Wealth inequality is a serious problem. While rectifying the wealth gap has long been a core tenet of the ideological left, it has - in recent years - become a concern across the political spectrum. According to pre-pandemic , 61% of Americans view inequality as a concern; since the start of Covid-19, the inequality problem . polling from Pew has only metastasized While it’s one thing to note an obvious problem, proposing solutions to such a problem can be much more difficult. Thus far, most of the potential solutions to inequality have come from the progressives, who advocate for a redistributive model, specifically taxing the profits of the wealthiest individuals and institutions and giving the money to the 99%. While this model certainly has appeal - after all, why shouldn’t those benefiting from their entrenched positions atop the financial system pay their so-called fair share? - I believe that there is another approach that, at the very least, deserves equal consideration to the government-led taxation model: Guaranteeing equal access to sophisticated financial tools. Most people focus on the inequality of economic outcome: An inequality-of-ends. However, there is a lesser scrutinized inequality of means. The reason we see so much wealth concentrated at the top is largely due to the dichotomy between how wealthy individuals and “regular” people manage their investments and benefit from financial technology. Algorithmic Trading Before we go further, a history lesson is in order: For the majority of the twentieth century, investing was an analog activity. Humans on trading floors were the sole executors of trading strategies. While those with money and power may have been able to afford the most capable and experienced money managers, the fact remains that there was relative technical equity, across the financial system. In the latter decades of the twentieth century, as computing power grew exponentially, the nature of trading changed. Computer algorithms, programmed to process previously unfathomable amounts of data and react with inconceivable speed to changing trends, became the centerpiece of the financial system. These algorithms now dominate most markets. According to some estimates, trading volume is done via algorithm. In other sectors, such as , the percentage is even higher.  Today, those who control the algorithms control the market. nearly 75% of the equities market foreign exchange Inequality in Trading The result of the finance industry's pivot toward tech is noticeable, even resulting in a whole new portmanteau: FinTech. Hedge funds, big banks, and other institutional wealth managers derive their power from technology. It is no coincidence the power of these financial institutions ballooned, as tech became increasingly intertwined in the day-to-day operations of these institutions. The investing reality for a typical retail investor or day trader stands in stark contrast. The average person does not actively utilize algorithmic trading. While the digital revolution has come to day trading, in the form of apps like eToro and Robinhood, these apps have only changed the way investors interface with the trading system. These apps haven’t provided retail investors with any additional computational power. Retail investors active on Robinhood and similar platforms have to make decisions based on their own views of the market. This is inherently reactive. Whereas a computer can react to market movements imperceptibly fast, people are slow to process data and sort through the potentially flawed suggestions of their social circles. In a contest between a human brain and a computer, the computer will always win. Ultimately this means that popular platforms used for retail trading aren’t up to par with the tools used by the 1%. It is no wonder that wealth inequality compounds when retail investors sit at such a profound investing disadvantage. Reinvigorating Competition When it comes to solving inequality, most people don’t want a handout. What they want is a level playing field. The solution to investing inequality is simply to build trading algorithms for the people. Building 1% tools for the 99% is easier than it sounds. Not only do investors have access to a previously unimaginable amount of quantitative data, but - through the use of technically accessible interfaces - investors can build customizable trading tools, with little backend knowledge. Equalizing access to investor resources isn’t a silver bullet solution to inequality - but it's a necessary start to rebuilding a financial environment conducive to the self-starting, innovative ideals upon which our country has grown and thrived.

Retail Trading Tech Trends, the Positive Impacts, and More

Sign up with Pluto today!

Read My Stories

Too Long; Didn't Read

Boost your HackerNoon story @ $159.99! 🚀

Fintech-Populism: Using Technology to Level the Financial Playing Field

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Untitled Story

Q&A with Pluto Co-Founder and CEO Jacob Sansbury

10 Indications That You Should Invest in Automation Via APIs

10 Commandments for AI-Assisted Social Media Marketers

11 Best Automation Testing Tools to Try in 2021

12 Use Cases of AI and Machine Learning In Finance

Q&A with Pluto Co-Founder and CEO Jacob Sansbury

10 Indications That You Should Invest in Automation Via APIs

10 Commandments for AI-Assisted Social Media Marketers

11 Best Automation Testing Tools to Try in 2021

12 Use Cases of AI and Machine Learning In Finance

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps