## Abstract

**We evaluate BIST 100 Index prediction models with Deductive Inference (ML) and Sign Test ^{1,2,3,4} and conclude that the BIST 100 Index 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 BIST 100 Index stock.**

**BIST 100 Index, BIST 100 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- How useful are statistical predictions?
- Game Theory
- Prediction Modeling

## BIST 100 Index Target Price Prediction Modeling Methodology

We consider BIST 100 Index Stock Decision Process with Sign Test where A is the set of discrete actions of BIST 100 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 γ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Sign 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(Deductive Inference (ML)) X S(n):→ (n+4 weeks) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of BIST 100 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?

## BIST 100 Index Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**BIST 100 Index BIST 100 Index

**Time series to forecast n: 04 Sep 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold BIST 100 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

BIST 100 Index assigned short-term Ba3 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Deductive Inference (ML) with Sign Test ^{1,2,3,4} and conclude that the BIST 100 Index 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 BIST 100 Index stock.**

### Financial State Forecast for BIST 100 Index Stock Options & Futures

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

Outlook* | Ba3 | Ba1 |

Operational Risk | 74 | 85 |

Market Risk | 34 | 69 |

Technical Analysis | 63 | 78 |

Fundamental Analysis | 74 | 70 |

Risk Unsystematic | 72 | 48 |

### Prediction Confidence Score

## References

- J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
- Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
- M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
- Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
- Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
- Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
- J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.

## Frequently Asked Questions

Q: What is the prediction methodology for BIST 100 Index stock?A: BIST 100 Index stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Sign Test

Q: Is BIST 100 Index stock a buy or sell?

A: The dominant strategy among neural network is to Hold BIST 100 Index Stock.

Q: Is BIST 100 Index stock a good investment?

A: The consensus rating for BIST 100 Index is Hold and assigned short-term Ba3 & long-term Ba1 forecasted stock rating.

Q: What is the consensus rating of BIST 100 Index stock?

A: The consensus rating for BIST 100 Index is Hold.

Q: What is the prediction period for BIST 100 Index stock?

A: The prediction period for BIST 100 Index is (n+4 weeks)

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