Abstract

We evaluate S&P 500 Index prediction models with Modular Neural Network (Market News Sentiment Analysis) and Sign Test1,2,3,4 and conclude that the S&P 500 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 Buy S&P 500 Index stock.

Keywords: S&P 500 Index, S&P 500 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Which neural network is best for prediction?
2. Can stock prices be predicted?
3. What statistical methods are used to analyze data?

S&P 500 Index Target Price Prediction Modeling Methodology

We consider S&P 500 Index Stock Decision Process with Sign Test where A is the set of discrete actions of S&P 500 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+1 year) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of S&P 500 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?

S&P 500 Index Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: S&P 500 Index S&P 500 Index
Time series to forecast n: 03 Sep 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Buy S&P 500 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

S&P 500 Index assigned short-term B1 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Sign Test1,2,3,4 and conclude that the S&P 500 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 Buy S&P 500 Index stock.

Financial State Forecast for S&P 500 Index Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B2
Operational Risk 6630
Market Risk6461
Technical Analysis4452
Fundamental Analysis4959
Risk Unsystematic7661

Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 776 signals.

References

1. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
2. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
3. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
4. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
5. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
6. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
7. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
Frequently Asked QuestionsQ: What is the prediction methodology for S&P 500 Index stock?
A: S&P 500 Index stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Sign Test
Q: Is S&P 500 Index stock a buy or sell?
A: The dominant strategy among neural network is to Buy S&P 500 Index Stock.
Q: Is S&P 500 Index stock a good investment?
A: The consensus rating for S&P 500 Index is Buy and assigned short-term B1 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of S&P 500 Index stock?
A: The consensus rating for S&P 500 Index is Buy.
Q: What is the prediction period for S&P 500 Index stock?
A: The prediction period for S&P 500 Index is (n+1 year)