Outlook: Enzo Biochem Inc. Common Stock (\$0.01 Par Value) is assigned short-term Ba1 & long-term Ba1 estimated rating.
Time series to forecast n: 26 Mar 2023 for (n+6 month)
Methodology : Modular Neural Network (CNN Layer)

## Abstract

Enzo Biochem Inc. Common Stock (\$0.01 Par Value) prediction model is evaluated with Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the ENZ stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

## Key Points

1. Game Theory
2. Can machine learning predict?
3. Decision Making

## ENZ Target Price Prediction Modeling Methodology

We consider Enzo Biochem Inc. Common Stock (\$0.01 Par Value) Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of ENZ 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(Statistical Hypothesis Testing)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 (CNN Layer)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of ENZ stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

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?

## ENZ Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: ENZ Enzo Biochem Inc. Common Stock (\$0.01 Par Value)
Time series to forecast n: 26 Mar 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

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 Enzo Biochem Inc. Common Stock (\$0.01 Par Value)

1. 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.
2. However, the designation of the hedging relationship using the same hedge ratio as that resulting from the quantities of the hedged item and the hedging instrument that the entity actually uses shall not reflect an imbalance between the weightings of the hedged item and the hedging instrument that would in turn create hedge ineffectiveness (irrespective of whether recognised or not) that could result in an accounting outcome that would be inconsistent with the purpose of hedge accounting. Hence, for the purpose of designating a hedging relationship, an entity must adjust the hedge ratio that results from the quantities of the hedged item and the hedging instrument that the entity actually uses if that is needed to avoid such an imbalance
3. The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
4. Measurement of a financial asset or financial liability and classification of recognised changes in its value are determined by the item's classification and whether the item is part of a designated hedging relationship. Those requirements can create a measurement or recognition inconsistency (sometimes referred to as an 'accounting mismatch') when, for example, in the absence of designation as at fair value through profit or loss, a financial asset would be classified as subsequently measured at fair value through profit or loss and a liability the entity considers related would be subsequently measured at amortised cost (with changes in fair value not recognised). In such circumstances, an entity may conclude that its financial statements would provide more relevant information if both the asset and the liability were measured as at fair value through profit or loss.

*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

Enzo Biochem Inc. Common Stock (\$0.01 Par Value) is assigned short-term Ba1 & long-term Ba1 estimated rating. Enzo Biochem Inc. Common Stock (\$0.01 Par Value) prediction model is evaluated with Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the ENZ stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

### ENZ Enzo Biochem Inc. Common Stock (\$0.01 Par Value) Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB1Baa2
Balance SheetBa2Baa2
Leverage RatiosCaa2Caa2
Cash FlowBaa2B1
Rates of Return and ProfitabilityBaa2C

*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: 77 out of 100 with 598 signals.

## References

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Frequently Asked QuestionsQ: What is the prediction methodology for ENZ stock?
A: ENZ stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Statistical Hypothesis Testing
Q: Is ENZ stock a buy or sell?
A: The dominant strategy among neural network is to Buy ENZ Stock.
Q: Is Enzo Biochem Inc. Common Stock (\$0.01 Par Value) stock a good investment?
A: The consensus rating for Enzo Biochem Inc. Common Stock (\$0.01 Par Value) is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ENZ stock?
A: The consensus rating for ENZ is Buy.
Q: What is the prediction period for ENZ stock?
A: The prediction period for ENZ is (n+6 month)