Technical paper
Backward induction for future values
A new framework for derivatives pricing with valuation adjustments
Expanding the benchmarked equity portfolio management paradigm
Hamza Bahaji, Stephanie Ridon and Emmanuel Bourdeix propose a tracking error driven allocation approach applicable to a broad equity universe
Robust valuation and hedging of tolling agreements and physical assets
Flexible, martingale duality-based method provides reliable valuation
KVA: capital valuation adjustment by replication
KVA are introduced to take into account the effect of capital on funding
Back-testing expected shortfall
Three easy-to-implement methods for back-testing expected shortfall
Commodity leveraged ETFs: Tracking errors, volatility decay and trading strategies
Tracking performance of ETFs is examined, with a focus on volatility decay
Quant ideas: Liquidity in commodity risk management
Liquidity plays a vastly underappreciated role in commodity markets
Cutting edge intro: Righting wrong-way risk
Models that describe wrong-way risk should move away from simplistic copula models, critics say.
Heston model: shifting on the volatility surface
Stochastic volatility model combining Heston vol model and CIR++
Path-consistent wrong-way risk
A copula-based model for wrong way risk
Cutting edge intro: history in the modelling
Bloomberg quant Guyon delivers an alternative to stochastic local volatility
Swapping from headline to core inflation and commodity hedging
The case for targeting core rather than headline inflation for long-term hedgers
Pricing American-style options by Monte Carlo simulation: alternatives to ordinary least squares
The authors investigate the performance of the ordinary least squares (OLS) regression method in Monte Carlo simulation algorithms for pricing American options.
Counterparty credit risk pricing and measurement of swaption portfolios
This paper introduces a technique for pricing and risk measurement of portfolios containing swaption contracts in the presence of counterparty credit risk, under general market model and volatility assumptions.
Numerical algorithms for research and development stochastic control models
The authors consider the optimal strategy of research and development (R&D) expenditure adopted by a firm that engages in R&D to develop an innovative product to be launched in the market.