Danske Bank

About: Danske Bank is a based out in . It is known for research contribution in the topics: Volatility (finance) & Volatility smile. The organization has 69 authors who have published 145 publications receiving 3733 citations. The organization is also known as: Danske Bank A/S.

Asset Price Dynamics with Limited Attention

Abstract: This paper studies the role that limited attention and inefficient risk sharing play in stock price deviations from the efficient prices at horizons from one day to one month. We expand the Duffie (2010) slow-moving capital model to analyze multiple groups of investors who have varying levels of attention. We test the model’s implications through an analysis of the joint dynamics of stock price movements and trading by the different types of investors. The model is consistent with contemporaneous, lead, and lag correlations among returns and trading at daily, weekly, biweekly, and monthly frequencies. We quantify limited attention’s economic effects on asset prices by estimating a reduced form version of our model on New York Stock Exchange data. A one standard deviation change in market maker inventories is associated with transitory price movements of 65 basis points at a daily frequency and 159 basis points at a monthly frequency. 8% of a stock’s daily idiosyncratic return variance and 25% of a its monthly idiosyncratic variance are due to transitory price changes (noise) and the trading variables explain 32% of this noise.

Testing the martingale restriction for option implied densities

Abstract: This paper contributes to the forecasting literature by presenting a new evaluation method for density and probability estimates. This procedure is particularly well suited for analyzing time series of forecasts implied from option prices, although the results are very general and can be applied also outside this framework. A small scale simulation study documents that valid and accurate inference can be drawn for option implied densities with the proposed method. The new testing procedure is demonstrated in an empirical application on density estimates implied from $/£ currency options.

Projection on a Quadratic Model by Asymptotic Expansion with an Application to LMM Swaption

Abstract: We develop a technique of parameter averaging and Markovian projection on a quadratic volatility model based on a term-by-term matching of the asymptotic expansions of option prices in volatilities. In doing so, we revisit the procedure of asymptotic expansion and show that the use of the product formula for iterated Ito integrals leads to a considerable simplification in comparison with the approach currently prevalent in the literature. Results are applied to the classic problem of LIBOR Market Model (LMM) swaption pricing. We confirm numerically that the retention of the quadratic term gives a marked improvement over the standard approximation based on the projection on a displaced diffusion.

Don’t Text While Driving: The Effect of Smartphone Text Messaging on Road Safety during Simulated Driving

Abstract: Text messaging on smartphones uses a full soft keyboard instead of the numeric buttons on traditional mobile phones. While being more intuitive, the lack of tactile feedback from physical buttons increases the need for user focus, which may compromise safety in certain settings. This paper reports from an empirical study of the effect of text messaging on road safety. We compared the use of a traditional mobile phone and a smartphone for writing text messages during simulated driving. The results confirm that driver performance when texting decreases considerably as there are significant increases in reaction time, car-following distance, lane violation, number of crash/near-crash incidents, perceived task load and the amount of time the driver is looking away from the road. The results also show that smartphones makes this even worse; on key performance parameters they increase the threat from text messaging while driving. These results suggest that drivers should never text while driving, especially not with a smartphone.