Allana's Avatar
published in Blogs
Mar 01, 2021

What’s the Difference between Big Data Artificial Intelligence

In the battle of buzzwords, it would be hard to defeat Big Data and Artificial Intelligence. Each occupies significant space in modern print, thought, and conversation, and while big data and AI are different from each other in strict definition, they remain complementary – symbiotic, even.

More formally defined by renowned research and advisory company Gartner as “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation,” big data refers to the idea that almost everything we do – the purchases we make, the internet searches we type, the art we enjoy, the security footage from a convenience store, a photograph – is data that can be collected, examined, and (theoretically) monetized by those who can extract the right insights.

Volume, velocity, and variety – sometimes characterized as the three V’s – are the parameters that define how big data is processed. Looking at big data means examining “high volumes of low-density, unstructured data”, says Oracle in a primer on their website. It requires the capability to receive and react to information at increased velocity, “[operating] in real time or near real time.” It also means having the ability to deal with a wide variety of data, structured and unstructured, that “[requires] additional preprocessing to derive meaning and support metadata.”

Artificial intelligence is an amalgam of different fields (like computer science, logic, neuroscience, psychology, and more) with the goal of creating automated systems that can perform tasks previously requiring human intelligence. AI does so by analyzing vast amounts of data to recognize patterns, in turn using that data to make quick, efficient decisions. It can even “learn” (another buzzword: machine learning) over time through that analysis, retaining insights from information it has examined and using them to glean new ones.

Advances in technology have eased the process of both amassing data and learning from it. AI can now perform natural language processing, which involves analyzing and learning the meaning of human speech; speech and text recognition are advancing in leaps and bounds. It is used in robots in many homes (think Siri or Alexa) and in the systems governing self-driving cars – what feels like the tip of the iceberg.

This ability to pore through, and derive insight from, massive quantities of information means AI is a natural fit for working with big data. AI is typically programmed to perform a specific task –identifying discrepancies in MRIs, for example – at a speed far greater than any human. Once big data is collected and structured, AI reacts to and makes sense of it. The more information available to analyze, the better an AI system works. Big data and artificial intelligence need each other to exist.

 

If You’re Wondering When A.I. Will Start Making Market Predictions…

Guess what – it already is. Hedge funds and large institutional investors have been using Artificial Intelligence to analyze large data sets for investment opportunities, and they have also unleashed A.I. on charts to discover patterns and trends. Not only can the A.I. scan thousands of individual securities and cryptocurrencies for patterns and trends, and it generates trade ideas based on what it finds. Hedge funds have had a leg-up on the retail investor for some time now.

Not anymore. Tickeron has launched a new investment platform, and it is designed to give retail investors access to sophisticated AI for a multitude of functions:

And much more. No longer is AI just confined to the biggest hedge funds in the world. It can now be accessed by everyday investors. Learn how on Tickeron.com.

John Jacques's Avatar
published in Blogs
May 16, 2022
A.I. Stock Market Predictions: Head & Shoulders

A.I. Stock Market Predictions: Head & Shoulders

Statistics for the Head-and-Shoulders Bottom Pattern The days where only hedge funds used algorithms to trade stocks are officially over. Now retail investors can use Artificial Intelligence (A.I.  Here’s an example of the algorithm in action: Late last year, Tickeron’s A.I.
Edward Flores's Avatar
published in Blogs
Apr 29, 2022
How to Become the Millionaire Next Door

How to Become the Millionaire Next Door

The Golden Gate Bridge is always a fixture of these walks too, one of man's most beautiful creations.  As we were walking, at one point she turned to me and said, "Man, I'll never have a million dollars."" My girlfriend is 27 years old and works as a graphic designer, making about $75,000 a year.
Sergey Savastiouk's Avatar
published in Blogs
May 16, 2022
When Is the Next Recession Coming?

When Is the Next Recession Coming?

However, we also know that economists predicted 22 recessions out of 11 that took place since 1945. Are there real recession signs we should watch for?Indeed, the answer is yes, and here are a few very important ones: The first one is almost obvious and known to everyone – it is the Fed.
Sergey Savastiouk's Avatar
published in Blogs
Mar 14, 2023
How to Start Trading Penny Stocks

How to Start Trading Penny Stocks

Penny stocks have long been marginalized within the professional investment community, oftentimes being painted with a broad brush of simply being “too risky.” Leonardo DiCaprio’s depiction of the penny stock peddling conman, Jordan Belfort, in the Wolf of Wall Street certainly didn’t help.Here are four reasons to start trading them now. Reason #1: Let’s State the Obvious -- Penny Stocks are Cheap A single share of Apple Inc. costs over $350.
Dmitry Perepelkin's Avatar
published in Blogs
Mar 14, 2023
5 Habits that Lead to Successful Investing

5 Habits that Lead to Successful Investing

To consistently make money in this industry, you need emotional fortitude, an analytical mind, and a willingness to self-reflect. Despite trading and investing being two different activities, these principles can be applied to both.Conversely, investors with good habits often become great traders.  Rather than full sentences for titles, we’ve labeled each of our top-five investing habits using a single word principle.
Allana's Avatar
published in Blogs
Mar 23, 2023
What’s the Difference Between Data Analytics and Machine Learning?

What’s the Difference Between Data Analytics and Machine Learning?

Artificial intelligence (AI) technology is developing rapidly.Data mining can deliver raw numbers, but it does not necessarily provide actionable insights. Structure is necessary to taking abstract information and extracting commonalities, like averages, ratios, and percentages.
Sergey Savastiouk's Avatar
published in Blogs
Mar 13, 2023
4 Tips for Fast, Effective Stock Analysis

4 Tips for Fast, Effective Stock Analysis

With just a few clicks, an investor can search for individual stocks, categories of stocks, sectors, or investment themes, and then he or she can conduct a full range of technical and fundamental analysis within seconds.All powered by Artificial Intelligence.  Below, we give you 5 tips for fast, effective stock analysis using Tickeron’s Screener.
Sergey Savastiouk's Avatar
published in Blogs
Mar 20, 2023
5 Golden Principles in Investing

5 Golden Principles in Investing

You have enough faith in that stock, based on research, that the return will equal or exceed the investment.  Do unto others.The principles outlined here will ensure that happens.  Principle #1: Diversification Investors can’t be one-dimensional when constructing a portfolio.
John Jacques's Avatar
published in Blogs
Mar 24, 2023
If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

If Hedge Funds are Using AI to Invest, Why Shouldn’t You?

Some of the world’s biggest financial institutions have devoted multi-million dollar budgets to developing algorithms that can find patterns in the market, identify trends, and perform automated trading designed to take advantage of even the smallest price movements. The AI revolution is so big that as it stands today, the world’s five biggest hedge funds all use systems-based approaches to trade financial markets.Indeed, quantitative trading hedge funds now manage $918 billion (according to HFR), which amounts to 30% of the $3 trillion hedge fund industry – a percentage continues to grow with each year that passes.
Sergey Savastiouk's Avatar
published in Blogs
Mar 15, 2023
The five most important Lessons Learned After 10,000 hours of Trading