Outlook: Kelly Services Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 20 Jun 2023 for 6 Month
Methodology : Transfer Learning (ML)

## Summary

Kelly Services Inc. Class A Common Stock prediction model is evaluated with Transfer Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the KELYA stock is predictable in the short/long term. Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

## Key Points

1. Is Target price a good indicator?
2. How useful are statistical predictions?
3. What is the use of Markov decision process?

## KELYA Target Price Prediction Modeling Methodology

We consider Kelly Services Inc. Class A Common Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of KELYA 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(Chi-Square)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(Transfer Learning (ML)) X S(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 KELYA stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Transfer Learning (ML)

Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.

### Chi-Square

A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.

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?

## KELYA Stock Forecast (Buy or Sell) for 6 Month

Sample Set: Neural Network
Stock/Index: KELYA Kelly Services Inc. Class A Common Stock
Time series to forecast n: 20 Jun 2023 for 6 Month

According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

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 Kelly Services Inc. Class A Common Stock

1. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
2. An entity that first applies IFRS 17 as amended in June 2020 at the same time it first applies this Standard shall apply paragraphs 7.2.1–7.2.28 instead of paragraphs 7.2.38–7.2.42.
3. The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
4. 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.

*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

Kelly Services Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Kelly Services Inc. Class A Common Stock prediction model is evaluated with Transfer Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the KELYA stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Sell

### KELYA Kelly Services Inc. Class A Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Ba3
Balance SheetBaa2Ba3
Leverage RatiosB2Baa2
Cash FlowB1Caa2
Rates of Return and ProfitabilityB1Caa2

*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 550 signals.

## References

1. 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
2. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
3. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
4. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
5. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
6. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
7. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
Frequently Asked QuestionsQ: What is the prediction methodology for KELYA stock?
A: KELYA stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Chi-Square
Q: Is KELYA stock a buy or sell?
A: The dominant strategy among neural network is to Sell KELYA Stock.
Q: Is Kelly Services Inc. Class A Common Stock stock a good investment?
A: The consensus rating for Kelly Services Inc. Class A Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of KELYA stock?
A: The consensus rating for KELYA is Sell.
Q: What is the prediction period for KELYA stock?
A: The prediction period for KELYA is 6 Month