Cryptocurrencies Are Taxable and Not Free From Fraud

In this report, the authors discuss cryptocurrencies — especially bitcoin — and argue that because the IRS lists them as property, they are taxable, and because they are not as anonymous as once thought, they are not free from fraud. Cryptocurrencies are digital assets used as a medium of exchange, but they are not really coins. They can be sent electronically from one entity to another almost anywhere in the world with an internet connection. There are many cryptocurrencies in the market, including bitcoin, ethereum, ethereum classic, litecoin, nem, dash, iota, bitshares, monero, neo, and ripple. Many of the cryptocurrency networks are not controlled by a single entity or company; instead, a decentralized network of computers keeps track of the currency using a token ID. A ledger maintains a continuously growing list of date stamped transactions in real time called “blocks.” This technology is known as blockchain, which records, verifies, and stores transactions without a trusted central authority. The network instead relies on decentralized autonomous organizations (DAOs) with uncertain legal standing

Debt management when monetary and fiscal policies clash: some empirical evidence

We explore the effects of fiscal and monetary policy shocks on key debt management variables and provide empirical evidence supporting the notion of a strict separation of economic policy from the debt management agenda. We find that a tighter monetary policy coupled with fiscal expansion increases the risk that government debt will have to be rolled over at unusually high cost. This is especially the case in a downturn, where low or even negative interest rates often provide incentives for debt managers to invest predominantly in short-term bonds. Our findings echo the post-crisis environment of low or even negative interest rates, where many debt managers altered their portfolios' structure in favor of short-term bonds. In this respect, we argue that debt managers should use a longer optimization horizon and base their strategy on the medium- and long-term economic outlook.Web of Science23128025

Coin.AI: A Proof-of-Useful-Work Scheme for Blockchain-based Distributed Deep Learning

One decade ago, Bitcoin was introduced, becoming the first cryptocurrency and establishing the concept of "blockchain" as a distributed ledger. As of today, there are many different implementations of cryptocurrencies working over a blockchain, with different approaches and philosophies. However, many of them share one common feature: they require proof-of-work to support the generation of blocks (mining) and, eventually, the generation of money. This proof-of-work scheme often consists in the resolution of a cryptography problem, most commonly breaking a hash value, which can only be achieved through brute-force. The main drawback of proof-of-work is that it requires ridiculously large amounts of energy which do not have any useful outcome beyond supporting the currency. In this paper, we present a theoretical proposal that introduces a proof-of-useful-work scheme to support a cryptocurrency running over a blockchain, which we named Coin.AI. In this system, the mining scheme requires training deep learning models, and a block is only mined when the performance of such model exceeds a threshold. The distributed system allows for nodes to verify the models delivered by miners in an easy way (certainly much more efficiently than the mining process itself), determining when a block is to be generated. Additionally, this paper presents a proof-of-storage scheme for rewarding users that provide storage for the deep learning models, as well as a theoretical dissertation on how the mechanics of the system could be articulated with the ultimate goal of democratizing access to artificial intelligence.Comment: 17 pages, 5 figure