I have a new working paper out on “#Crypto Premium and Jump Risk” with Paolo Santucci de Magistris #EconTwitter Link: ssrn.com/abstract=38891… [1/n]
The paper shows that sudden and large price moves in bitcoin prices (jumps) explain a large portion in the variation in bitcoin returns [2/n]
Study tail-risk in crypto markets is important for at least two reasons 1/ is tail-risk priced similarly to that in equity markets? 2/ to characterize the SDF of the marginal investor and price alternative cryptocurrencies and tokens and do risk-management [3/n]
We start from the model in Maheu, McCurdy and Zhao (JFE 2013) to characterize the conditional mean of daily bitcoin excess returns (the crypto premium) and use high-frequency measurements of daily volatility to separate jumps from the diffusive component of volatility [3/n]
We find that the conditional skewness and kurtosis are both significantly priced, and that a relevant portion of the variability of bitcoin returns can be attributed to compensation for the jump term [4/n]
The crypto premium is related to crypto factors (in line w/Liu and Tsyvinski (RFS 2020)), and higher investor attention and lower crypto liquidity are associated with higher expected excess returns, conditional variance and jump intensity, and lower conditional skewness [5/n]
Finally, we show that the price of crypto risk is time-varying, and higher in bad times for investors, when the conditional variance and kurtosis are high [6/n]
In order to do so, we consider a large number of portfolios constructed using 100 cryptocurrencies and predictors of returns explored in Liu, Tsyvinski and Wu (2020) and let the risk prices be function of the conditional components of the SDF [7/n]
The cross-sectional asset pricing estimates confirm that the price of crypto risk is time-varying, and higher in bad times for investors when the conditional variance and kurtosis are high.

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More from @nicolaborri

19 May
The narrative of the rollercoaster day for cryptocurrency markets centers around the fears of stricter regulation in China (which might want to push its future CBDC). I shamlessy take the opportunity to advertise some of my prior work [1/n] #EconTwitter
In Borri and Shakhnov (FRL 2019) we look at a similar big shock when China de facto ordered the closing of cryptocurrency exchanges. [2/n]

Link to paper: sciencedirect.com/science/articl…
The shock had a huge effect on the global share of trading volume that took place on Chinese cryptocurrency exchanges: in a matter of months it went from 90% to less than 1% (caveat: part of it could have been wash trading) [3/n] Image
Read 6 tweets
29 Mar
I am very happy that my paper with @KShakhnov “Global Risk in Long-Term Sovereign Debt” has been accepted in @RevOfAssetPric #EconTwitter

Thread 1/n
Our paper is motivated by recent work by @HannoLustig et al. (AER 2019) who found that currency carry trade strategies with T-bonds are different from those with T-bills because local currency term premia offset currency premia 2/n
Results in Lustig et al. (AER 2019) are for advanced economies with no/low default risk and imply that the volatility of the permanent component of investors’ SDF must be equalized across countries 3/n
Read 15 tweets
28 Sep 20
New wp with @FSobbrio @francedrago @ChSantantonio #EconTwitter
Many countries used lockdowns to control the pandemics. We provide quantitative estimates of benefits in terms of reduction of mortality by #COVID19👇
(also @cepr_org DP15317) 1/n
We focus on Italy -- one of the first country struck by #COVIDー19 -- where the lockdown design offers a source of exogenous variation in the intensity of the lockdown at a granular level 2/n
In the second (economic) lockdown (March 22) the Italian government defined a detailed list of essential economic activities. All other activities were either suspended or allowed to operate only remotely 3/n
Read 18 tweets
13 Sep 20
I am very happy to share that my paper "Optimal Taxation with Home Ownership and Wealth Inequality" with Pietro Reichlin has been now accepted for publication at the @RevEconDyn [1/n] #EconTwitter Image
In the paper we consider optimal taxation in a model with wealth-poor and wealth-rich households, where wealth derives from business capital and home ownership, and investigate the consequences of a rising wealth inequality at steady state on these tax rates [2/n]
We find that the optimal tax structure includes some taxation of labor, zero taxation of financial and business capital, and critically a housing wealth tax on the wealth-rich households and a housing subsidy on the wealth-poor households [3/n]
Read 8 tweets
10 Sep 20
My paper with K. Shakhnov on Regulation spillovers across cryptocurrency markets is now available on FRL at this link authors.elsevier.com/c/1bjLs5VD4Kcw… (with 50 days free access) #EconTwitter [thread 1/n]
In this paper we look at the unprecedented drop in trading volume on the Chinese cryprocurrency market after a significant regulatory change that de facto banned bitcoin in early 2017 in China [thread 2/n] Image
We find large spillovers of this regulatory shock on other cryptocurrency markets: 1) we observe a large increase in trading volume for bitcoin vs. Korean won, Japanese yen and U.S. dollars; ... [3/n]
Read 6 tweets
10 Jun 20
1/n A new version of my paper with Kirill Shakhnov on "Cryptomarket Discounts" is now available at: ssrn.com/abstract=31243… #EconTwitter [short thread] Image
2/n Investors buy #bitcoin on a multitude of exchanges, located in different countries, and against different fiat and cryptocurrencies.
3/n Their distribution is leptokurtic, with negative skewness for fiat pairs, and a standard deviation of 4.5%. Image
Read 7 tweets

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