Outlook: Tyson Foods Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 24 Jan 2023 for (n+1 year)
Methodology : Inductive Learning (ML)

## Abstract

Tyson Foods Inc. Common Stock prediction model is evaluated with Inductive Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the TSN stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

## Key Points

1. Reaction Function
2. How accurate is machine learning in stock market?
3. What is neural prediction?

## TSN Target Price Prediction Modeling Methodology

We consider Tyson Foods Inc. Common Stock Decision Process with Inductive Learning (ML) where A is the set of discrete actions of TSN 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(Logistic 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(Inductive Learning (ML)) X S(n):→ (n+1 year) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of TSN 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?

## TSN Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: TSN Tyson Foods Inc. Common Stock
Time series to forecast n: 24 Jan 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 Tyson Foods Inc. Common Stock

1. If the contractual cash flows on a financial asset have been renegotiated or otherwise modified, but the financial asset is not derecognised, that financial asset is not automatically considered to have lower credit risk. An entity shall assess whether there has been a significant increase in credit risk since initial recognition on the basis of all reasonable and supportable information that is available without undue cost or effort. This includes historical and forwardlooking information and an assessment of the credit risk over the expected life of the financial asset, which includes information about the circumstances that led to the modification. Evidence that the criteria for the recognition of lifetime expected credit losses are no longer met may include a history of up-to-date and timely payment performance against the modified contractual terms. Typically a customer would need to demonstrate consistently good payment behaviour over a period of time before the credit risk is considered to have decreased.
2. If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
3. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.
4. For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.

*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

Tyson Foods Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Tyson Foods Inc. Common Stock prediction model is evaluated with Inductive Learning (ML) and Logistic Regression1,2,3,4 and it is concluded that the TSN stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

### TSN Tyson Foods Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2B1
Balance SheetBaa2Ba3
Leverage RatiosBaa2Baa2
Cash FlowB2Baa2
Rates of Return and ProfitabilityBaa2B3

*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: 78 out of 100 with 691 signals.

## References

1. R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
2. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
3. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
4. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Short/Long Term Stocks: FOX Stock Forecast. AC Investment Research Journal, 101(3).
5. Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
6. 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.
7. Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
Frequently Asked QuestionsQ: What is the prediction methodology for TSN stock?
A: TSN stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Logistic Regression
Q: Is TSN stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes TSN Stock.
Q: Is Tyson Foods Inc. Common Stock stock a good investment?
A: The consensus rating for Tyson Foods Inc. Common Stock is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of TSN stock?
A: The consensus rating for TSN is Wait until speculative trend diminishes.
Q: What is the prediction period for TSN stock?
A: The prediction period for TSN is (n+1 year)