**Outlook:**IAC Inc. Common Stock assigned short-term Baa2 & long-term B2 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 06 Dec 2022**for (n+4 weeks)

**Methodology :**Modular Neural Network (Market Direction Analysis)

## Abstract

In this paper we investigate ways to use prior knowledge and neural networks to improve multivariate prediction ability. Daily stock prices are predicted as a complicated real-world problem, taking non-numerical factors such as political and international events are into account. We have studied types of prior knowledge which are difficult to insert into initial network structures or to represent in the form of error measurements. (Parray, I.R., Khurana, S.S., Kumar, M. and Altalbe, A.A., 2020. Time series data analysis of stock price movement using machine learning techniques. Soft Computing, 24(21), pp.16509-16517.)** We evaluate IAC Inc. Common Stock prediction models with Modular Neural Network (Market Direction Analysis) and Paired T-Test ^{1,2,3,4} and conclude that the IAC stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy IAC stock.**

## Key Points

- Investment Risk
- Market Risk
- Is Target price a good indicator?

## IAC Target Price Prediction Modeling Methodology

We consider IAC Inc. Common Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of IAC 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(Paired T-Test)

^{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+4 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of IAC 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?

## IAC Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**IAC IAC Inc. Common Stock

**Time series to forecast n: 06 Dec 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy IAC 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 IAC Inc. Common Stock

- The risk of a default occurring on financial instruments that have comparable credit risk is higher the longer the expected life of the instrument; for example, the risk of a default occurring on an AAA-rated bond with an expected life of 10 years is higher than that on an AAA-rated bond with an expected life of five years.
- If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess whether the fair value of a prepayment feature was insignificant in accordance with paragraph B4.1.12(c) on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the exception for prepayment features in paragraph B4.1.12. (See also paragraph 42S of IFRS 7.)
- Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.
- Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.

*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

IAC Inc. Common Stock assigned short-term Baa2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Paired T-Test ^{1,2,3,4} and conclude that the IAC stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy IAC stock.**

### Financial State Forecast for IAC IAC Inc. Common Stock Options & Futures

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

Outlook* | Baa2 | B2 |

Operational Risk | 79 | 67 |

Market Risk | 82 | 33 |

Technical Analysis | 90 | 87 |

Fundamental Analysis | 62 | 50 |

Risk Unsystematic | 51 | 38 |

### Prediction Confidence Score

## References

- S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
- Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
- Athey S, Mobius MM, Pál J. 2017c. The impact of aggregators on internet news consumption. Unpublished manuscript, Grad. School Bus., Stanford Univ., Stanford, CA
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
- Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.

## Frequently Asked Questions

Q: What is the prediction methodology for IAC stock?A: IAC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Paired T-Test

Q: Is IAC stock a buy or sell?

A: The dominant strategy among neural network is to Buy IAC Stock.

Q: Is IAC Inc. Common Stock stock a good investment?

A: The consensus rating for IAC Inc. Common Stock is Buy and assigned short-term Baa2 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of IAC stock?

A: The consensus rating for IAC is Buy.

Q: What is the prediction period for IAC stock?

A: The prediction period for IAC is (n+4 weeks)