LPSN LivePerson Inc. Common Stock

Outlook: LivePerson Inc. Common Stock assigned short-term Ba1 & long-term Ba3 forecasted stock rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 19 Dec 2022 for (n+3 month)
Methodology : Transfer Learning (ML)

Abstract

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks' historical data. Most of these existing approaches have focused on short term prediction using stocks' historical price and technical indicators.(Chen, W., Zhang, H., Mehlawat, M.K. and Jia, L., 2021. Mean–variance portfolio optimization using machine learning-based stock price prediction. Applied Soft Computing, 100, p.106943.) We evaluate LivePerson Inc. Common Stock prediction models with Transfer Learning (ML) and Multiple Regression^1,2,3,4 and conclude that the LPSN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. Stock Rating
2. What is a prediction confidence?
3. Trading Signals

LPSN Target Price Prediction Modeling Methodology

We consider LivePerson Inc. Common Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of LPSN 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(Multiple 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(Transfer Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of LPSN stock

j:Nash equilibria (Neural Network)

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?

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

Sample Set: Neural Network
Stock/Index: LPSN LivePerson Inc. Common Stock
Time series to forecast n: 19 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 (Grey to Black): *Technical Analysis%

Adjusted IFRS* Prediction Methods for LivePerson Inc. Common Stock

1. The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
2. Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
3. Interest Rate Benchmark Reform—Phase 2, which amended IFRS 9, IAS 39, IFRS 7, IFRS 4 and IFRS 16, issued in August 2020, added paragraphs 5.4.5–5.4.9, 6.8.13, Section 6.9 and paragraphs 7.2.43–7.2.46. An entity shall apply these amendments for annual periods beginning on or after 1 January 2021. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
4. If a put option written by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the associated liability is measured at the option exercise price plus the time value of the option. The measurement of the asset at fair value is limited to the lower of the fair value and the option exercise price because the entity has no right to increases in the fair value of the transferred asset above the exercise price of the option. This ensures that the net carrying amount of the asset and the associated liability is the fair value of the put option obligation. For example, if the fair value of the underlying asset is CU120, the option exercise price is CU100 and the time value of the option is CU5, the carrying amount of the associated liability is CU105 (CU100 + CU5) and the carrying amount of the asset is CU100 (in this case the option exercise price).

*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

LivePerson Inc. Common Stock assigned short-term Ba1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Multiple Regression^1,2,3,4 and conclude that the LPSN stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Financial State Forecast for LPSN LivePerson Inc. Common Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba3
Operational Risk	80	74
Market Risk	62	47
Technical Analysis	82	83
Fundamental Analysis	84	49
Risk Unsystematic	42	52

Prediction Confidence Score

Trust metric by Neural Network: 82 out of 100 with 561 signals.

References

1. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
2. G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
3. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
4. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
5. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
6. Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
7. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.

Frequently Asked Questions

Q: What is the prediction methodology for LPSN stock?
A: LPSN stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Multiple Regression
Q: Is LPSN stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes LPSN Stock.
Q: Is LivePerson Inc. Common Stock stock a good investment?
A: The consensus rating for LivePerson Inc. Common Stock is Wait until speculative trend diminishes and assigned short-term Ba1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LPSN stock?
A: The consensus rating for LPSN is Wait until speculative trend diminishes.
Q: What is the prediction period for LPSN stock?
A: The prediction period for LPSN is (n+3 month)

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