## Summary

Stock price prediction has always been a challenging task for the researchers in financial domain. While the Efficient Market Hypothesis claims that it is impossible to predict stock prices accurately, there are work in the literature that have demonstrated that stock price movements can be forecasted with a reasonable degree of accuracy, if appropriate variables are chosen and suitable predictive models are built using those variables. In this work, we present a robust and accurate framework of stock price prediction using statistical, machine learning and deep learning methods** We evaluate Hyliion Holdings Corp. Class A Common Stock prediction models with Modular Neural Network (Market Direction Analysis) and Stepwise Regression ^{1,2,3,4} and conclude that the HYLN stock is predictable in the short/long term. **

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold HYLN stock.**

## Key Points

- Operational Risk
- Reaction Function
- What is a prediction confidence?

## HYLN Target Price Prediction Modeling Methodology

We consider Hyliion Holdings Corp. Class A Common Stock Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of HYLN 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(Stepwise 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 (Market Direction Analysis)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of HYLN 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?

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

**Sample Set:**Neural Network

**Stock/Index:**HYLN Hyliion Holdings Corp. Class A Common Stock

**Time series to forecast n: 29 Nov 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold HYLN stock.**

**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 (Yellow to Green): *Technical Analysis%**

## Adjusted IFRS* Prediction Methods for Hyliion Holdings Corp. Class A Common Stock

- A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
- For some types of fair value hedges, the objective of the hedge is not primarily to offset the fair value change of the hedged item but instead to transform the cash flows of the hedged item. For example, an entity hedges the fair value interest rate risk of a fixed-rate debt instrument using an interest rate swap. The entity's hedge objective is to transform the fixed-interest cash flows into floating interest cash flows. This objective is reflected in the accounting for the hedging relationship by accruing the net interest accrual on the interest rate swap in profit or loss. In the case of a hedge of a net position (for example, a net position of a fixed-rate asset and a fixed-rate liability), this net interest accrual must be presented in a separate line item in the statement of profit or loss and other comprehensive income. This is to avoid the grossing up of a single instrument's net gains or losses into offsetting gross amounts and recognising them in different line items (for example, this avoids grossing up a net interest receipt on a single interest rate swap into gross interest revenue and gross interest expense).
- When designating a risk component as a hedged item, the hedge accounting requirements apply to that risk component in the same way as they apply to other hedged items that are not risk components. For example, the qualifying criteria apply, including that the hedging relationship must meet the hedge effectiveness requirements, and any hedge ineffectiveness must be measured and recognised.
- When an entity, consistent with its hedge documentation, frequently resets (ie discontinues and restarts) a hedging relationship because both the hedging instrument and the hedged item frequently change (ie the entity uses a dynamic process in which both the hedged items and the hedging instruments used to manage that exposure do not remain the same for long), the entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component is separately identifiable—only when it initially designates a hedged item in that hedging relationship. A hedged item that has been assessed at the time of its initial designation in the hedging relationship, whether it was at the time of the hedge inception or subsequently, is not reassessed at any subsequent redesignation in the same hedging relationship.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Hyliion Holdings Corp. Class A Common Stock assigned short-term B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Stepwise Regression ^{1,2,3,4} and conclude that the HYLN stock is predictable in the short/long term.**

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold HYLN stock.**

### Financial State Forecast for HYLN Hyliion Holdings Corp. Class A Common Stock Stock Options & Futures

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

Outlook* | B1 | B1 |

Operational Risk | 58 | 57 |

Market Risk | 85 | 76 |

Technical Analysis | 34 | 59 |

Fundamental Analysis | 53 | 37 |

Risk Unsystematic | 69 | 59 |

### Prediction Confidence Score

## References

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- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.

## Frequently Asked Questions

Q: What is the prediction methodology for HYLN stock?A: HYLN stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Stepwise Regression

Q: Is HYLN stock a buy or sell?

A: The dominant strategy among neural network is to Hold HYLN Stock.

Q: Is Hyliion Holdings Corp. Class A Common Stock stock a good investment?

A: The consensus rating for Hyliion Holdings Corp. Class A Common Stock is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of HYLN stock?

A: The consensus rating for HYLN is Hold.

Q: What is the prediction period for HYLN stock?

A: The prediction period for HYLN is (n+6 month)