We provide the first systematic study of liquidity in the foreign exchange market. We find significant variation in liquidity across exchange rates, substantial illiquidity costs, and strong ...commonality in liquidity across currencies and with equity and bond markets. Analyzing the impact of liquidity risk on carry trades, we show that funding (investment) currencies offer insurance against (exposure to) liquidity risk. A liquidity risk factor has a strong impact on carry trade returns from 2007 to 2009, suggesting that liquidity risk is priced. We present evidence that liquidity spirals may trigger these findings.
The Euro Interbank Repo Market Mancini, Loriano; Ranaldo, Angelo; Wrampelmeyer, Jan
The Review of financial studies,
07/2016, Volume:
29, Issue:
7
Journal Article
Peer reviewed
The search for a market design that ensures stable bank funding is at the top of regulators' policy agenda. This paper empirically shows that the central counterparty (CCP)-based euro interbank repo ...market features this stability. Using a unique and comprehensive data set, we show that the market is resilient during crisis episodes and may even act as a shock absorber, in the sense that repo lending increases with risk, while spreads, maturities, and haircuts remain stable. Our comparison across different repo markets shows that anonymous CCP-based trading, safe collateral, and the absence of an unwind mechanism are the key characteristics to ensure market resilience.
We study the term structure of variance swaps, equity and variance risk premia. A model-free analysis reveals a significant price jump component in variance swaps. A model-based analysis shows that ...investors’ willingness to ensure against volatility risk increases after a market drop. This effect is stronger for short maturities, but more persistent for long maturities. During the financial crisis investors demanded large risk premia to hold equities, but the risk premia largely depended on and strongly decreased with the holding horizon. The term structure of equity and variance risk premia responds differently to various economic indicators.
We introduce a novel class of term structure models for variance swaps. The multivariate state process is characterized by a quadratic diffusion function. The variance swap curve is quadratic in the ...state variable and available in closed form, greatly facilitating empirical analysis. Various goodness-of-fit tests show that quadratic models fit variance swaps on the S&P 500 remarkably well, and outperform affine models. We solve a dynamic optimal portfolio problem in variance swaps, index option, stock index and bond. An empirical analysis uncovers robust features of the optimal investment strategy.
Abstract
We develop a novel class of time-changed Lévy models, which are tractable and readily applicable, capture the leverage effect, and exhibit pure jump processes with finite or infinite ...activity. Our models feature four nested processes reflecting market, volatility and jump risks, and observation error of time changes. To operationalize the models, we use volume-based proxies of the unobservable time changes. To estimate risk premia, we derive the change of measure analytically. An extensive time series and option pricing analysis of sixteen time-changed Lévy models shows that infinite activity processes carry significant jump risk premia, and largely outperform many finite activity processes.
Abstract
Theory has recently shown that corporate policies should depend on firms’ exposure to short- and long-lived cash flow shocks and the correlation between these shocks. We provide granular ...estimates of these parameters for Compustat firms using a new filter that uses only cash flow data and the theoretical restrictions of a canonical cash flow model. As predicted by theory, we find that the estimated parameters are strongly related to corporate liquidity and financing choices, that firms with a higher estimated correlation between shocks implement riskier policies, and that the sign of this correlation determines the cash flow sensitivity of cash.
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
Parametric option pricing models are widely used in finance. These models capture several features of asset price dynamics; however, their pricing performance can be significantly enhanced when they ...are combined with nonparametric learning approaches that learn and correct empirically the pricing errors. In this article we propose a new nonparametric method for pricing derivatives assets. Our method relies on the state price distribution instead of the state price density, because the former is easier to estimate nonparametrically than the latter. A parametric model is used as an initial estimate of the state price distribution. Then the pricing errors induced by the parametric model are fitted nonparametrically. This model-guided method, called automatic correction of errors (ACE), estimates the state price distribution nonparametrically. The method is easy to implement and can be combined with any model-based pricing formula to correct the systematic biases of pricing errors. We also develop a nonparametric test based on the generalized likelihood ratio to document the efficacy of the ACE method. Empirical studies based on S& P 500 index options show that our method outperforms several competing pricing models in terms of predictive and hedging abilities.
Scientific research measures Frittelli, Marco; Mancini, Loriano; Peri, Ilaria
Journal of the Association for Information Science and Technology,
12/2016, Volume:
67, Issue:
12
Journal Article
Peer reviewed
Open access
The evaluation of scientific research is crucial for both the academic community and society as a whole. Numerous bibliometric indices have been proposed for the ranking of research performance, ...mainly on an ad hoc basis. We introduce the novel class of Scientific Research Measures (SRMs) to rank scientists' research performance and provide a rigorous theoretical foundation for these measures. In contrast to many bibliometric indices, SRMs take into account the whole citation curve of the scientist, offer appealing structural properties, allow a finer ranking of scientists, correspond to specific features of different disciplines, research areas and seniorities, and include several bibliometric indices as special cases. Thus SRMs result in more accurate rankings than ad hoc bibliometric indices. We also introduce the further general class of Dual SRMs that reflect the “value” of journals and permit the ranking of research institutions based on theoretically sound criteria, which has been a central theme in the scientific community over recent decades. An empirical application to the citation curves of 173 finance scholars shows that SRMs can be easily calibrated to actual citation curves and generate different authors' rankings than those produced by seven traditional bibliometric indices.
We propose a new method for pricing options based on GARCH models with filtered historical innovations. In an incomplete market framework, we allow for different distributions of historical and ...pricing return dynamics, which enhances the model's flexibility to fit market option prices. An extensive empirical analysis based on S&P 500 index options shows that our model outperforms other competing GARCH pricing models and ad hoc Black-Scholes models. We show that the flexible change of measure, the asymmetric GARCH volatility, and the nonparametric innovation distribution induce the accurate pricing performance of our model. Using a nonparametric approach, we obtain decreasing state-price densities per unit probability as suggested by economic theory and corroborating our GARCH pricing model. Implied volatility smiles appear to be explained by asymmetric volatility and negative skewness of filtered historical innovations.
We develop an econometric method to detect “abnormal trades” in option markets, i.e., trades which are not driven by liquidity motives. Abnormal trades are characterized by unusually large increments ...in open interest, trading volume, and option returns, and are not used for option hedging purposes. We use a multiple hypothesis testing technique to control for false discoveries in abnormal trades. We apply the method to 9.6 million of daily option prices.
•We develop two statistical methods to detect option abnormal trades.•We apply these methods to a massive dataset, i.e., 9.6 million of option prices.•Abnormal trades are detected around major corporate events.•False discoveries in abnormal trades are controlled by multiple hypothesis testing.
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