LSEG Starmine Smart Holdings and Credit Risk Models

Author

Reads 810

Colleagues collaborating on financial charts and graphs using mobile and paper documents in the office.
Credit: pexels.com, Colleagues collaborating on financial charts and graphs using mobile and paper documents in the office.

LSEG Starmine Smart Holdings and Credit Risk Models are designed to provide investors with a more accurate picture of a company's financial health. This is achieved through the use of advanced data analytics and machine learning algorithms.

These models can identify potential credit risks by analyzing a company's financial statements and other publicly available data. By doing so, investors can make more informed decisions about their investments.

One key feature of LSEG Starmine is its ability to estimate a company's credit rating, which can be a valuable tool for investors looking to assess a company's creditworthiness. This estimate is based on a combination of financial and non-financial factors.

LSEG Starmine's credit risk models are highly regarded for their accuracy and reliability, with many investors relying on them to inform their investment decisions.

Data Analysis

StarMine Analytics is a powerful tool that helps you make more accurate decisions.

It's based on SmartEstimates, which are weighted towards top analysts' recent forecasts to anticipate directionally correct earnings surprises.

Graph and Line Chart Printed Paper
Credit: pexels.com, Graph and Line Chart Printed Paper

Revenue SmartEstimates deliver a 78% directionally correct surprise accuracy figure, giving you a reliable edge in your decision-making.

SmartEconomics outperform a simple consensus forecast for macroeconomic data accuracy, providing you with more precise insights.

By using StarMine Analytics, you can tap into the collective knowledge of top analysts and make more informed decisions.

Smart Holdings Overview

The StarMine Smart Holdings Model is a game-changer for investors. It's a global stock selection model that ranks stocks based on the expected future increase or decrease in institutional ownership.

By leveraging the actions of financial institutions, short sellers, and corporate insiders, the Smart Holdings Model provides insights into the collective appeal or demand for a stock relative to all other stocks by region. This is done by reverse engineering each fund's purchasing profile based on fundamental factors such as price/earnings and debt/equity ratios.

The model uses 25 common quant factors to generate screening profiles for each fund, and the final component combination provides a low volatility signal that produces attractive risk-adjusted returns with minimal draw-downs and is relatively uncorrelated with common factors.

Credit: youtube.com, Supercharge with Workspace: StarMine Earnings and Predicted surprise

Here are some key benefits of the Smart Holdings Model:

  • Smart Holdings is a predictive model that accurately predicts which stocks will see an increase or decrease in institutional ownership.
  • A long/short trading strategy based on Smart Holdings ranking produces high Sharpe ratios and annual returns.
  • Smart Holdings model uses 25 common quant factors to generate screening profiles for each fund.
  • The final component combination provides a low volatility signal that produces attractive risk-adjusted returns with minimal draw-downs and is relatively uncorrelated with common factors.

Structural Credit Risk

Structural Credit Risk is a key aspect of StarMine's offerings, and it's essential to understand how it works. StarMine's Structural Credit Risk Model (SCR) evaluates the equity market's view of credit risk. This model is based on Robert Merton's structural default prediction framework, which models a company's equity as a call option on its assets.

The SCR model is more accurate at predicting defaults than the Altman Z-score or a basic Merton model. This is due to StarMine's proprietary extension of the structural default prediction framework, which incorporates the Value-Momentum model in the drift rate formulation. By leveraging this expertise, StarMine has improved the traditional framework.

One of the key benefits of the SCR model is its ability to assess the equity market's view of credit risk. This is achieved by mapping default probabilities to letter ratings and ranking them to create 1-100 percentile scores. This provides a more comprehensive understanding of credit risk.

Credit: youtube.com, Starmine - the combined alpha model

The SCR model also eliminates erroneous outputs inherent to most structural model frameworks that solve simultaneous non-linear equations numerically. This is achieved through a closed-form solution for the model equations. By using this approach, StarMine has optimized the formulations for default point and volatility.

Here are some key features of the SCR model:

  • The SCR model is considerably more accurate at predicting defaults than the Altman Z-score or a basic Merton model.
  • Assesses equity market's view of credit risk.
  • SCR probability of default equates to the probability that the option expires worthless.

Analyst Insights

The StarMine Awards recognize the most accurate forecasters in Reuters polls, and the winners are announced in February of the following year.

These awards are based on the historical accuracy of each contributor's forecasts, assessed by the StarMine SmartEconomics model.

The model evaluates the accuracy of each contributor at every point in time on every poll in which they provided a forecast.

Media Sentiment

The StarMine MarketPsych Media Sentiment Model can help predict the following month's relative share price returns of U.S.-listed stocks. This is an equity returns model based on news and social media sentiment and complements fundamental models.

Credit: youtube.com, FameSense Full Demo: Master Social Media Sentiment Analytics with AI

The Media Sentiment Model uses news and social media sentiment to make predictions, which can be a valuable tool for investors looking to make informed decisions.

This model complements fundamental models, which focus on a company's financial statements and other quantitative data, by considering the emotional tone of news and social media.

The Media Sentiment Model is an equity returns model, meaning it's specifically designed to predict stock price movements.

You might like: Lseg News

Overview of Analyst Revisions

Analyst revisions are a key indicator of a stock's potential price movement, and understanding how they work can give you a competitive edge in the market.

The StarMine Analyst Revisions Model (ARM) is a security-ranking model that looks at revisions to sell-side analysts' estimates of earnings, revenue, and EBITDA, as well as changes in buy/hold/sell recommendations.

ARM is a percentile ranking of stocks based on changes in analyst sentiment, with 100 representing the highest rank. It's highly predictive of relative price movement.

Credit: youtube.com, Analyst Insight: Morgan Stanley Expects Significant, Upward Revisions For CSX Corp

The model incorporates more accurate earnings estimates through StarMine's proprietary SmartEstimate earnings prediction service. This means you can trust the data to make informed investment decisions.

ARM improves upon basic EPS-only revision models by incorporating proprietary inputs and a unique blend of several factors. This makes it a more comprehensive tool for analyzing analyst revisions.

Here are some key benefits of using ARM:

  • ARM intelligently blends both EPS and non-EPS factors and leverage StarMine’s SmartEstimates and Predicted Surprises.
  • ARM uses a dynamic weighting scheme that is driven by company profitability and relative analyst coverage.
  • ARM incorporates changes in buy/sell recommendations and looks at revisions over multiple time horizons.
  • Our research has shown that past revisions are highly predictive of future revisions, which in turn are highly correlated to stock price movements.

By understanding how analyst revisions work and using tools like ARM, you can gain valuable insights into a stock's potential performance. This can help you make more informed investment decisions and stay ahead of the market.

Smart Money

Smart Money is a powerful tool that helps predict stock price changes by analyzing the actions of financial institutions, short sellers, and corporate insiders. It's like having a crystal ball to anticipate market movements!

The StarMine Smart Money model incorporates insights from various sources, including institutions, short sellers, and corporate insiders. This comprehensive approach provides a complete picture of market sentiment.

Credit: youtube.com, Forecast relative share returns with Refinitiv StarMine MarketPsych Media Sentiment Model

The model includes the StarMine Insider Filings, which analyzes the buying and selling activities of corporate insiders. This information can be a strong indicator of a company's future performance.

The StarMine Smart Holdings Model (SH) is a global stock selection model that ranks stocks based on expected future increase or decrease in institutional ownership. It's a sophisticated algorithm that reverse engineers each fund's purchasing profile.

The model looks at fundamental factors such as price/earnings and debt/equity ratios to determine the alignment between a stock and a fund's purchasing profile. This helps identify stocks with high demand and potential for growth.

By aggregating the results across all funds, the model ranks each stock based on its collective appeal or demand relative to other stocks by region. This provides a clear picture of market trends and opportunities.

Frequently Asked Questions

What does LSEG actually do?

LSEG provides critical infrastructure and data to the global financial markets, serving customers across the entire value chain. From trading to data analytics, LSEG enables seamless financial transactions and insights.

What is StarMine?

StarMine is a tool that evaluates analyst performance by tracking their stock recommendations and simulating a portfolio based on their picks. It helps identify top-performing analysts and their industry expertise through its Industry Excess Return metric.

Tommy Weber

Lead Assigning Editor

Tommy Weber is a seasoned Assigning Editor with a keen eye for detail and a passion for storytelling. With extensive experience in assigning articles across various categories, Tommy has honed his skills in identifying and selecting compelling topics that resonate with readers. Tommy's expertise lies in assigning articles related to personal finance, specifically in the areas of bank card credit and bank credit cards.

Love What You Read? Stay Updated!

Join our community for insights, tips, and more.