Buy, Sell, or Hold? (BIST 100 Index Stock Forecast)

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.

Keywords: 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.

Key Points

1. How useful are statistical predictions?
2. Game Theory
3. 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(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

Trust metric by Neural Network: 91 out of 100 with 515 signals.

References

1. 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
2. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
3. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
4. Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
5. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
6. Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
7. 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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