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Feb 10, 2021

One Reason Everyone Needs Blockchain

One Reason Everyone Needs Blockchain

Big data rules the world. Our everyday lives are filled with products – the smartphones we can’t live without, the websites we browse, even the thermostats in our homes. These smart products gather raw data for companies to store, analyze, and use, and then the raw data takes on exponentially greater value as more and more companies find increasingly efficient and intelligent ways to mine and interpret it. So why are big companies, not individuals, the ones who seem to profit? Blockchain may change this outcome.

A big advantage

The world’s largest companies (like Facebook, Netflix, Google, and Apple in the US and Alibaba, Baidu, and Tencent in China) have a significant advantage in the race to accumulate data because of their size – they have the vast reach, and by extension the capital, to collect, store, and analyze the massive amounts of information they gather. They also have the resources to hire the cream of the crop in data science and AI, who then build models to understand the data. The more data stored and analyzed, the more accurate the model. The result is self-fulfilling prophecy – the biggest and best get bigger and better. 

Is that really a bad thing?

The fact that large companies have taken advantage of their resources to better interact with data is not inherently negative, nor surprising. But there are problematic aspects to their dominance – one major one is that the barrier to entry becomes so high that innovation is limited to the companies with the capital to get involved. It also means that important information about their AI models remains behind closed doors. This isn’t an issue when it comes to our interactions with Siri, but it is significant when multiple publications detail how an AI model used for helping to sentence criminals is racially biased, and the manufacturer of the model refuses to discuss its makeup or allow others to examine the nuts and bolts that contribute to its behavior.



So, what can be done?

There is a potential way to neutralize, or at least lessen, these advantages – blockchain. Blockchains are defined most simply as structures of data linked and secured using cryptography, and they have potential to shift more and more power to algorithm builders and everyday people. They provide a way to take ownership of personal information in a world where data is commoditized; additionally, they offer a method to make information available to AI builders who may not work at a large company. The potential result is more accurate AI models, with the benefit of security and transparency.

Multiple networks exist that aim to reward people for sharing their information in a decentralized data marketplace – we will focus on Ocean Protocol, SingularityNet, SEED, and Tickeron.

Ocean Protocol

Ocean Protocol’s goal is to build a “decentralized data exchange protocol and network that incentivizes the publishing of data for use in the training of artificial intelligence models.” In layman’s terms: you are compensated (in Ocean tokens) if you upload data to the Ocean network and your personal data is used to train AI models.

This is valuable for multiple reasons. Take a Nest thermostat – Nest is constantly sending information from its users to Google, who receive it for free. With their significant resources, it wouldn’t be a stretch to imagine the company building an AI service that, through data, identifies when to contact you about replacing your windows. With a decentralized marketplace like Ocean’s, an ambitious AI scientist can license your data and use it to build their own service. Through blockchain, there is a cost-effective way to lease or buy your data while signifying clear ownership and maintaining data integrity (by confirming it is from a trusted source). Everyone is happy, and the risk of bias or error in the data is minimized by transparency.


SingularityNet is working to be the first AI-as-a-service, blockchain-based marketplace. Their goal is to help the enterprising AI scientist in our previous example sell or rent her model to other scientists to use with their datasets. A search engine even helps users to find and integrate a model with additional complementary models. This would be useful if, for example, AI scientist #1 wrote a model studying home energy markets in San Francisco. Scientist #1 could combine that with models studying Oakland, Palo Alto, and San Jose, providing additional insight into energy consumption. Blockchain makes it clear the model is Alice’s intellectual property, and she would be compensated in SingularityNet tokens when someone uses her model. 


SEED is working to help us trust the increasingly-popular bots (think Apple’s Siri or Amazon’s Alexa) around us. As the bot market grows, according to SEED, from an estimated “$3 billion to $20 billion by 2021”, the chance of encountering a biased, inaccurate, or hijacked bot increases. SEED has established an open-source, decentralized network where any bot interactions can be viewed and verified. It provides the skeleton necessary to ensure that information fed into the bot can be assigned to an owner, who can then be compensated. Their marketplace allows bot creators to license or sell their builds to those who might need to use them, and their tokens compensate creators and data owners for the value they create within the SEED network. These services mean higher confidence in the quality of the bot and greater protection for user’s data.


Investors know that flipping on CNBC at any given time during the day means hearing a wide array of market forecasts and predictions. Whether it’s a stock or an industry that’s headed skyward or due for plummet, the sheer volume of advice is mind-boggling. Tickeron identified this as a major issue when it comes to financial intelligence, which Tickeron calls “FinIP.” How can the consumer know that they’re getting advice from a pundit or market analyst who is trustworthy, smart, and most importantly, who is right more often than they’re wrong? As it stands today, there is very little accountability for the talking heads who give all sorts of financial advice on a daily basis. That creates a problem for the consumer, because it is impossible to know which advice is actually valuable. 

But there is another problem in the world of FinIP – it is really only the behemoth Wall St. firms with huge marketing budgets who get traction on the web. What about the data scientist or quant who has no marketing budget but who has built a platform that can beat the market? How can they show the world of consumers and investors how successful their platform is? And most importantly, what mechanism exists for giving the consumer a trustworthy account of the advisor’s track record? 

Tickeron is seeking to use blockchain to change how the world of financial advice works. They are an SEC-regulated internet financial advisor that has developed a decentralized “marketplace” of artificial and human intelligence for the financial industry, where advisors and people making predictions have their track records logged and evaluated. The end result is having all of the participants in the marketplace establish verifiable seller reputations, which makes it easy for the consumer to know whose advice is superior. Tickeron’s marketplace would also establish a “protocol of commerce,” which would create a secure exchange between the creators of financial intelligence and consumers of it. 

A Promising Future

Blockchain-based AI is still in its nascent stages, but as blockchain becomes mainstream, increasingly more data will hit decentralized marketplaces. Everyday people will be able to monetize their personal data, developers will be rewarded for their contributions to the marketplace, and open, transparent systems will be the rule, not the exception.

Related Ticker: NFLX

NFLX's MACD Histogram just turned positive

The Moving Average Convergence Divergence (MACD) for NFLX turned positive on February 29, 2024. Looking at past instances where NFLX's MACD turned positive, the stock continued to rise in of 49 cases over the following month. The odds of a continued upward trend are .

Price Prediction Chart

Technical Analysis (Indicators)

Bullish Trend Analysis

The Momentum Indicator moved above the 0 level on February 14, 2024. You may want to consider a long position or call options on NFLX as a result. In of 84 past instances where the momentum indicator moved above 0, the stock continued to climb. The odds of a continued upward trend are .

Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where NFLX advanced for three days, in of 319 cases, the price rose further within the following month. The odds of a continued upward trend are .

The Aroon Indicator entered an Uptrend today. In of 270 cases where NFLX Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are .

Bearish Trend Analysis

The RSI Indicator has been in the overbought zone for 1 day. Expect a price pull-back in the near future.

The Stochastic Oscillator demonstrated that the ticker has stayed in the overbought zone for 5 days. The longer the ticker stays in the overbought zone, the sooner a price pull-back is expected.

Following a 3-day decline, the stock is projected to fall further. Considering past instances where NFLX declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .

NFLX broke above its upper Bollinger Band on March 01, 2024. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.

Fundamental Analysis (Ratings)

Fear & Greed

The Tickeron Price Growth Rating for this company is (best 1 - 100 worst), indicating outstanding price growth. NFLX’s price grows at a higher rate over the last 12 months as compared to S&P 500 index constituents.

The Tickeron PE Growth Rating for this company is (best 1 - 100 worst), pointing to outstanding earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.

The Tickeron SMR rating for this company is (best 1 - 100 worst), indicating strong sales and a profitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.

The Tickeron Seasonality Score of (best 1 - 100 worst) indicates that the company is fair valued in the industry. The Tickeron Seasonality score describes the variance of predictable price changes around the same period every calendar year. These changes can be tied to a specific month, quarter, holiday or vacation period, as well as a meteorological or growing season.

The Tickeron Profit vs. Risk Rating rating for this company is (best 1 - 100 worst), indicating well-balanced risk and returns. The average Profit vs. Risk Rating rating for the industry is 88, placing this stock slightly better than average.

The Tickeron Valuation Rating of (best 1 - 100 worst) indicates that the company is significantly overvalued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (12.937) is normal, around the industry mean (5.314). P/E Ratio (51.182) is within average values for comparable stocks, (88.464). Projected Growth (PEG Ratio) (1.634) is also within normal values, averaging (2.952). Dividend Yield (0.000) settles around the average of (0.125) among similar stocks. P/S Ratio (8.210) is also within normal values, averaging (4.020).

Notable companies

The most notable companies in this group are Netflix (NASDAQ:NFLX), Walt Disney Company (The) (NYSE:DIS), Roku (NASDAQ:ROKU), Paramount Global (NASDAQ:PARA), iQIYI (NASDAQ:IQ), AMC Entertainment Holdings (NYSE:AMC), HUYA (NYSE:HUYA).

Industry description

Movies/entertainment industry include companies that produce and distribute motion pictures, and companies that operate general entertainment facilities like amusement parks and bowling centers. Some companies in this industry also have professional sports franchises. Live Nation Entertainment, Inc., Liberty Media Corp. and Viacom Inc. are some of the biggest companies in this space.

Market Cap

The average market capitalization across the Movies/Entertainment Industry is 8.77B. The market cap for tickers in the group ranges from 134 to 268.03B. NFLX holds the highest valuation in this group at 268.03B. The lowest valued company is LRDG at 134.

High and low price notable news

The average weekly price growth across all stocks in the Movies/Entertainment Industry was 2%. For the same Industry, the average monthly price growth was 3%, and the average quarterly price growth was 4%. GOAI experienced the highest price growth at 170%, while ICABY experienced the biggest fall at -44%.


The average weekly volume growth across all stocks in the Movies/Entertainment Industry was 26%. For the same stocks of the Industry, the average monthly volume growth was 59% and the average quarterly volume growth was -24%

Fundamental Analysis Ratings

The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows

Valuation Rating: 52
P/E Growth Rating: 60
Price Growth Rating: 51
SMR Rating: 84
Profit Risk Rating: 87
Seasonality Score: -6 (-100 ... +100)
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Correlation & Price change

A.I.dvisor tells us that NFLX and ROKU have been poorly correlated (+32% of the time) for the last year. This A.I.-generated data suggests there is low statistical probability that NFLX and ROKU's prices will move in lockstep.

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