Archives 2018

Don’t Be Fooled by CVS’s New “Guaranteed Net Cost” PBM Business Model

Summary:

The pharmacy benefit manager (PBM) CVS Caremark has offered its self-insured corporate clients an alternative business model called “Guaranteed Net Cost”.  The pricing scheme features 100% pass-through of drug rebates and the end of rebate retention as an opaque source of PBM gross profits.

But, CVS has glossed over the fact that their “guaranteed net cost” price to plans is not the same as the net costs to them.  Until CVS tells us otherwise, the new business model allows for a opaque markup on top of PBM net cost. In graphs below, we demonstrate how a markup of guaranteed net costs serves as an opaque offset to foregone rebate retention.  

It is naive to think that CVS Caremark is about to give back a significant source of its annual gross profits without some sort of offset. In fact, CVS admits as much as their spokesperson is quoted as saying

CVS’ manager of corporate communications, Christina Beckerman, told Fierce Healthcare that the company does not expect CVS Health’s profitability to increase or decrease as a result of the shift to 100 percent pass-through rebates.

It is not even clear that CVS’s new business model lessens the incentives to Pharma to inflate list prices in order to compete on rebates for formulary placement.

The Problem With the Current PBM Business Model

The current PBM reseller business model features five major streams of revenue and gross profits.  Four of the five are opaque.

  1. Opaque rebate retention % on speciality (biotech) drugs in return for preferred or exclusive placement on formularies;
  2. Opaque rebate retention % on small molecule brand drugs in return for preferred or exclusive status on formularies;
  3. Opaque profit margins on 90-day generic Rx filled by captive mail order operations of the PBM;
  4. Opaque “spread margins” added by the PBM on top of reimbursements to retail pharmacies included in their networks;
  5. Transparent claims processing and data fees.

The opacity of drug rebates is magnified by the fact that reimbursements for brand drug Rx and related rebates come at different times.   It is impossible for plans match up these two streams and calculate a single net price its pays per drug.

Since the early 2000s, PBMs have continually come under attack for not acting in the best interest of their clients.  We have written a number of papers since 2004 pinpointing an opaque reseller business model as the source of this misalignment.

The PBM reseller business model is in stark contrast to two other transparent business models used by managed care companies:  

  1. a PMPY fee-for-service agency model where 100% of all reimbursements and rebates are passed through to plans.
  2. a risk-based insurance model with capitated premiums paid by plans.

Until the PBM Medco’s merger with Express Scripts in 2012, Medco’s financial 10-Q and 10-K reports to the SEC broke out gross rebates received — a credit to cost of sale — and rebates retained — a credit to sales.  We were able to calculate with certainty Medco’s “rebate retention rate”, a name we coined fifteen year ago in 2003.

We calculated that Medco’s rebate retention rate — the percentage of gross rebates retained — fell from 55% in 1Q03 to 28% in 2Q05.  This rapid decline was due to the sudden awareness by clients of the whole rebate retention scheme. To offset this loss, Medco began to push clients toward its captive mail order and fat margins it began to earn on mail order generic Rx fills.

The share of Medco’s overall gross profits coming from retained rebates reflected  outrageous rebate retention rates.  For 3Q04, we derived with certainty from Medco’s 10-Q that 71% of its gross profits came from retained rebates from small molecule brand drugs.  By 2Q05, we estimated with certainty that Medco’s retained rebate share of gross profits had dropped to 48% with the difference going to their newly found focus on mail order generics.

In our 2017 paper “Three Phases of the PBM Business Model”, we carried forward our mid-2000s work on disaggregating PBM gross profits by sources.  Below is a summary of that work.

Here is a graph of the above data:

CVS’s Guaranteed Net Cost Business Model

On December 5, 2018,  CVS Caremark introduced a new pharmacy benefit manager (PBM) business model option for self-insured corporate drug benefit plans.   

The core of this new business model is a simplified reimbursement price paid by plans to CVS that the company craftily describes as “Guaranteed Net Cost”.  Craftily, in that this so-called “cost” is really a “price” where the difference between “cost” and “price” is a markup.

The company touts the following distinguishing features of this simplified reimbursement price.

  • Drug cost predictability and simplicity
  • 100% of rebates are passed through to plan sponsors
  • Simpler payments flow — no retrospective rebates or inflation adjustments
  • Simpler way to compare different PBM contract proposals

Note this new pricing model is for brand drugs only dispensed at retail, mail order and specialty pharmacies.  The generic Rx drug reimbursement pricing scheme remains the same. That is to say, it preserves an opaque “spread margins” that PBMs like CVS add on top of CVS reimbursements to retail pharmacies for generic Rx drug fills.

This new CVS’s initiative clearly is in response to the tsunami of criticism by plan sponsors over an opaque PBM business model and the difficulty in matching initial Rx reimbursements at an inflated list prices with retrospective rebates occurring months later.

The Problem with CVS’s Guaranteed Net Cost Business Model

One: Opaque Markups

The problem with CVS’s new business model is that guaranteed net cost to plans is not necessarily the same as the net cost to PBMs. CVS never states unequivocally that its guaranteed net cost to plans = net cost to CVS.  In other words, CVS’s new business model allows for an opaque markup on top of its net cost.

Consider this meta:  CVS opaquely is substituting one opaque source of gross profits — guaranteed net cost markup — for another opaque source — retained rebates.

It is naive to think that CVS is about to give back some of its oligopolistic profits.  In fact, CVS admits as much as their spokesperson is quoted as saying

“ CVS’ manager of corporate communications, Christina Beckerman, told Fierce Healthcare that the company does not expect CVS Health’s profitability to increase or decrease as a result of the shift to 100 percent pass-through rebates”

The following is a numeral example of how the opaque markup can serve as a 1-for-1 substitute for retained rebates:

Here is a graphical depiction of our view that CVS is substituting an opaque markup for an opaque rebate retention:

To CVS’s credit, its new guaranteed net cost eliminates timing complexity. It does this by taking a risk and netting the current period Rx reimbursement with an estimated “expected” rebate rather than wait to credit plans with the actual rebate when it is paid by Pharma months later.  

CVS certainly is justified in including some markup as compensation for taking the risk that their estimated expected rebates turn out to be less than actual rebates.

Instead, CVS decided not mention markup at all,  let alone a justified markup as a compensation for assuming timing risk.

TWO: Doubtful Elimination of Incentive to Play the High List – High Rebate Game

Under the current retained rebate business model,  PBMs are incentivized to favor drugs with the highest gross rebates to the exclusion of therapeutically equivalent drugs with the lowest net cost.  To be in a position to win this rebate game, Pharma is driven by the PBM-created rebate game to inflate list prices for its brand drugs.  See our paper: Blame PBMs (Not Pharma) for Drive Drug Price Inflation.

The list price – net price bubble began around 2010 and reached its peak in 2017. It was in 2017 that AbbVie first broke the PBM rebate game  winning formulary placement by Express Scripts despite pricing its late entrant Hepatitis C Virus (HCV) drug Mavyret with an ultra low list price with no rebate potential.  However, this was an exception and the norm remains that the basis for formulary placement is gross rebates over net price (list price – gross rebates).

Below is a graphical depiction of how AbbVie broke the rebate game with its ultra low list = no rebate drug HCV drug Mavyret.

It is possible that the rebate game of high list – high gross rebate may be lessened under CVS’s new guaranteed net cost new business model. This is because the basis for PBM profits — markups — could be any number as opposed to being tethered to something like % of gross rebates or % of net cost.

Below is a depiction of CVS’s flexibility in choosing a markup that is independent of the list price or gross rebate. 

On the other hand, we can see the possibility that the new business model preserves the status quo. Here is our line of reasoning for this:

it is likely that brand drug list prices, which are publically available,  will serve as an upward bound for guaranteed net cost as it would look bad for CVS to set a guaranteed net cost that exceeded a drug’s list price.

To look good, CVS will want to show that guaranteed net costs is consistently 40% to 70% below the brand list prices.  

To achieve these percentages while still having room for oligopolistic markups, CVS will signal to Pharma that, while formulary placement is no longer based on gross rebates, high list – high rebate drugs afford CVS latitude in setting guaranteed net cost markups.

Below is a graphical depiction of why, under the new business model, CVS still would be incentivized to favor the high list – high rebate drug.


An Alternative to the Order Book as the Market Design of a Crypto-Economic Trading Platform

In a crypto-economic trading platform:

  • “The network becomes the exchange”
  • Snapchat (ephemeral) bid-asks
  • User-defined smart contracts

The order book is a market design for the exchange of goods and assets.  It dates back to the European coffee houses of the late 1600s.  In London, Jonathan’s Coffee House was a significant meeting place for traders in London in the 1700s. It later became the site of the first London Stock Exchange.

In the late 1700s, in what later became known as New York City, Dutch traders met at a Buttonwood tree in lower Manhattan island to buy and sell goods coming into the port.   Now know as Wall Street, this location became the center of financial asset exchange in the United States.

Until the 1970s, stock exchanges were characterized by a market design involving traders gathering around pits with specialists manually matching bids and asks in paper order books (see below).

The great financial economist Fisher Black wrote a prophetic article in 1971 called “Toward A Fully Automatic Stock Exchange”   where he laid out the implications of the coming automation of the manual order book.  He speculated on what the computerization of the order book would mean for bidding mechanisms, liquidity and overall stock market efficiency.

Screenshot of Bid-Ask Order Book of Poloniex

Market design, indeed all design related to computers, is coupled tightly to the computer technology itself.  Just because one design is associated with a particular computer technology does not mean that the same design should be mindlessly carried over when the computer technology changes.

We recall the mindless carry over of the 80 character line limit established by IBM for punch cards in the 1920s to cathode ray tube (CRT) terminals in the 1970s.

There is a whole host of other instances of mindless carry over of designs when the technology changes.  One notable example is the organization of the factory floor after the conversion of machine power from a centralized shaft driven by water to decentralized electric power.

In the last several years, there has emerged a new decentralized, peer-to-peer (p2p) paradigm in computer architecture propelled by several trends — Internet of Things (IoT), autonomous vehicle-to-device (v2x) communication, and crypto.

This change demands a rethinking of the appropriateness of the centralized client-server order book market design in a crypto-economic platform.

The trend away from client server architecture is driven by a need to do more raw compute “at the edge” before sending data to the server for storage and higher order analytics.  This is known as “edge computing.”  The use cases for edge computing are Internet of Things (IoT) and autonomous vehicle-to-device (V2X) communication.

The trend away from client server architecture is also driven by the tremendous interest in Bitcoin, Blockchain and Ethereum.  Interest in crypto could be the start of a paradigm shift away client server financial intermediaries earning opaque rents and toward decentralized, trustless p2p protocols for validating and accounting for the exchange of financial assets.

A true true, decentralized crypto-economy involves not only a DLT layer but also high speed transaction layer. 

The thesis of this paper is that the time is now to consider a transaction layer with a true decentralized market design.

We believe that publish-subscribe will be the leading protocol of the transaction layer as it has already been deployed at scale an the platform behind several MMO games (from MZ) and chat platforms (WhatApp from Facebook, WeChat from TenCent).

 What is needed is an innovative p2p market design.  It could be along the lines a many-to-many, high frequency “take it or leave it” (TIOLI) publish-subscribe mechanism which could also be described as a discrete time, many-to-many, high frequency version of the Myerson auction.

Value Proposition:

  • user-defined contracts ( e.g. options with odd expiration dates, long-short pairs, straddles)
  • tokens earned by peers supplying liquidity spread contracts
  • elimination of latency rents going to HFT and server co-location fees going to exchange
  • elimination of “data ownership” rents earned by exchange

Specification suggestions:

  • high frequency, many-to-many, pub-sub protocol
  • messages in form of  Myerson “take it or leave it” (TIOLI) bid-asks
  • “serverless” with ephemeral matching with-in Redis-like in-memory data structure store, used as a database, cache and message broker.
  • ephemeral bid-ask data, only data “owned” is history of matches.
  • discrete time, batch process (i.e. events) following  Eric Budish’s work on continuous time design flaw in  HFT platforms 
  • third party AI bid bots
  • third party custodial services
  • settlement a function of DTL layer

Companies with pub-sub platforms

  • Satori (formerly MZ)
  • Facebook (WhatsApp)
  • TenCent (WeChat)
  • Google (Cloud Pub/Sub)

Some relevant URLs

Gabe Leydon, CEO Satori (MZ) TokenPost Interview During Korea Blockchain Open Forum,  July, 2018 https://www.youtube.com/watch?

Satori’s “AI Mesh network” transaction layer  stats — 500 Million “messages” per second or 1 million publishers sending 100 bytes a second 

Hadera Hashgraph’s DLT stats — 500,000 transactions per second with 100% consensus based on a “gossip of gossip protocol” and a consensus latency of 3.5 seconds.

Eric Budish, The Design of Financial Exchange, Some Open Questions at the Intersection of Econ and CS.  Simons Institute of Computing UCB, November 2015 https://www.youtube.com/watch?v=Rilv2AJ1TWM

Eric Budish, “Will the Market Fix the Market?”, AEA/AFA Joint Luncheon Talk, January 2017 https://www.aeaweb.org/webcasts/2017/luncheon

Albert “Pete” Kyle, “Continuous Auctions and Inside Trading”, Econometrica, November 1985   https://www.rhsmith.umd.edu/files/Documents/Centers/CFP/research/kyle1985.pdf

Albert “Pete” Kyle, “The Changing Nature of Trading Markets”, U of Maryland Conference,  May 2017 https://www.rhsmith.umd.edu/files/Documents/Centers/CFP/2017/kyle.pdf

Fisher Black, Toward A Fully Automatic Stock Exchange, 1971  http://17mj9yvb9fl2p5m872gtgax5.wpengine.netdna-cdn.com/wp-content/uploads/2017/07/Towards-a-fully-automated-stock-exhchange-part-1.pdf

 


The Missing Piece in Crypto Exchange: A Decentralized Alternative to the Order Book

In a crypto-economic trading platform:

  • “The network becomes the exchange”
  • Snapchat (ephemeral) bid-asks
  • User-defined smart contracts

Exchanges are regulated by the SEC and take years to gain approval.  Recently, the SEC has announced that all crypto exchanges are illegal unless they register with SEC.

There are two key design principles informing a market design presented below for a crypto-economy platform involving the exchange of digital assets including cryptocurrency deemed securities by SEC.

  • Eliminate enormous multi-million dollar rents captured by exchange intermediaries and front running HFT
  • Accept regulation by the SEC, but as an Electronic Communications Network (ECN) not an exchange. 

Traditional currency or asset exchange involve a two-sided auction market design better known as an order book.  Currently,  all crypto exchanges whether custodial, so-called “decentralized” exchanges (DEX), or relays with 0x smart contracts , still feature order books as a market design.

What we propose is a market design where “the network is the exchange”.  We strongly believe that this design would allow for registration with the SEC as a broker-dealer running an Electronic Communication Network (ECN) which is a subset of a Alternative Trading System (ATS) .  Getting approval for an ECN would be must faster than getting approval as an exchange.

Value Proposition:

  • user-defined contracts ( e.g. options with odd expiration dates, long-short pairs, straddles)
  • tokens earned by peers supplying liquidity spread contracts
  • elimination of latency rents going to HFT and server co-location fees going to exchange
  • elimination of “data ownership” rents earned by exchange

Specification suggestions:

  • high frequency, many-to-many, pub-sub protocol
  • messages in form of  Myerson “take it or leave it” (TIOLI) bid-asks
  • “serverless” with ephemeral matching with-in Redis-like in-memory data structure store, used as a database, cache and message broker.
  • ephemeral bid-ask data, only data “owned” is history of matches.
  • discrete time, batch process (i.e. events) following  Eric Budish’s work on continuous time design flaw in  HFT platforms 
  • third party AI bid bots
  • third party custodial services
  • settlement a function of DTL layer

 

Companies with pub-sub platforms

  • Satori (formerly MZ)
  • Facebook (WhatsApp)
  • TenCent (WeChat)
  • Google (Cloud Pub/Sub)

Satori is leading the integration of a pub-sub transaction layer with a DLT called Hedera Hashgraph.

 

 

The question is what will be the market design for the transaction layer?

Gabe Leydon, CEO Satori, TokenPost Interview During Korean Blockchain Open Forum, July 2018 https://www.youtube.com/watch?v=3Gc2wRk5WE4

Satori’s “AI Mesh network” transaction layer  stats — 500 Million “messages” per second or 1 million publishers sending 100 bytes a second 

Hedera Hashgraph’s DLT stats — 500,000 transactions per second with less than a second to 100% consensus based on a “gossip of gossip protocol”

Some URLs relevant to stock and asset market design choices:

Eric Budish, The Design of Financial Exchange, Some Open Questions at the Intersection of Econ and CS.  Simons Institute of Computing UCB, November 2015 https://www.youtube.com/watch?v=Rilv2AJ1TWM

Eric Budish, “Will the Market Fix the Market?”, AEA/AFA Joint Luncheon Talk, January 2017 https://www.aeaweb.org/webcasts/2017/luncheon

Albert “Pete” Kyle, “The Changing Nature of Trading Markets, U of Maryland Conference,  May 2017 https://www.rhsmith.umd.edu/files/Documents/Centers/CFP/2017/kyle.pdf

Albert ” Pete” Kyle, “Continuous Auctions and Insider Trading” Econometrica, November 1985 http://Albert “Pete” Kyle, “The Changing Nature of Trading Markets,

Fisher Black, Toward A Fully Automatic Stock Exchange, 1971  http://17mj9yvb9fl2p5m872gtgax5.wpengine.netdna-cdn.com/wp-content/uploads/2017/07/Towards-a-fully-automated-stock-exhchange-part-1.pdf

Target Markets:

continuous time order-processing client-server exchanges with massive multi-million dollar rents going to server owners and HFT snipers.

  • Pseudo-crypto DEX with client server order books
  • FOREX with tokenized fiat money
  • Swaps
  • Options
  • Dark Pools
  • Replace “book-maker” gambling with p2p gambling

 


Iron Throne: Kingdom — Another Failed Game Release By Netmarble

Summary:

Netmarble’s newly released game Iron Throne: Kingdom is a failure based on App Annie data.

While the stock did fall to a low of 123,000 KRW in August 2017, it has since recovered since April 2018 due to a timely 25%  investment in a Korean music label that is home to the K-Pop sensation BTS.

Once the failure of this new game become evident to investors, we believe that the stock will again test its all time low of 123,000 KRW.

Analysis

Our analysis of Netmarble’s April 2017 IPO was that it was “priced for perfection”.  While the Lineage 2 game releases have been near perfect in Korea and Japan, its release in the USA has been a bust and the release in China is on hold due to geopolitical tensions.

As a result, we predicted that Netmarble’s stock would fall 45% from its November 26, 2017 closing price of 188,500 KRW to around 103,378 KRW once the revenue impacts of the USA and China releases were fully understood by investors.

While the stock did fall to a low of 123,000 KRW in August 2017, it has since recovered since April 2018 due to a timely 25%  investment in a Korean music label that is home to the K-Pop sensation BTS

 

Recently, Netmarble announced a May 2018 world-wide release of another MMO game called Iron Throne: Kingdom.

Based on App Annie data, we can already tell that the game is a bust with a global annualized revenue run rate (ARR)  that will never be more that $50 Million USD.  This is a drop in the bucket for Netmarble whose 2017 revenue in the range of $2,000 Million USD.

Here are the current revenue ranks on iOS Apple Store for the Iron Throne: Kingdom:

  • USA — #177
  • Japan – #363
  • South Korea — #29

The relation between revenue and revenue rank for mobile games is a power function which we have discussed in other papers.  A top 3 revenue rank game generally translates into a ARR of $1+ Billion which was the case for Lineage II.  A top 10 game drops down severely to $ 160 ARR.

 

 

Here are the App Annie revenue rank charts for the game on iOS Apple for the USA, Japan, and South Korea.

iOS USA — revenue rank 177 on June 4, 2018

iOS Japan – revenue rank 262 on June 4, 2018


An Outline of an Decentralized Alternative to the Order Book

In a crypto-economic trading platform:

  • “The network becomes the exchange”
  • Snapchat (ephemeral) bid-asks
  • User-defined smart contracts

The order book is a market design for the exchange of goods and assets. It dates back to the European coffee houses of the late 1600s.  In London, Jonathan’s Coffee House was a significant meeting place for traders in London in the 1700s. It later became the site of the first London Stock Exchange.

In the late 1700s, in what later became known as New York City, Dutch traders met at a Buttonwood tree in lower Manhattan island to buy and sell goods.   Now known as Wall Street, this location became the center of financial asset exchange in the United States.

Until the 1970s, stock exchanges were characterized by a market design involving traders gathering around pits with specialists manually matching bids and asks in paper order books (see below).

 

The great financial economist Fisher Black wrote a prophetic article in 1971 called “Toward A Fully Automatic Stock Exchange”   where he laid out the implications of the coming automation of the manual order book.  He speculated on what the computerization of the order book would mean for bidding mechanisms, liquidity and overall stock market efficiency.

Screenshot of Bid-Ask Order Book of Poloniex

Market design, indeed all design related to computers, is coupled tightly to the computer technology itself.  Just because one design is associated with a particular computer technology does not mean that the same design should be mindlessly carried over when the computer technology changes.

We recall the mindless carry over of the 80 character line limit established by IBM for punch cards in the 1920s to cathode ray tube (CRT) terminals in the 1970s.

There is a whole host of other instances of mindless carry over of design when the technology changes.  One notable example is the organization of the factory floor after the conversion of machine power from a centralized shaft driven by water to decentralized electric power.

In the last several years, there has emerged a new decentralized, serverless, peer-to-peer (p2p) paradigm in computer architecture propelled by several trends: Internet of Things (IoT), autonomous vehicle-to device communication (V2X), and crypto.

This technological change demands a rethinking of the appropriateness of the centralized client-server order book market design as the core of a transaction layer in a crypto-economic platform.

The trend away from client server architecture is driven by a need to do more raw compute “at the edge” before sending data to the server for storage and higher order analytics.  This is known as “edge computing.”  The use cases for edge computing are Internet of Things (IoT) and autonomous vehicle-to-device (V2X) communication.

The trend away from client server architecture is also driven by the tremendous interest in Bitcoin, Blockchain and Ethereum.  Interest in crypto could be the start of a paradigm shift away from client server financial intermediaries earning opaque rents and toward decentralized, trustless p2p protocols for validating and accounting for the exchange of financial assets.

A true decentralized crypto-economy involves not only a DLT layer but also a high speed transaction layer. 

The thesis of this paper is that the time is now to consider the possibility of pairing a transaction layer with a true decentralized market design with a decentralized distributed ledger technology (DLT).

We believe that publish-subscribe  currently is the leading protocol for the transaction layer as it has already been deployed at scale an the platform behind several MMO games (from MZ) and chat platforms (WhatApp from Facebook, WeChat from TenCent).

We believe that MZ’s recently spun-off subsidiary Satori is leading the integration of a pub-sub transaction layer with a DLT called Hedera Hashgraph. The question is what will be the market design for the transaction layer?

Some URLs relevant to Satori’s plans:

Gabe Leydon, CEO Satori, TokenPost Interview During Korean Blockchain Open Forum, July 2018

Gabe Leydon, CEO Satori (MZ) Fireside Chat Crypto Invest Summit, May 2018

CEO Gabe Laydon leaves MZ to focus on crypto — Venturebeat June 1, 2018

Gabe Leydon video at Hedera Hashgraph NY announcement April 18, 2018

Satori’s “AI Mesh network” transaction layer  stats — 500 Million “messages” per second or 1 million publishers sending 100 bytes a second 

Hedera Hashgraph’s DLT stats — 500,000 transactions per second with 100% consensus based on a “gossip of gossip protocol” and a consensus latency of a 3.5 seconds.

 

 

 

 

 

 

 

 

In a crypto-economic trading platform:

  • “The network becomes the exchange”
  • Snapchat (ephemeral) bid-asks
  • User-defined smart contracts

Value Proposition:

  • user-defined contracts ( e.g. options with odd expiration dates, long-short pairs, straddles)
  • tokens earned by peers supplying liquidity spread contracts
  • elimination of latency rents going to HFT and server co-location fees going to exchange
  • elimination of “data ownership” rents earned by exchange

Specification suggestions:

  • high frequency, many-to-many, pub-sub protocol
  • messages in form of  Myerson “take it or leave it” (TIOLI) bid-asks
  • “serverless” with ephemeral matching with-in Redis-like in-memory data structure store, used as a database, cache and message broker.
  • ephemeral bid-ask data, only data “owned” is history of matches.
  • discrete time, batch process (i.e. events) following  Eric Budish’s work on continuous time design flaw in  HFT platforms 
  • third party AI bid bots
  • third party custodial services
  • settlement a function of DTL layer

 

Companies with pub-sub platforms

  • Satori (formerly MZ)
  • Facebook (WhatsApp)
  • TenCent (WeChat)
  • Google (Cloud Pub/Sub)

Register with the SEC as an ATS or ECN not an exchange.

Targets — continuous time order-processing client-server exchanges with massive multi-million dollar rents going to server owners and HFT snipers.

  • Pseudo-crypto DEX with client server order books
  • FOREX with tokenized fiat money
  • Swaps
  • Options
  • Dark Pools
  • Replace “book-maker” gambling with p2p gambling

 

Abrams tweets on the need for decentralized market design as part of a true decentralized crypto-economics transaction layer