TPH Tri Pointe Homes Stock Forecast Outlook:Negative Period (n+7) 14 Feb 2021


Stock Forecast


As of Sat Feb 13 2021 00:00:02 GMT+0000 (Coordinated Universal Time) shares of TPH Tri Pointe Homes -1.72 percentage change in price since the previous day's close. Around 1092100 of 126825000 changed hand on the market. The Stock opened at 21.37 with high and low of 21.09 and 21.59 respectively. The price/earnings ratio is: 9.97 and earning per share is 2.12. The stock quoted a 52 week high and low of 5.89 and 22.17 respectively.

BOSTON (AI Forecast Terminal) Sun, Feb 14, '21 AI Forecast today took the forecast actions: In the context of stock price realization of TPH Tri Pointe Homes is a decision making process between multiple investors each of which controls a subset of design variables and seeks to minimize its cost function subject to future forecast constraints. That is, investors act like players in a game; they cooperate to achieve a set of overall goals.Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from the Neural Network and Support Vector Machines. Machine Learning based technical analysis (n+7) for TPH Tri Pointe Homes as below:
Using machine learning modified The random walk index model RWI equivalent to a model of stock market dynamics with price expectations, we analyze the reaction of investors to speculations. Analyzing those data we were able to establish the amount by which each stock felt the speculative attacks, a dampening factor which expresses the capacity of a market of absorving a shock, and also a frequency related with volatility after the speculation. Using the correlation matrices, the speculative buffer for the shares of TPH Tri Pointe Homes as below:

TPH Tri Pointe Homes Credit Rating Overview


We rerate TPH Tri Pointe Homes because of no indications exist that private equity, management, or shareholders may reduce or prevent the maintenance of capital. We use econometric methods for period (n+7) simulate with Sustainability Stepwise Regression. Reference code is: 2474. Beta DRL value REG 30 Rational Demand Factor LD 6186.0834. When evaluating uses of liquidity, we include all debt maturities over the liquidity horizon that are either recourse to the company, or nonrecourse that we believe the company will support even in times of stress. In cases where the debt includes a put option held by debtholders, we will consider the date of the put option the effective debt maturity--i.e., we will assume the debt will need to be repaid/refinanced on the day the put can be first exercised. Credit Rating AI Process rely on primary sources of information: Sec Filings, Financial Statements, Credit Ratings, Semantic Signals. Take a look at Machine Learning section for Financial Deep Reinforcement Learning.

Oscillators are used for generating credit risk signals by using the semantic and financial signals. The value of the oscillators indicate the strength of trend. Using the correlation matrices, the risk map for TPH Tri Pointe Homes as below:
Frequently Asked QuestionsQ: What is TPH Tri Pointe Homes stock symbol?
A: TPH Tri Pointe Homes stock referred as NYSE:TPH
Q: What is TPH Tri Pointe Homes stock price?
A: On share of TPH Tri Pointe Homes stock can currently be purchased for approximately 21.19
Q: Do analysts recommend investors buy shares of TPH Tri Pointe Homes ?
A: Machine Learning utilizes multiple learning algorithms to obtain better predictive powers. In our research, we utilize machine learning to combine the results from the Neural Network and Support Vector Machines. View Machine Learning based technical analysis for TPH Tri Pointe Homes at daily forecast section
Q: What is the earning per share of TPH Tri Pointe Homes ?
A: The earning per share of TPH Tri Pointe Homes is 2.12
Q: What is the market capitalization of TPH Tri Pointe Homes ?
A: The market capitalization of TPH Tri Pointe Homes is 2687421817
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Disclaimers: AC Investment Inc. currently does not act as an equities executing broker, credit rating agency or route orders containing equities securities. In our Machine Learning experiment, we focus on an approach known as Decision making using game theory. We apply principles from game theory to model the relationships between rating actions, news, market signals and decision making.The rating information provided is for informational, non-commercial purposes only, does not constitute investment advice and is subject to conditions available in our Legal Disclaimer. Usage as a credit rating or as a benchmark is not permitted.

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