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A traditional VaR approach is not suitable to assess the risk that merger arbitrage funds carry in their portfolios. We propose a simple two-state or three-state model that captures the risk characteristics of the deals in which merger arbitrage funds invest.This model has been tested on a set...
Persistent link: https://www.econbiz.de/10013148123
A traditional VaR approach is not suitable to assess the risk of merger arbitrage hedge funds. We recently proposed a simple two- or three-state model that captures the risk characteristics of the deals in which merger arbitrage funds invest. Here, we refine the model, and demonstrate that it...
Persistent link: https://www.econbiz.de/10013148125
Finally, Stéphane Daul and Elena Gutíerrez Vidal present a set of case studies on insurance liability replication. Under modern valuation conventions, insurance firms increasingly use market-consistent techniques to value both their assets and liabilities. Consequently, the market...
Persistent link: https://www.econbiz.de/10013150745
We analyze the performance of investable portfolios built using predicted stock returns from machine learning methods and attribute their performance to linear, marginal non-linear and interaction effects. We use a large set of features including price-based, fundamental-based, and...
Persistent link: https://www.econbiz.de/10014433684
We describe a model that takes into account the tail dependence present in a large set of historical risk factor data using the modern concept of copulas. We extend the popular t-copula to obtain a new grouped t-copula which describes more accurately the dependence among risk factors of...
Persistent link: https://www.econbiz.de/10014209904
What are the implications of disagreement about environmental, social, and governance (ESG) ratings for portfolio choice? Constructing an optimal portfolio for each ESG rating agency by minimizing tracking error while satisfying a portfolio-level ESG constraint, we found that ESG rating...
Persistent link: https://www.econbiz.de/10014254834