## Abstract

**We evaluate TA 35 Index prediction models with Ensemble Learning (ML) and Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the TA 35 Index 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 Hold TA 35 Index stock.**

**TA 35 Index, TA 35 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Decision Making
- Why do we need predictive models?
- Is it better to buy and sell or hold?

## TA 35 Index Target Price Prediction Modeling Methodology

We consider TA 35 Index Stock Decision Process with Wilcoxon Rank-Sum Test where A is the set of discrete actions of TA 35 Index 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 Î³ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Wilcoxon Rank-Sum 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(Ensemble Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of TA 35 Index 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?

## TA 35 Index Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**TA 35 Index TA 35 Index

**Time series to forecast n: 09 Sep 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold TA 35 Index 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

TA 35 Index assigned short-term B2 & long-term Baa2 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with Wilcoxon Rank-Sum Test ^{1,2,3,4} and conclude that the TA 35 Index 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 Hold TA 35 Index stock.**

### Financial State Forecast for TA 35 Index Stock Options & Futures

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

Outlook* | B2 | Baa2 |

Operational Risk | 54 | 90 |

Market Risk | 51 | 65 |

Technical Analysis | 79 | 82 |

Fundamental Analysis | 43 | 55 |

Risk Unsystematic | 45 | 89 |

### Prediction Confidence Score

## References

- R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
- Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
- N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
- Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
- R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.

## Frequently Asked Questions

Q: What is the prediction methodology for TA 35 Index stock?A: TA 35 Index stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Wilcoxon Rank-Sum Test

Q: Is TA 35 Index stock a buy or sell?

A: The dominant strategy among neural network is to Hold TA 35 Index Stock.

Q: Is TA 35 Index stock a good investment?

A: The consensus rating for TA 35 Index is Hold and assigned short-term B2 & long-term Baa2 forecasted stock rating.

Q: What is the consensus rating of TA 35 Index stock?

A: The consensus rating for TA 35 Index is Hold.

Q: What is the prediction period for TA 35 Index stock?

A: The prediction period for TA 35 Index is (n+3 month)