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1. The rise and fall of cryptocurrency coins and tokens

   https://doi.org/10.1007/s10203-021-00329-8  

   Gandal, Neil ; Hamrick, J. T. ; Moore, Tyler ; Vasek, Marie ( June 2021 , Decisions in Economics and Finance)

   null (Ed.)

   Since Bitcoin’s introduction in 2009, interest in cryptocurrencies has soared. One manifestation of this interest has been the explosion of newly created coins and tokens. In this paper, we analyze the dynamics of this burgeoning industry. We consider both cryptocurrency coins and tokens. The paper examines the dynamics of coin and token creation, competition and destruction in the cryptocurrency industry. In order to conduct the analysis, we develop a methodology to identify peaks in prices and trade volume, as well as when coins and tokens are abandoned and subsequently “resurrected”. We also study trading activity. Our data spans more than 4 years: there are 1082 coins and 725 tokens in the data. While there are some similarities between coins and tokens regarding dynamics, there are some striking differences as well. Overall, we find that 44% of publicly-traded coins are abandoned, at least temporarily. 71% of abandoned coins are later resurrected, leaving 18% of coins to fail permanently. Tokens experience abandonment less frequently, with only 7% abandonment and 5% permanent token abandonment at the end of the data. Using linear regressions, we find that market variables such as the bitcoin price are not associated with the rate of introducing new coins, though they are positively associated with issuing new tokens. We find that for both coins and tokens, market variables are positively associated with resurrection. We then examine the effect that the bursting of the Bitcoin bubble in December 2017 had on the dynamics in the industry. Unlike the end of the 2013 bubble, some alternative cryptocurrencies continue to flourish after the bursting of this bubble. 

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2. Market making under a weakly consistent limit order book model

   https://doi.org/10.1002/hf2.10050  

   Law, Baron ; Viens, Frederi ( January 2020 , High Frequency)

   We develop a new market‐making model, from the ground up, which is tailored toward high‐frequency trading under a limit order book (LOB), based on the well‐known classification of order types in market microstructure. Our flexible framework allows arbitrary order volume, price jump, and bid‐ask spread distributions as well as the use of market orders. It also honors the consistency of price movements upon arrivals of different order types. For example, it is apparent that prices should never go down on buy market orders. In addition, it respects the price‐time priority of LOB. In contrast to the approach of regular control on diffusion as in the classical Avellaneda and Stoikov (Quantitative Finance, 8, 217, 2008) market‐making framework, we exploit the techniques of optimal switching and impulse control on marked point processes, which have proven to be very effective in modeling the order book features. The Hamilton‐Jacobi‐Bellman quasi‐variational inequality (HJBQVI) associated with the control problem can be solved numerically via finite‐difference method. We illustrate our optimal trading strategy with a full numerical analysis, calibrated to the order book statistics of a popular exchanged‐traded fund (ETF). Our simulation shows that the profit of market‐making can be severely overstated under LOBs with inconsistent price movements.

    

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3. Analyzing Target-Based Cryptocurrency Pump and Dump Schemes

   https://doi.org/10.1145/3464967.3488591  

   Hamrick, JT ; Rouhi, Farhang ; Mukherjee, Arghya ; Vasek, Marie ; Moore, Tyler ; Gandal, Neil ( November 2021 , DeFi '21: Proceedings of the 2021 ACM CCS Workshop on Decentralized Finance and Security)

   null (Ed.)

   As the number of cryptocurrencies has exploded in recent years, so too has the fraud. One popular strategy is when actors promote coordinated purchases of coins in hopes of temporarily driving up prices. Prior work investigating such pump and dump schemes has focused on the immediate impact to prices following pump signals, which were largely interpreted as following the same strategy. The reality, as with most cybercrimes, is that the operators of the schemes try out a much more heterogeneous mix of tactics. From a population of 12,252 pump signals observed between July 2017 and January 2019, we identify and examine 3,683 so-called target-based pump signals that announce promoted coins alongside buy and sell targets, but without a coordinated purchase time. We develop a strategy to measure the success of target pumps over longer time horizons. We find that around half of these pumps reach at least one of their sell targets, and that reaching their peak price often takes days, as opposed to the seconds or minutes required in pumps studied previously. We also examine the various groups promoting coins and present evidence that groups try a variety of distinct strategies and experience varying success. We find that the most successful groups promote many coins and issue many pumps, but not for the same coins. As decentralized finance becomes more popular, a deeper understanding of price manipulation techniques like target pumps is needed to combat fraud. 

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4. Detecting Text Reuse in Cryptocurrency Whitepapers

   https://doi.org/10.1109/ICBC51069.2021.9461147  

   Morin, Andrew ; Vasek, Marie ; Moore, Tyler ( May 2021 , 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC))

   null (Ed.)

   Thousands of new cryptocurrencies have been introduced in recent years. Most are introduced with a so-called "whitepaper" containing a mix of technical documentation, legal boilerplate and marketing material. Notably, many proposed currencies reuse text from previous established cryptocurrencies. We analyze the whitepapers from 1 260 actively traded cryptocurrencies and 2 039 ICOs. We develop two measures of similarity. Moderately similar papers reuse text in a portion of the paper, often the legal disclaimers. By contrast, some highly similar whitepapers appear to copy most of the text. 4% of coin and 19% of ICO whitepapers are highly similar to those of traded coins. The fraction rises to 64% for coins and 67% for ICOs when we consider moderate text reuse. 

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5. Efficient Off-Chain Transaction to Avoid Inaccessible Coins in Cryptocurrencies

   https://doi.org/10.1109/TrustCom50675.2020.00260  

   Rezaeighaleh, Hossein ; Zou, Cliff C. ( December 2020 , 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom))

   null (Ed.)

   Bitcoin and other altcoin cryptocurrencies use the Elliptic-Curve cryptography to control the ownership of coins. A user has one or more private keys to sign a transaction and send coins to others. The user locks her private keys with a password and stores them on a piece of software or a hardware wallet to protect them. A challenge in cryptocurrencies is losing access to private keys by its user, resulting in inaccessible coins. These coins are assigned to addresses which access to their private keys is impossible. Today, about 20 percent of all possible bitcoins are inaccessible and lost forever. A promising solution is the off-chain recovery transaction that aggregates all available coins to send them to an address when the private key is not accessible. Unfortunately, this recovery transaction must be regenerated after all sends and receives, and it is time-consuming to generate on hardware wallets. In this paper, we propose a new mechanism called lean recovery transaction to tackle this problem. We make a change in wallet key management to generate the recovery transaction as less frequently as possible. In our design, the wallet generates a lean recovery transaction only when needed and provides better performance, especially for micropayment. We evaluate the regular recovery transaction on two real hardware wallets and implement our proposed mechanism on a hardware wallet. We achieve a %40 percentage of less processing time for generating payment transactions with few numbers of inputs. The performance difference becomes even more significant, with a larger number of inputs. 

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