Short/Long Term Stocks: SWK Stock Forecast

Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. We evaluate Stanley Black & Decker prediction models with Transductive Learning (ML) and Stepwise Regression^1,2,3,4 and conclude that the SWK 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 Hold SWK stock.

Keywords: SWK, Stanley Black & Decker, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. How do predictive algorithms actually work?
2. What is a prediction confidence?
3. Trust metric by Neural Network

SWK 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 Stanley Black & Decker Stock Decision Process with Stepwise Regression where A is the set of discrete actions of SWK 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(Stepwise Regression)^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(Transductive Learning (ML)) X S(n):→ (n+16 weeks) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of SWK 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?

SWK Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: SWK Stanley Black & Decker
Time series to forecast n: 03 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold SWK 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%

Adjusted IFRS* Prediction Methods for Stanley Black & Decker

1. The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
2. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.
3. For the avoidance of doubt, the effects of replacing the original counterparty with a clearing counterparty and making the associated changes as described in paragraph 6.5.6 shall be reflected in the measurement of the hedging instrument and therefore in the assessment of hedge effectiveness and the measurement of hedge effectiveness
4. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Stanley Black & Decker assigned short-term Baa2 & long-term B3 forecasted stock rating. We evaluate the prediction models Transductive Learning (ML) with Stepwise Regression^1,2,3,4 and conclude that the SWK 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 Hold SWK stock.

Financial State Forecast for SWK Stanley Black & Decker Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Baa2	B3
Operational Risk	59	33
Market Risk	84	38
Technical Analysis	84	56
Fundamental Analysis	90	41
Risk Unsystematic	79	48

Prediction Confidence Score

Trust metric by Neural Network: 88 out of 100 with 470 signals.

References

1. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
2. Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
3. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
4. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
5. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
6. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
7. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60

Frequently Asked Questions

Q: What is the prediction methodology for SWK stock?
A: SWK stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Stepwise Regression
Q: Is SWK stock a buy or sell?
A: The dominant strategy among neural network is to Hold SWK Stock.
Q: Is Stanley Black & Decker stock a good investment?
A: The consensus rating for Stanley Black & Decker is Hold and assigned short-term Baa2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of SWK stock?
A: The consensus rating for SWK is Hold.
Q: What is the prediction period for SWK stock?
A: The prediction period for SWK is (n+16 weeks)

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