Thursday, December 24, 2020

Peak Hype: Timing Cryptocurrency Tops with Social Media Data

From insights.santiment.net

Over the past few years, a growing number of Wall Street and cryptocurrency analysts have started to rely on a relatively underutilized source of information to try and beat their respective markets with: social media.


For obvious reasons, social media is seen as a potential treasure trove of market sentiment information, and the macro analysis of forum messages, twitter comments and other social data to gain an edge has quickly been embraced by veteran quants. However, the ability of this data to actually and accurately predict price trends and develop new market alpha is still hotly contested by many crypto traders.


Hopefully, our latest study might finally put an end to this debate.


Trading Crypto with Social Media Data


At Santiment, we gather a massive amount of information from social media to try and determine its impact on the crypto market. As you read this, our system is collecting all incoming messages from over 1000 crypto-specific social media channels, including hundreds of Telegram groups, crypto subreddits, vetted twitter accounts, professional trader chats not indexed by Google and more.


We’ve already developed various market indicators using this dataset, like our ‘Social Volume’ metric which shows the amount of coin-specific mentions on crypto social media over time:

The amount of ‘Bitcoin’-related mentions on crypto social media over the past year (Source: Sanbase)

Though the initial results looked promising, in the early days of building our social dataset we too weren’t really sure whether this tool will end up producing any actionable insights about the crypto market, or mostly prove to be trivial intelligence or useless noise.

We quickly found out it was going to be the former.


Timing Price Tops by ‘Peak Hype’


The first real clues about the usefulness of social media data came when we created Emerging Trends, a handy list of the top 10 words with the highest growth ih crypto-related social mentions, which automatically updates every hour.

Every hour, our Emerging Trends list calculates the top 10 words gaining the most steam on crypto social media

The initial goal of this tool was to build an easy way to discover fresh and quickly developing topics in the crypto community before they hit the ‘mainstream’, and many of our customers still primarily use it in this way.


However, we quickly discovered that this tool also had a nifty side effect. Whenever a particular coin’s name would appear in the top 3 positions on the list, it usually meant two things:


  1. 1. The coin is experiencing a strong price rally. This, of course, made sense - even in 2020, outside of Bitcoin and Ethereum most cryptocurrencies only ever attract serious attention from the general crypto community during a pump.

  2. 2. A price correction was imminent. Think of this as ‘peak hype’ - the bigger the spike in a coin’s social mentions, the more likely everyone interested in the project has ‘bought in’ already, leaving mostly sell pressure.


This second point was a big deal. If we could prove this to be true beyond anecdotal evidence, it would turn our Emerging Trends tool from a nifty ‘market overview’ tool to an entirely new leading price indicator for cryptocurrencies.


So after more than a year of data gathering - and some nicely executed trades based on this information by the Santiment team and community members - we recently put this theory to a proper test.


The Social Backtest


To stress-test the theory that a high placement on our Emerging Trends list indicated a looming correction, we used a so-called ‘event study’ which analyzes the coin price a set amount of days before and after a certain signal fires, and then averages this price information for all observed signals.


Our signal ‘trigger’ was simple - any time that a coin’s name appears in the top 3 words on our Emerging Trends list.

Recently, the price of TFUEL dropped by -35.87% in the 6 days after showing up on our Emerging Trends list

(One important caveat - the top 5 cryptocurrencies were excluded from this study. Unlike with mid and low-cap coins, the spikes in the mentions of Bitcoin or Ethereum aren’t always purely pump related. They also happen around major project announcements and often near local bottoms as well. The impact of social data on top cryptocurrencies will be the subject of a future study.)


So far, there have been 198 instances that satisfied our selected criteria - a coin’s name appearing in the top 3 positions on our Emerging Trends. So we analyzed the average coin price for these 198 signals - from the 2 weeks before to the 2 weeks after these coins claimed a top 3 position on our Emerging Trends list:

As you can see, there is a sharp increase in the price of these coins before the signal triggers. This further gives legs to our theory that price pumps are in fact the biggest reason why all of these coins suddenly get talked about a whole lot more than usual.


The 0 point on the X axis marks the average price of the analyzed coins on the day that the signal triggers. The most important part of the backtest is what happens afterwards:


Within the next 12 days after a coin claims a top 3 position on our list of Emerging Trends, its price drops by an average of 8.2 percent!


Again - this is on a sample size of almost 200 observed signals.


Now, an experienced analyst would also ask about the behavior of the market itself. Afterall, the market might have been going down anyway, which would’ve contributed to a decline in the prices of these coins.


For this reason, an event study also looks at the market itself and tries to nullify its impact by removing a calculated beta.


What does that mean? The below graph shows the results of our backtest alongside the average price behavior of Bitcoin, used here as a proxy for the crypto market:

With this information, we can now go back and calculate a ‘beta’, or a measure of how much each of our analyzed assets typically reacted to the market. Then, we can use this to remove the market’s impact on their price performance.


With the beta calculated, here are the results of our backtest after we removed the impact of the market from the analysis (in orange):

Even though the downtrend has reduced slightly after the signal triggers, the general behavior remained very much the same. With the overall market impact removed, the analyzed coins lost an average of 6% in the 12 days after appearing on our list of Emerging Trends.


Automated vs Human Signals


The initial results of our event study demonstrate the massive potential of social media information as a leading sell indicator in cryptocurrencies. That said, placing aggregated data in proper market context is key to profitable trading in the long-term. And this is something that no amount of automation can achieve.


This is also why we at Santiment don’t only provide hard data about the crypto market, but also focus on producing daily insights and analysis to contextualize this market behavior in a way that only a human analyst can. You can read our latest market reports and analysis over on insight.santiment.net:

Of course, many of our insights in the past have been inspired by different coins showing up on our list of Emerging Trends. ‘Coin go moon’ is often an interesting starting point to try and explain the fundamental factors that have enabled the rally, and to determine where the coin might go from here.


In a small portion of these insights - or whenever we identify clear trends in both the coin’s social and its on-chain data - we also give explicit SELL calls.


We recently started doing this more often, but for the purpose of this analysis, we looked at 18 insights where we explicitly called a ‘top’ based on the fact that a coin’s name appeared on our list of Emerging Trends.


Here is the price performance of the coins featured in those 18 insights, 2 weeks before and 2 weeks after we wrote about them:

Minus some ebbs and flows, the general pattern is again the same - the coins pump prior to our article(s), and begin to decline shortly afterward. This time, however, the actual size of an average downtrend is much stronger compared to automated signals: in the 12 days after we published our ‘top’ calls, the price of these coins decreased by an average of 18.1%!


The same pattern holds when we calculate the ‘beta’ to remove the impact of the market on the price of these coins:

While the sample size is considerably smaller, this further validates our belief that - in order to truly be effective - market data needs to be interpreted by experienced analysts. Information is power but only in the right hands, which is why the Santiment team and vetted community members publish unique analysis about the crypto market each and every day. Again, you can find all of our market reports and daily insights on insights.santiment.net


Conclusion


As laid out above, the results of our event study clearly showcase the potential of social media data as a leading sell indicator in cryptocurrencies. The second backtest also suggests that an enrichment of data through human interpretation typically yields the best results.


When used to predict downtrends, the appearance of a coin in the top 3 words on our Emerging Trends list suggests an average downtrend of 8.2% for automated signals and 18.1% for human-created signals.


In the future, we will attempt to extend this study to include the largest cryptocurrencies as well, and analyze the predictive power of other social metrics, like our ‘crowd sentiment’ indicators that we have recently introduced to Sanbase Pro.


In the meantime, you can check out Emerging Trends live on Sanbase and try its predictive power for yourself. The tool is still 100% free - for now *wink wink*

Tuesday, December 22, 2020

Bitcoin Rebounds Despite SEC "Attack On Crypto Industry"

 From Zero Hedge:

Cryptos broadly dived overnight as Ripple tumbled on headlines suggesting an imminent SEC lawsuit over XRP sales.

Source: Bloomberg

Since then Bitcoin has rebounded (and so has XRP modestly)...

Source: Bloomberg

CoinTelegraph's Jon Rice reports that Ripple will be sued by the United States Security and Exchange Commission for allegedly selling unlicensed securities in the form of XRP tokens, according to Fortune.

image courtesy of CoinTelegraph

In a move reminiscent of Coinbase's recent front-running of a New York Times expose of its alleged treatment of employees of color, Ripple CEO Brad Garlinghouse has taken the unusual step of posting to Twitter to seemingly legislate the issue in the court of public opinion.

“It’s not just Grinch-worthy, it’s shocking,” said Garlinghouse.

“It’s an attack on the entire crypto industry and American innovation.”

Bitcoin (BTC) and Ether (ETH) have both escaped SEC enforcement due to their decentralized nature. However, XRP, the token associated with Ripple, has long been criticized by some members of the crypto community as highly centralized. Ripple has maintained an escrow account of around 50 billion XRP, or around half of the total supply, which the company's chief technical officer David Schwartz claims to have been "gifted" by the creators of the third-largest cryptocurrency.

Despite class-action lawsuits and acrimonious splits between the original founders, Ripple has survived to become one of the fintech industry's richest companies, with a reserve — primarily held in XRP — that could theoretically be worth almost $25 billion, even after a dramatic 13.5% drop in the price of the cryptocurrency token following the news of the potential lawsuit.

A source with connections to Ripple told Cointelegraph:

"There's no way it [XRP] is not a security."

Ripple posted a Wells submission document to its website explaining its position, claiming, "By alleging that Ripple’s distributions of XRP are investment contracts while maintaining that bitcoin and ether are not securities, the Commission is picking virtual currency winners and losers, destroying U.S.-based, consumer-friendly innovation in the process."

The company continued to allege, without evidence, that Bitcoin and Ether are "two Chinese-controlled virtual currencies that the SEC has stated are not securities," and that "innovation in the cryptocurrency industry will be fully ceded to China" should the potential lawsuit brought by the SEC be successful.

According to Fortune, both Garlinghouse and co-founder Chris Larsen, whose combined wealth is estimated at $13 billion, are expected to be named as defendants in the possible lawsuit.

Although Garlinghouse has stated that Ripple would continue to thrive even with a security designation for XRP, the company has recently claimed to be seeking new headquarters outside of the United States, claiming that a lack of regulatory clarity was forcing its hand.

Cointelegraph reached out to Ripple for comment on whether Larsen and Garlinghouse would stay in the United States in light of the potential lawsuit, and had not received a response at the time of publication.

Monday, December 21, 2020

Pork City: Here Are The Most Ridiculous Pet Projects In $900 Billion Stimulus Package

 From Zero Hedge:

As Congress prepares to pass a $900 billion COVID-19 stimulus bill rolled into a consolidated appropriations package - with funding for assistance for households and businesses, along with vaccine distribution and other pandemic-related measures, the bill also includes a ton of pork per usual.

We already know about the $600 checks for each adult and dependent. This time, however, 'mixed-status' households where eligible citizens live with illegal immigrants, will not only receive payments - they can retroactively claim benefits after being left out of the last round.

Illustration via WSJ.com

And now, on to the pork... which includes billions to foreign countries, US military weapons purchases which go above and beyond their budgets, $40 million for the Kennedy Center, and nearly $200 million so that federal HIV/AIDS workers overseas can buy cars and car insurance, among other things.

FOREIGN HANDOUTS:

minimum of $3.3 billion in grants to Israel.

Also included is $453 million to Ukraine, on top of the $400 million Trump eventually released. No word on how much of that goes to the 'big guy.'

$10 million for "gender programs" in Pakistan.

$1.3 billion to Egypt, and $700 million to Sudan.

$135 million to Burma, $85.5 million to Cambodia, $1.4 billion for an "Asia Reassurance Initiative Act," and $130 million to Nepal.

BOMBS AWAY

$4 billion for Navy weapons procurement, $2 billion for Space Force and $2 billion for Air Force missiles.

BUREAUCRATIC BONANZA AND OTHER MALARKEY

$208 million to upgrade the Census Bureau's computer systems (which couldn't have waited until the next count in 2030?).

$40 million for the Kennedy Center, and funding to discourage teenagers from drinking and hooking up.

$193 million for federal HIV/AIDS workers to buy cars and car insurance overseas, and a feminist museum.

Funding for a commission to educate consumers "about the dangers associated with using or storing portable fuel containers for flammable liquids near an open flame." (What?)

Just remember, $600 is a significant amount...


Do Mask Mandates Work? New Analysis Suggests They Don't

 From Zero Hedge:

Do mask mandates work? As we've noted repeatedly in recent months, evidence is piling up that they do not.

According to analysis by data expert Justin Hart, who has been following COVID-19 data for months, demonstrated in a Sunday Twitter thread that states with mask mandates had a greater number of COVID cases per 100,000 people than states without mandates.

See thread below:

And while there were some objections to Hart's analysis - such as whether there might be bias towards getting tested for mask-wearers, or regional differences in population density, many of the replies to Hart's thread support his findings:

And a hypothesis: 

Maybe the CDC, WHO, Dr. Fauci and the Surgeon General were right in February when they said masks don't work? On the other hand, they're so useful for other things...

Sunday, December 20, 2020

How Belarus Exposes the Lockdown Lie

 From Off Guardian

Most European governments instituted the shutdown of economies, restrictions on freedom of movement and other policies known as lockdown. This was allegedly in response to the spread of Sars-Cov-2, a dangerous respiratory virus that originated in Wuhan, China.

Few countries rejected this approach; Sweden is the most well known of these. However, a more interesting case of dissent from the official narrative is Belarus and its leader Aleksandr Lukashenka.

This article will outline Lukashenka’s approach to the alleged pandemic, followed by an analysis of death figures and how the Belarussian case exposes the lies of lockdown advocates.

THE BELARUSSIAN APPROACH TO COVID 19

The alleged pandemic broke out in Europe in March 2020, and most European governments followed the severe strategy of imposing lockdowns. Lukashenka’s response was much more limited. A Belarussian press release from the 25th March talks about the quarantines set up for people who enter Belarus:

Quarantine stations were set up at all the points of entry. Screening measures include temperature checks. This system of control really works, [healthcare minister] Vladimir Karanik noted. This helped identify symptoms of a viral infection in more than 250 people, however the absolute majority of them had influenza, parainfluenza, and adenovirus. If a person tests positive for coronavirus, healthcare workers put their contacts under medical observation. “Such a targeted approach helps curb the spread of the virus,” the minister said.”

Lukashenka also advocated staying at home if one has symptoms of the virus. He also famously made some comments – reported widely in the Western media – giving health advice:

I am teetotal, but in recent times I say jokingly, that it is necessary to not only wash hands with vodka, but probably that [consuming] 40-50 grams of a measure of clean spirit a day – [can] “poison” [in commas in original text] this virus. But not at work.” He then says that “Today, go to the sauna. But if [you go] two-three times a week that is even healthier. The Chinese have told us that this virus cannot withstand temperatures of 60 degrees”.

Overall, the Belarussian approach has been the least authoritarian in Europe. Belarussian football went ahead as normal and fans were allowed to continue attending games. Theatres, cafes and other social events continued and there was no shutdown of the economy. Victory Day Parades also went ahead on the 9th May despite being cancelled in countries such as Russia. Neither did Lukashenka delay scheduled elections, unlike Jacinda Ardern of New Zealand.

Western media treated Lukashenka’s approach as a laughable curiosity (in cases where they did not ignore it entirely). They mocked Lukashenka’s comments about vodka and saunas, using this was a way to avoid asking any deeper questions.

According to the official narrative, Belarus should have been a zone of death, destruction and disaster. Neil Ferguson’s modelling – one of the key pieces of propaganda used to put Britain in lockdown – predicted that left unchecked Covid 19 would kill between 54,090 and 71,616 Belarussians.

So what are the facts?

COVID DEATHS AND BELARUS

The population of Belarus is around 9.5million. Of this population, as of December 12, 2020, a total of 1,263 deaths are recorded as being from Covid 19. It appears the first death in Belarus attributed to this disease was Mar 31, with between 2 and 11 deaths recorded each day up until Dec.12.

It goes without saying that 1,263 deaths out of a population of 9.5m is minuscule and hardly indicative of a deadly pandemic sweeping the country. But critics of the Belarussian approach may claim that Lukashenka is hiding the reality of Covid 19 deaths in the country.

The most logical way to examine this question is to look at whether there are any excess deaths in Belarus in general over this period, and if so, how many. Of course, just because there were excess deaths would not prove that the deaths were caused – or otherwise – by hidden cases of Covid 19. But a relatively low number of excess deaths would reveal that the claim that Lukashenka is hiding mass deaths from Covid 19 is not plausible.

According to the data, there were some excess deaths in Belarus in the second quarter of 2020 (April, May and June). 35,858 died in Belarus during this period, 5606 higher than in 2019. Examining the data, we can see that the vast majority of these excess deaths were in June, with virtually none in April and a small excess in May.

This figure is rather small compared with the predictions of doom and destruction put forward by the likes of Neil Ferguson.

BELARUS VS ENGLAND AND WALES

A comparison with another country that did pursue lockdowns gives further evidence that the scaremongering predictions regarding the consequences of not locking down are unfounded.

This analysis was performed by taking the number of excess deaths for Belarus and then calculating the same figures for England and Wales from the weekly death data from 2019 and 2020. Belarus had 5605 excess deaths in April, May and June 2020 from a population of 9.5 million. England and Wales had 54,798 excess deaths in the same period from a population of 59.5 million.

The population of England and Wales is 6.26 times larger than that of Belarus, so dividing the 54,798 figure by 6.26 gives a result of 8754. If Belarus had the same excess death rate as England and Wales another 3,149 deaths in Belarus would have been observed. Or to phrase this data another way, if England and Wales had the same excess death rate as Belarus, there would have been 19,711 fewer deaths over the period.

The BMJ’s article on Belarus: Saving the Case for Lockdowns?

This evidence looks damning for lockdown supporters. However, there is one attempt to explain the low Belarus death rate despite the fact that there was no lockdown there, printed in the British Medical Journal. The article puts forward four reasons why Belarus has a low death rate, some of which offer comparative data with the UK.

The first reason given in the article is that Belarus has a much higher amount of beds per capita – 11 per 1000 as opposed to the UK’s 2.5 per 1000.

Health services generally strike a balance between having enough beds available to deal with a crisis, and not so many that money is being wasted on unnecessary beds. The argument can be made that the NHS gets the balance wrong and leans towards having too few beds per capita. For example, the UK had a large number of flu cases in the 2017-2018 season with hospitals having high bed occupancy rates.

However, bed occupancy in the UK significantly decreased due to the lockdowns and NHS policy of discharging as many patients as possible. On the 13th April, a few weeks into lockdown, acute beds were 40% unoccupied. This hardly suggests a health service that would have been totally overwhelmed had it not locked down (for comparison, NHS beds are usually 90% full). It may actually have been the case that the lockdown cost lives by cancelling treatment, expelling people from hospitals and promoting a fear based message that discouraged people from seeking treatment.

Another main argument of the article is that Belarus has a small number of elderly people in care homes (it has 203 per 100,000, as opposed to the UK 854 per 100,000). It is true that a respiratory pathogen will find it easier to spread in an environment like a care home because of the close proximity of vulnerable individuals. It is also true that the UK had a large number of care home deaths during this period.

However, the UK government policy towards care homes likely contributed at least some of the excess deaths caused during this period. People in care homes were routinely denied hospital treatment and were unable to get access to GPs. The lack of visits by family caused many elderly patients to mentally give up and their condition deteriorated. Any deaths that resulted from this, therefore, cannot be attributed to a virus but government policy.

The argument also fails as a motivation for lockdowns. If the majority of deaths are in the fairly contained environment such as a care home, locking down the whole society, such as closing shops and sports events, is going to have no effect on transmission within that environment.

Two other reasons given in the article – the better Belarussian testing system, and the lack of interest in Belarus as a travel destination – also do not have any bearings on whether lockdowns are an effective strategy.

There is no evidence of people with a positive test but no symptoms being infectious. It follows that testing more people isn’t going to lead to fewer deaths, so this cannot explain the low Belarus death rate without a lockdown. Belarus did carry out quarantine measures, whereas the UK continued to allow flights into the country.

The piece argues that it is easier for Belarus (than the UK) to close its borders because it is not a major travel destination, which is true, but it can’t seriously be argued that setting up quarantine measures costs more than shutting down the entire country. Once any hypothetical virus is also present in a country in significant numbers quarantine also becomes irrelevant.

CONCLUSION

The Belarussian case is a significant problem for those individuals who argue that lockdowns were necessary to prevent mass deaths from the deadly Covid 19 pandemic. The limited measures taken in Belarus meant a lower death rate than lockdown supporting England and Wales. There are also no clear arguments as to why Belarus is so unique it could go without lockdowns while other countries had them.

Given the cost to the economy and mental wellbeing of imposing lockdowns, as well as the draconian restrictions on basic liberties, these facts strongly suggest that leaders that did impose lockdowns have a case to answer from their citizens.