Outlook: PUBLIC POLICY HOLDING COMPANY, INC. is assigned short-term B1 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Hold
Time series to forecast n: for Weeks2
Methodology : Statistical Inference (ML)
Hypothesis Testing : Chi-Square
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.

PUBLIC POLICY HOLDING COMPANY, INC. prediction model is evaluated with Statistical Inference (ML) and Chi-Square1,2,3,4 and it is concluded that the LON:PPHC stock is predictable in the short/long term. Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold

## Key Points

1. Which neural network is best for prediction?
2. Can machine learning predict?

## LON:PPHC Stock Price Forecast

We consider PUBLIC POLICY HOLDING COMPANY, INC. Decision Process with Statistical Inference (ML) where A is the set of discrete actions of LON:PPHC 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

Sample Set: Neural Network
Stock/Index: LON:PPHC PUBLIC POLICY HOLDING COMPANY, INC.
Time series to forecast: 4 Weeks

According to price forecasts, the dominant strategy among neural network is: Hold

F(Chi-Square)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(Statistical Inference (ML)) X S(n):→ 4 Weeks $∑ i = 1 n r i$

n:Time series to forecast

p:Price signals of LON:PPHC stock

j:Nash equilibria (Neural Network)

k:Dominated move of LON:PPHC stock holders

a:Best response for LON:PPHC target price

Statistical inference is a process of drawing conclusions about a population based on data from a sample of that population. In machine learning (ML), statistical inference is used to make predictions about new data based on data that has already been seen.5 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.6,7

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?

### LON:PPHC Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

### Financial Data Adjustments for Statistical Inference (ML) based LON:PPHC Stock Prediction Model

1. When an entity discontinues measuring the financial instrument that gives rise to the credit risk, or a proportion of that financial instrument, at fair value through profit or loss, that financial instrument's fair value at the date of discontinuation becomes its new carrying amount. Subsequently, the same measurement that was used before designating the financial instrument at fair value through profit or loss shall be applied (including amortisation that results from the new carrying amount). For example, a financial asset that had originally been classified as measured at amortised cost would revert to that measurement and its effective interest rate would be recalculated based on its new gross carrying amount on the date of discontinuing measurement at fair value through profit or loss.
2. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
3. 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.
4. Changes in market conditions that give rise to market risk include changes in a benchmark interest rate, the price of another entity's financial instrument, a commodity price, a foreign exchange rate or an index of prices or rates.

*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.

### LON:PPHC PUBLIC POLICY HOLDING COMPANY, INC. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Income StatementCaa2Baa2
Balance SheetB1B3
Leverage RatiosBaa2Caa2
Cash FlowCB1
Rates of Return and ProfitabilityBa3Ba1

*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?

## References

1. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
2. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
3. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
4. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
5. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
6. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. MRNA: The Next Big Thing in mRNA Vaccines. AC Investment Research Journal, 220(44).
7. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:PPHC stock?
A: LON:PPHC stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Chi-Square
Q: Is LON:PPHC stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:PPHC Stock.
Q: Is PUBLIC POLICY HOLDING COMPANY, INC. stock a good investment?
A: The consensus rating for PUBLIC POLICY HOLDING COMPANY, INC. is Hold and is assigned short-term B1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of LON:PPHC stock?
A: The consensus rating for LON:PPHC is Hold.
Q: What is the prediction period for LON:PPHC stock?
A: The prediction period for LON:PPHC is 4 Weeks
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