Image: MichaelGoodin (Flickr)

Fannie Mae’s Latest Survey Highlights Pessimism in the Real Estate Market

 

Good time to buy? Good time to sell? Unlike the stock or even bond market, the real estate market can’t always be avoided. None of us “need” an investment account, but we all could use shelter from the rain and a safe place to sleep. Having said that, all markets are related. When the values of homes go up, households feel wealthier and more confident in their spending. This drives economic growth and stock valuations. When valuations go down, people are less likely to make improvements and have less equity to borrow from for purchases. So real estate is an important market for stock market investors to pay attention to.

The Federal National Mortgage Association, Fannie Mae (FNMA) just released two survey results on housing optimism/pessimism that are of value to anyone who has investments. The surveys measure attitudes and expectations. The results highlight the highest reading ever recorded in a couple of categories.

The surveys are the National Housing Survey and the Home Purchaser Sentiment Survey Index.

 

What Fannie Mae’s National Housing Survey Tells Us

Consumer attitudes are measured in the NHS through a telephone poll of approximately 1,000 households to assess their attitudes toward owning and renting a home, home and rental price changes, homeownership distress, the economy, household finances, and overall consumer confidence. Homeowners and renters are asked more than 100 questions designed to track attitude changes

The most recent survey answers were collected between March 1 and March 24, 2022.

 

What Fannie Mae’s Home Purchase Sentiment Index Tells Us

The HPSI creates a single number using information about consumers’ home purchase sentiment from Fannie Mae’s National Housing Survey which it weights. The number reflects consumers’ current views and forward-looking expectations of housing market conditions. It is distilled from six questions that answer consumers’ overall thoughts on, do they think that it is a good or bad time to buy or sell a house, what direction they expect home prices and mortgage interest rates to move, how concerned they are about losing their jobs, and whether their incomes are higher than they were a year earlier.

What Fannie Mae Learned

69% of respondents expect mortgage rates to go up in the next 12 months

The Home Purchase Sentiment Index decreased by 2.1 points to 73.2 in March, as consumers continue to be pessimistic regarding the direction of mortgage rates and the homebuying climate. Overall, four of the index’s six components decreased month over month, including the components asking consumers whether they expect mortgage rates to go up and whether they believe it’s a good time to buy a home. On the whole, the “Good Time to Buy” component set a new survey low, with 73% of respondents reporting that it’s a bad time to buy a home.

Year over year, the HPSI index is down 8.5 points.

 Only 24% of consumers believe it’s a good time to buy a home, with similar levels of pessimism expressed by nearly all of the demographic groups surveyed.

In March the survey also broke a new high of consumers expecting their financial situations to worsen over the next year; this was especially true among current homeowners. These concerns, together with the run-up in mortgage rates since the end of 2021, will likely lower mortgage demand from move-up buyers – and fewer move-up buyers mean fewer available entry-level homes. This adds to the rising-rate hurdles for potential first-time homebuyers. If consumer pessimism toward homebuying conditions continues and the recent mortgage rate increases are sustained, then there can be an accelerated cooling of the housing market.

Granular Details

Good/Bad Time to Buy: The percentage of those surveyed who said it’s a good time to buy a home decreased from 29% to 24%, while the percentage who said it is a bad time to buy increased from 67% to 73%. As a result, the net of those who say it is a good time to buy decreased 11 percentage points month over month.

Good/Bad Time to Sell: The percentage of respondents who say it is a good time to sell a home increased from 72% to 74%, while the percentage who say it’s a bad time to sell decreased from 22% to 21%. As a result, the net share of those who say it is a good time to sell increased 3 percentage points month over month.

Home Price Expectations: The percentage of respondents who say home prices will go up in the next 12 months increased from 46% to 48%, while the percentage who say home prices will go down increased from 16% to 20%. The share who think home prices will stay the same decreased from 32% to 28%. As a result, the net share of Americans who say home prices will go up decreased 2 percentage points month over month.

Mortgage Rate Expectations: The percentage of respondents who say mortgage rates will go down in the next 12 months increased from 3% to 4%, while the percentage who expect mortgage rates to go up increased from 67% to 69%. The share who think mortgage rates will stay the same increased from 22% to 23%. As a result, the net share of Americans who say mortgage rates will go down over the next 12 months decreased 1 percentage point month over month.

Job Concerns: The percentage of respondents who say they are not concerned about losing their job in the next 12 months decreased from 87% to 86%, while the percentage who say they are concerned increased from 9% to 11%. As a result, the net share of Americans who say they are not concerned about losing their job decreased 3 percentage points month over month.

Household Income: The percentage of respondents who say their household income is significantly higher than it was 12 months ago increased from 27% to 29%, while the percentage who say their household income is significantly lower increased from 12% to 13%. The percentage who say their household income is about the same decreased from 56% to 53%. As a result, the net share of those who say their household income is significantly higher than it was 12 months ago increased 1 percentage point month over month.

Take-Away

Economic activity impacts stock prices. Stock prices impact households’ views on their wealth and whether they should open their pocketbooks and stimulate the economy or retrench. Consumers’ views on their home values or ability to buy or rent impact spending patterns and economic activity as well. Real Estate investors are right to watch the bond market for clues related to interest rates that impact mortgage lending. For the same reason, stock market investors should keep aware of what is going on in both the fixed income sector and housing market.

 

Paul Hoffman

Managing Editor, Channelchek

 

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Sources

https://www.fanniemae.com/media/43251/display

 

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Twitter Gets a New Board Member Who Instantly Causes Stock to Rocket

 

Elon Musk, known to be one of the most innovative CEOs of this generation, has been causing the SEC to become more innovative just to keep him from violating
disclosure rules and other regulations. Some of his more public SEC problems are with what he
posts on Twitter as the CEO of Tesla. On Monday, he filed the wrong regulatory paperwork, and filed it late. The report disclosed a huge stake in Twitter. On Tuesday, he refiled.

 

Background

On Monday (March 4), Elon Musk disclosed that he bought a 9.2% stake in the social media platform Twitter. This made him the company’s largest shareholder and set off a rally in its shares of more than 27%. US securities law requires that within ten days of acquiring 5% or more of a company, a report must be filed reporting the event. The filing said that March 14, 2022, is the date of the event that required the disclosure. Under this timeline, March 24 would have been the day the ownership report should have been filed. The penalty for this is determined per violation and could amount to $207,183, according to Urska Velikonja, a law professor at Georgetown University Law Center.

Based on the 27% increase in Twitter’s stock price, on $3 billion invested, the civil penalty wouldn’t be felt at all. But there is concern the SEC could look into market manipulation allegations regarding the Twitter stock purchase, and seek harsher sanctions in a previous and ongoing SEC problem regarding a sale he made in Tesla (TSLA) stock to raise money to pay
$11 billion in taxes.

Edit Button on SEC Reports

Do-over. Elon Musk has taken the step to refile his disclosure, placing himself in the category of an active investor. The old filing (form 13G classified him as a passive investor). The new disclosure (form 13D) categorizes Musk as an active investor. It shows he had been acquiring Twitter shares almost daily between January 31 and April 1. The price range was $32.80 to $40.30. Twitter closed Tuesday at $50.98.

Board Seat

Elon Musk has been involved in such diverse companies as Paypal (PYPL), SpaceX, Tesla (TSLA), The Boring Company, and even the Dogecoin
Foundation. No doubt, he recognizes the power of social media or micro-blogging. He is also, in his own words a, “free speech absolutist.” So, for Musk to be in the position of being the largest shareholder and have a seat in the boardroom as the company decides the best road to take for its shareholders, is considered a positive for Twitter. The company has lost significant share price this year as users have become disheartened with management’s policies regarding Tweet rules and behind the scene elevation of some discussions over others.

Take-Away

On March 25, Musk tweeted a poll: “Free speech is essential to a functioning democracy. Do you believe Twitter rigorously adheres to this principle?” The next day he Tweeted he was giving “serious thought” to building a new social media platform.  This week he moved in that direction.

His public concern is that Twitter is not an open forum. The serial entrepreneur is likely to put his mark on the company as a board member and as a significant shareholder. Investors have reacted positively to the news.

 

Suggested Reading

Elon Reminds Jeff Bezos that He’s Pulling Away

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Sources

https://www.nasdaq.com/articles/analysis-teslas-musk-may-add-to-sec-ire-with-late-report-about-twitter-stake

www.finance.yahoo.com/news/musk-refiles-disclosure-show-221958940.html

 

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Tuesday, April 05, 2022

CoreCivic, Inc. (CXW)
What Can End of Title 42 Mean?

CoreCivic is a diversified government solutions company with the scale and experience needed to solve tough government challenges in flexible, cost-effective ways. We provide a broad range of solutions to government partners that serve the public good through corrections and detention management, a growing network of residential reentry centers to help address America’s recidivism crisis, and government real estate solutions. We are a publicly traded real estate investment trust and the nation’s largest owner of partnership correctional, detention and residential reentry facilities. We also believe we are the largest private owner of real estate used by U.S. government agencies. The Company has been a flexible and dependable partner for government for more than 35 years. Our employees are driven by a deep sense of service, high standards of professionalism and a responsibility to help government better the public good.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Title 42 to End? The Biden Administration has stated the enforcement of Title 42 to expel immigrants will end May 23rd. First authorized in March 2020 during the COVID crisis, Title 42 continued to be enforced by the Biden Administration over the past year as a key tool to stop the spread of the virus in border facilities, but with the decline in COVID cases, the Administration will end the use of Title 42.

Poised for a Surge? In the first five months of the government fiscal year, monthly Southwest border encounters are averaging nearly 170,000 and are on pace to top two million for the year.  Some reports suggest the number of people crossing once the restriction is lifted could triple to 18,000 per day, or more than double the current monthly encounter amount …

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

 

Tuesday, April 05, 2022

The GEO Group, Inc. (GEO)
What Can End of Title 42 Mean?

With over 94,000 beds owned, leased or managed across its business lines and serving over 260,000 people daily, GEO is a leading provider of mission critical real estate to its governmental partners. The Company is the first fully integrated equity REIT specializing in the design, financing, development, and operation of secure facilities, processing centers, and community reentry centers in the U.S., Australia, South Africa, and the U.K.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Title 42 to End? The Biden Administration has stated the enforcement of Title 42 to expel immigrants will end May 23rd. First authorized in March 2020 during the COVID crisis, Title 42 continued to be enforced by the Biden Administration over the past year as a key tool to stop the spread of the virus in border facilities, but with the decline in COVID cases, the Administration will end the use of Title 42.

Poised for a Surge? In the first five months of the government fiscal year, monthly Southwest border encounters are averaging nearly 170,000 and are on pace to top two million for the year.  Some reports suggest the number of people crossing once the restriction is lifted could triple to 18,000 per day, or more than double the current monthly encounter amount …

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

 

From the Blackhawks to the Biotech Industry, Daniel Carcillo Is On A Mission

The 18th annual conference will be “live” again! To celebrate the return to IN PERSON, thanks to our sponsors, investor registration is FREE

 

After seven recorded concussions as a result of his nine-year NHL career, Daniel Carcillo was left sleepless, plagued with migraines and at times suicidal. For years after leaving the ice, Carcillo relentlessly looked for solutions. For him and the millions who suffer from post-concussion syndrome, TBI and other mental health issues. In addition to creating a non-profit organization that assists former NHL-players with problems like his, Carcillo is the founder and CEO of Wesana Health, a life sciences company that leverages psilocybin-based medicine to treat traumatic brain injuries. Wesana recently announced that the FDA granted the Company’s request for a pre-IND (Investigational New Drug) meeting to discuss the novel therapy and proprietary protocol of SANA-013 for the treatment of Traumatic Brain Injury (TBI) related major depressive disorder (MDD). Wesana is in the lineup of companies presenting at NobleCon18, and you can hear Daniel’s story as a panelist on the “Psychedelics: The Next Breakthrough in Mental Health Treatment?” Panel (Thursday, April 21, 8:00am). ADMISSION IS FREE for institutional to self-directed novice investors, thanks to Noble, Channelchek, Sponsors and The Presenting Companies. Attendance is limited to 1,000. NobleCon18 – Noble Capital Markets 18th Annual Small and Microcap Investor Conference – April 19-21, 2022 – Hard Rock, Hollywood, FL 100 Public Company Presentations | Scheduled Breakouts | Panel Presentations | High-Profile Keynotes | Educational Sessions | Receptions & Networking Events REGISTER FREE AS AN INVESTOR  |  PRESENTING COMPANY INQUIRIES  |  NOBLECON INFO PAGE  |  NOBLECON18.COM  |  PRESENTING COMPANIES  |  SCHEDULED SPEAKERS

Tuesday, April 05, 2022

The GEO Group, Inc. (GEO)
What Can End of Title 42 Mean?

With over 94,000 beds owned, leased or managed across its business lines and serving over 260,000 people daily, GEO is a leading provider of mission critical real estate to its governmental partners. The Company is the first fully integrated equity REIT specializing in the design, financing, development, and operation of secure facilities, processing centers, and community reentry centers in the U.S., Australia, South Africa, and the U.K.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Title 42 to End? The Biden Administration has stated the enforcement of Title 42 to expel immigrants will end May 23rd. First authorized in March 2020 during the COVID crisis, Title 42 continued to be enforced by the Biden Administration over the past year as a key tool to stop the spread of the virus in border facilities, but with the decline in COVID cases, the Administration will end the use of Title 42.

Poised for a Surge? In the first five months of the government fiscal year, monthly Southwest border encounters are averaging nearly 170,000 and are on pace to top two million for the year.  Some reports suggest the number of people crossing once the restriction is lifted could triple to 18,000 per day, or more than double the current monthly encounter amount …

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

 

Tuesday, April 05, 2022

CoreCivic, Inc. (CXW)
What Can End of Title 42 Mean?

CoreCivic is a diversified government solutions company with the scale and experience needed to solve tough government challenges in flexible, cost-effective ways. We provide a broad range of solutions to government partners that serve the public good through corrections and detention management, a growing network of residential reentry centers to help address America’s recidivism crisis, and government real estate solutions. We are a publicly traded real estate investment trust and the nation’s largest owner of partnership correctional, detention and residential reentry facilities. We also believe we are the largest private owner of real estate used by U.S. government agencies. The Company has been a flexible and dependable partner for government for more than 35 years. Our employees are driven by a deep sense of service, high standards of professionalism and a responsibility to help government better the public good.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Title 42 to End? The Biden Administration has stated the enforcement of Title 42 to expel immigrants will end May 23rd. First authorized in March 2020 during the COVID crisis, Title 42 continued to be enforced by the Biden Administration over the past year as a key tool to stop the spread of the virus in border facilities, but with the decline in COVID cases, the Administration will end the use of Title 42.

Poised for a Surge? In the first five months of the government fiscal year, monthly Southwest border encounters are averaging nearly 170,000 and are on pace to top two million for the year.  Some reports suggest the number of people crossing once the restriction is lifted could triple to 18,000 per day, or more than double the current monthly encounter amount …

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision. 

 

A Tool for Predicting the Future – Helping Nonexperts Make Forecasts Using Data Collected Over Time

 

Adam Zewe | MIT News Office

 

Whether someone is trying to predict tomorrow’s weather, forecast future stock prices, identify missed opportunities for sales in retail, or estimate a patient’s risk of developing a disease, they will likely need to interpret time-series data, which are a collection of observations recorded over time.

Making predictions using time-series data typically requires several data-processing steps and the use of complex machine-learning algorithms, which have such a steep learning curve they aren’t readily accessible to nonexperts.

To make these powerful tools more user-friendly, MIT researchers developed a system that directly integrates prediction functionality on top of an existing time-series database. Their simplified interface, which they call tspDB (time series predict database), does all the complex modeling behind the scenes so a nonexpert can easily generate a prediction in only a few seconds.

The new system is more accurate and more efficient than state-of-the-art deep learning methods when performing two tasks: predicting future values and filling in missing data points.

One reason tspDB is so successful is that it incorporates a novel time-series-prediction algorithm, explains electrical engineering and computer science (EECS) graduate student Abdullah Alomar, an author of a recent research paper in which he and his co-authors describe the algorithm. This algorithm is especially effective at making predictions on multivariate time-series data, which are data that have more than one time-dependent variable. In a weather database, for instance, temperature, dew point, and cloud cover each depend on their past values.

The algorithm also estimates the volatility of a multivariate time series to provide the user with a confidence level for its predictions.

“Even as the time-series algorithm can effectively capture any time-series structure out there, data becomes more and more complex. It feels like we have found the right lens to look at the model complexity of time-series data,” says senior author Devavrat Shah, the Andrew and Erna Viterbi Professor in EECS and a member of the Institute for Data, Systems, and Society and of the Laboratory for Information and Decision Systems.

Joining Alomar and Shah on the paper is lead author Anish Agrawal, a former EECS graduate student who is currently a postdoc at the Simons Institute at the University of California at Berkeley. The research will be presented at the ACM SIGMETRICS conference.

 

Adapting a New Algorithm

Shah and his collaborators have been working on the problem of interpreting time-series data for years, adapting different algorithms and integrating them into tspDB as they built the interface.

About four years ago, they learned about a particularly powerful classical algorithm, called singular spectrum analysis (SSA), that imputes and forecasts single time series. Imputation is the process of replacing missing values or correcting past values. While this algorithm required manual parameter selection, the researchers suspected it could enable their interface to make effective predictions using time series data. In earlier work, they removed this need to manually intervene for algorithmic implementation. 

The algorithm for single time series transformed it into a matrix and utilized matrix estimation procedures. The key intellectual challenge was how to adapt it to utilize multiple time series.  After a few years of struggle, they realized the answer was something very simple: “Stack” the matrices for each individual time series, treat it as a one big matrix, and then apply the single time-series algorithm on it.

This utilizes information across multiple time series naturally — both across the time series and across time, which they describe in their new paper.

This recent publication also discusses interesting alternatives, where instead of transforming the multivariate time series into a big matrix, it is viewed as a three-dimensional tensor. A tensor is a multi-dimensional array, or grid, of numbers. This established a promising connection between the classical field of time series analysis and the growing field of tensor estimation, Alomar says.

“The variant of mSSA that we introduced actually captures all of that beautifully. So, not only does it provide the most likely estimation, but a time-varying confidence interval, as well,” Shah says.

 

The Simpler, the Better

They tested the adapted mSSA against other state-of-the-art algorithms, including deep-learning methods, on real-world time-series datasets with inputs drawn from the electricity grid, traffic patterns, and financial markets.

Their algorithm outperformed all the others on imputation and it outperformed all but one of the other algorithms when it came to forecasting future values. The researchers also demonstrated that their tweaked version of mSSA can be applied to any kind of time-series data.

“One reason I think this works so well is that the model captures a lot of time series dynamics, but at the end of the day, it is still a simple model. When you are working with something simple like this, instead of a neural network that can easily overfit the data, you can actually perform better,” Alomar says.

 

The impressive performance of mSSA is what makes tspDB so effective, Shah explains. Now, their goal is to make this algorithm accessible to everyone.

One a user installs tspDB on top of an existing database, they can run a prediction query with just a few keystrokes in about 0.9 milliseconds, as compared to 0.5 milliseconds for a standard search query. The confidence intervals are also designed to help nonexperts to make a more informed decision by incorporating the degree of uncertainty of the predictions into their decision making.

For instance, the system could enable a nonexpert to predict future stock prices with high accuracy in just a few minutes, even if the time-series dataset contains missing values.

Now that the researchers have shown why mSSA works so well, they are targeting new algorithms that can be incorporated into tspDB. One of these algorithms utilizes the same model to automatically enable change point detection, so if the user believes their time series will change its behavior at some point, the system will automatically detect that change and incorporate that into its predictions.

They also want to continue gathering feedback from current tspDB users to see how they can improve the system’s functionality and user-friendliness, Shah says.

“Our interest at the highest level is to make tspDB a success in the form of a broadly utilizable, open-source system. Time-series data are very important, and this is a beautiful concept of actually building prediction functionalities directly into the database. It has never been done before, and so we want to make sure the world uses it,” he says.

“This work is very interesting for a number of reasons. It provides a practical variant of mSSA which requires no hand tuning, they provide the first known analysis of mSSA, and the authors demonstrate the real-world value of their algorithm by being competitive with or out-performing several known algorithms for imputations and predictions in (multivariate) time series for several real-world data sets,” says Vishal Misra, a professor of computer science at Columbia University who was not involved with this research. “At the heart of it all is the beautiful modeling work where they cleverly exploit correlations across time (within a time series) and space (across time series) to create a low-rank spatiotemporal factor representation of a multivariate time series. Importantly this model connects the field of time series analysis to that of the rapidly evolving topic of tensor completion, and I expect a lot of follow-on research spurred by this paper.”

 

Suggested Reading

Are Economic Excesses Creating Investment Opportunity?

Retail Investors May Soon See More Safety Measures Including Coursework and Testing

How Your Data is Used to Generate Big Returns

What Makes a Country a Tax Haven?

 

Stay up to date. Follow us:

A Tool for Predicting the Future – Helping Nonexperts Make Forecasts Using Data Collected Over Time

 

Adam Zewe | MIT News Office

 

Whether someone is trying to predict tomorrow’s weather, forecast future stock prices, identify missed opportunities for sales in retail, or estimate a patient’s risk of developing a disease, they will likely need to interpret time-series data, which are a collection of observations recorded over time.

Making predictions using time-series data typically requires several data-processing steps and the use of complex machine-learning algorithms, which have such a steep learning curve they aren’t readily accessible to nonexperts.

To make these powerful tools more user-friendly, MIT researchers developed a system that directly integrates prediction functionality on top of an existing time-series database. Their simplified interface, which they call tspDB (time series predict database), does all the complex modeling behind the scenes so a nonexpert can easily generate a prediction in only a few seconds.

The new system is more accurate and more efficient than state-of-the-art deep learning methods when performing two tasks: predicting future values and filling in missing data points.

One reason tspDB is so successful is that it incorporates a novel time-series-prediction algorithm, explains electrical engineering and computer science (EECS) graduate student Abdullah Alomar, an author of a recent research paper in which he and his co-authors describe the algorithm. This algorithm is especially effective at making predictions on multivariate time-series data, which are data that have more than one time-dependent variable. In a weather database, for instance, temperature, dew point, and cloud cover each depend on their past values.

The algorithm also estimates the volatility of a multivariate time series to provide the user with a confidence level for its predictions.

“Even as the time-series algorithm can effectively capture any time-series structure out there, data becomes more and more complex. It feels like we have found the right lens to look at the model complexity of time-series data,” says senior author Devavrat Shah, the Andrew and Erna Viterbi Professor in EECS and a member of the Institute for Data, Systems, and Society and of the Laboratory for Information and Decision Systems.

Joining Alomar and Shah on the paper is lead author Anish Agrawal, a former EECS graduate student who is currently a postdoc at the Simons Institute at the University of California at Berkeley. The research will be presented at the ACM SIGMETRICS conference.

 

Adapting a New Algorithm

Shah and his collaborators have been working on the problem of interpreting time-series data for years, adapting different algorithms and integrating them into tspDB as they built the interface.

About four years ago, they learned about a particularly powerful classical algorithm, called singular spectrum analysis (SSA), that imputes and forecasts single time series. Imputation is the process of replacing missing values or correcting past values. While this algorithm required manual parameter selection, the researchers suspected it could enable their interface to make effective predictions using time series data. In earlier work, they removed this need to manually intervene for algorithmic implementation. 

The algorithm for single time series transformed it into a matrix and utilized matrix estimation procedures. The key intellectual challenge was how to adapt it to utilize multiple time series.  After a few years of struggle, they realized the answer was something very simple: “Stack” the matrices for each individual time series, treat it as a one big matrix, and then apply the single time-series algorithm on it.

This utilizes information across multiple time series naturally — both across the time series and across time, which they describe in their new paper.

This recent publication also discusses interesting alternatives, where instead of transforming the multivariate time series into a big matrix, it is viewed as a three-dimensional tensor. A tensor is a multi-dimensional array, or grid, of numbers. This established a promising connection between the classical field of time series analysis and the growing field of tensor estimation, Alomar says.

“The variant of mSSA that we introduced actually captures all of that beautifully. So, not only does it provide the most likely estimation, but a time-varying confidence interval, as well,” Shah says.

 

The Simpler, the Better

They tested the adapted mSSA against other state-of-the-art algorithms, including deep-learning methods, on real-world time-series datasets with inputs drawn from the electricity grid, traffic patterns, and financial markets.

Their algorithm outperformed all the others on imputation and it outperformed all but one of the other algorithms when it came to forecasting future values. The researchers also demonstrated that their tweaked version of mSSA can be applied to any kind of time-series data.

“One reason I think this works so well is that the model captures a lot of time series dynamics, but at the end of the day, it is still a simple model. When you are working with something simple like this, instead of a neural network that can easily overfit the data, you can actually perform better,” Alomar says.

 

The impressive performance of mSSA is what makes tspDB so effective, Shah explains. Now, their goal is to make this algorithm accessible to everyone.

One a user installs tspDB on top of an existing database, they can run a prediction query with just a few keystrokes in about 0.9 milliseconds, as compared to 0.5 milliseconds for a standard search query. The confidence intervals are also designed to help nonexperts to make a more informed decision by incorporating the degree of uncertainty of the predictions into their decision making.

For instance, the system could enable a nonexpert to predict future stock prices with high accuracy in just a few minutes, even if the time-series dataset contains missing values.

Now that the researchers have shown why mSSA works so well, they are targeting new algorithms that can be incorporated into tspDB. One of these algorithms utilizes the same model to automatically enable change point detection, so if the user believes their time series will change its behavior at some point, the system will automatically detect that change and incorporate that into its predictions.

They also want to continue gathering feedback from current tspDB users to see how they can improve the system’s functionality and user-friendliness, Shah says.

“Our interest at the highest level is to make tspDB a success in the form of a broadly utilizable, open-source system. Time-series data are very important, and this is a beautiful concept of actually building prediction functionalities directly into the database. It has never been done before, and so we want to make sure the world uses it,” he says.

“This work is very interesting for a number of reasons. It provides a practical variant of mSSA which requires no hand tuning, they provide the first known analysis of mSSA, and the authors demonstrate the real-world value of their algorithm by being competitive with or out-performing several known algorithms for imputations and predictions in (multivariate) time series for several real-world data sets,” says Vishal Misra, a professor of computer science at Columbia University who was not involved with this research. “At the heart of it all is the beautiful modeling work where they cleverly exploit correlations across time (within a time series) and space (across time series) to create a low-rank spatiotemporal factor representation of a multivariate time series. Importantly this model connects the field of time series analysis to that of the rapidly evolving topic of tensor completion, and I expect a lot of follow-on research spurred by this paper.”

 

Suggested Reading

Are Economic Excesses Creating Investment Opportunity?

Retail Investors May Soon See More Safety Measures Including Coursework and Testing

How Your Data is Used to Generate Big Returns

What Makes a Country a Tax Haven?

 

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Robinhood Continues to Push to Expand Their Users’ Possibilities

 

Robinhood (HOOD) has taken another step toward users having the ability to trade from their platform around the clock, seven days a week. It announced that the online brokerage service is extending its premarket and after-hours trading to provide a 13-hour window. Robinhood’s stated mission has always been to revolutionize the markets and bring more people into the financial system. Yesterday’s (March 29) announcement is another step toward that goal.

The company said this is an important step toward 24/7 equities investing; their new extended hours will allow users to trade from 7 am until 8pm. This adds four hours for users to transact. Its extended trading hours had been from 9 am to 9:30 am. ET and 4 pm to 6 pm ET.

 In a Blog post the online stockbroker that introduced transaction free trades in 2014, added crypto in 2018, fractional shares in 2019, automatic investments in 2020, and 24/7 customer support in 2021 said about their mission to revolutionize the markets, “Today’s launch is just another step on this journey, and we’re just getting started.”

 

Robinhood has studied their data and said that they have, “…seen a community of Robinhood early birds and night owls who log in exclusively outside of regular market hours.” They believe the new extended trading hours, leading toward 24/7, will provide more opportunities to more customers to manage their portfolio at a convenient time for them.

The stock jumped 24%, its third-best trading day since the company went public last summer.

A Word of Caution

Trading is typically thinner pre and post-market. While access may be helpful, until there are a large number of transactions taking place, extended-hours trading can be riskier than the regular session. At the same time, it may also provide opportunities or dislocations worth considering. These risks would presumably lessen as extended hours volume increases.

Paul Hoffman

Managing Editor, Channelchek

 

Suggested Reading

Regulators May Add New Guard Rails to Temper Investment Risk

AMC Entertainment’s Plot Twist Gets Even More Interesting to Investors

 

Sources

https://robinhood.com/us/en/support/articles/extendedhours-trading/

https://blog.robinhood.com/

 

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Rob Goldman – Former Head of Growth, Monetization and Advertising, Facebook (Meta) – Joins NobleCon18 Lineup

The 18th annual conference will be “live” again! To celebrate the return to IN PERSON, thanks to our sponsors, investor registration is FREE

 

NobleCon is pleased to announce that Rob Goldman will be a featured Metaverse panelist at NobleCon18. Joining Facebook in 2012 reporting directly to CEO Mark Zuckerberg, Goldman was charged with growing and monetizing the burgeoning social media platforms (including subsidiaries such as Instagram); during his tenure at Facebook revenues grew from $5 billion to over $70 billion in a span of seven years. Goldman’s move to Facebook happened when his company, Threadsy, was acquired by FB in a move that many refer to as one of “Mark Zuckerberg’s acqui-hires.” Goldman’s company started out as a way for people to see their social feeds and communication from different networks, like Facebook and Twitter, in one place. But Goldman soon changed the focus towards a paid service that helped brands see which influencers they needed to establish relationships with in order to find new customers on social networks. The change resulted in the development of the social marketing tool Swaylo, which ultimately attracted the attention of Zuckerberg. Mr. Goldman is a graduate of Harvard Business School and is a Board Member of Indiegogo, Stratim Systems, Cerebellum Capital and Thisnext. ADMISSION IS FREE for institutional to self-directed novice investors, thanks to Noble, Channelchek, Sponsors and The Presenting Companies. Attendance is limited to 1,000. NobleCon18 – Noble Capital Markets 18th Annual Small and Microcap Investor Conference – April 19-21, 2022 – Hard Rock, Hollywood, FL 100 Public Company Presentations | Scheduled Breakouts | Panel Presentations | High-Profile Keynotes | Educational Sessions | Receptions & Networking Events REGISTER FREE AS AN INVESTOR  |  PRESENTING COMPANY INQUIRIES  |  NOBLECON INFO PAGE  |  NOBLECON18.COM  |  PRESENTING COMPANIES  |  SCHEDULED SPEAKERS

NobleCon18 Presenting Companies
April 19-21, 2022

REGISTER FREE AS AN INVESTOR  |  PRESENTING COMPANY INQUIRIES  |  CONFIRMED SPEAKERS  |  NOBLECON18.COM

Click the logos to view more information on each company
Click the preview link to watch a preview video from the presenter
New companies and preview videos are added regularly

ATNM (NYSE)	ALCO (NasdaqGS)	AUXXF (OTCQX)	ARLP (NasdaqGS)
ALVOF (OTCQX)	Aurox (Private)	ASM (NYSE) Watch the Preview	AXLA (Nasdaq)
BCCEF (OTCPK) Watch the Preview	BXRX (Nasdaq) Watch the Preview	BBGI (Nasdaq) Watch the Preview	BSGM (Nasdaq) Watch the Preview
BLBX (Nasdaq)	BSFC (Nasdaq)	BOWL (Nasdaq)	CHKKF (OTCQB) Watch the Preview
CING (Nasdaq)	CTXR (Nasdaq)	COCP (Nasdaq) Watch the Preview	LODE (NYSE)
CMTL (NasdaqGS)	CMLS (Nasdaq)	CYDVF (OTCQB)	DMIFF (OTCQB)
DTGI (OTCQB)	DMS (NYSE)	DLHC (Nasdaq)	EGLE (NasdaqGS) Watch the Preview
EEIQ (Nasdaq)	UUUU (NYSE)	GAME (Nasdaq)	EVC (NYSE) Watch the Preview
EZFL (Nasdaq)	FGI (Nasdaq)	FLHLF (OTCQB) Watch the Preview	FTK (NYSE)
OPA (NYSE) Watch the Preview	VINE (NYSE) Watch the Preview	GABLF (OTCQB)	GNK (NYSE)
GNPX (Nasdaq) Watch the Preview	JETMF (OTC)	HHS (Nasdaq)	HCTI (Nasdaq) Watch the Preview
HMNC (Private) Watch the Preview	III (Nasdaq) Watch the Preview	IPOOF (OTCQX)	INLB (OTCQX)
IZOZF (OTCQB)	JAGX (Nasdaq) Watch the Preview	KELYA (NasdaqGS) Watch the Preview	LEE (NYSE)
LCTX (NYSE)	LQWDF (OTCQB) Watch the Preview	MGMLF (OTCQB) Watch the Preview	M8G (ETR)
MMAT (Nasdaq)	MLSS (NYSE) Watch the Preview	MSGM (Nasdaq) Watch the Preview	NSCIF (OTCQX) Watch the Preview
NMTC (OTCQB) Watch the Preview	NRGOF (OTCQB)	OCGN (Nasdaq)	Odyssey Wellness
OSS (Nasdaq)	PRFX (Nasdaq) Watch the Preview	PANL (Nasdaq) Watch the Preview	KTTA (Nasdaq)
PENMF (OTC) Watch the Preview	PYNKF (OTC) Watch the Preview;	OILCF (OTCQB)	PSYCF (OTCQB) Watch the Preview
RICK (Nasdaq) Watch the Preview	RMTI (OTCQB)	SALM (Nasdaq) Watch the Preview	SHWZ (OTCQX) Watch the Preview
SMTS (NYSE) Watch the Preview	SMFL (Nasdaq) Watch the Preview	SBEV (NYSE)	SKYX (Nasdaq)
SURG (OTCQB)	GEO (NYSE)	TNXP (Nasdaq)	TSQ (NYSE)
VIVK (Nasdaq)	VNRX (NYSE)	VOXCF (OTCQB) Watch the Preview	VYGVF (OTCQB)
WSNAF (OTCQB) Watch the Preview	WRAP (Nasdaq)

Monday, March 14, 2022

Kelly Services (KELYA)
Russia, and Potentially Wider, Impact

Kelly Services Inc is a provider of workforce solutions and consulting and staffing services. The company’s operations are divided into three business segments namely Americas Staffing, Global Talent Solutions (“GTS”) and International Staffing. It provides staffing solutions through its branch networks in Americas and International operations and also provides a suite of innovative talent fulfilment and outcome-based solutions through GTS segment. Americas Staffing generates maximum revenue from its operations.

Joe Gomes, Senior Research Analyst, Noble Capital Markets, Inc.

Joshua Zoepfel, Research Associate, Noble Capital Markets, Inc.

Refer to the full report for the price target, fundamental analysis, and rating.

Russia Exposure. Given the recent Russia/Ukraine events, we reviewed Kelly’s direct exposure to the two countries. In 2021, Russia accounted for $132.2 million, or approximately 2.7%, of Kelly’s overall revenue. As of January 2, 2022, Kelly’s Russian operations comprised approximately 1% of the Company’s assets. Customer accounts receivable is the primary asset in Russia. Kelly does not have a subsidiary or employees in Ukraine.

Sanctions.  According to the Company, sanctions issued since February 24, 2022 by the European Union, United States, and other countries against certain Russian entities and persons and certain activities involving Russia or Russian entities, have created uncertain economic conditions. The current economic environment, along with the suspension of services by some of the Company’s service providers …

This Company Sponsored Research is provided by Noble Capital Markets, Inc., a FINRA and S.E.C. registered broker-dealer (B/D).

*Analyst certification and important disclosures included in the full report. NOTE: investment decisions should not be based upon the content of this research summary. Proper due diligence is required before making any investment decision.