## Summary

Predictions on stock market prices are a great challenge due to the fact that it is an immensely complex, chaotic and dynamic environment. There are many studies from various areas aiming to take on that challenge and Machine Learning approaches have been the focus of many of them. There are many examples of Machine Learning algorithms been able to reach satisfactory results when doing that type of prediction. This article studies the usage of LSTM networks on that scenario, to predict future trends of stock prices based on the price history, alongside with technical analysis indicators.** We evaluate AXIS Capital prediction models with Modular Neural Network (Market Volatility Analysis) and Polynomial Regression ^{1,2,3,4} and conclude that the AXS 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 Sell AXS stock.**

## Key Points

- What is prediction model?
- Market Risk
- Market Outlook

## AXS Target Price Prediction Modeling Methodology

We consider AXIS Capital Stock Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of AXS 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(Polynomial 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 Volatility Analysis)) X S(n):→ (n+6 month) $\sum _{i=1}^{n}\left({s}_{i}\right)$

n:Time series to forecast

p:Price signals of AXS 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?

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

**Sample Set:**Neural Network

**Stock/Index:**AXS AXIS Capital

**Time series to forecast n: 18 Nov 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Sell AXS 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 AXIS Capital

- An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. 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.
- An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
- The requirements in paragraphs 6.8.4–6.8.8 may cease to apply at different times. Therefore, in applying paragraph 6.9.1, an entity may be required to amend the formal designation of its hedging relationships at different times, or may be required to amend the formal designation of a hedging relationship more than once. When, and only when, such a change is made to the hedge designation, an entity shall apply paragraphs 6.9.7–6.9.12 as applicable. An entity also shall apply paragraph 6.5.8 (for a fair value hedge) or paragraph 6.5.11 (for a cash flow hedge) to account for any changes in the fair value of the hedged item or the hedging instrument.
- If the group of items does have offsetting risk positions (for example, a group of sales and expenses denominated in a foreign currency hedged together for foreign currency risk) then an entity shall present the hedging gains or losses in a separate line item in the statement of profit or loss and other comprehensive income. Consider, for example, a hedge of the foreign currency risk of a net position of foreign currency sales of FC100 and foreign currency expenses of FC80 using a forward exchange contract for FC20. The gain or loss on the forward exchange contract that is reclassified from the cash flow hedge reserve to profit or loss (when the net position affects profit or loss) shall be presented in a separate line item from the hedged sales and expenses. Moreover, if the sales occur in an earlier period than the expenses, the sales revenue is still measured at the spot exchange rate in accordance with IAS 21. The related hedging gain or loss is presented in a separate line item, so that profit or loss reflects the effect of hedging the net position, with a corresponding adjustment to the cash flow hedge reserve. When the hedged expenses affect profit or loss in a later period, the hedging gain or loss previously recognised in the cash flow hedge reserve on the sales is reclassified to profit or loss and presented as a separate line item from those that include the hedged expenses, which are measured at the spot exchange rate in accordance with IAS 21.

*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

AXIS Capital assigned short-term Baa2 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Polynomial Regression ^{1,2,3,4} and conclude that the AXS 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 Sell AXS stock.**

### Financial State Forecast for AXS AXIS Capital Stock Options & Futures

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

Outlook* | Baa2 | Ba3 |

Operational Risk | 85 | 54 |

Market Risk | 83 | 42 |

Technical Analysis | 58 | 60 |

Fundamental Analysis | 67 | 65 |

Risk Unsystematic | 73 | 84 |

### Prediction Confidence Score

## References

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- Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67

## Frequently Asked Questions

Q: What is the prediction methodology for AXS stock?A: AXS stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Polynomial Regression

Q: Is AXS stock a buy or sell?

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

Q: Is AXIS Capital stock a good investment?

A: The consensus rating for AXIS Capital is Sell and assigned short-term Baa2 & long-term Ba3 forecasted stock rating.

Q: What is the consensus rating of AXS stock?

A: The consensus rating for AXS is Sell.

Q: What is the prediction period for AXS stock?

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

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