Social media comments have in the past had an instantaneous effect on stock markets. This paper investigates the sentiments expressed on the social media platform Twitter and their pr edictive impact on the Stock Market. We evaluate Take-Two Interactive prediction models with Statistical Inference (ML) and ElasticNet Regression1,2,3,4 and conclude that the TTWO 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 Hold TTWO stock.

Keywords: TTWO, Take-Two Interactive, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. What is a prediction confidence?
2. Stock Forecast Based On a Predictive Algorithm
3. Understanding Buy, Sell, and Hold Ratings

## TTWO Target Price Prediction Modeling Methodology

The presented paper modeled and predicted stock returns using LSTM. The historical data of stock market were transformed into 30-days-long sequences with 10 learning features and 7-day earning rate labeling. The model was fitted by training on 1200000 sequences and tested using the other 350000 sequences. We consider Take-Two Interactive Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of TTWO 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(ElasticNet Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Statistical Inference (ML)) 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 TTWO 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?

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

Sample Set: Neural Network
Stock/Index: TTWO Take-Two Interactive
Time series to forecast n: 13 Oct 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold TTWO 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

Take-Two Interactive assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with ElasticNet Regression1,2,3,4 and conclude that the TTWO 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 Hold TTWO stock.

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

Rating Short-Term Long-Term Senior
Outlook*B1B1
Operational Risk 7266
Market Risk8563
Technical Analysis4587
Fundamental Analysis6333
Risk Unsystematic3442

### Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 472 signals.

## References

1. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
2. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
3. Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99
4. Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
5. G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
6. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
7. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
Frequently Asked QuestionsQ: What is the prediction methodology for TTWO stock?
A: TTWO stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and ElasticNet Regression
Q: Is TTWO stock a buy or sell?
A: The dominant strategy among neural network is to Hold TTWO Stock.
Q: Is Take-Two Interactive stock a good investment?
A: The consensus rating for Take-Two Interactive is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of TTWO stock?
A: The consensus rating for TTWO is Hold.
Q: What is the prediction period for TTWO stock?
A: The prediction period for TTWO is (n+4 weeks)

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