Blockchain Papers

Justice Kyei-Mensah

No abstract is available for this record.

Zhaxylyk Seifulov

The study investigates the no-arbitrage parity conditions in Bitcoin spot and futures markets, focusing on the efficiency of the spot-futures (SFP) and futures spread parity (FSP) models in estimating the Bitcoin futures prices. Utilizing data from the Chicago Mercantile Exchange (CME) and Binance exchange, the research analyzes the relationship between spot and futures prices of Bitcoin, moreover, examines the relationship between intramarket Bitcoin futures contracts. The study finds that the mean pricing error of SFP is greater than FSP, indicating the greater efficiency of FSP in pricing Bitcoin futures. It also explores arbitrage opportunities by testing the equality of means of the bid-ask spread and mispricing, revealing that arbitrage opportunities are not consistently present. Few exploitable arbitrage opportunities in bullish markets are found, but overall, the arbitrage profit is not feasible when considering the costs such as bid-ask spread.

Hugo Eduardo Ramirez, Julián Fernando Sanchéz

No abstract is available for this record.

Artur Sepp, Vladimir Lucic

Currently the most liquidly traded options on the crypto underlying are the so-called inverse options. An inverse option contract is quoted and traded in the units of the underlying cryptocurrency. The main economic reason for popularity of inverse contracts in the crypto exchanges (such as Deribit) is that inverse contracts enable to operate without maintaining fiat cash accounts. For the theoretical part, we show that inverse options are just regular vanilla options considered under the martingale measure using the forward of the underlying as the numéraire. This measure requires an adjustment to option delta. For the empirical part, we use Deribit options data of past four years to backtest delta-hedged option strategies. We introduce USD and Coin accounting of trading Profit&Loss (P&L) which is important for designing strategies in crypto options. We show empirically that USD and Coin accounting rules are equivalent when performance is measured is Coin and USD units, respectively. We establish that the risk-premia observed in options on Deribit is negative and significant so that strategies selling volatility are expected to generate positive risk-adjusted performance in the long-term.

Kristof Lommers, Jack Kim, Mohamed Baioumy

No abstract is available for this record.

Kristof Lommers, Jack Kim, Mohamed Baioumy

No abstract is available for this record.

Sean Grover

Exchange-traded funds (ETFs) investing in bitcoin futures contracts first listed for trading in the fall of 2021. This research evaluates the extent to which the returns of bitcoin futures and bitcoin correspond to determine if bitcoin futures provide an effective proxy for a direct bitcoin investment. A no-arbitrage framework for bitcoin futures is established, which provides the basis for the empirical analyses that follow. The empirical analyses of returns correspondence between bitcoin futures and bitcoin use daily and monthly returns to estimate single-factor asset pricing regressions, finding coefficients of expected magnitude and that bitcoin returns explain over 97% of the variation in bitcoin futures returns. This research also estimates two-factor asset pricing regressions that include a novel excess carry term. The two-factor regressions find statistically significant excess carry term coefficients and over 99% explained variation. Finding strong evidence that the returns of bitcoin futures and bitcoin closely correspond, this research concludes that bitcoin futures provide an effective proxy for a direct bitcoin investment.

Fabian E. Eska, Yanghua Shi, Erik Theissen, Marliese Uhrig‐Homburg

Abstract We analyze whether the design of cryptocurrencies helps to explain the Huge cross-sectional variation in the market values of cryptocurrencies. We propose a taxonomy of design features and Hand-collect data on these features for a sample of 79 cryptocurrencies. Using a two-stage regression approach and LASSO regressions, we find, inter alia, that forks and deviations from the design of Bitcoin are associated with lower valuation. In contrast, non-anonymous cryptocurrencies and cryptocurrencies that do not pass on any transaction fees and/or tips to agents who maintain the integrity of the network have, on average, higher market values. These results are robust to variations in the way we measure market valuation.

Amit Chaudhary, Roman Kozhan, Ganesh Viswanath-Natraj

This paper studies determinants of interest rates on Decentralized lending protocols. Using transaction level data, we show these protocols are being used to make long or short leveraged positions in the cryptocurrency market. We identify a significant relationship between the interest rate differential and the perpetual futures premium for the ETH/USDT market. However, the link is economically weak, indicating that the speculative beliefs in the two markets are only weakly correlated and that the markets are segmented. Arbitrage across the two markets is ineffective due to wide no-arbitrage bounds, which are governed by high trading costs, gas fees, and price impacts.

Takeshi Yoshihara, Taisei Kaizoji

We applied the SVAR-LiNGAM to illustrate the causal relationships between the spot exchange rate, and three crypto-asset exchange rates, Bitcoin, Ethereum, and Ripple. It was notable that the causal order, the EUR_USD spot rate->Bitcoin->Ethereum->Ripple, was obtained by this approach. All the instantaneous effects were strongly positive. Moreover, it was notable that Bitcoin can influence the EUR_USD spot rate positively with a one-day time lag.

Yongjing Wang, Zubair Ahmad, Faridoon Khan, Dalia Kamal Alnagar · 7 authors

This paper offers the introduction of a new updated form of the Dagum distribution. The new updated form of the Dagum model is called a novel generalized-Dagum distribution. The proposed novel generalized-Dagum distribution is a prominent updated form of the Dagum model with a single additional/extra parameter. The novel generalized-Dagum model is produced by mixing the Dagum distribution with the novel generalized-M distributions approach. The heavy-tailed properties of the novel generalized-Dagum model are obtained. The derivation of the estimators and a simulation study of the novel generalized-Dagum distribution are also provided. Finally, the novel generalized-Dagum model is illustrated by analyzing two real-life data sets related to the financial sector. The first data set represents the Bitcoin exchange rates vs the United States dollars. Whereas, the second data set represents the Ethereum exchange rates vs the United States dollars. Using the Bitcoin and Ethereum exchange rates data sets, the fitting power of the novel generalized-Dagum model is compared with the transmuted Dagum distribution and a new modified Dagum distribution.

Jimmy E. Hilliard, Julie T.D. Ngo

We investigate Bitcoin pricing characteristics and find evidence of jumps and positive convenience yield. We develop a theoretical jump diffusion model for options on spots and use simulations to evaluate non-linear parameter estimates. Data from the Deribit exchange is used to compare the performance of the jump diffusion models with Practitioner Black–Scholes models. Using Diebold–Marino statistics and standard error metrics, we find that the jump diffusion models significantly outperform Practitioner Black–Scholes models. We conclude that Bitcoin behaves more like a commodity than a currency.

Mnacho Echenim, Emmanuel Gobet, Anne-Claire Maurice

We design a novel calibration procedure that is designed to handle the specific characteristics of options on cryptocurrency markets, namely large bid-ask spreads and the possibility of missing or incoherent prices in the considered data sets. We show that this calibration procedure is significantly more robust and accurate than the standard one based on trade and mid-prices.

Fernanda Maria Müller, Samuel Solgon Santos, Thalles Weber Gössling, Marcelo Brutti Righi

No abstract is available for this record.

Artur Sepp

No abstract is available for this record.

Jonathan Reiter

We examine the distribution of realized Bitcoin daily log-returns and find significantly-thin tails. From there we construct a simple connection back to traditional volatility modelling. And then we discuss how this connection can serve as a foundation to leverage existing derivative quant research to explore cryptocurrency market dynamics. These results also suggest a connection between cryptocurrency exchange structure and trading dynamics.

Sky Guo, Joseph Kreitem, Thomas Moser

No abstract is available for this record.

Chen Jian, Michael P. Clements, Andrew Urquhart

No abstract is available for this record.

David Cerezo Sánchez

Optimal simple rules for the monetary policy of the first stochastically dominant crypto-currency are derived in a Dynamic Stochastic General Equilibrium (DSGE) model, in order to provide optimal responses to changes in inflation, output, and other sources of uncertainty. The optimal monetary policy stochastically dominates all the previous crypto-currencies, thus the efficient portfolio is to go long on the stochastically dominant crypto-currency: a strategy-proof arbitrage featuring a higher Omega ratio with higher expected returns, inducing an investment-efficient Nash equilibrium over the crypto-market. Zero-knowledge proofs of the monetary policy are committed on the blockchain: an implementation is provided.

Julian Winkel, Wolfgang Karl Härdle

Bitcoin Pricing Kernels (PKs) are estimated using a novel data set from Deribit, the leading Bitcoin options exchange. The PKs, as the ratio between risk-neutral and physical density, dynamically reflect the change in investor preferences. Thus, the PKs improve the understanding of investor expectations and risk premiums in a new asset class. Bootstrap-based confidence bands are estimated in order to validate the results. Investors are heterogeneous in their risk profiles and preferences with respect to volatility and investment horizon. The empirical PKs turn out to be U-shaped for short-dated instruments and W-shaped for long-dated instruments. We find that investors are willing to pay a substantial risk premium to insure themselves against short-term price movements. The risk premium is smaller for longer-dated instruments and their traders are risk averse. The shape of the empirical PKs reveals the existence of a time-varying risk premium. The similarity between the shape of empirical PKs for Bitcoin and other markets that represent aggregate wealth shows that Bitcoin is becoming an established asset class.

Minhao Leong, Simon Kwok

No abstract is available for this record.

Masaaki Fukasawa, Basile Maire, Marcus Wunsch

Impermanent Loss in Decentralized Finance can be hedged with weighted variance swaps

Carol Alexander, Arben Imeraj

We analyse robust dynamic delta hedging of bitcoin options using a set of smile-implied and other smile-adjusted deltas that are either model-free, in the sense that they are the same for every scale-invariant stochastic and/or local volatility model, or they are based on simple regime-dependent parameterisations of local volatility. These deltas are popular with option market makers in traditional assets because they are very easy to implement. Previous empirical research on dynamic delta hedging is based solely on equity index options, but analysis of our unique data on hourly historical bitcoin option prices reveals that bitcoin implied volatility curves behave very differently from those of equity index options. For call and put options with a wide range of moneyness and with synthetic constant maturities of 10, 20 and 30 days, we compare the dynamic hedging performance of different smile-adjusted deltas over two one-year periods. We also examine the use of the perpetual contract rather than the standard futures as hedging instrument because the basis risk for the perpetual is very much smaller than it is for calendar futures. Results are presented as testable statistics of hedging error variance ratios. In certain periods the use of smile-implied hedge ratios can significantly out-perform the simple Black–Scholes delta hedge, especially when using the perpetual swap as hedging instrument, where efficiency gains can exceed 30% for out-of-the-money puts, and reach an average of 15% when hedging short-term out-of-the money calls during periods when the implied volatility curve slopes upwards. The advantage of using the perpetual contract is especially evident during 2021, for the longer-term contracts for which the basis is still rather large.

Carlos Trucíos, James W. Taylor

Abstract Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the literature. Among them, long‐memory processes, procedures taking into account the presence of extreme observations, procedures that include more than a single regime, and quantile regression‐based models have performed substantially better than standard methods in terms of forecasting risk measures. Those procedures are revisited in this paper, and their value at risk and expected shortfall forecasting performance are evaluated using recent Bitcoin and Ethereum data that include periods of turbulence due to the COVID‐19 pandemic, the third halving of Bitcoin, and the Lexia class action. Additionally, in order to mitigate the influence of model misspecification and enhance the forecasting performance obtained by individual models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting exercise, reveal that, for Bitcoin, there is no single procedure outperforming all other models, but for Ethereum, there is evidence showing that the GAS model is a suitable alternative for forecasting both risk measures. We found that the combining methods were not able to outperform the better of the individual models.