FNKO Stock: Set a stop-loss order

Outlook: Funko Inc. Class A Common Stock is assigned short-term Ba2 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised* :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks*
Methodology : Statistical Inference (ML)
Hypothesis Testing : Independent T-Test
Surveillance : Major exchange and OTC

*The accuracy of the model is being monitored on a regular basis.(15-minute period)

*Time series is updated based on short-term trends.

Summary

Funko Inc. Class A Common Stock prediction model is evaluated with Statistical Inference (ML) and Independent T-Test^1,2,3,4 and it is concluded that the FNKO 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 16 Weeks period, the dominant strategy among neural network is: Speculative Trend

Key Points

1. Dominated Move
2. Can stock prices be predicted?
3. Stock Rating

FNKO Target Price Prediction Modeling Methodology

We consider Funko Inc. Class A Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of FNKO 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(Statistical Inference (ML)) X S(n):→ 16 Weeks $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of FNKO 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.

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?

FNKO Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: FNKO Funko Inc. Class A Common Stock
Time series to forecast: 16 Weeks

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

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 Statistical Inference (ML) based FNKO Stock Prediction Model

1. An alternative benchmark rate designated as a non-contractually specified risk component that is not separately identifiable (see paragraphs 6.3.7(a) and B6.3.8) at the date it is designated shall be deemed to have met that requirement at that date, if, and only if, the entity reasonably expects the alternative benchmark rate will be separately identifiable within 24 months. The 24-month period applies to each alternative benchmark rate separately and starts from the date the entity designates the alternative benchmark rate as a non-contractually specified risk component for the first time (ie the 24- month period applies on a rate-by-rate basis).
2. However, an entity is not required to separately recognise interest revenue or impairment gains or losses for a financial asset measured at fair value through profit or loss. Consequently, when an entity reclassifies a financial asset out of the fair value through profit or loss measurement category, the effective interest rate is determined on the basis of the fair value of the asset at the reclassification date. In addition, for the purposes of applying Section 5.5 to the financial asset from the reclassification date, the date of the reclassification is treated as the date of initial recognition.
3. Interest Rate Benchmark Reform—Phase 2, which amended IFRS 9, IAS 39, IFRS 7, IFRS 4 and IFRS 16, issued in August 2020, added paragraphs 5.4.5–5.4.9, 6.8.13, Section 6.9 and paragraphs 7.2.43–7.2.46. An entity shall apply these amendments for annual periods beginning on or after 1 January 2021. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
4. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.

*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.

FNKO Funko Inc. Class A Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba2	Ba1
Income Statement	Baa2	Baa2
Balance Sheet	Baa2	Caa2
Leverage Ratios	B1	Baa2
Cash Flow	B2	Ba3
Rates of Return and Profitability	Baa2	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?

Conclusions

Funko Inc. Class A Common Stock is assigned short-term Ba2 & long-term Ba1 estimated rating. Funko Inc. Class A Common Stock prediction model is evaluated with Statistical Inference (ML) and Independent T-Test^1,2,3,4 and it is concluded that the FNKO stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Speculative Trend

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 817 signals.

References

1. D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.
2. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
3. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
4. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
5. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
6. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
7. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55

Frequently Asked Questions

Q: What is the prediction methodology for FNKO stock?
A: FNKO stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Independent T-Test
Q: Is FNKO stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend FNKO Stock.
Q: Is Funko Inc. Class A Common Stock stock a good investment?
A: The consensus rating for Funko Inc. Class A Common Stock is Speculative Trend and is assigned short-term Ba2 & long-term Ba1 estimated rating.
Q: What is the consensus rating of FNKO stock?
A: The consensus rating for FNKO is Speculative Trend.
Q: What is the prediction period for FNKO stock?
A: The prediction period for FNKO is 16 Weeks

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