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Modern Trader
False prophets

Art by Mario Zucca

Modern Trader
False prophets

Garrett Baldwin
Illustrated by Mario Zucca



This is a story about trust. About why many Americans have tuned out and lost hope in financial “experts.” It's about the insights, foresights, reckless predictions and lack of conviction from media outlets, Wall Street analysts and talking heads that monopolize today’s market dialogue.  

It’s also a story about the power of statistics; how one emerging trend can reverse a glaring problem brewing in America. Although markets roared back from the financial crisis, the mainstream Wall Street apparatus has failed to address one startling issue. America has a serious investing problem. Despite the six-year bull-run, 52% of Americans hold no investments in the market, according to Bankrate.com. CNN reports that stock-market participation has fallen from 65% in 2007 to 48% so far in 2015.

The primary reason is a lack of capital. However, the next three would-be investor gripes in Bankrate’s March Market Pulse Survey are quite fixable. First is a lack of trust in the markets and experts responsible for providing actionable investment advice. Second is a fundamental lack of investment education. Third is an aversion to risk. The problem isn’t a lack of investment insight or access to financial tools. In a sea of noise—fueled by a non-stop 24-hour news cycle—it’s impossible for some to know where to start, whom to trust or how to get ahead. Experienced traders already know the fallibility of institutional research and the talking heads that dominate the airwaves.

However, they might be surprised to know that some sources and pundits deemed highly credible—ones investors trust and trade off of—have underwhelming performance records, yet still maintain influence due to a staggering lack of accountability. Fortunately, these concerns are poised to abate as a new class of social curation and finance experts, financial technology entrepreneurs and data scientists redefine market conversation, and help investors obtain actionable insights from an emerging class of credible and accountable sources. These new voices—which we profile in the following pages—help to separate the signals from the noise.

Whom to trust in a sea of market noise?​

The financial media has exploded in size with the rise of the Internet, digital networks and 24-hour market news. Proliferation of opinion has expanded exponentially — from the millions of tweets sent each day to countless financial blogs and news sites. More than 250 million visitors hit financial sites each month for unlimited market opinion and research: Some good and some very bad. Broadcast networks fill 20 hours a day with non-stop coverage of earnings reports, Fed talk, government data and rampant speculation. Social media has evolved at a breakneck pace. According to Adobe, 12 social media platforms now have more than 100 million users. 

Without insight on who is credible, millions of investors are exposed to untested recommendations,  and an ocean of new insight washes them away moments later as if they never existed. With so much noise, it is difficult to trust news sources for actionable investment insight. 

In January, Modern Trader collaborated with Spectrem Group, a market research and consulting firm specializing in wealth and retirement markets, and conducted a survey to determine the level of exposure investors have to certain forms of media and insights and how credible they deem these outlets. The survey asked investors to rate each source as credible, very credible, not very credible, not credible at all, or neutral. (There was a high level of neutrality due to exposure levels.)

Insights deemed either “credible” or “very credible” swayed heavily to traditional forms of financial media and investment research, particularly among respondents who said they have “very much” investment knowledge. Among the sources ranked most credible were mainstream financial journalists, Wall Street research analysts, investment brokers and  trading peers. 

Investors with “very much” investment knowledge trusted both Wall Street analysts and mainstream financial journalists by a significant margin vs. the average respondent.

Meanwhile, financial bloggers, social media platforms and content curation outlets received single-digit confidence when it came to levels of credibility for their content and insight (see “Trusted or Troubled?,” right).

But despite perceptions of social media technologies, or when one examines performance of top-ranked independent analysts, the harnessing and structuring of social data has proven to offer some of the purest signals in the markets, while performance of traditional stock pickers has been  mixed. 

Meanwhile, many top financial bloggers are outperforming top Wall Street research analysts when social investment platforms curate and examine stock recommendations and earnings estimates--a pattern recognized by several emerging social curation platforms that have given a voice to non-professional traders. 

So, who should you really trust? The answer begins with the broader designation of today’s so-called market experts, although it’s more accurate if we called the worst offenders what they really are: False prophets.

Credibility gap 

Despite the vaunted status of many mainstream financial pundits, their performance doesn’t justify this status. Numerous studies show that many so-called financial experts have poor track records predicting  performance. 

Economist and former Invesco Senior Market Strategist Fritz Meyer conducts an evaluation of Barron’s yearly stock market outlook (Barron’s offers annual recommendations of 10 reputable market strategists’ views of 10 sectors). 

“I was always skeptical about that Wall Street research I was seeing, but I couldn’t hold anyone accountable,” says Meyer, who has tracked eight years of forecasts. “The Barron’s annual forecast was an easy way to measure performance,” he adds. 

The results revealed big misses by the experts. For example, in 2014, six of 10 top strategists forecasted that the utilities sector would be among the worst performing. To the contrary, utilities rose more than 24%, the top yearly sector performance. In 2013, most surveyed analysts were bearish or neutral on consumer discretionary stocks, but the sector saw gains of 41% that year (see “Throwing darts,” below). “These were the two most hated sectors back-to-back for two years,” Meyer says. “And they were the best performers.”

Eight years of data analysis has heightened Meyer’s  suspicions. “This [study] suggests that Wall Street analysts cannot systematically add alpha with what amounts to tactical asset allocation by advising people on underweight and overweight projections,” he says.

While 10 analysts’ views fail to quantify statistical significance, when you expand the scope of analyst recommendations, investment success is no better than the flip of a coin. Roughly 86.5% of analyst recommendations have buy ratings, which are wrong 50.2% of the time, according to TipRanks (Sage, page 75), a financial-accountability engine that ranks market advice published online to assess accuracy and credibility of pundits and analysts. The challenge for investors to find credible insight grows more daunting when evaluating sell-side research. TipRanks notes that 34 stocks on average will have conflicting buy and sell recommendations each month on New York exchanges alone.

At the institutional level, stock pickers are struggling. According to multiple accounts, 2014 was supposed to have been “a stock picker’s year.” And although the S&P 500 hit its fifth straight yearly gain, and ninth in the last 10 years, roughly 85% of active large-cap stock funds lagged their benchmarks, according to Lipper data. Just 13% of large-cap stock pickers beat the S&P 500.

The more concerning – and often least accountable – insight is on television. Given financial broadcasting’s power and reach, channels like CNBC and Fox Business have become the gatekeepers in deciding which voices should be considered credible and which should not among the public. 

But countless examples of prominent pundits missing big on prognostication exist. In 2012, Bill Gross argued that stocks were dead and a Ponzi scheme. But within 18 months, the Dow jumped more than 3,500 points. David Tice – a regular and bearish television contributor and head of an investment management firm that bears his name – predicted in August 2014 that the odds of a market crash sat at 60%. While that turns heads to televisions, investors should know that Tice issued similar forecasts in 2010 and 2012, when the S&P 500 returned 12.78% and 13.41% respectively. Marc Faber, a regular television guest and publisher of the popular Gloom, Boom & Doom report, predicted that the 2014 crash (that never came) would be worse than the 1987 crash (that did). Faber began predicting a bear market on U.S. stocks in 2011, and, in late April he  predicted another 40% decline for the markets in 2015 on CNBC. 

Finally, there are  commentators like the network’s Jim Cramer. The host of Mad Money says he is dedicated to financial education. “For years I have been trying to help people like you, who own stocks and feel like they’re on the outside looking in, become better investors,” he writes in his Mad Money Manifesto. “That’s the mission statement, plain and simple.”

Still Cramer’s stock-picking performance is spotty, according to multiple evaluations of his picks by bloggers and news firms over the years. For example, in 2013 Allen Roth at Money Watch highlighted that Cramer advised viewers to sell Hewlett Packard (HPQ) and Best Buy (BBY), and both  surged more than 100% in the following six months. Certainly, some investors followed his advice. And though Cramer isn’t the media’s sole stock picker, he’s one of the most recognized and followed. 

Too often, on-air recommendations and picks on financial sites are not backed up with sound data or back testing. Rather, raw emotion of personalities can influence the pick, and  if a pick is very wrong, virtually no accountability exists. 

For years, these voices have been the most public for insight and guidance in the markets. Traders have waded through all this noise--unaccountable information--while the financial media (the guardians of credibility) continued to offer a voice to many pundits with questionable performance records.

The system of elevating the best insight is broken, and the financial crisis, which affected media credibility, has fueled little emphasis on accountability for  talking heads who offer poor insight.

“The financial crisis hasn’t changed the way people view trust in who gets to be heard,” says Leigh Drogen, Founder and CEO at Estimize, an open financial estimates platform that facilitates the aggregation of fundamentally based predictions from independent analysts. “The broader story is the incentive structure. When you look at who used to be on television, they were mostly from the sell-side. Television needs sell-side analysts for content, and the sell-side needs television’s megaphone to make everyone believe they are the smartest and most important people. They often are the smartest, but their incentive, which is to gather assets, is often in conflict with providing unbiased accurate analysis.  The anchor will ask for opinion, and they’ll reply safely by saying something along the lines of: ‘I’m cautiously positive.’ There’s no incentive to put your neck on the line when making a specific call [on television].”

It’s no coincidence that credibility of on-air pundits is underwater, according to Spectrem Group’s research. Just 21% of investors ranked on-air experts as credible, while 28% shared an unfavorable view. Perhaps even more striking is that just 21% of investors said they were “frequently” or “very frequently” exposed to the opinions of on-air financial experts, while 46% said they were exposed “rarely” or “never.” 

This suggests that many have tuned out the opinions of these so-called experts. 

This comes at a time that CNBC soon saw its daytime Nielsen ratings decline so sharply that they recently ditched Nielsen as their audience measurement platform. In 2014 — which Nielsen data suggests was its least-watched year since 1995 — the network maintained an audience of 177,000 from the hours of 9:30 a.m. to 5 p.m. The network argues that Nielsen fails to capture out-of-home viewership.

Drogen argues that the financial broadcast media would benefit by continuing to curate the insight of analysts with alternative incentive structures, particularly those who are attempting to build a reputation and would be more accountable to the performance of their insight. That includes independent traders, managers of small hedge funds and even bloggers. The challenge is that CNBC has the capacity to bolster the popularity of any pundit, and the network likely needs to see the value of alternative insights for its core audience. 

“They have a big bullhorn,” Drogen says. “They are scared to trust new people because they are placing their stamp of approval on that person. The way people are sourced and who is heard is changing. But this is going to take some time.”

Part of that transition will also require the networks to realize that Wall Street credentials do not necessarily warrant credibility or guarantee accurate insight. 

“At the end of the day, it’s a comforting thought that the guy talking on TV has passed FINRA or has a CFA,” says TipRanks CEO Uri Gruenbaum. For accuracy, Gruenbaum also suggests that investors look elsewhere for actionable investment advice. 

Fortunately, a new crop of alternative voices have received opportunities to shine thanks to the rise of social data platforms that include TipRanks, Estimize, Openfolio, and others  that curate primary research across countless data and information streams. 

These new data and social platforms allow investors to obtain actionable insight while benefiting from increased market transparency and audience accountability. In addition, they provide both a voice and credibility to many non-professional traders who have the grit, intelligence and strong performance record, but might lack a sell-side shop’s name on a business card. They are the future in financial media. 

The rise of social media and finance

Tom Glocer, the former CEO of Thomson Reuters and longtime media pioneer, sees opportunities to disrupt a sector dominated by unaccountable pundits and revolutionize how traders make actionable decisions. 

“I’m a little down on traditional media as a source of investment,” says Glocer. “I’m very optimistic about being able to harness huge amounts of primary data to make better investment decisions; it’s a really rich time for that.”

He’s not alone, although it has taken time for traders to accept social media and data platforms as havens of actionable insight – tools that actually can separate signals from the noise.

Early on, social media integration was slow in the financial sector. Many believed that trading professionals didn’t want to share information or investment opinions. The adoption of social data analytics was limited to a small number of hedge funds and high-frequency trading houses. That has changed dramatically. 

Data streams and platforms harnessing social media have emerged. Many retail traders have embraced technical analysis and tools once considered the work of financial witch doctors. The migration to social curation accelerated in 2013 after three distinct events: when the SEC allowed companies to release key financial information on social media; a Twitter message that caused a 140-point drop in the market after a hacked Associated Press feed said explosions rocked the White House; and a Carl Icahn Tweet that offered a bullish outlook on Apple (AAPL) that sent shares soaring. 

Still, the social integration trend in finance began with the foundation of StockTwits, co-founded by Howard Lindzon and Soren Macbeth in 2008. Today, more than 300,000 investors, market professionals, and public companies share information and ideas about the market and individual stocks on the platform. 

“As the world moves toward mobile technology, and millennials move into the financial food chain, StockTwits sees itself as a place for investment idea generation,” says Lindzon. “It’s a community for active and non-active traders. We’re always on.”

Its massive content reservoir creates countless information streams for an audience of more than 
40 million across financial web and social media platforms. StockTwits is most recognizable for its iconic “Cashtag,” a $ symbol placed before a ticker to enable conversations about stocks. (Cashtags were adopted by Twitter in 2012.)

StockTwits offers distinct value in two specific areas. First is its ability to harness investment ideas and encourage communication and education among traders. StockTwits has harnessed social information, moved investment discussions onto mobile platforms  and enabled a two-way dialogue among traders. 

That has been especially valuable when so many concerns have emerged about trust and lack of investment knowledge among all age groups in America. Although the figures are well above 80% across all age demographics, nowhere are they more damning than among millennials. Roughly 93% of millennials say they distrust financial markets or they lack investing knowledge to make decisions, based on a March Capital One Sharebuilder survey. 

The second reason why StockTwits has been invaluable is next-generation social data curation and analytics are based on its platform. At least 600 applications and media platforms rely on this platform to locate actionable trading insights and gauge investor sentiment through data streams. “Without StockTwits,” says Drogen, “Estimize and many other platforms wouldn’t exist.”

The StockTwits platform allows both professional and non-professional traders to share insights and information in an environment that welcomes anonymity. The audience includes both hedge fund managers and college students, but it allows everyone to operate under the assumption that they are not losing any edge.

“The overall goal is to make markets more efficient through transparency and more information and to allow those people who are most accurate to go to the top,”  Drogen says. “We do this through structured data. StockTwits is where these philosophies started. Howard [Lindzon] brought the idea of pseudonymity to the markets.  He brought the idea that people would share without any incentive structure. He wanted to produce a better community and data set for each other. Many people thought that the financial community would not do this, even though every other community actually does on the web. Every other sector shares information.”

Drogen, who worked in multiple roles at StockTwits before launching Estimize in 2013, argues that the perception that the financial sector would reject information sharing is rooted in industry shifts from the 1980s. Specifically, the rise of hedge funds produced a perceived culture of secrecy and a desire to protect trading information that in many ways didn’t exist. Before the 1980s, traders received their most important information from other traders. “People were in the pits, and would turn to the person next to them and ask ‘What do you think?’ We would talk to one another openly because we needed to know expectations from our peers,” Drogen says. “The markets are ready for this again.”

Drogen also notes that similar doubt emerged over social curation of information during the foundation of Wikipedia. Years ago, many doubted the long-term success of social curation due to the complexity of certain issues and anticipated disagreements, including the location of national borders, religious and political history interpretations, and other hot topics around the world. However, Wikipedia’s success is evident by its second-by-second expansion and its ability to displace traditional information sources.

Naturally, additional concerns exist about the basic nature of social media and investment insight shared on StockTwits and other platforms. Chris Roush, senior associate dean for undergraduate studies at University of North Carolina and strong advocate of improving the quality of financial journalism, raised an important – and common – concern about the basic nature of information sharing on social media. 

“New technologies like Twitter and other social media in the long run will be inherently beneficial. The more business and financial news that can be distributed, the more opportunities it has to be read,” Roush says. “The one potential harm is that you can only say so much in 140 characters, and sometimes you lose some of the context with longer forms of media.”

In a 140-character Tweet, the message fails to provide insight on risk or the intelligence on which the recommendation is based. In addition, there is a bias against Twitter, which is dominated by celebrity accounts and a stereotype of mindless followers. This may help explain why investors in Spectrem Group’s survey indicate a credibility level of 4% for the medium, while 64% of users said social media and content curation sites were either “Not very credible” or “Not credible at all.” 

“You’re dealing with money,” Drogen says. “People get pitched on the phone by a brokerage, even one with bad track records, and they give them their money. But when it comes to trusting an independent trader on Twitter – someone with 10,000 followers – they ignore him because he’s giving his information away for free.”

Still, advocates of social curation and data harnessing feel they are on the cusp of raising credibility and changing the landscape of financial media as investors embrace statistics, and the algorithms show an enhanced ability to separate the signal from the vast amount of noise across multiple channels by leveraging incredible amounts of primary data.

“People don’t really think much about where information comes from on what is essentially the event-processing engine in the word,” Glocer says. “The Twitter feed has an incredible torrent of information. There is a lot of it noise. But if you have the algorithms to extract things of significance, it arguably is the news agency of the future. User-generated content or citizen journalism was believed to be critical in the past, but it lacked the algorithms to separate the signal from the noise. The challenge is to report on one tweet- or to use an algorithm that enables verification from other sources including foreign news sites or satellite imagery. That is happening now.”

Still, that bias is expected to remain against social curation until word spreads of its value to traders, particularly in its ability to determine the most credible voices, ensure accountability among experts and non-experts and, most importantly, provide sources of actionable investment insight.

“It has taken time for people to adopt the pseudonymity of structured data because we’re measuring people [and their ideas] statistically,” Drogen says. “You can throw numbers in front of people about how Estimize’s data is 70% more accurate than aggregate earnings estimates. But unless [investors and the financial media] come to accept the core philosophy, or they have a visceral understanding of why this takes place, they do not accept statistics. About 18 months ago, we got the public to accept it and now we’re scaling up. Today, our data is becoming a must use for investors.”

The full-scale adoption of these platforms will not happen overnight, but the modern trader who focuses on this trend now is more likely to see greater Alpha potential while others drag their feet.

Finding informed, actionable insight

For too long, many traders suffered from the markets’ legacy of information-inequality. This phenomenon offered institutional and professional investors a distinctive information advantage over the retail investor. 

New data platforms are narrowing that information gap, providing investors with distinct tools and actionable insights to trade with greater confidence. For example, Eidosearch has returned the focus to the basic nature of trading: A calculation of probabilities. 

“All investing decisions come down to the range of outcomes that one can expect on a time horizon,” says David Kedmey, president and co-founder of EidoSearch. “When you talk about forecasting a range of outcomes, what is the most likely case? What is the risk around that?  What is the probability of that range? It’s very fundamental. Markets are about probabilities, and nobody has an effective way to quantify that. If you ask a fundamental portfolio manager about price targets and probabilities, it’s like sticking a finger in the air.” 

EidoSearch’s functionality is simple. By examining one performance pattern, EidoSearch can examine 100 million patterns in a second and find historical data similarities. By capturing actual outcomes of these similar conditions in a historical database, the firm can generate projections on the likely outcomes today, allowing investors to calculate risk and make informed decisions. 

“Our insight was to use data to determine probabilities and free oneself of the burden of modeling,” Kedmey says. ”Simply say, ‘When have we seen this before, and what were the outcomes?’ That gives you an empirical range and a certain set of probabilities.”

Meanwhile, emerging media giant Benzinga, founded by Jason Raznick, has evolved from a financial blog into a data-driven trading network that curates  trading ideas through its proprietary platform Marketfy.

“We started off as a blog five-and-a-half years ago, but it didn’t capture Jason’s vision of ‘providing access,’” says Benzinga CEO Kyle Bazzy. “We got into the news business because Reuters and the The Wall Street Journal might print 10,000 articles, but most of this news isn’t actionable. A trader doesn’t need to know that a CEO is talking in California today. We started by putting 800 articles out a day  impacting traders. Now, we’re putting investment into event-driven data, things that investors can build a strategy around.”

Its proprietary platform Marketfy curates trading tools, ideas, education and alerts. In addition, the company provides a portal that allows users to engage in a social community and network directly with traders, providing real-time trading advice. The company recently launched a platform allowing users to learn from and trade alongside its analyst Roberto Pedone.

“One thousand people signed up in the first month, and no one ever had access to this sort of education,” Bazzy says. “[Pedone] is making actionable recommendations. We took transparency to a different level. We created a virtual brokerage through Marketfy.”

Winning the earnings game  

Credibility is about performance. In an age of information sharing and social curation, the company on the business card doesn’t matter. Nor is it based on the rankings of search engines.

“The pseudonymity aspect of the web is starting to change the way people view trust,” says Estimize’s Drogen. “Trust needs to be based on statistics, and we’re at the beginning of it.”

When it comes to earnings, investors have little faith in aggregated earnings estimates; 20% of  respondents ranked them credible. Drogen’s distrust dates back to his time as a hedge fund analyst in 2007. “There are a few problems in our industry, specifically the estimates industry,” he says, referring to both the incentives of sell-side analysts and the limited number of opinions pooled each quarter.

More data means more accuracy, which is why Estimize accepts earnings estimate contributions from more than 7,000 analysts. This prompts coverage of more than 1,500 stocks each quarter. That’s a much larger roster than the Thomson Reuters/IBIS database, and Estimize contributors range from veterans of Wall Street to bloggers and first-time analysts. 

“If you have a larger number of estimates, you’ll have a more reliable picture of what’s happening,” says Drogen. That sentiment is backed by a 2014 report by Deutsche Bank’s Quantitative Research team that analyzed Estimize’s data. 

Deutsche Bank’s report stated: “[We] found multiple benefits to using the Estimize dataset; especially in the case of short-term applications in which accuracy is essential. Another interesting byproduct of the analysis was the power of crowdsourcing. We found that some of the value-added in the Estimize dataset was due to the wisdom of crowds effect as more predictions give way to greater accuracy. Moreover, the diversity of the contributors provides a greater spectrum of information, which can potentially improve investment strategies based on estimates.”

While some have raised concerns about allowing non-professional research analysts to contribute, Estimize has proven the value of public content curation. Thanks to accountability metrics (analysts are ranked by performance on the platform), individuals make the decision whether to submit insight.

“There is a severe self-selection bias among people who contribute,” Drogen says. “We don’t make people contribute in order to see the data. The people who contribute are the ones who want to contribute because they feel they have good information. A professional analyst may cover 50 stocks, but may only have a good read on 20 of them. Meanwhile, non-pros might be covering five stocks a quarter, which they are picking more specifically.” 

The Estimize consensus has proven more accurate than comparable sell side data sets more than 69% of the time. And Estimize’s statistical analysis has ensured that non-serious information is filtered out of its network, or at least called out.

“Our algorithms prevent gaming,” Drogen says. “We conduct IP checks, so we don’t need a person’s name. We know how long ago a person has signed up, what they did on the page before they filled out estimates. How many times the estimate was changed. All of this data is put into a behavioral model.” 

Algorithms are doing more than determining whose insight is the most credible in the age of pseudonymity. They’re also verifying information across a massive sea of data streams to determine the credibility of information from non-traditional sources. 

DataMinr was founded by brothers Peter and Ted Bailey and Jeff Kinsey. The company’s event mining engine is able to produce new sources of alpha by detecting events long before major media outlets report them. “When information breaks we can classify It and correlate it to tickers and sectors and things that a financial professional would care about. And through a variety of delivery systems, deliver it into their workflow,” says DataMinr Chief Strategy Officer Peter Bailey.

For example, in February, an explosion rocked Exxon Mobil’s Torrance, Calif., refinery, injuring several workers and shaking homes across the city. Nearly an hour before rival Tesoro Corp.’s stock rose 3% on the news, DataMinr detected the event through messages on Twitter, verified them, and alerted users on its DataMinr for Finance platform.

“Our system can look at every single tweet, and based on data patterns, determine the credibility,” Bailey says. “We have the full power of the full data pipe from Twitter. That means we are able to find event from sources that not anyone would know.” 

The platform also alerted users of an exclusive report by technology blog Wired that outlined the FCC commissioner’s plan for net neutrality, the broader market picked up the benefits for broadband providers that surpassed market expectations. Comcast Corp. (CMCSA) and Time Warner Cable’s (TWC) shares would rise 5% and 6% respectively that day, after the story reached a broader audience. 

The firm’s infrastructure isn’t limited to markets. It is also engaged in security and crisis management services. DataMinr’s platform provides early warning signals to nations and corporations on emerging threats and crises. This helps ensure that companies are better able to protect their assets, employees and interests. It also enables first responders to more quickly detect, confirm and respond to events. DataMinr’s success recently fueled a $130 million growth capital investment, and its broad roster of investors includes Fidelity, Wellington, Credit Suisse, John Mack, Vikram Pandit, Tom Glocer, GLG founder Noam Gottesman, WorldQuant Ventures, Glynn Capital and Goldman Sachs.

Making insight accountable

A massive sea of data and opinion masquerading as actionable insight has been floating across computer screens for the better part of two decades. Each day, thousands of articles scroll the world’s financial blogs, encouraging readers to buy this and sell that. 

However, there hasn’t been a structured set to ensure accountability and track so many opinions. 

Accountability engine TipRanks was founded under one simple question: “Who is worth listening to and who isn’t?” The company’s founders Uri Gruenbaum and Gilad Giat wondered if there was a way to determine whether investors should invest in a stock pundit’s recommendations. No one publishes a weekly poll of the top 25 financial analysts.

Today, TipRanks provides a financial accountability engine that analyzes everything you can find around the web.  “It’s important to note there are other measurements to rank analysts, such as compensation and company prestige,” TipRanks CEO Uri Gruenbaum says. “This platform only evaluates analyst recommendations.”

The firm’s platform allows investors to see analysts’ performance, search stock symbols to see the top- ranked analysts covering that equity, and obtain real-time stock recommendations made by top-ranked analysts and bloggers. 

The company has made some interesting discoveries since its foundation. In addition to noting that the majority of information out there is underperforming, it also has found that the top stock-picking bloggers are outperforming the stock-picking analysts. 

TipRanks plans to analyze the performance of television “experts” later this year, and it has explored discussions with broadcast media about providing meta-data on guest predictions. However, it is unclear whether broadcast executives will embrace this much-needed level of accountability, or if doing so could quickly expose the current lack of quality insight.

Meanwhile, Rishi Singh at trading-platform Tiingo has taken the accountability discussion a step further. Singh has created a number of revolutionary tools that not only help investors make actionable trades and reduce the substantial cost of risk management, but he  also encourages greater transparency and accountability among the trading community.

Tiingo’s community philosophy is simple: less clutter, less noise and more information. A former chemist, quant trader and web developer, Singh envisioned a platform designed to provide retail traders with most – if not more – of the functionality enjoyed by institutional traders.  And Tiingo’s community has been formed with ethics, social integration and accountability in mind.

“This whole thing is based on ethics. Finance screwed over a lot of people in 2008 and that’s fresh on the retail trader’s mind. Google (GOOG) has the mantra,‘don’t be evil.’ In finance, I no longer think that’s good enough,” Singh says. “We have to do good for things that happened in the past. We have to take it a step further and embrace a new mantra: ‘Actively be good.’”

With similar functionality to a Bloomberg Terminal, Singh’s platform allows users to stress test portfolios (an expensive institutional function), to conduct research on funds and to chat with other investors. It also provides educational tools in the form of live podcasts.  Singh has even written a language algorithm designed to curate content from other news sites, but through translation eliminates ones that are considered click-bait or non-relevant information to investors. This holds major news sites accountable for the content of their online articles before readers even open them.

In addition, Tiingo is working to integrate accountability into the conversations shared by users of the platform. Through this platform, users can provide feedback on other users based on their contributions toward the chat discussion. If a chat topic is good, a user can save it into a forum where the data is structured.

Should a user ask an intelligent question or if they offer intelligent insight, they are rewarded by reputation.
Keeping track of a user’s quantitative reputation not only promotes fruitful discussion and education. The community would boost/reduce an individual’s reputation by upvoting/downvoting a discussion.

“This means that a person can harness their digital reputation into one that’s public-facing,” says Singh. “This has worked wonders in the programming and open-source communities, and it will work as such among investors and traders.”

Singh has embraced a user-generated revenue model and continues to add original tools to the site. For what has largely been a one-man operation, the platform is a remarkable tool for investors of all experience levels. 

Investing with confidence

Without widespread credibility and accountability, traditional financial media will continue to broadcast to a declining audience of investors against the backdrop of disruptive new fintech entrepreneurs identifying new means to separate the signal from the noise and empowering investors in their quest to identify actionable trading ideas. Modern Trader will take a leading role in redefining the narrative of the markets, to boost accountability, call out the bad actors and to introduce traders to a new generation of voices and tools that align with this mission.
















































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Modern Trader, William Ziemba





Cybersecurity

Fire-sale: Were Three Leading Organizations Hit By A Global Cyber-Attack?


Dr. Timothy Summers and Dr. Joseph Wall


Real Talk

CNBC Demystified


Doug Litowitz


OTC

Why OTC is Back in Vogue


Edward Lopez



Modern Trader Magazine

Does Your Alma Mater?







TAP Innovation Series

Alpha Pages Innovation Series: Acorns


Garrett Baldwin


Alternative Energy

Yield Cos? More like Yield Can’ts!


Bryan Birsic


Vice Spending

April Vice Index Shows Strong Rebound


Andrew Zatlin


Disruptive Technology

Part II: Possible Hedges Against the Robot Apocalypse


Garrett Baldwin


Disruptive Technology

Part I: Possible Hedges Against the Robot Apocalypse


Garrett Baldwin


Water Investment

Rick Rule: Time to Change California’s Water Policy


Global AgInvesting


Insider Trading

Why The Second Circuit Refuses to Reconsider Its Newman Decision


Jonathan N. Halpern, Ehren M. Fournier


Futures Magazine

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