**Outlook:**HARLAND & WOLFF GROUP HOLDINGS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 11 Feb 2023**for (n+8 weeks)

**Methodology :**Modular Neural Network (DNN Layer)

## Abstract

HARLAND & WOLFF GROUP HOLDINGS PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Multiple Regression^{1,2,3,4}and it is concluded that the LON:HARL stock is predictable in the short/long term.

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell**

## Key Points

- How do predictive algorithms actually work?
- Game Theory
- Nash Equilibria

## LON:HARL Target Price Prediction Modeling Methodology

We consider HARLAND & WOLFF GROUP HOLDINGS PLC Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of LON:HARL 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(Multiple Regression)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (DNN Layer)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of LON:HARL 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?

## LON:HARL Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:HARL HARLAND & WOLFF GROUP HOLDINGS PLC

**Time series to forecast n: 11 Feb 2023**for (n+8 weeks)

**According to price forecasts for (n+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 HARLAND & WOLFF GROUP HOLDINGS PLC

- For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.
- Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
- When assessing a modified time value of money element, an entity must consider factors that could affect future contractual cash flows. For example, if an entity is assessing a bond with a five-year term and the variable interest rate is reset every six months to a five-year rate, the entity cannot conclude that the contractual cash flows are solely payments of principal and interest on the principal amount outstanding simply because the interest rate curve at the time of the assessment is such that the difference between a five-year interest rate and a six-month interest rate is not significant. Instead, the entity must also consider whether the relationship between the five-year interest rate and the six-month interest rate could change over the life of the instrument such that the contractual (undiscounted) cash flows over the life of the instrument could be significantly different from the (undiscounted) benchmark cash flows. However, an entity must consider only reasonably possible scenarios instead of every possible scenario. If an entity concludes that the contractual (undiscounted) cash flows could be significantly different from the (undiscounted) benchmark cash flows, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and therefore cannot be measured at amortised cost or fair value through other comprehensive income.
- Rebalancing does not apply if the risk management objective for a hedging relationship has changed. Instead, hedge accounting for that hedging relationship shall be discontinued (despite that an entity might designate a new hedging relationship that involves the hedging instrument or hedged item of the previous hedging relationship as described in paragraph B6.5.28).

*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

HARLAND & WOLFF GROUP HOLDINGS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. HARLAND & WOLFF GROUP HOLDINGS PLC prediction model is evaluated with Modular Neural Network (DNN Layer) and Multiple Regression^{1,2,3,4} and it is concluded that the LON:HARL stock is predictable in the short/long term. ** According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell**

### LON:HARL HARLAND & WOLFF GROUP HOLDINGS PLC Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Income Statement | Baa2 | Baa2 |

Balance Sheet | Baa2 | Caa2 |

Leverage Ratios | Caa2 | B1 |

Cash Flow | Caa2 | Baa2 |

Rates of Return and Profitability | B3 | Ba2 |

*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

## References

- Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
- A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
- Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
- Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
- M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015

## Frequently Asked Questions

Q: What is the prediction methodology for LON:HARL stock?A: LON:HARL stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Multiple Regression

Q: Is LON:HARL stock a buy or sell?

A: The dominant strategy among neural network is to Sell LON:HARL Stock.

Q: Is HARLAND & WOLFF GROUP HOLDINGS PLC stock a good investment?

A: The consensus rating for HARLAND & WOLFF GROUP HOLDINGS PLC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of LON:HARL stock?

A: The consensus rating for LON:HARL is Sell.

Q: What is the prediction period for LON:HARL stock?

A: The prediction period for LON:HARL is (n+8 weeks)

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