NHTC Stock: Is This the End of the Bull Market?

Outlook: Natural Health Trends Corp. Common Stock is assigned short-term B3 & long-term Ba3 estimated rating.
Dominant Strategy : Speculative Trend
Time series to forecast n: 24 Jun 2023 for 8 Weeks
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Summary

Natural Health Trends Corp. (NHTC) is a direct-selling and e-commerce company that markets premium quality personal care, wellness, and "quality of life" products under the NHT Global brand. The Company operates subsidiaries throughout Asia, the Americas, and Europe.

NHT Global was founded in 1988 as Lexxus International, Inc. The company's name was changed to Natural Health Trends Corp. in 2001. NHTC went public in 2003 and is traded on the Nasdaq stock exchange under the ticker symbol "NHTC."

NHT Global's products are sold through a network of independent distributors. The company's products are available in over 50 countries around the world.

NHT Global's products include:

Personal care products, such as skin care, hair care, and oral care products.
Wellness products, such as dietary supplements, weight management products, and energy drinks.
"Quality of life" products, such as home fragrance products, air purifiers, and water filters.

NHT Global has been growing rapidly in recent years. In 2021, the company's revenue was $49.1 million, up from $40.2 million in 2020. The company's growth has been driven by increasing demand for its products, as well as the expansion of its distribution channels.

Natural Health Trends Corp. Common Stock prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the NHTC stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend Graph 37

Key Points

Can we predict stock market using machine learning?
Can stock prices be predicted?
Fundemental Analysis with Algorithmic Trading

NHTC Target Price Prediction Modeling Methodology

We consider Natural Health Trends Corp. Common Stock Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of NHTC 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(Polynomial Regression)^5,6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ 8 Weeks

\sum_{i = 1}^{n} (s_{i})

n:Time series to forecast

p:Price signals of NHTC stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Market News Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.

Polynomial Regression

Polynomial regression is a type of regression analysis that uses a polynomial function to model the relationship between a dependent variable and one or more independent variables. Polynomial functions are mathematical functions that have a polynomial term, which is a term that is raised to a power greater than 1. In polynomial regression, the dependent variable is modeled as a polynomial function of the independent variables. The degree of the polynomial function is determined by the researcher. The higher the degree of the polynomial function, the more complex the model will be.

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?

NHTC Stock Forecast (Buy or Sell) for 8 Weeks

Sample Set: Neural Network
Stock/Index: NHTC Natural Health Trends Corp. Common Stock
Time series to forecast n: 24 Jun 2023 for 8 Weeks

According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend

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 Natural Health Trends Corp. Common Stock

When an entity, consistent with its hedge documentation, frequently resets (ie discontinues and restarts) a hedging relationship because both the hedging instrument and the hedged item frequently change (ie the entity uses a dynamic process in which both the hedged items and the hedging instruments used to manage that exposure do not remain the same for long), the entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component is separately identifiable—only when it initially designates a hedged item in that hedging relationship. A hedged item that has been assessed at the time of its initial designation in the hedging relationship, whether it was at the time of the hedge inception or subsequently, is not reassessed at any subsequent redesignation in the same hedging relationship.
Lifetime expected credit losses are not recognised on a financial instrument simply because it was considered to have low credit risk in the previous reporting period and is not considered to have low credit risk at the reporting date. In such a case, an entity shall determine whether there has been a significant increase in credit risk since initial recognition and thus whether lifetime expected credit losses are required to be recognised in accordance with paragraph 5.5.3.
An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
When defining default for the purposes of determining the risk of a default occurring, an entity shall apply a default definition that is consistent with the definition used for internal credit risk management purposes for the relevant financial instrument and consider qualitative indicators (for example, financial covenants) when appropriate. However, there is a rebuttable presumption that default does not occur later than when a financial asset is 90 days past due unless an entity has reasonable and supportable information to demonstrate that a more lagging default criterion is more appropriate. The definition of default used for these purposes shall be applied consistently to all financial instruments unless information becomes available that demonstrates that another default definition is more appropriate for a particular financial instrument.

*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

Natural Health Trends Corp. Common Stock is assigned short-term B3 & long-term Ba3 estimated rating. Natural Health Trends Corp. Common Stock prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the NHTC stock is predictable in the short/long term.

According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend

NHTC Natural Health Trends Corp. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B3	Ba3
Income Statement	Baa2	Baa2
Balance Sheet	C	C
Leverage Ratios	C	B2
Cash Flow	Baa2	Ba3
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

Trust metric by Neural Network: 87 out of 100 with 452 signals.

References

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Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
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.
Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322

Frequently Asked Questions

Q: What is the prediction methodology for NHTC stock?
A: NHTC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Polynomial Regression
Q: Is NHTC stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend NHTC Stock.
Q: Is Natural Health Trends Corp. Common Stock stock a good investment?
A: The consensus rating for Natural Health Trends Corp. Common Stock is Speculative Trend and is assigned short-term B3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of NHTC stock?
A: The consensus rating for NHTC is Speculative Trend.
Q: What is the prediction period for NHTC stock?
A: The prediction period for NHTC is 8 Weeks