Search arXivSearch

arXiv · 1103.2567

Interest Rates After The Credit Crunch: Multiple-Curve Vanilla Derivatives and SABR

Abstract

We present a quantitative study of the markets and models evolution across the credit crunch crisis. In particular, we focus on the fixed income market and we analyze the most relevant empirical evidences regarding the divergences between Libor and OIS rates, the explosion of Basis Swaps spreads, and the diffusion of collateral agreements and CSA-discounting, in terms of credit and liquidity effects. We also review the new modern pricing approach prevailing among practitioners, based on multiple yield curves reflecting the different credit and liquidity risk of Libor rates with different tenors and the overnight discounting of cash flows originated by derivative transactions under collateral with daily margination. We report the classical and modern no-arbitrage pricing formulas for plain vanilla interest rate derivatives, and the multiple-curve generalization of the market standard SABR model with stochastic volatility. We then report the results of an empirical analysis on recent market data comparing pre- and post-credit crunch pricing methodologies and showing the transition of the market practice from the classical to the modern framework. In particular, we prove that the market of Interest Rate Swaps has abandoned since March 2010 the classical Single-Curve pricing approach, typical of the pre-credit crunch interest rate world, and has adopted the modern Multiple-Curve CSA approach, thus incorporating credit and liquidity effects into market prices. The same analysis is applied to European Caps/Floors, finding that the full transition to the modern Multiple-Curve CSA approach has retarded up to August 2010. Finally, we show the robustness of the SABR model to calibrate the market volatility smile coherently with the new market evidences.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Marco Bianchetti, Mattia Carlicchi. 2012-04-02. Interest Rates After The Credit Crunch: Multiple-Curve Vanilla Derivatives and SABR. https://arxiv.org/abs/1103.2567

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Fundamentals of Perpetual Futures

Perpetual futures are the most popular cryptocurrency derivatives. Perpetuals offer leveraged exposure to their underlying without rollover or direct ownership. Unlike fixed-maturity futures, perpetuals are not guaranteed to converge to the spot price. To minimize the gap between perpetual and spot prices, long investors periodically pay shorts a funding rate proportional to this difference. We derive no-arbitrage prices for perpetual futures in frictionless markets and bounds in markets with trading costs. Empirically, deviations from these prices in crypto are larger than in traditional currency markets, comove across currencies, and diminish over time. An implied arbitrage strategy yields high Sharpe ratios.

q-fin.PR

A deep learning approach for pricing convertible bonds with path-dependent reset and call provisions

This paper develops a deep learning framework for pricing convertible bonds with path-dependent downward reset and issuer call provisions governed by rolling-window triggers. We formulate the valuation problem as a path-dependent partial differential equation (PPDE) that captures both the historical stock-price path and the evolution of the conversion price. Model-specific PPDEs are derived under GBM, CEV, and Heston dynamics. Under suitable conditions, we establish the existence and uniqueness of a piecewise viscosity solution linked by contractual transmission conditions at monitoring dates. For computation, we construct a fixed-grid backward dynamic programming scheme and approximate its conditional expectations using neural networks, with $L^2$ convergence to the exact fixed-grid recursion as the approximation errors vanish. An application to the China CITIC Bank Convertible Bond produces stable prices across the three models and close agreement with the LSMC benchmark, but outperforms in dimensional scaling. The results show that contractual provisions have a greater valuation effect than the choice of underlying dynamics. The call provision reduces the bond value by truncating upside gains, whereas the downward reset provision increases it under the benchmark specification because improved conversion terms dominate the effect of earlier redemption. Delta and Gamma obtained by automatic differentiation of smooth local network approximations closely agree with central finite-difference estimates. The framework provides a flexible approach to pricing and sensitivity analysis for convertible bonds with complex path-dependent provisions.

q-fin.PR

Confidence intervals for empirical convergence rates of randomised quasi-Monte Carlo, with applications to option pricing

Empirical comparisons of quasi-Monte Carlo rules often report fitted convergence exponents without intervals. We estimate the root mean square error from independent randomisations, fit its log slope over a declared sample-size window, and resample whole randomisations to construct an interval. For a fixed window, we establish asymptotic validity under finite fourth moments and a positive limiting variance. We measure coverage of four interval constructions on integrands with known exponents. With Gaussian errors, all four are compatible with nominal coverage at 128 and 512 randomisations, and jackknife-$t$ already at 32. All four undercover for the two higher-kurtosis families even at 512 randomisations. For differences between slopes, including null and small effects, preserving the dependence between paired randomisations can greatly narrow intervals, but it does not ensure nominal coverage. In option pricing, a steeper slope and a smaller error at a fixed budget can rank rules differently. Preintegration lowers a digital Asian option's exponent by about 0.5 in every tested window. For a barrier option it reduces the error six- to ninefold while changing the exponent by less than four hundredths. An arithmetic basket's gain grows with sample size. A geometric basket remains a ridge function as assets are added, limiting its use as a dimension benchmark. For multi-asset Asian options, different bases within a degenerate PCA eigenspace can change the measured exponent, in a direction that depends on the payoff.

q-fin.PR