Bastien Buchwalter is an Assistant Professor of Finance at SKEMA Business School in Paris, France. His research interests are in FinTech, Financial Stability and Sustainable Finance. Bastien’s research investigates financial stability implications of crypto-assets in the wider financial system, alternative investment strategies using crypto-assets, as well as the potential benefit of parallel currencies in fostering growth of local economies. He holds a PhD in Finance from ESSEC Business School, an MSc in Quantitative Economics from the University of Tübingen and has been a visiting scholar at the Bank of Canada.


Research Interests

Bastien's main research focus is on the emerging field of crypto-assets and the blokchcain technology. Crypto-assets are based on a distributed network and can provide a wide variety of services, ranging from payment systems to distributed cloud storage by proposing a novel and innovative framework that allows for peer to peer interaction without the need of a centralized third party. His research investigates financial stability implications of crypto-assets in the wider financial system, as well as alternative investment strategies using crypto-assets. Lastly, empirical asset pricing and sustainable finance constitute further areas of interest.

Working Papers

Contagious Volatility

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Keywords: Volatility Spillovers, Crypto-assets, Financial Stability

How does uncertainty of crypto-assets affect traditional asset classes? Using a vector autoregression (VAR) methodology, we answer this question by analyzing volatility spillovers between five asset classes (crypto-assets, stocks, bonds, fiat- currencies, and commodities). Given the vast heterogeneity within each asset class, our VAR specification accounts for cross-sectional variation across and within each asset class. By transforming the VAR residuals into sectoral shocks, we are able to distinguish between volatility spillovers across, and volatility co-movements within asset classes. We find that on average volatility of crypto-assets accounts for 15% of the volatility contagion received by traditional asset classes. The directional spillovers from crypto-asset to bonds and to fiat-currencies are particularly strong, capturing the wealth channel and the remittance channel, respectively.

Decrypting Crypto-assets

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Keywords: Blockchain, Classification of Crypto-assets, Coins and Tokens

This paper, which is intended for a non-technical audience, aims at explaining the blockchain technology and addressing misconceptions about crypto-assets. We define crypto-assets as all assets that are based on a distributed blockchain. The greatest misunderstanding consists of the fact that not all crypto-assets are crypto-currencies. It is true that each distributed blockchain has a native currency. However, it primarily serves as an incentive mechanism for individuals to maintain and update the distributed network. Crypto-assets can, for instance, also be used as a mean of cloud storage or cloud computing. Understanding how different crypto-assets interact with the blockchain technology and what other purpose the native currency fulfills is key to establishing a comprehensive classification.

Tail Risk, Core Risk and Expected Stock Returns

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Keywords: Realized Variance, Asymmetry, Predictability

Expected returns should not only include rewards for accepting the risk of a po- tential downside loss, but also discounts for potential upside gains. Since investors care differently about upside gains versus downside losses, they require a risk pre- mium for bearing the relative downside risk. We show that conditional asymmetry forecasts equity market returns in the short run. Our short-term expected return predictors, the tail asymmetry and the core asymmetry, capture more variation in equity returns than the variance risk premium, a forward-looking measure, or the price-dividend ratio. Further, our predictors can easily be extracted from realized return series.

Heterogeneity and Volatility Regimes of Crypto-assets

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Keywords: Crypto-assets, Regime Switching Models, Heterogeneity

Crypto-assets attract more and more investors due to their potential returns and diversification benefits. Contrary to popular believe, only a minority of crypto-assets are crypto-currencies. Thus in our study, we distinguish between payment crypto- assets (i.e. crypto-currencies), platform crypto-assets and protocol crypto-assets. In light of the heterogeneity of crypto-asset, we show that they present different regime dynamics. More precisely, the different subgroups of crypto-assets tend to regroup in three separate clusters. That is, the analysis yields four regimes with different lev- els of variance: ranging from extremely ‘low’ through ‘neutral’ and ‘high’ volatility regimes up to ‘explosive’ volatility. The clusters of crypto-assets distinguish them- selves by the time they spend in the ‘explosive’ and ‘neutral’ volatility regime.

Work in Progress

Risk Sharing in Blockchain Mining Pools

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Keywords: Mining Pools, Blockchain, Risk Sharing

This paper formalizes a framework to explain why (and under which circumstances) individual miners decide to join a mining pool. The multiple agent setup endogenously determines pool size and pool fees based on the miners’ risk aversion.


Teaching Philosophy

His motivation to pursue a career in academia not only stems from his passion in doing research, but also builds on his wish to train, mentor, and inspire students. His philosophy of teaching is built on three objectives: he wants students to learn the fundamental concepts, develop problem-solving strategies and be able to apply those skills outside the classroom.

Classes and Teaching Interests

His teaching interests concentrate around Finance, Econometrics, and Financial Techonologies. In the recent years we witnessed a wide reaching transformation of the finance world with new financial products providing new ways to invest and interact.

List of classes:

Course Evaluations

His overall teaching and learning experience scores 96% as expressed by students' course evaluations. Please feel free to send an e-mail for more details. The following comments are quoted from the course evaluations:


Academic Positions

2020 - present Assistant Professor, Finance at SKEMA Business School, Paris, France
2019 - 2020 Lecturer, Finance at ESSEC Business School, Paris, France


Ph.D. Finance ESSEC Business School, Paris, France, 2020
M.Phil. Finance ESSEC Business School, Paris, France, 2017
M.Sc. Quantitative Economics Eberhard Karls University, Tübingen, Germany, 2015

Selected Seminars and Conferences

2020 Seminar Series, SKEMA, Paris, France
Seminar Series, Boston University, Boston, USA
2019 Paris December Finance Meeting, Paris, France
Seminar Series, Bank of Canada, Ottawa, Canada
CEMA Annual Meeting, Carnegie Mellon University, Pittsburgh, USA
2018 Computational and Financial Econometrics, University of Pisa, Pisa, Italy
FinTech and Crypto-Finance, NEOMA Business School, Paris, France

Curriculum Vitae

For more information please feel free to download the CV here or to send an e-mail directly.


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Bastien Buchwalter

Assistant Professor, Finance

SKEMA Business School

[email protected]

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