Stock prediction with data mining techniques is one of the most important issues in finance being investigated by researchers across the globe. Data mining techniques can be used extensively in the financial markets to help investors make qualitative decision. One of the techniques is artificial neural network (ANN). However, in the application of ANN for predicting the financial market the use of technical analysis variables for stock prediction is predominant. In this paper, we present a hybridized approach which combines the use of the variables of technical and fundamental analysis of stock market indicators for prediction of future price of stock in order to improve on the existing approaches. We evaluate QuidelOrtho prediction models with Statistical Inference (ML) and Paired T-Test1,2,3,4 and conclude that the QDEL stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold QDEL stock.
Keywords: QDEL, QuidelOrtho, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Can machine learning predict?
- Stock Rating
- What are main components of Markov decision process?
QDEL Target Price Prediction Modeling Methodology
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 consider QuidelOrtho Stock Decision Process with Paired T-Test where A is the set of discrete actions of QDEL 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(Paired T-Test)5,6,7= X R(Statistical Inference (ML)) X S(n):→ (n+4 weeks)
n:Time series to forecast
p:Price signals of QDEL stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
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QDEL Stock Forecast (Buy or Sell) for (n+4 weeks)
Sample Set: Neural NetworkStock/Index: QDEL QuidelOrtho
Time series to forecast n: 25 Oct 2022 for (n+4 weeks)
According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold QDEL 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
QuidelOrtho assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Paired T-Test1,2,3,4 and conclude that the QDEL stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold QDEL stock.
Financial State Forecast for QDEL Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B2 | B1 |
| Operational Risk | 49 | 68 |
| Market Risk | 78 | 74 |
| Technical Analysis | 30 | 56 |
| Fundamental Analysis | 35 | 67 |
| Risk Unsystematic | 78 | 31 |
Prediction Confidence Score
References
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- 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
- Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
- A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
- Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
- V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
- Firth JR. 1957. A synopsis of linguistic theory 1930–1955. In Studies in Linguistic Analysis (Special Volume of the Philological Society), ed. JR Firth, pp. 1–32. Oxford, UK: Blackwell
Frequently Asked Questions
Q: What is the prediction methodology for QDEL stock?A: QDEL stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Paired T-Test
Q: Is QDEL stock a buy or sell?
A: The dominant strategy among neural network is to Hold QDEL Stock.
Q: Is QuidelOrtho stock a good investment?
A: The consensus rating for QuidelOrtho is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of QDEL stock?
A: The consensus rating for QDEL is Hold.
Q: What is the prediction period for QDEL stock?
A: The prediction period for QDEL is (n+4 weeks)
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