LSI Industries Inc. Common Stock Forecast & Analysis

Outlook: LSI Industries Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 14 Jun 2023 for 8 Weeks
Methodology : Deductive Inference (ML)

Abstract

LSI Industries Inc. Common Stock prediction model is evaluated with Deductive Inference (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the LYTS stock is predictable in the short/long term. Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

Key Points

1. Reaction Function
2. What are main components of Markov decision process?
3. Can neural networks predict stock market?

LYTS Target Price Prediction Modeling Methodology

We consider LSI Industries Inc. Common Stock Decision Process with Deductive Inference (ML) where A is the set of discrete actions of LYTS 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(Wilcoxon Rank-Sum Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Deductive Inference (ML)) X S(n):→ 8 Weeks $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of LYTS stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Deductive Inference (ML)

Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses.

Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.

 

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?

LYTS Stock Forecast (Buy or Sell) for 8 Weeks

Sample Set: Neural Network
Stock/Index: LYTS LSI Industries Inc. Common Stock
Time series to forecast n: 14 Jun 2023 for 8 Weeks

According to price forecasts for 8 Weeks 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 LSI Industries Inc. Common Stock

1. When designating a group of items as the hedged item, or a combination of financial instruments as the hedging instrument, an entity shall prospectively cease applying paragraphs 6.8.4–6.8.6 to an individual item or financial instrument in accordance with paragraphs 6.8.9, 6.8.10, or 6.8.11, as relevant, when the uncertainty arising from interest rate benchmark reform is no longer present with respect to the hedged risk and/or the timing and the amount of the interest rate benchmark-based cash flows of that item or financial instrument.
2. An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.
3. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
4. At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.

*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

LSI Industries Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. LSI Industries Inc. Common Stock prediction model is evaluated with Deductive Inference (ML) and Wilcoxon Rank-Sum Test^1,2,3,4 and it is concluded that the LYTS stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

LYTS LSI Industries Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	C	Caa2
Balance Sheet	Baa2	Baa2
Leverage Ratios	B2	Ba3
Cash Flow	B2	Ba3
Rates of Return and Profitability	Baa2	B2

*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: 85 out of 100 with 818 signals.

References

1. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
2. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
3. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. How is the price of gold determined? (No. Stock Analysis). AC Investment Research.
4. Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
5. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
6. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
7. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014

Frequently Asked Questions

Q: What is the prediction methodology for LYTS stock?
A: LYTS stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Wilcoxon Rank-Sum Test
Q: Is LYTS stock a buy or sell?
A: The dominant strategy among neural network is to Sell LYTS Stock.
Q: Is LSI Industries Inc. Common Stock stock a good investment?
A: The consensus rating for LSI Industries Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LYTS stock?
A: The consensus rating for LYTS is Sell.
Q: What is the prediction period for LYTS stock?
A: The prediction period for LYTS is 8 Weeks

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