Did Liquidity Providers Become Liquidity Seekers?

The misalignment between corporate bond and credit default swap (CDS) spreads (i.e., CDSbond basis) during the 2007-09 financial crisis is often attributed to corporate bond dealers shedding off their inventory, right when liquidity was scarce. This paper documents evidence against this widespread perception. In the months following Lehman's collapse, dealers, including proprietary trading desks in investment banks, provided liquidity in response to the large selling by clients. Corporate bond inventory of dealers rose sharply as a result. Although providing liquidity, limits to arbitrage, possibly in the form of limited capital, obstructed the convergence of the basis. We further show that the unwinding of precrisis 'basis trades' by hedge funds is the main driver of the large negative basis. Price drops following Lehman's collapse were concentrated among bonds with available CDS contracts and high activity in basis trades. Overall, our results indicate that hedge funds that serve as alternative liquidity providers at times, not dealers, caused the disruption in the credit market

The decision rule approach to optimization under uncertainty: methodology and applications

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naïvely partition or discretize the support of the random problem parameters are limited to small and medium-sized problems, or they require restrictive modeling assumptions (e.g., absence of recourse actions). In the last few decades, several solution techniques have been proposed that aim to alleviate the curse of dimensionality. Amongst these is the decision rule approach, which faithfully models the random process and instead approximates the feasible region of the decision problem. In this paper, we survey the major theoretical findings relating to this approach, and we investigate its potential in two applications areas

Forecasting Bond Risk Premia Using Technical Analysis

This paper is selected as one of the Top Ten Paper in Forecasting in SSRN

The value of tradeability

This paper determines the value of asset tradeability in an option pricing framework. In our model, tradeability is valuable since it allows investors to exploit temporary mispricings of stocks. The model delivers several novel insights on the value of tradeability: The value of tradeability is the larger, the higher the pricing efficiency of the market is. Uncertainty increases the value of tradeability, no matter whether the uncertainty results from noise trading or from new information about the fundamental value of the stock. The value of tradeability is the larger, the longer the illiquid stock cannot be traded and the more trading dates the liquid stock offers

Online tracking of the degree of nonlinearity within complex signals

A novel method for online tracking of the changes in the nonlinearity within complex-valued signals is introduced. This is achieved by a collaborative adaptive signal processing approach by means of a hybrid filter. By tracking the dynamics of the adaptive mixing parameter within the employed hybrid filtering architecture, we show that it is possible to quantify the degree of nonlinearity within complex-valued data. Simulations on both benchmark and real world data support the approach