AC Investment Research

HALL Hallmark Financial Services Inc. Common Stock Research Report

Outlook: Hallmark Financial Services Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 10 Jan 2023 for (n+6 month)
Methodology : Deductive Inference (ML)

Abstract

Hallmark Financial Services Inc. Common Stock prediction model is evaluated with Deductive Inference (ML) and Sign Test1,2,3,4 and it is concluded that the HALL stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

Key Points

  1. Is Target price a good indicator?
  2. Understanding Buy, Sell, and Hold Ratings
  3. Market Risk

HALL Target Price Prediction Modeling Methodology

We consider Hallmark Financial Services Inc. Common Stock Decision Process with Deductive Inference (ML) where A is the set of discrete actions of HALL 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(Sign Test)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Deductive Inference (ML)) X S(n):→ (n+6 month) e x rx

n:Time series to forecast

p:Price signals of HALL 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?

HALL Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: HALL Hallmark Financial Services Inc. Common Stock
Time series to forecast n: 10 Jan 2023 for (n+6 month)

According to price forecasts for (n+6 month) 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 Hallmark Financial Services Inc. Common Stock

  1. In the reporting period that includes the date of initial application of these amendments, an entity is not required to present the quantitative information required by paragraph 28(f) of IAS 8.
  2. When identifying what risk components qualify for designation as a hedged item, an entity assesses such risk components within the context of the particular market structure to which the risk or risks relate and in which the hedging activity takes place. Such a determination requires an evaluation of the relevant facts and circumstances, which differ by risk and market.
  3. An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.
  4. Adjusting the hedge ratio allows an entity to respond to changes in the relationship between the hedging instrument and the hedged item that arise from their underlyings or risk variables. For example, a hedging relationship in which the hedging instrument and the hedged item have different but related underlyings changes in response to a change in the relationship between those two underlyings (for example, different but related reference indices, rates or prices). Hence, rebalancing allows the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item chang

*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

Hallmark Financial Services Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Hallmark Financial Services Inc. Common Stock prediction model is evaluated with Deductive Inference (ML) and Sign Test1,2,3,4 and it is concluded that the HALL stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Hold

HALL Hallmark Financial Services Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Baa2
Balance SheetCaa2Baa2
Leverage RatiosBa2Caa2
Cash FlowCaa2Caa2
Rates of Return and ProfitabilityB1C

*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: 83 out of 100 with 730 signals.

References

  1. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
  2. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
  3. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
  4. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
  5. V. Mnih, K. Kavukcuoglu, D. Silver, A. Rusu, J. Veness, M. Bellemare, A. Graves, M. Riedmiller, A. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 02 2015.
  6. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
  7. Firth JR. 1957. A synopsis of linguistic theory 1930–1955. In Studies in Linguistic Analysis (Special Volume of the Philological Society), ed. JR Firth, pp. 1–32. Oxford, UK: Blackwell
Frequently Asked QuestionsQ: What is the prediction methodology for HALL stock?
A: HALL stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Sign Test
Q: Is HALL stock a buy or sell?
A: The dominant strategy among neural network is to Hold HALL Stock.
Q: Is Hallmark Financial Services Inc. Common Stock stock a good investment?
A: The consensus rating for Hallmark Financial Services Inc. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of HALL stock?
A: The consensus rating for HALL is Hold.
Q: What is the prediction period for HALL stock?
A: The prediction period for HALL is (n+6 month)

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