Market restructure in the age of Alternative Data

February 15th, 2022 4 minutes read

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As more efforts have been made to make trading even more efficient with the use of data, the market has become even more difficult to navigate. Information surrounds traders 24 hours, and so it becomes more and more difficult to differentiate. Moreover, traders not only get their information from various, imbalanced sources, as Bloomberg, brokers or a combination of these sources, but also the amount of information that is being accumulated is reaching numbers or hundreds of zetabytes. More than ever market participants have to rely on news from non-traditional sources.

In order to seek efficiency in the trading space, one should look at the drivers of answers. The asymmetric structure of credit assets makes them dependent on microeconomic factors. Thus, their payoff depends on market risk, in how they can drive specific corporate and market risk away, which can be encapsulated into distance to default and distance to liquidity. Since both of these two elements are non-linear, the nature of credit deals is non-linear, which implies that asymmetric information can have a great influence on the value of the deal. A small distortion in data can represent significant valuation results.

A way of mitigating risk is cleaning and validating data, as well as evaluating how irrelevant information pollutes decision-making and how to solve this. The ultimate goal is to look for unique, efficient alpha. A solution could be found in repetitive frameworks are things that should be standardized as they are generic and could be copied. Such frameworks may enable traders if they are integrated with traders’ unique information. However, investors need to integrated their “internal” data with external one.

One way to solve this problem is to have a natural party closer to the facts, such as generic data. Such a party needs to possess two characteristics: (a) be neutral to the trading action as much as possible, and (b) be close to the facts about the trade as much as possible. These two characteristics mean that such a party needs to provide the trading counterparties the same information at the same time.

A reliable, non-centralized, deal handling way, can be found in smart contracts in blockchains. On blockchain, the goal of a smart contract is to simplify business and trade between both anonymous and identified parties. It significantly reduces the need for middlemen. A smart contract scales down on formality and costs associated with traditional methods. It does so without compromising authenticity and credibility by keeping transactions statistically guaranteed. Depending on its implementation it offers security, near real time execution, transparency, confidentiality and accuracy. 

Coordinating the two processes is essential for a proper market design.  While data comes from many different sources and deals can as well, the objects are different and require different consolidations. Having a central data distribution saves time to produce results. Having a central deal distribution less so. The longer traders are on the chain, the more informed they become and thus the network effect is natural.Such centralized structure of filtering and distributing data will bring liquidity to currently very illiquid assets. 












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