In 2020 retail investors set new records of stock market participation, artificial intelligence continues transforming investment research, investment firms rely on alternative data in an environment of extreme uncertainty, and even the most secretive and conventional financial institutions have to face the new reality of managing remote workforce.

All these major changes are also monetizable opportunities for fintech entrepreneurs.

1. Best investment ideas platform-alpha capture meets social trading.

Automated alpha capture systems enable professional research analysts who work for investment banks and broker dealers to submit trading ideas in a standardized electronic format. Buy-side firms pay for those ideas…


“Man vs machine” has been a popular discussion in the investment management industry in the last few years. The proponents of the cutting edge technology application to portfolio management claim that algorithms are more efficient and less prone to emotional biases than human investors. They even believe that some day in the not so distant future, artificial intelligence will completely take over the entire industry of active asset management leaving intuition based fundamental investors behind.

Their opponents, equally smart and experienced financial experts, argue that AI no matter how advanced, will never be able to figure out the ever…


A big part of a data vendor’s value add comes down to productization, i.e., creating a data product that is usable and meets the end user’s needs.

But often data vendors have an incorrect perception of what the end user is looking for, and tend to run to one of the two extremes: They either sell raw, messy data with minimum (if any) pre-processing and some major quality issues to fix, or they attempt to create ready-to-use trading signals and composite scores.

Of course, over-processing data is risky, as it may accidentally remove the insights that traders are looking for…


According to media headlines, hedge funds spend millions on alternative data. Cost of alternative data sets is one of the most popular discussions at industry events. New vendors are struggling to determine the right price to charge, and data buyers complain about lack of transparency when it comes to pricing.

In search of a meaningful formula, data vendors came up with an AUM-based model. The logic behind it is that larger funds make larger bets and make more money using the data set. …


Last week at Beryl Elites Alternative Investment Conference 2018, we started our panel discussion about finding an informational edge with the definition of alternative data. Turns out, in a highly heterogeneous and unstructured alternative data market, even the definition is not standardized.

Most people think of alternative data as a very niche esoteric segment of unstructured data that was created recently and has not been used in the investment process before. The most common examples usually include geolocation, satellite images or social media feeds. …


Data sourcing is not all about finding alternative data vendors. Identifying potentially interesting data sets is only the beginning of the long path from data to alpha. In fact, now that so many alternative data products are available on the market, the biggest challenge is how to evaluate them, select the ones worth using and implement new data sources in the existing research process.

According to a recent report “A buyer’s guide to alternative data” by Greenwich Associates, it could take two highly-paid quantitative engineers on average 85 person-hours to assess a new alternative data source. In our company (as…


“Alternative data” recently became a buzzword. Asset managers are now actively using data initially intended for marketing, surveillance, supply chain management, etc., in their investment decision-making process. Hedge funds already spend more than $170 million annually on alternative data, and this spending is expected to exceed $7 billion annually by 2020.

Quantitative asset managers were natural early adopters since they were accustomed to data-driven investment process. Big quant firms employ dedicated teams to source and analyze alternative data sets; some even build their own data evaluation platforms.

Despite the growing demand, alternative data is not necessarily an easy sell. For…

Olga Kane

Managing Director at www.synthesis.im

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