INST Stock: The Wild Ride Continues

Jorgenson, Dale W.; Weitzman, Martin L.; ZXhang, Yoshua X; Haxo, Yann M; Mat , Ying X

Outlook: Instructure Holdings Inc. Common Stock is assigned short-term B3 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (News Feed Sentiment Analysis)
Hypothesis Testing : Pearson Correlation
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

Instructure Holdings Inc. Common Stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Pearson Correlation^1,2,3,4 and it is concluded that the INST stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.⁵ According to price forecasts for 1 Year period, the dominant strategy among neural network is: Speculative Trend

Key Points

Modular Neural Network (News Feed Sentiment Analysis) for INST stock price prediction process.
Pearson Correlation
What is a prediction confidence?
Can statistics predict the future?
How do you decide buy or sell a stock?

INST Stock Price Forecast

We consider Instructure Holdings Inc. Common Stock Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of INST 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

Sample Set: Neural Network
Stock/Index: INST Instructure Holdings Inc. Common Stock
Time series to forecast: 1 Year

According to price forecasts, the dominant strategy among neural network is: Speculative Trend

F(Pearson Correlation)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ 1 Year

\vec{S} = (s_{1}, s_{2}, s_{3})

n:Time series to forecast

p:Price signals of INST stock

j:Nash equilibria (Neural Network)

k:Dominated move of INST stock holders

a:Best response for INST target price

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.⁵ Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.^6,7

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INST Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Modular Neural Network (News Feed Sentiment Analysis) based INST Stock Prediction Model

However, in some cases, the time value of money element may be modified (ie imperfect). That would be the case, for example, if a financial asset's interest rate is periodically reset but the frequency of that reset does not match the tenor of the interest rate (for example, the interest rate resets every month to a one-year rate) or if a financial asset's interest rate is periodically reset to an average of particular short- and long-term interest rates. In such cases, an entity must assess the modification to determine whether the contractual cash flows represent solely payments of principal and interest on the principal amount outstanding. In some circumstances, the entity may be able to make that determination by performing a qualitative assessment of the time value of money element whereas, in other circumstances, it may be necessary to perform a quantitative assessment.
An entity shall assess whether contractual cash flows are solely payments of principal and interest on the principal amount outstanding for the currency in which the financial asset is denominated.
To the extent that a transfer of a financial asset does not qualify for derecognition, the transferor's contractual rights or obligations related to the transfer are not accounted for separately as derivatives if recognising both the derivative and either the transferred asset or the liability arising from the transfer would result in recognising the same rights or obligations twice. For example, a call option retained by the transferor may prevent a transfer of financial assets from being accounted for as a sale. In that case, the call option is not separately recognised as a derivative asset.
Adjusting the hedge ratio allows an entity to respond to changes in the relationship between the hedging instrument and the hedged item that arise from their underlyings or risk variables. For example, a hedging relationship in which the hedging instrument and the hedged item have different but related underlyings changes in response to a change in the relationship between those two underlyings (for example, different but related reference indices, rates or prices). Hence, rebalancing allows the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item chang

*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.

INST Instructure Holdings Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B3	B2
Income Statement	C	C
Balance Sheet	Ba3	B2
Leverage Ratios	Caa2	Caa2
Cash Flow	Caa2	Baa2
Rates of Return and Profitability	Baa2	Caa2

*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?

References

Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
P. Marbach. Simulated-Based Methods for Markov Decision Processes. PhD thesis, Massachusetts Institute of Technology, 1998
E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004

Frequently Asked Questions

Q: Is INST stock expected to rise?
A: INST stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Pearson Correlation and it is concluded that dominant strategy for INST stock is Speculative Trend
Q: Is INST stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend INST Stock.
Q: Is Instructure Holdings Inc. Common Stock stock a good investment?
A: The consensus rating for Instructure Holdings Inc. Common Stock is Speculative Trend and is assigned short-term B3 & long-term B2 estimated rating.
Q: What is the consensus rating of INST stock?
A: The consensus rating for INST is Speculative Trend.
Q: What is the forecast for INST stock?
A: INST target price forecast: Speculative Trend

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