Development of linguistic technologies and penetration of social media provide powerful possibilities to investigate users' moods and psychological states of people. In this paper we discussed possibility to improve accuracy of stock market indicators predictions by using data about psychological states of Twitter users. For analysis of psychological states we used lexicon-based approach.** We evaluate Ralph Lauren Corporation prediction models with Ensemble Learning (ML) and Spearman Correlation ^{1,2,3,4} and conclude that the RL stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell RL stock.**

**RL, Ralph Lauren Corporation, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Decision Making
- Is Target price a good indicator?
- How can neural networks improve predictions?

## RL Target Price Prediction Modeling Methodology

Complex networks in stock market and stock price volatility pattern prediction are the important issues in stock price research. Previous studies have used historical information regarding a single stock to predict the future trend of the stock's price, seldom considering comovement among stocks in the same market. In this study, in order to extract the information about relation stocks for prediction, we try to combine the complex network method with machine learning to predict stock price patterns. We consider Ralph Lauren Corporation Stock Decision Process with Spearman Correlation where A is the set of discrete actions of RL 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(Spearman Correlation)

^{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(Ensemble Learning (ML)) X S(n):→ (n+3 month) $\overrightarrow{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of RL stock

j:Nash equilibria

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?

## RL Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**RL Ralph Lauren Corporation

**Time series to forecast n: 05 Oct 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell RL 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%**

## Conclusions

Ralph Lauren Corporation assigned short-term B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with Spearman Correlation ^{1,2,3,4} and conclude that the RL stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell RL stock.**

### Financial State Forecast for RL Stock Options & Futures

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

Outlook* | B1 | B1 |

Operational Risk | 72 | 65 |

Market Risk | 46 | 56 |

Technical Analysis | 48 | 32 |

Fundamental Analysis | 74 | 57 |

Risk Unsystematic | 53 | 82 |

### Prediction Confidence Score

## References

- S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
- Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
- Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
- Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
- Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
- Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
- Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97

## Frequently Asked Questions

Q: What is the prediction methodology for RL stock?A: RL stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Spearman Correlation

Q: Is RL stock a buy or sell?

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

Q: Is Ralph Lauren Corporation stock a good investment?

A: The consensus rating for Ralph Lauren Corporation is Sell and assigned short-term B1 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of RL stock?

A: The consensus rating for RL is Sell.

Q: What is the prediction period for RL stock?

A: The prediction period for RL is (n+3 month)