Variance
Covid halted variance trading. Can Cboe revive the market?
With liquidity in variance swaps drying up, traders may finally be ready to give futures a shot
Obtaining arbitrage-free FX implied volatility by variational inference
An ML-based algorithm that provides implied volatilities from bid-ask prices is proposed
‘Perfect’ VKO trades knock the smile off vol
Dealer hedging of options which profit from ‘spot down, vol down’ may have amplified rare dynamic
Subsampling and other considerations for efficient risk estimation in large portfolios
The authors apply multilevel Monte Carlo simulation to the problems inherent in computing risk measures of a financial portfolio with large numbers of derivatives.
Detecting prudence and temperance in risk exposure: the hybrid variance framework
This paper analyses the correlations between returns and HVs in the short and long terms while developing a risk measure designed to contain the impacts of prudence and temperance on risk aversion.
The future of skew
Forward start volatility swaps and their pricing and hedging models are introduced
Fat-tailed factors
Independent component analysis is proposed as an alternative to principal component analysis
Automatic differentiation for diffusion operator integral variance reduction
This paper demonstrates applications of automatic differentiation with nested dual numbers in the diffusion operator integral variance-reduction framework originally proposed by Heath and Platen.
Rough volatility moves to exotic frontiers
New simulation scheme clears the way for broader application of the rough Heston model
Efficient simulation of affine forward variance models
Andersen's quadratic-exponential scheme is used for simulations of rough volatility models
Is short vol taking the long count?
Short volatility players try to box clever after strategy’s Covid rout
How accurate is the accuracy ratio in credit risk model validation?
The author presents four methods to estimate the sample variance of the accuracy ratio and the area under the curve.
Before and after the Covid-19 storm: buy-side risk survey
Wide-ranging survey reveals what worked and what didn’t in March – and what will change as a result
Dark materials: how one academic is delving into data
David Hand shines a light on dark data and the dangers of distortion by absence
Variance optimal hedging with application to electricity markets
In this paper, the author uses the mean–variance hedging criterion to value contracts in incomplete markets.
Harnessing AI to achieve Libor transition
Chris Dias, principal at KPMG, explains how the vast increase in accuracy that artificial intelligence (AI) offers when dealing with large volumes of complex agreements is crucial to exploring the market opportunities and mitigating the risks of the…
Risk premia strategies – Lessons learned for the future
After a difficult 2018, investors are increasingly wary of risk premia, concerned that factors leading to underperformance might be a recurring problem. Imene Moussa, executive director at UBS, clarifies this issue
Application of the Heath–Platen estimator in the Fong–Vasicek short rate model
In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.
Equity vol strategies get defensive
Floored short funding legs and long vega worked in latest US selloff, dealers claim
Insights into robust optimization: decomposing into mean–variance and risk-based portfolios
The authors of this paper aim to demystify portfolios selected by robust optimization by looking at limiting portfolios in the cases of both large and small uncertainty in mean returns.