Dominant Strategy : Speculative Trend
Time series to forecast n: 24 Jun 2023 for 8 Weeks
Methodology : Reinforcement Machine Learning (ML)
Abstract
MamaMancini's Holdings Inc. is a manufacturer and distributor of a line of all natural, beef meatballs with sauce, turkey meatballs with sauce, chicken meatballs with sauce, pork meatballs with sauce, and other similar Italian products. The company was founded in 2009 by Dan Mancini, who began selling his grandmother's meatballs at local farmers markets.
MamaMancini's products are sold through a variety of channels, including grocery stores, club stores, and online. The company has also partnered with QVC to sell its products on the home shopping network.
MamaMancini's has been growing rapidly in recent years. In 2021, the company's revenue was $56.3 million, up from $36.4 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.
MamaMancini's is a publicly traded company, listed on the Nasdaq stock exchange under the ticker symbol "MMMB." The company's stock price has been volatile in recent years, but it has been on an upward trend since the beginning of 2023.
Key Points
- Operational Risk
- How do you know when a stock will go up or down?
- What is prediction model?
MMMB Target Price Prediction Modeling Methodology
We consider MamaMancini's Holdings Inc. Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of MMMB 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(Beta)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ 8 Weeks
n:Time series to forecast
p:Price signals of MMMB stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Reinforcement Machine Learning (ML)
Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.Beta
In statistics, beta (β) is a measure of the strength of the relationship between two variables. It is calculated as the slope of the line of best fit in a regression analysis. Beta can range from -1 to 1, with a value of 0 indicating no relationship between the two variables. A positive beta indicates that as one variable increases, the other variable also increases. A negative beta indicates that as one variable increases, the other variable decreases. For example, a study might find that there is a positive relationship between height and weight. This means that taller people tend to weigh more. The beta coefficient for this relationship would be positive.
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?
MMMB Stock Forecast (Buy or Sell) for 8 Weeks
Sample Set: Neural NetworkStock/Index: MMMB MamaMancini's Holdings Inc. 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 MamaMancini's Holdings Inc. Common Stock
- The expected credit losses on a loan commitment shall be discounted using the effective interest rate, or an approximation thereof, that will be applied when recognising the financial asset resulting from the loan commitment. This is because for the purpose of applying the impairment requirements, a financial asset that is recognised following a draw down on a loan commitment shall be treated as a continuation of that commitment instead of as a new financial instrument. The expected credit losses on the financial asset shall therefore be measured considering the initial credit risk of the loan commitment from the date that the entity became a party to the irrevocable commitment.
- If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess a modified time value of money element in accordance with paragraphs B4.1.9B–B4.1.9D on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the requirements related to the modification of the time value of money element in paragraphs B4.1.9B–B4.1.9D. (See also paragraph 42R of IFRS 7.)
- 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).
- IFRS 17, issued in May 2017, amended paragraphs 2.1, B2.1, B2.4, B2.5 and B4.1.30, and added paragraph 3.3.5. Amendments to IFRS 17, issued in June 2020, further amended paragraph 2.1 and added paragraphs 7.2.36‒7.2.42. An entity shall apply those amendments when it applies IFRS 17.
*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
MamaMancini's Holdings Inc. Common Stock is assigned short-term B1 & long-term B3 estimated rating. MamaMancini's Holdings Inc. Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Beta1,2,3,4 and it is concluded that the MMMB stock is predictable in the short/long term.
According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative TrendMMMB MamaMancini's Holdings Inc. Common Stock Financial Analysis*
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B1 | B3 |
| Income Statement | Ba1 | B2 |
| Balance Sheet | Caa2 | C |
| Leverage Ratios | B1 | B1 |
| Cash Flow | B2 | C |
| Rates of Return and Profitability | Baa2 | C |
*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
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- Matzkin RL. 2007. Nonparametric identification. In Handbook of Econometrics, Vol. 6B, ed. J Heckman, E Learner, pp. 5307–68. Amsterdam: Elsevier
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- Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
- 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.
- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
Frequently Asked Questions
Q: What is the prediction methodology for MMMB stock?A: MMMB stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Beta
Q: Is MMMB stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend MMMB Stock.
Q: Is MamaMancini's Holdings Inc. Common Stock stock a good investment?
A: The consensus rating for MamaMancini's Holdings Inc. Common Stock is Speculative Trend and is assigned short-term B1 & long-term B3 estimated rating.
Q: What is the consensus rating of MMMB stock?
A: The consensus rating for MMMB is Speculative Trend.
Q: What is the prediction period for MMMB stock?
A: The prediction period for MMMB is 8 Weeks
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