Outlook: AFC Gamma Inc. Common Stock is assigned short-term B3 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks2
Methodology : Supervised Machine Learning (ML)
Hypothesis Testing : Linear Regression
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

AFC Gamma Inc. Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the AFCG stock is predictable in the short/long term. Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

## Key Points

1. What is the use of Markov decision process?
2. Can statistics predict the future?
3. What are buy sell or hold recommendations?

## AFCG Target Price Prediction Modeling Methodology

We consider AFC Gamma Inc. Common Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of AFCG 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(Linear Regression)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(Supervised Machine Learning (ML)) X S(n):→ 4 Weeks $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of AFCG stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Supervised Machine Learning (ML)

Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.

### Linear Regression

In statistics, linear regression is a method for estimating the relationship between a dependent variable and one or more independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Linear regression assumes that the relationship between the dependent variable and the independent variables is linear. This means that the dependent variable can be represented as a straight line function of the independent variables.

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?

## AFCG Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: AFCG AFC Gamma Inc. Common Stock
Time series to forecast: 4 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 Supervised Machine Learning (ML) based AFCG Stock Prediction Model

1. If an entity previously accounted for a derivative liability that is linked to, and must be settled by, delivery of an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) at cost in accordance with IAS 39, it shall measure that derivative liability at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings of the reporting period that includes the date of initial application.
2. The accounting for the forward element of forward contracts in accordance with paragraph 6.5.16 applies only to the extent that the forward element relates to the hedged item (aligned forward element). The forward element of a forward contract relates to the hedged item if the critical terms of the forward contract (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the forward contract and the hedged item are not fully aligned, an entity shall determine the aligned forward element, ie how much of the forward element included in the forward contract (actual forward element) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.16). An entity determines the aligned forward element using the valuation of the forward contract that would have critical terms that perfectly match the hedged item.
3. The change in the value of the hedged item determined using a hypothetical derivative may also be used for the purpose of assessing whether a hedging relationship meets the hedge effectiveness requirements.
4. A layer component that includes a prepayment option is not eligible to be designated as a hedged item in a fair value hedge if the prepayment option's fair value is affected by changes in the hedged risk, unless the designated layer includes the effect of the related prepayment option when determining the change in the fair value of the hedged item.

*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.

### AFCG AFC Gamma Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B3Ba1
Income StatementCBa3
Balance SheetBaa2Baa2
Leverage RatiosCaa2Ba2
Cash FlowCaa2Ba2
Rates of Return and ProfitabilityCBa3

*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

AFC Gamma Inc. Common Stock is assigned short-term B3 & long-term Ba1 estimated rating. AFC Gamma Inc. Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the AFCG stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

### Prediction Confidence Score

Trust metric by Neural Network: 73 out of 100 with 728 signals.

## References

1. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
2. E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
3. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
4. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
5. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
6. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
7. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
Frequently Asked QuestionsQ: What is the prediction methodology for AFCG stock?
A: AFCG stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Linear Regression
Q: Is AFCG stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend AFCG Stock.
Q: Is AFC Gamma Inc. Common Stock stock a good investment?
A: The consensus rating for AFC Gamma Inc. Common Stock is Speculative Trend and is assigned short-term B3 & long-term Ba1 estimated rating.
Q: What is the consensus rating of AFCG stock?
A: The consensus rating for AFCG is Speculative Trend.
Q: What is the prediction period for AFCG stock?
A: The prediction period for AFCG is 4 Weeks