Outlook: TuSimple Holdings Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Time series to forecast n: 26 Feb 2023 for (n+16 weeks)
Methodology : Supervised Machine Learning (ML)

## Abstract

TuSimple Holdings Inc. Class A Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Beta1,2,3,4 and it is concluded that the TSP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

## Key Points

1. Stock Forecast Based On a Predictive Algorithm
2. What are main components of Markov decision process?

## TSP Target Price Prediction Modeling Methodology

We consider TuSimple Holdings Inc. Class A Common Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of TSP 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(Beta)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Supervised Machine Learning (ML)) X S(n):→ (n+16 weeks) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of TSP 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?

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

Sample Set: Neural Network
Stock/Index: TSP TuSimple Holdings Inc. Class A Common Stock
Time series to forecast n: 26 Feb 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

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%

## IFRS Reconciliation Adjustments for TuSimple Holdings Inc. Class A Common Stock

1. The requirements in paragraphs 6.8.4–6.8.8 may cease to apply at different times. Therefore, in applying paragraph 6.9.1, an entity may be required to amend the formal designation of its hedging relationships at different times, or may be required to amend the formal designation of a hedging relationship more than once. When, and only when, such a change is made to the hedge designation, an entity shall apply paragraphs 6.9.7–6.9.12 as applicable. An entity also shall apply paragraph 6.5.8 (for a fair value hedge) or paragraph 6.5.11 (for a cash flow hedge) to account for any changes in the fair value of the hedged item or the hedging instrument.
2. If any instrument in the pool does not meet the conditions in either paragraph B4.1.23 or paragraph B4.1.24, the condition in paragraph B4.1.21(b) is not met. In performing this assessment, a detailed instrument-byinstrument analysis of the pool may not be necessary. However, an entity must use judgement and perform sufficient analysis to determine whether the instruments in the pool meet the conditions in paragraphs B4.1.23–B4.1.24. (See also paragraph B4.1.18 for guidance on contractual cash flow characteristics that have only a de minimis effect.)
3. If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.
4. If there is a hedging relationship between a non-derivative monetary asset and a non-derivative monetary liability, changes in the foreign currency component of those financial instruments are presented in profit or loss.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

## Conclusions

TuSimple Holdings Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. TuSimple Holdings Inc. Class A Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Beta1,2,3,4 and it is concluded that the TSP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

### TSP TuSimple Holdings Inc. Class A Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2B2
Balance SheetBaa2Baa2
Leverage RatiosCCaa2
Cash FlowBa2B3
Rates of Return and ProfitabilityBa3Baa2

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

### Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 545 signals.

## References

1. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Trading Signals (WTS Stock Forecast). AC Investment Research Journal, 101(3).
3. Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
4. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
5. Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
6. M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
7. Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.
Frequently Asked QuestionsQ: What is the prediction methodology for TSP stock?
A: TSP stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Beta
Q: Is TSP stock a buy or sell?
A: The dominant strategy among neural network is to Buy TSP Stock.
Q: Is TuSimple Holdings Inc. Class A Common Stock stock a good investment?
A: The consensus rating for TuSimple Holdings Inc. Class A Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of TSP stock?
A: The consensus rating for TSP is Buy.
Q: What is the prediction period for TSP stock?
A: The prediction period for TSP is (n+16 weeks)