Outlook: Vishay Precision Group Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 18 Jan 2023 for (n+1 year)
Methodology : Modular Neural Network (CNN Layer)

## Abstract

Vishay Precision Group Inc. Common Stock prediction model is evaluated with Modular Neural Network (CNN Layer) and Pearson Correlation1,2,3,4 and it is concluded that the VPG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

## Key Points

1. How do you decide buy or sell a stock?
2. Understanding Buy, Sell, and Hold Ratings
3. What is the use of Markov decision process?

## VPG Target Price Prediction Modeling Methodology

We consider Vishay Precision Group Inc. Common Stock Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of VPG 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 (CNN Layer)) X S(n):→ (n+1 year) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of VPG 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?

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

Sample Set: Neural Network
Stock/Index: VPG Vishay Precision Group Inc. Common Stock
Time series to forecast n: 18 Jan 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

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 Vishay Precision Group Inc. Common Stock

1. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).
2. The accounting for the time value of options in accordance with paragraph 6.5.15 applies only to the extent that the time value relates to the hedged item (aligned time value). The time value of an option relates to the hedged item if the critical terms of the option (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the option and the hedged item are not fully aligned, an entity shall determine the aligned time value, ie how much of the time value included in the premium (actual time value) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.15). An entity determines the aligned time value using the valuation of the option that would have critical terms that perfectly match the hedged item.
3. The purpose of estimating expected credit losses is neither to estimate a worstcase scenario nor to estimate the best-case scenario. Instead, an estimate of expected credit losses shall always reflect the possibility that a credit loss occurs and the possibility that no credit loss occurs even if the most likely outcome is no credit loss.
4. Interest Rate Benchmark Reform—Phase 2, which amended IFRS 9, IAS 39, IFRS 7, IFRS 4 and IFRS 16, issued in August 2020, added paragraphs 5.4.5–5.4.9, 6.8.13, Section 6.9 and paragraphs 7.2.43–7.2.46. An entity shall apply these amendments for annual periods beginning on or after 1 January 2021. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.

*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

Vishay Precision Group Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Vishay Precision Group Inc. Common Stock prediction model is evaluated with Modular Neural Network (CNN Layer) and Pearson Correlation1,2,3,4 and it is concluded that the VPG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

### VPG Vishay Precision Group Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2B2
Balance SheetB1Baa2
Leverage RatiosCaa2B2
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBaa2Baa2

*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: 93 out of 100 with 602 signals.

## References

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3. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
4. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
5. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is DOW Stock Expected to Go Up?(Stock Forecast). AC Investment Research Journal, 101(3).
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7. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
Frequently Asked QuestionsQ: What is the prediction methodology for VPG stock?
A: VPG stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Pearson Correlation
Q: Is VPG stock a buy or sell?
A: The dominant strategy among neural network is to Hold VPG Stock.
Q: Is Vishay Precision Group Inc. Common Stock stock a good investment?
A: The consensus rating for Vishay Precision Group Inc. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of VPG stock?
A: The consensus rating for VPG is Hold.
Q: What is the prediction period for VPG stock?
A: The prediction period for VPG is (n+1 year)