Abstract
We evaluate KOSPI Index prediction models with Statistical Inference (ML) and Stepwise Regression1,2,3,4 and conclude that the KOSPI Index stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold KOSPI Index stock.
Keywords: KOSPI Index, KOSPI Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Why do we need predictive models?
- Understanding Buy, Sell, and Hold Ratings
- Market Risk

KOSPI Index Target Price Prediction Modeling Methodology
We consider KOSPI Index Stock Decision Process with Stepwise Regression where A is the set of discrete actions of KOSPI 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(Stepwise Regression)5,6,7= X R(Statistical Inference (ML)) X S(n):→ (n+1 year)
n:Time series to forecast
p:Price signals of KOSPI 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?
KOSPI Index Stock Forecast (Buy or Sell) for (n+1 year)
Sample Set: Neural NetworkStock/Index: KOSPI Index KOSPI Index
Time series to forecast n: 01 Sep 2022 for (n+1 year)
According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold KOSPI 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
KOSPI Index assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Stepwise Regression1,2,3,4 and conclude that the KOSPI Index stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold KOSPI Index stock.
Financial State Forecast for KOSPI Index Stock Options & Futures
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | Ba3 |
Operational Risk | 39 | 67 |
Market Risk | 85 | 61 |
Technical Analysis | 36 | 50 |
Fundamental Analysis | 75 | 52 |
Risk Unsystematic | 31 | 75 |
Prediction Confidence Score
References
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- M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
- Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
- Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
- Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
- Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
Frequently Asked Questions
Q: What is the prediction methodology for KOSPI Index stock?A: KOSPI Index stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Stepwise Regression
Q: Is KOSPI Index stock a buy or sell?
A: The dominant strategy among neural network is to Hold KOSPI Index Stock.
Q: Is KOSPI Index stock a good investment?
A: The consensus rating for KOSPI Index is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of KOSPI Index stock?
A: The consensus rating for KOSPI Index is Hold.
Q: What is the prediction period for KOSPI Index stock?
A: The prediction period for KOSPI Index is (n+1 year)