Predictive Analytics for Stock Investing
Dear MarketStraddle users,
Imagine it is the year 2031. John is ready to commute to work in his self-driving Uber scheduled to pick him up at 9 am. John gets in his Uber and receives a notification soon after from MarketStraddle, telling him that due to unfolding political events in the orient, the probability of his assets in emerging markets to underperform have increased from 30% to 70%, asking him to relocate that capital to a higher performance asset based on probability. John presses yes and continues on to listen to his audiobook, The Odyssey.
As the company’s mission statement states, MarketStraddle sets out to “transform the way people invest.” In the year 2031, we are glad to report that we have reached our goal of giving seed funding to 50,000 groups of investors US$1,000,000 across the US, Ireland, England, Hong Kong, and Singapore, totaling US$50B of net assets. Very importantly, we have been able to prove that people make better investment decisions as a group and outperform the general stock market rather than investing alone. Over the past 15 years, the S&P 500 has returned investors on average 7% annually while the funds managed by MarketStraddle groups have returned on average 15% annually across several investment strategies and markets. Moreover, 30% of the MarketStraddle groups went on to establish hedge funds with most managing over US$2B.
Despite our success, we have learned from many failures. Our risk management team has been able to filter which groups to finance, and we have increased our success rate from 20% to 40% successfully funded groups. Additionally, we have established better systemic risk management measures which reduced our exposure to windfalls by 35%, which reduced our losses well over US$500M. This has made our model more robust improved with financial science, trial and error, and data scientist working with big data.
As envisioned 15 years ago when we started, investment management has moved away from the “solo” trader and star hedge fund manager and transitioned to a collective group of decisions makers, implementing our group decision tools and analytics. Very importantly, we have made it easier for investment managers to use their talent with increased transparency and greater meritocracy. The industry as a whole has started to focus less on hiring analysts from Ivy League universities with high grades and moved towards making hiring decisions based on acumen and talent managing capital.
We have seen many new entrants in the seed funding market for investment groups, particularly algorithmic trading ones. This competition has squeezed our profit margins; however, our data scientist and financial economics teams are developing artificial intelligence based on all the proprietary data we have collected over the years based on behavioral finance. Going forward, MarketStraddle will be using algorithmic trading models for robots to make investment decisions based on predictive analytics and mimic winning trades during different economics circumstances. That way John and others can feel comfortable with the investment decisions they make. We believe that will be our growth driver going forward, and we look forward to continuing to transform the way people invest for many years to come.
Happy investing,
The MarketStraddle team
