A risk-averse agent hedges her exposure to a non-tradable risk factor U using a correlated traded asset S and accounts for the impact of her trades on both factors. The effect of the agent's trades on U is referred to as cross-impact. By solving the agent's stochastic control problem, we obtain...

We investigate the effect of including variance derivatives as calibration and hedging instruments for pricing and hedging exotic structures. This is studied empirically using market data for SPX and VIX derivatives applied in a stochastic volatility jump diffusion model

In this study, we investigate the pricing of risks in the cross-section of cryptocurrency returns. In doing so, we decompose total variations into systematic and idiosyncratic components, as well as differentiate jumps from diffusive variations. We show that a hedged portfolio sorted on...

We study the term structure of variance (total risk), systematic and idiosyncratic risk. Consistent with the expectations hypothesis, we find that, for the entire market, the slope of the term structure of variance is mainly informative about the path of future variance. Thus, there is little...

In this paper, we establish a comparison between one of the most traded financial derivatives in the markets, the so-called catastrophe bonds (abbreviated as cat bonds) and the corporate bonds. In the first section, we start from a brief definition as well as some basic concepts. In section two,...

Wir untersuchen den Querschnitt von über 1200 Kryptowährungen, gesammelt von 350 Handelsplätzen, in der Zeitspanne von Januar 2014 bis Juni 2020. Im speziellen untersuchen wir, ob weit verbreitete Charakteristika, wie Beta (Fama/MacBeth (1973)), Size (Banz (1981)) oder Momentum...

In investment, particularly in the portfolio management, the risk and returns are two crucial measures in making investment decisions. This paper attempts to provide a brief theoretical explanation with examples on determining the returns and associated risk of shares, and of the portfolio of...

Dynamic beta is a program that dynamically allocates to beta assets based on formal rules. It contrasts with standard mean-variance optimization and static risk-parity approaches, which are static. Dynamic beta lowers the overall risk of the fund — where risk includes volatility of returns...

We establish that the risk-return tradeoff of cryptocurrencies (Bitcoin, Ripple, and Ethereum) is distinct from those of stocks, currencies, and precious metals. Cryptocurrencies have no exposure to most common stock market and macroeconomic factors or to the returns of currencies and...

One of the main explanations for the idiosyncratic volatility (IVOL) puzzle (i.e., the negative relation between lagged IVOL and returns) is a missing risk factor. We show analytically that if IVOL proxies for a missing risk factor, then the negative relation between IVOL and returns should...