Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person's interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI). We evaluate DSW CAPITAL PLC prediction models with Deductive Inference (ML) and Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:DSW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Sell LON:DSW stock.
Keywords: LON:DSW, DSW CAPITAL PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Market Signals
- Can stock prices be predicted?
- Is now good time to invest?
LON:DSW Target Price Prediction Modeling Methodology
The stock market is one of the key sectors of a country's economy. It provides investors with an opportunity to invest and gain returns on their investment. Predicting the stock market is a very challenging task and has attracted serious interest from researchers from many fields such as statistics, artificial intelligence, economics, and finance. An accurate prediction of the stock market reduces investment risk in the market. Different approaches have been used to predict the stock market. The performances of Machine learning (ML) models are typically superior to those of statistical and econometric models. We consider DSW CAPITAL PLC Stock Decision Process with Statistical Hypothesis Testing where A is the set of discrete actions of LON:DSW 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(Statistical Hypothesis Testing)5,6,7= X R(Deductive Inference (ML)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of LON:DSW stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
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How do AC Investment Research machine learning (predictive) algorithms actually work?
LON:DSW Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: LON:DSW DSW CAPITAL PLC
Time series to forecast n: 22 Sep 2022 for (n+16 weeks)
According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Sell LON:DSW 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
DSW CAPITAL PLC assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:DSW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Sell LON:DSW stock.
Financial State Forecast for LON:DSW Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | Ba3 | B2 |
| Operational Risk | 51 | 67 |
| Market Risk | 68 | 69 |
| Technical Analysis | 47 | 58 |
| Fundamental Analysis | 76 | 33 |
| Risk Unsystematic | 73 | 43 |
Prediction Confidence Score
References
- Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
- A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
- Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
- E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
- Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
- Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
Frequently Asked Questions
Q: What is the prediction methodology for LON:DSW stock?A: LON:DSW stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Statistical Hypothesis Testing
Q: Is LON:DSW stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:DSW Stock.
Q: Is DSW CAPITAL PLC stock a good investment?
A: The consensus rating for DSW CAPITAL PLC is Sell and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:DSW stock?
A: The consensus rating for LON:DSW is Sell.
Q: What is the prediction period for LON:DSW stock?
A: The prediction period for LON:DSW is (n+16 weeks)
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