MMC Target Price Forecast

Social media comments have in the past had an instantaneous effect on stock markets. This paper investigates the sentiments expressed on the social media platform Twitter and their pr edictive impact on the Stock Market. We evaluate Marsh McLennan prediction models with Multi-Instance Learning (ML) and ElasticNet Regression^1,2,3,4 and conclude that the MMC stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold MMC stock.

Keywords: MMC, Marsh McLennan, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

1. Understanding Buy, Sell, and Hold Ratings
2. What is prediction model?
3. Operational Risk

MMC Target Price Prediction Modeling Methodology

The search for models to predict the prices of financial markets is still a highly researched topic, despite major related challenges. The prices of financial assets are non-linear, dynamic, and chaotic; thus, they are financial time series that are difficult to predict. Among the latest techniques, machine learning models are some of the most researched, given their capabilities for recognizing complex patterns in various applications. We consider Marsh McLennan Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of MMC 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(ElasticNet 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(Multi-Instance Learning (ML)) X S(n):→ (n+3 month) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of MMC 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?

MMC Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: MMC Marsh McLennan
Time series to forecast n: 12 Sep 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold MMC 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

Marsh McLennan assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Multi-Instance Learning (ML) with ElasticNet Regression^1,2,3,4 and conclude that the MMC stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold MMC stock.

Financial State Forecast for MMC Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B1
Operational Risk	86	59
Market Risk	60	46
Technical Analysis	31	37
Fundamental Analysis	68	75
Risk Unsystematic	44	73

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 624 signals.

References

1. Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
2. V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
3. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
4. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
5. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
6. Abadie A, Imbens GW. 2011. Bias-corrected matching estimators for average treatment effects. J. Bus. Econ. Stat. 29:1–11
7. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.

Frequently Asked Questions

Q: What is the prediction methodology for MMC stock?
A: MMC stock prediction methodology: We evaluate the prediction models Multi-Instance Learning (ML) and ElasticNet Regression
Q: Is MMC stock a buy or sell?
A: The dominant strategy among neural network is to Hold MMC Stock.
Q: Is Marsh McLennan stock a good investment?
A: The consensus rating for Marsh McLennan is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of MMC stock?
A: The consensus rating for MMC is Hold.
Q: What is the prediction period for MMC stock?
A: The prediction period for MMC is (n+3 month)

Premium

• Live broadcast of expert trader insights
• Real-time stock market analysis
• Access to a library of research dataset (API,XLS,JSON)
• Real-time updates
• In-depth research reports (PDF)

Login