Updated March 21 #coronavirus#Italy -- thread
Today dramatic increase in the number of deaths (793 or +20% respect prev day). Relatively better news with respect to total number of infected which increases by 4821 units, or 13% with respect to previous day
1/ I think the large increase in number of deaths, as dramatic as it is, was expected given the large number of people that are currently infected (more than 42K). So better to focus on the flattening of the curve for the newly infected, and in mean time #StayAtHome
2/ Today more about 26K tests were conducted and 18% of the tests results positive. Total number of tests so far 230K. Many experts are calling for more tests, and a contact tracing strategy as in Korea.
3/ It is important to look at breakdown by regions, as they are in different stages of the virus spread. In the last two days Piemonte is giving signs of slowing down of the increase in infected and deaths, but many regions appear on similar path of Lombardia.
4/ My figures by regions are now in log-scale. Emilia Romagna, Liguria, Marche and Tuscany along Piemonte seem more or less to be following Lombardia. Regions in the South are a few more days behind. In the mean time #StayAtHome#StaySafe#staystrong
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I am very excited to share my new working paper titled “#Crypto Risk Premia” (with Daniele Massacci, @RubinMirco and Dario Ruzzi). A short 🧵 follows. Please, share it if you like it. Comments are very welcome [1/n]
Before “crypto winter” hit markets at the beginning of 2022, cryptocurrency was getting “boring” as some of the craziness of the earlier times was fading out and institutional investors had started to pour in, allocating a part of their large portfolios to crypto. [2/n]
To inform investment and risk management decisions, and guide portfolio allocation to crypto assets, it is fundamental to i) identify the set of risk factors driving crypto returns and ii) correctly quantify the prices associated with these sources of risk. [3/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]
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 ft.com/content/c4c29b…
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]
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]
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
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
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
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]