Journal: Journal of Risk and Financial Management

Abbreviation

Publisher

MDPI

Journal Volumes

ISSN

1911-8074

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2020 - 20234
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Publications1 - 4 of 4
  • Deciphering DeFi: A Comprehensive Analysis and Visualization of Risks in Decentralized Finance
    Item type: Journal Article
    Weingärtner, Tim; Fasser, Fabian; Reis Sá da Costa, Pedro; et al. (2023)
    Journal of Risk and Financial Management
    Decentralized finance (DeFi) promises a revolution in financial accessibility, transparency, and automation. Yet, its very novelty exposes participants to a number of additional risks and challenges. This study aims to address the risks associated with DeFi, while also conducting a comparative analysis to those of classical/traditional finance (TradFi). After introducing DeFi and its defining characteristics, such as the use of smart contracts, blockchain technology, and decentralized governance, the paper outlines the principal risks associated with DeFi. Drawing insights from an extensive literature review of 200 recent articles, of which 50 were thoroughly analyzed, the study compares risks of DeFi and TradFi, categorizing these into systematic and unsystematic risks. Furthermore, we introduce the ‘risk wheel’, an innovative tool tailored to understand and navigate the subtleties of DeFi risks, finding potential applications in risk assessment, management, and even education. This paper’s primary objective is to provide a detailed and impartial examination of the risks associated with DeFi and their comparison to traditional finance in order to assist stakeholders in making informed decisions and mitigating possible losses.
  • Diversification and Fund Performance-An Analysis of Buyout Funds
    Item type: Journal Article
    Huss, Matthias; Steger, Daniel (2020)
    Journal of Risk and Financial Management
    This paper studies the relationship between portfolio diversification and fund performance, based on an unexplored, hand-collected dataset of buyout funds. The dataset comprises detailed information at the level of portfolio companies, which allows measuring the concentration of the fund portfolios towards individual companies, industrial, and geographical focus. Our results suggest that diversification within, but not across industries, associates with higher buyout fund performance. We do not find a significant relationship between geographical diversification and performance. These results partly contradict results documented in prior literature.
  • Pricing and Hedging American-Style Options with Deep Learning
    Item type: Journal Article
    Becker, Sebastian; Cheridito, Patrick; Jentzen, Arnulf (2020)
    Journal of Risk and Financial Management
    In this paper we introduce a deep learning method for pricing and hedging American-style options. It first computes a candidate optimal stopping policy. From there it derives a lower bound for the price. Then it calculates an upper bound, a point estimate and confidence intervals. Finally, it constructs an approximate dynamic hedging strategy. We test the approach on different specifications of a Bermudan max-call option. In all cases it produces highly accurate prices and dynamic hedging strategies with small replication errors
  • Deep Partial Hedging
    Item type: Journal Article
    Hou, Songyan; Krabichler, Thomas; Wunsch, Marcus (2022)
    Journal of Risk and Financial Management
    Using techniques from deep learning, we show that neural networks can be trained successfully to replicate the modified payoff functions that were first derived in the context of partial hedging by Follmer and Leukert. Not only does this approach better accommodate the realistic setting of hedging in discrete time, it also allows for the inclusion of transaction costs as well as general market dynamics. It needs to be noted that, without further modifications, the approach works only if the risk aversion is beyond a certain level.
Publications1 - 4 of 4