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