Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. This paper will showcase how to perform stock prediction using Machine Learning algorithms. We evaluate VN 30 Index prediction models with Modular Neural Network (Market News Sentiment Analysis) and Spearman Correlation1,2,3,4 and conclude that the VN 30 Index stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold VN 30 Index stock.

Keywords: VN 30 Index, VN 30 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Can machine learning predict?
2. Decision Making
3. What is Markov decision process in reinforcement learning?

## VN 30 Index Target Price Prediction Modeling Methodology

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor's gains. This paper proposes a machine learning model to predict stock market price. We consider VN 30 Index Stock Decision Process with Spearman Correlation where A is the set of discrete actions of VN 30 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(Spearman Correlation)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(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+16 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of VN 30 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?

## VN 30 Index Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: VN 30 Index VN 30 Index
Time series to forecast n: 22 Oct 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold VN 30 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

VN 30 Index assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Spearman Correlation1,2,3,4 and conclude that the VN 30 Index stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold VN 30 Index stock.

### Financial State Forecast for VN 30 Index Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B2
Operational Risk 3990
Market Risk4131
Technical Analysis8232
Fundamental Analysis8834
Risk Unsystematic7264

### Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 712 signals.

## References

1. Mnih A, Teh YW. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pp. 419–26. La Jolla, CA: Int. Mach. Learn. Soc.
2. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
3. Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67
4. D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
5. Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
6. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
7. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
Frequently Asked QuestionsQ: What is the prediction methodology for VN 30 Index stock?
A: VN 30 Index stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Spearman Correlation
Q: Is VN 30 Index stock a buy or sell?
A: The dominant strategy among neural network is to Hold VN 30 Index Stock.
Q: Is VN 30 Index stock a good investment?
A: The consensus rating for VN 30 Index is Hold and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of VN 30 Index stock?
A: The consensus rating for VN 30 Index is Hold.
Q: What is the prediction period for VN 30 Index stock?
A: The prediction period for VN 30 Index is (n+16 weeks)