A unified approach to pricing and risk management of equity and credit risk

We propose a unified framework for equity and credit risk modeling, where the default time is a doubly stochastic random time with intensity driven by an underlying affine factor process. This approach allows for flexible interactions between the defaultable stock price, its stochastic volatility and the default intensity, while maintaining full analytical tractability. We characterize all risk-neutral measures which preserve the affine structure of the model and show that risk management as well as pricing problems can be dealt with efficiently by shifting to suitable survival measures. As an example, we consider a jump- to-default extension of the Heston stochastic volatility model

Derivative pricing for a multi-curve extension of the Gaussian, exponentially quadratic short rate model

The recent financial crisis has led to so-called multi-curve models for the term structure. Here we study a multi-curve extension of short rate models where, in addition to the short rate itself, we introduce short rate spreads. In particular, we consider a Gaussian factor model where the short rate and the spreads are second order polynomials of Gaussian factor processes. This leads to an exponentially quadratic model class that is less well known than the exponentially affine class. In the latter class the factors enter linearly and for positivity one considers square root factor processes. While the square root factors in the affine class have more involved distributions, in the quadratic class the factors remain Gaussian and this leads to various advantages, in particular for derivative pricing. After some preliminaries on martingale modeling in the multi-curve setup, we concentrate on pricing of linear and optional derivatives. For linear derivatives, we exhibit an adjustment factor that allows one to pass from pre-crisis single curve values to the corresponding post-crisis multi-curve values

Modelling credit spreads with time volatility, skewness, and kurtosis

This paper seeks to identify the macroeconomic and financial factors that drive credit spreads on bond indices in the US credit market. To overcome the idiosyncratic nature of credit spread data reflected in time varying volatility, skewness and thick tails, it proposes asymmetric GARCH models with alternative probability density functions. The results show that credit spread changes are mainly explained by the interest rate and interest rate volatility, the slope of the yield curve, stock market returns and volatility, the state of liquidity in the corporate bond market and, a heretofore overlooked variable, the foreign exchange rate. They also confirm that the asymmetric GARCH models and Student-t distributions are systematically superior to the conventional GARCH model and the normal distribution in in-sample and out-of-sample testing

Probabilistic computing with voltage-controlled dynamics in magnetic tunnel junctions

Probabilistic (p-) computing is a physics-based approach to addressing computational problems which are difficult to solve by conventional von Neumann computers. A key requirement for p-computing is the realization of fast, compact, and energy-efficient probabilistic bits. Stochastic magnetic tunnel junctions (MTJs) with low energy barriers, where the relative dwell time in each state is controlled by current, have been proposed as a candidate to implement p-bits. This approach presents challenges due to the need for precise control of a small energy barrier across large numbers of MTJs, and due to the need for an analog control signal. Here we demonstrate an alternative p-bit design based on perpendicular MTJs that uses the voltage-controlled magnetic anisotropy (VCMA) effect to create the random state of a p-bit on demand. The MTJs are stable (i.e. have large energy barriers) in the absence of voltage, and VCMA-induced dynamics are used to generate random numbers in less than 10 ns/bit. We then show a compact method of implementing p-bits by using VC-MTJs without a bias current. As a demonstration of the feasibility of the proposed p-bits and high quality of the generated random numbers, we solve up to 40 bit integer factorization problems using experimental bit-streams generated by VCMTJs. Our proposal can impact the development of p-computers, both by supporting a fully spintronic implementation of a p-bit, and alternatively, by enabling true random number generation at low cost for ultralow-power and compact p-computers implemented in complementary metal-oxide semiconductor chips

Implications of return predictability for consumption dynamics and asset pricing

Two broad classes of consumption dynamics—long-run risks and rare disasters—have proven successful in explaining the equity premium puzzle when used in conjunction with recursive preferences. We show that bounds a-là Gallant, Hansen, and Tauchen that restrict the volatility of the stochastic discount factor by conditioning on a set of return predictors constitute a useful tool to discriminate between these alternative dynamics. In particular, we document that models that rely on rare disasters meet comfortably the bounds independently of the forecasting horizon and the asset returns used to construct the bounds. However, the specific nature of disasters is a relevant characteristic at the 1-year horizon: disasters that unfold over multiple years are more successful in meeting the predictors-based bounds than one-period disasters. Instead, at the 5-year horizon, the sole presence of disasters—even if one-period and permanent—is sufficient for the model to satisfy the bounds. Finally, the bounds point to multiple volatility components in consumption as a promising dimension for long-run risk models

Reaction of Swiss term premia to monetary policy surprises

An affine yield curve model is estimated on daily Swiss data 2002–2009. The market price of risk is modelled in terms of proxies for uncertainty, which are estimated from interest rate options. The estimated model generates innovations in the 3-month rate that are similar to external evidence of monetary policy surprises - as well as term premia that are consistent with survey data. The results indicate that a surprise increase in the policy rate gives a reasonably sized decrease (-0.25%) in term premia for longer maturities