Outlook: Local Bounti Corporation Common Stock is assigned short-term Ba3 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (Social Media Sentiment Analysis)
Hypothesis Testing : Pearson Correlation
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.

## Summary

Local Bounti Corporation Common Stock prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the LOCL 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 social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. 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 6 Month period, the dominant strategy among neural network is: Buy

## Key Points

1. Technical Analysis with Algorithmic Trading
2. What is Markov decision process in reinforcement learning?
3. What statistical methods are used to analyze data?

## LOCL Target Price Prediction Modeling Methodology

We consider Local Bounti Corporation Common Stock Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of LOCL 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(Pearson Correlation)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ 6 Month $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of LOCL stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Modular Neural Network (Social Media Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. 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.

### Pearson Correlation

Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.

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?

## LOCL Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: LOCL Local Bounti Corporation Common Stock
Time series to forecast: 6 Month

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

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 Modular Neural Network (Social Media Sentiment Analysis) based LOCL Stock Prediction Model

1. Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
2. An entity may retain the right to a part of the interest payments on transferred assets as compensation for servicing those assets. The part of the interest payments that the entity would give up upon termination or transfer of the servicing contract is allocated to the servicing asset or servicing liability. The part of the interest payments that the entity would not give up is an interest-only strip receivable. For example, if the entity would not give up any interest upon termination or transfer of the servicing contract, the entire interest spread is an interest-only strip receivable. For the purposes of applying paragraph 3.2.13, the fair values of the servicing asset and interest-only strip receivable are used to allocate the carrying amount of the receivable between the part of the asset that is derecognised and the part that continues to be recognised. If there is no servicing fee specified or the fee to be received is not expected to compensate the entity adequately for performing the servicing, a liability for the servicing obligation is recognised at fair value.
3. An entity shall apply this Standard retrospectively, in accordance with IAS 8 Accounting Policies, Changes in Accounting Estimates and Errors, except as specified in paragraphs 7.2.4–7.2.26 and 7.2.28. This Standard shall not be applied to items that have already been derecognised at the date of initial application.
4. One of the defining characteristics of a derivative is that it has an initial net investment that is smaller than would be required for other types of contracts that would be expected to have a similar response to changes in market factors. An option contract meets that definition because the premium is less than the investment that would be required to obtain the underlying financial instrument to which the option is linked. A currency swap that requires an initial exchange of different currencies of equal fair values meets the definition because it has a zero initial net investment.

*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.

### LOCL Local Bounti Corporation Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Income StatementBaa2Baa2
Balance SheetB3Caa2
Leverage RatiosB3B2
Cash FlowBa3Ba1
Rates of Return and ProfitabilityBaa2B2

*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

Local Bounti Corporation Common Stock is assigned short-term Ba3 & long-term Ba3 estimated rating. Local Bounti Corporation Common Stock prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the LOCL stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Buy

### Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 872 signals.

## References

1. G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
2. Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
3. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
4. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
5. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
6. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
7. Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
Frequently Asked QuestionsQ: What is the prediction methodology for LOCL stock?
A: LOCL stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Pearson Correlation
Q: Is LOCL stock a buy or sell?
A: The dominant strategy among neural network is to Buy LOCL Stock.
Q: Is Local Bounti Corporation Common Stock stock a good investment?
A: The consensus rating for Local Bounti Corporation Common Stock is Buy and is assigned short-term Ba3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of LOCL stock?
A: The consensus rating for LOCL is Buy.
Q: What is the prediction period for LOCL stock?
A: The prediction period for LOCL is 6 Month