Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN).** We evaluate Lincoln Financial prediction models with Inductive Learning (ML) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the LNC 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 LNC stock.**

**LNC, Lincoln Financial, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What is neural prediction?
- What are main components of Markov decision process?
- What are main components of Markov decision process?

## LNC Target Price Prediction Modeling Methodology

In today's economy, there is a profound impact of the stock market or equity market. Prediction of stock prices is extremely complex, chaotic, and the presence of a dynamic environment makes it a great challenge. Behavioural finance suggests that decision-making process of investors is to a very great extent influenced by the emotions and sentiments in response to a particular news. Thus, to support the decisions of the investors, we have presented an approach combining two distinct fields for analysis of stock exchange. We consider Lincoln Financial Stock Decision Process with Wilcoxon Sign-Rank Test where A is the set of discrete actions of LNC 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 Î³ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Wilcoxon Sign-Rank Test)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Inductive Learning (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^{n}\left({s}_{i}\right)$

n:Time series to forecast

p:Price signals of LNC 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?

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

**Sample Set:**Neural Network

**Stock/Index:**LNC Lincoln Financial

**Time series to forecast n: 14 Oct 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Sell LNC 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

Lincoln Financial assigned short-term B1 & long-term Baa2 forecasted stock rating.** We evaluate the prediction models Inductive Learning (ML) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the LNC 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 LNC stock.**

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

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B1 | Baa2 |

Operational Risk | 49 | 86 |

Market Risk | 66 | 83 |

Technical Analysis | 85 | 69 |

Fundamental Analysis | 58 | 85 |

Risk Unsystematic | 39 | 48 |

### Prediction Confidence Score

## References

- Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
- J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
- Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
- Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
- V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.
- LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221

## Frequently Asked Questions

Q: What is the prediction methodology for LNC stock?A: LNC stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Wilcoxon Sign-Rank Test

Q: Is LNC stock a buy or sell?

A: The dominant strategy among neural network is to Sell LNC Stock.

Q: Is Lincoln Financial stock a good investment?

A: The consensus rating for Lincoln Financial is Sell and assigned short-term B1 & long-term Baa2 forecasted stock rating.

Q: What is the consensus rating of LNC stock?

A: The consensus rating for LNC is Sell.

Q: What is the prediction period for LNC stock?

A: The prediction period for LNC is (n+16 weeks)