Category Archives: cryptocurrencies

15/2/21: Pump & Dump, Illicit Finance and Market Inefficiency: Cryptos under Review

 A fascinating fresh survey of microeconomics literature on crypto currencies: "The Microeconomics of Cryptocurrencies" by Hanna Halaburda, Guillaume Haeringer, Joshua Gans, Neil Gandal (CESifo Working Paper 8841, 2021, NBER version link here: https://www.nber.org/papers/w27477).

The paper is really too extensive to summarize here, so I encourage everyone interested in cryptos to read it. I can, however, offer some non-priority ordered comments on some of the passages I find interesting and novel.

Let's start with 'efficiency' and the 'nothing-at-stake problem'. Authors reference Saleh (2019) which derives "sufficient conditions that guarantee that consensus" to fork is an equilibrium. "Saleh then derives two additional results. 

  1. "First, restricting the ability to large stakeholders facilitates and speeds up consensus in case of a fork. The intuition is that [large] stakeholders have the most to lose from a disagreement, i.e., from the persistence of two or more branches." This seems to me a built-in incentives mechanism for increasing concentration of holdings of cryptos. Just as monopolistic power can lead to cartelization and collusion, so is the need for faster / more efficient consensus on development can lead to market dominance and concentration. The side effect of this would be likely reduced liquidity and also likely manipulation of exchange rates. Neither is good for cryptos susceptible to concentration becoming actual money (unit of account, unit of storage, unit of exchange).
  2. Second, "Saleh finds that the lower the miners' reward the better. The reason behind this counter-intuitive result is that low rewards enable the accumulation of vested interest in the blockchain (i.e., miners have less incentives to cash out their tokens). Given this, preserving one's vested interest in the blockchain (the tokens) increase the incentives to favor consensus." This is ugly. It further compounds holdings concentration and reduces liquidity. Worse, by inducing longer holding time horizons, it risks potential over-reaction to price movements in the longer run, so that markets price discovery can be severely restricted, and financial bubbles can form and inflate faster and more viciously.
Another issue, relating to efficiency, is transaction costs: the paper reviews Huberman et al. (2019) on this. There are several problems relating to the Bitcoin system capacity to process and record information that relates to the way transaction fees are being priced and charged. These are largely consistent also with Easley et al. (2019). One is that "miners are not only engaged into a hashing race, but they also strategically select transactions to process in order to grab the highest fees." Another is that the system requires congestion to generate fees. The third is that once block rewards are exhausted, the system can lead to concentration of market power as miners will rely solely on transaction fees to exist. This power concentration can lead to higher costs of transactions, and "may result in turn in a weakening of the system's safeguards against double-spending".  Lastly, "if all users pay the fee, the deviation to no fee is very costly, because it automatically puts the no fee transaction at the very end of the queue. This cost may be higher than the fee itself." In other words, in the "all users pay" environment, system congestion can lead to highly costly delays in processing of information.

User adoption: "Foley et al. (2019) fi nd that approximately one-quarter of bitcoin users are involved in illegal activity, which they estimate to represent 46% of bitcoin transactions. Based on their estimates, the illegal use of bitcoin generates approximately $76 billion of illegal activity per year. In terms of comparison, they note that the scale of the US and European markets for illegal drugs is only slightly larger! They do find that since 2016 the proportion of bitcoin activity associated with illegal trade has declined, but the absolute amount of activity (in USD) has continued to increase."

"One example of illegal activity that currently flourishes with Bitcoin is "ransomware" attacks in which criminals exploit vulnerabilities in computer networks to "lock" fi les so that the user cannot access them. As documented in an article in the New York Times by Nathaniel Popper, in 2019, more than 200,000 organizations submitted files that had been hacked in a ransomware attack. This was a 40 percent increase from the year before,"

The literature on the subject is "consistent with what we know about adoption by large merchants. According to the Economist magazine using data from Morgan Stanley, in 2018, only three of the largest 500 online retailers accept Bitcoin for payments", which is down from five such retailers accepting Bitcoin in 2017. "The conventional wisdom for the lack of adoption of Bitcoin as a payment system is that very few "legal" goods are purchased using Bitcoin because its value is not stable and the system is very slow in processing transactions."

User intent: "Most of the empirical research we discussed... suggest that currently, bitcoin demand is driven by speculation alongside likely illegal intent. A broader claim about bitcoin demand is that it is used as a hedge against inflation" (or as a form of 'digital gold'). The paper argues that BTC/USD pricing of July 2019 or something around USD9,630 per BTC would be consistent with all cryptocurrencies taken as whole replacing 100% of the privately held investment gold in the world for the gold price of USD 1,444 per ounce. As we say before running a Category V rapid... "Good luck on the down".

Pump and dump coins: "Hamrick et al. (2018) present compelling evidence of pervasive pump-and-dump schemes resulting from a systematic analysis of multiple datasets ... they identify more than 3,000 pump-and-dump schemes over a just 6 month period in 2018." 


21/1/20: Investor Fear and Uncertainty in Cryptocurrencies


Our paper on behavioral biases in cryptocurrencies trading is now published by the Journal of Behavioral and Experimental Finance volume 25, 2020:



We cover investor sentiment effects on pricing processes of 10 largest (by market capitalization) crypto-currencies, showing direct but non-linear impact of herding and anchoring biases in investor behavior. We also show that these biases are themselves anchored to the specific trends/direction of price movements. Our results provide direct links between investors' sentiment toward:

  1. Overall risky assets investment markets,
  2. Cryptocurrencies investment markets, and
  3. Macroeconomic conditions,
and market price dynamics for crypto-assets. We also show direct evidence that both markets uncertainty and investor fear sentiment drive price processes for crypto-assets.

9/1/20: Herding and Anchoring in Cryptocurrency Markets


Our new paper, with Daniel O'Loughlin, titled "Herding and Anchoring in Cryptocurrency Markets: Investor Reaction to Fear and Uncertainty" has been accepted to the Journal of Behavioral and Experimental Finance, forthcoming February 2020.

The working paper version is available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3517006.

Abstract:
Cryptocurrencies have emerged as an innovative alternative investment asset class, traded in data-rich markets by globally distributed investors. Although significant attention has been devoted to their pricing properties, to-date, academic literature on behavioral drivers remains less developed. We explore the question of how price dynamics of cryptocurrencies are influenced by the interaction between behavioral factors behind investor decisions and publicly accessible data flows. We use sentiment analysis to model the effects of public sentiment toward investment markets in general, and cryptocurrencies in particular on crypto-assets’ valuations. Our results show that investor sentiment can predict the price direction of cryptocurrencies, indicating direct impact of herding and anchoring biases. We also discuss a new direction for analyzing behavioral drivers of the crypto assets based on the use of natural language AI to extract better quality data on investor sentiment.

7/10/19: Bitcoin, ethereum and ripple: a fractal and wavelet analysis


Myself and Professor Shaen Corbet of DCU have a new article on the LSE Business Review site covering our latest published research into cryptocurrencies valuations and dynamics: https://blogs.lse.ac.uk/businessreview/2019/10/07/bitcoin-ethereum-and-ripple-a-fractal-and-wavelet-analysis/.

The article profiles in non-technical terms our paper "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple" currently in the process of publication with the The Quarterly Review of Economics and Finance (link here).