How Do You Pick a Stock? (CSE All-Share Index Stock Forecast)

Abstract

We evaluate CSE All-Share Index prediction models with Triple Exponential Moving Average (TRIX) and Independent T-Test^1,2,3,4 and conclude that the CSE All-Share 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 Buy CSE All-Share Index stock.

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

Key Points

1. Is it better to buy and sell or hold?
2. What is prediction in deep learning?
3. Technical Analysis with Algorithmic Trading

CSE All-Share Index Target Price Prediction Modeling Methodology

We consider CSE All-Share Index Stock Decision Process with Independent T-Test where A is the set of discrete actions of CSE All-Share 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(Independent T-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(Triple Exponential Moving Average (TRIX)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of CSE All-Share 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?

CSE All-Share Index Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: CSE All-Share Index CSE All-Share Index
Time series to forecast n: 01 Sep 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy CSE All-Share 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

CSE All-Share Index assigned short-term B1 & long-term Baa2 forecasted stock rating. We evaluate the prediction models Triple Exponential Moving Average (TRIX) with Independent T-Test^1,2,3,4 and conclude that the CSE All-Share 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 Buy CSE All-Share Index stock.

Financial State Forecast for CSE All-Share Index Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B1	Baa2
Operational Risk	84	57
Market Risk	87	58
Technical Analysis	30	81
Fundamental Analysis	54	82
Risk Unsystematic	40	89

Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 880 signals.

References

1. uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
2. Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
3. Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
4. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
5. N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
6. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
7. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68

Frequently Asked Questions

Q: What is the prediction methodology for CSE All-Share Index stock?
A: CSE All-Share Index stock prediction methodology: We evaluate the prediction models Triple Exponential Moving Average (TRIX) and Independent T-Test
Q: Is CSE All-Share Index stock a buy or sell?
A: The dominant strategy among neural network is to Buy CSE All-Share Index Stock.
Q: Is CSE All-Share Index stock a good investment?
A: The consensus rating for CSE All-Share Index is Buy and assigned short-term B1 & long-term Baa2 forecasted stock rating.
Q: What is the consensus rating of CSE All-Share Index stock?
A: The consensus rating for CSE All-Share Index is Buy.
Q: What is the prediction period for CSE All-Share Index stock?
A: The prediction period for CSE All-Share Index is (n+16 weeks)

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