This paper studies the possibilities of making prediction of stock market prices using historical data and machine learning algorithms. We evaluate IHG Hotels & Resorts prediction models with Modular Neural Network (Market Volatility Analysis) and ElasticNet Regression1,2,3,4 and conclude that the IHG stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold IHG stock.

Keywords: IHG, IHG Hotels & Resorts, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. How do you know when a stock will go up or down?
2. Short/Long Term Stocks
3. What is neural prediction?

## IHG Target Price Prediction Modeling Methodology

This study presents financial network indicators that can be applied to global stock market investment strategies. We propose to design both undirected and directed volatility networks of global stock market based on simple pair-wise correlation and system-wide connectedness of stock date using a vector auto-regressive model. We consider IHG Hotels & Resorts Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of IHG 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(ElasticNet Regression)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 Volatility Analysis)) X S(n):→ (n+3 month) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of IHG 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?

## IHG Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: IHG IHG Hotels & Resorts
Time series to forecast n: 13 Sep 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold IHG 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

IHG Hotels & Resorts assigned short-term Ba1 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with ElasticNet Regression1,2,3,4 and conclude that the IHG stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold IHG stock.

### Financial State Forecast for IHG Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba1B1
Operational Risk 8748
Market Risk3755
Technical Analysis7743
Fundamental Analysis7856
Risk Unsystematic7575

### Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 768 signals.

## References

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2. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
3. N. B ̈auerle and A. Mundt. Dynamic mean-risk optimization in a binomial model. Mathematical Methods of Operations Research, 70(2):219–239, 2009.
4. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
5. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
6. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
7. O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
Frequently Asked QuestionsQ: What is the prediction methodology for IHG stock?
A: IHG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and ElasticNet Regression
Q: Is IHG stock a buy or sell?
A: The dominant strategy among neural network is to Hold IHG Stock.
Q: Is IHG Hotels & Resorts stock a good investment?
A: The consensus rating for IHG Hotels & Resorts is Hold and assigned short-term Ba1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of IHG stock?
A: The consensus rating for IHG is Hold.
Q: What is the prediction period for IHG stock?
A: The prediction period for IHG is (n+3 month)