Liquidity Part Two – Will HFT Designated Market Makers Participate In The Security Token Industry

Please note, this is not intended to be a finished research product. It is meant to be the start of an analysis into the matter of security tokens and how they may be influenced by the broader capital markets in the future.

Our community have asked us more than once whether any academic research has been published on the topic of security tokens. Having noticed a dearth of this type of research, we make a first attempt here.

Market Structure and Trading Characteristics

In Part One of our Liquidity Series, we discuss the surprising (at least for some) phenomenon that up to 60% of the trading volume on the US public equities market is generated by algorithmic high frequency trading (HFT). We remarked that security tokens are often hailed for their ability to provide liquidity in the private markets.

However, much of the security token liquidity that we already take for granted must stem from an institutional class of traders with the firepower to make markets.

The question is, will HFT designated market makers (DMMs) be interested in participating in the security token industry, especially if market capitalizations are much lower than their public stock counterparts?

Introducing Our Analysis Framework

It is difficult for us to independently assess HFT contribution to liquidity absent specific data from an exchange’s market supervision department.

However, we intend to analyze the trading characteristics of publicly traded stocks to assess differences in liquidity across size.

Micro-cap stocks range from $50m to $300m. These are somewhat comparable in size to the capitalization of companies expected to launch STO later in 2019.

Large-cap stocks range from $10b – $200b. These are generally the household name brand stocks that we refer to when we mention the equity market.


  1. We obtain our stocks data from the free database
  2. We use the filter feature to distill seperate data sets of micro ($50m – $300m) and large cap stocks ($10b – $200b).
  3. For each size class we note the number of records.
  4. We use this information to generate a series of 10 random numbers within range, selecting the stocks corresponding to each generated number.
  5. We note information such as the company’s ticker symbol, name, industry, market capitalization, and trading volume.
  6. We create a 6th variable for each stock, intended as a measure for liquidity: volume ÷ market cap, and record the results.
  7. For each stock we calculate simple summary statistics to measure the central tendencies of market cap, volume, and our liquidity variable.


Raw data collected in this analysis:

Summary data collected in this analysis:

Equity Type



Average Market Cap



Average Volume



Average Volume/Market Cap




We seek to better understand the differences in scale between micro and large cap stocks.

Namely, in terms of average market capitalization, we observe that large-cap stocks are 295.79 times as large as micro-cap stocks. In terms of volume, large cap stocks are traded 25.20 times as much as their micro-cap counterparts.

These figures confirm what we would expect: equities that are large enough to be household names achieve significantly higher trading volume. These are the size of equities that we mention in our first piece  which highlights the contribution of high frequency trading to stock liquidity.

What interests us is that these differences in scale are not reflected in terms of liquidity relative to market cap.

We observe another metric, the ratio of trading volume to market cap, which we express as a percentage value.

We note that the average volume/market cap for micro-cap stocks is 0.099% while the average for large-cap stocks is only .008%. This indicates that relative to market capitalization, micro-cap stocks are traded 0.099%/0.008% = 12.375 times as actively as large-cap stocks.

This normalized data is useful for understanding how trading volume is affected by market cap. While in relative terms, micro-cap stocks appear traded more actively, it is clear that the greatest contributor to this figure is not the magnitude of trading activity, but rather the fact that micro cap stocks are rather small. That is, in relative terms, micro-cap stocks are traded 12.375 times as actively as large-cap stocks. However, in absolute terms, micro-cap stocks have valuations that are roughly 296 smaller than large-caps.

Ultimately, what we see from the data is that while large-cap stocks are far more liquid, micro-cap stocks (with market capitalizations resembling those of equity STOs) are punching above their weight class. Whether or not micro-cap liquidity will transfer over to security tokens when the trading infrastructure is fully online remains to be seen.

Further Analysis

In terms of further analysis, we first propose using a larger data set to re-calculate the figures noted in this article to see if values change significantly on account of new random data.

Also proposed is to futher explore the link between security token market caps and small-cap stocks. In other words, what groups of investors tend to invest in small-caps and why? Do we see any interest of awareness in security tokens from these investors?