Machine Learning stock prediction: RKT Stock Prediction

Prediction of stock market movement is extremely difficult due to its high mutable nature. The rapid ups and downs occur in stock market because of impact from foreign commodities like emotional behavior of investors, political, psychological and economical factors. Continuous unsettlement in the stock market is major reason why investors sell out at the wrong time and often fail to gain the benefit. While investing in stock market investors must not forget the risk of reward rule and expose their holdings to greater risks. Although it is not possible predict stock market movement with full accuracy, losses from selling stocks at wrong time and its impacts can be reduce to greater extent using prediction of stock market movement based on analysis of historical data. We evaluate Rocket Companies prediction models with Supervised Machine Learning (ML) and Sign Test^1,2,3,4 and conclude that the RKT stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold RKT stock.

Keywords: RKT, Rocket Companies, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Prediction Modeling
2. What is neural prediction?
3. Trading Signals

RKT Target Price Prediction Modeling Methodology

Stock price forecasting is a popular and important topic in financial and academic studies. Share market is an volatile place for predicting since there are no significant rules to estimate or predict the price of a share in the share market. Many methods like technical analysis, fundamental analysis, time series analysis and statistical analysis etc. are used to predict the price in tie share market but none of these methods are proved as a consistently acceptable prediction tool. In this paper, we implemented a Random Forest approach to predict stock market prices. We consider Rocket Companies Stock Decision Process with Sign Test where A is the set of discrete actions of RKT 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Supervised Machine Learning (ML)) X S(n):→ (n+6 month) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of RKT 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?

RKT Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: RKT Rocket Companies
Time series to forecast n: 20 Oct 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold RKT 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

Rocket Companies assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Supervised Machine Learning (ML) with Sign Test^1,2,3,4 and conclude that the RKT stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold RKT stock.

Financial State Forecast for RKT Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B2
Operational Risk	83	32
Market Risk	33	41
Technical Analysis	66	80
Fundamental Analysis	67	62
Risk Unsystematic	71	55

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 523 signals.

References

1. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
2. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
3. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
4. Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
5. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
6. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
7. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511

Frequently Asked Questions

Q: What is the prediction methodology for RKT stock?
A: RKT stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Sign Test
Q: Is RKT stock a buy or sell?
A: The dominant strategy among neural network is to Hold RKT Stock.
Q: Is Rocket Companies stock a good investment?
A: The consensus rating for Rocket Companies is Hold and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of RKT stock?
A: The consensus rating for RKT is Hold.
Q: What is the prediction period for RKT stock?
A: The prediction period for RKT is (n+6 month)

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