Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. However, there is no formal method to determine the optimal neural network for prediction purpose in the literature. In this paper, two kinds of neural networks, a feed forward multi layer Perceptron (MLP) and an Elman recurrent network, are used to predict a company's stock value based on its stock share value history. We evaluate Interactive Brokers prediction models with Modular Neural Network (Market Direction Analysis) and Independent T-Test1,2,3,4 and conclude that the IBKR stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to HoldBuy IBKR stock.

Keywords: IBKR, Interactive Brokers, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Dominated Move
2. What is neural prediction?
3. Can we predict stock market using machine learning?

## IBKR Target Price Prediction Modeling Methodology

Nowadays, people show more and more enthusiasm for applying machine learning methods to finance domain. Many scholars and investors are trying to discover the mystery behind the stock market by applying deep learning. This thesis compares four machine learning methods: long short-term memory (LSTM), gated recurrent units (GRU), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) to test which one performs the best in predicting the stock trend. We consider Interactive Brokers Stock Decision Process with Independent T-Test where A is the set of discrete actions of IBKR 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+8 weeks) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of IBKR 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?

## IBKR Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: IBKR Interactive Brokers
Time series to forecast n: 18 Sep 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to HoldBuy IBKR 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

Interactive Brokers assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Independent T-Test1,2,3,4 and conclude that the IBKR stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to HoldBuy IBKR stock.

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

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Operational Risk 7974
Market Risk3858
Technical Analysis7366
Fundamental Analysis4951
Risk Unsystematic8568

### Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 753 signals.

## References

1. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
2. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
3. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
4. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
5. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
6. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
7. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
Frequently Asked QuestionsQ: What is the prediction methodology for IBKR stock?
A: IBKR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Independent T-Test
Q: Is IBKR stock a buy or sell?
A: The dominant strategy among neural network is to HoldBuy IBKR Stock.
Q: Is Interactive Brokers stock a good investment?
A: The consensus rating for Interactive Brokers is HoldBuy and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of IBKR stock?
A: The consensus rating for IBKR is HoldBuy.
Q: What is the prediction period for IBKR stock?
A: The prediction period for IBKR is (n+8 weeks)