Search results for "jel:G13"
showing 8 items of 8 documents
European Option Pricing and Hedging with Both Fixed and Proportional Transaction Costs
2003
Abstract In this paper we provide a systematic treatment of the utility based option pricing and hedging approach in markets with both fixed and proportional transaction costs: we extend the framework developed by Davis et al. (SIAM J. Control Optim., 31 (1993) 470) and formulate the option pricing and hedging problem. We propose and implement a numerical procedure for computing option prices and corresponding optimal hedging strategies. We present a careful analysis of the optimal hedging strategy and elaborate on important differences between the exact hedging strategy and the asymptotic hedging strategy of Whalley and Wilmott (RISK 7 (1994) 82). We provide a simulation analysis in order …
Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options
2010
Weather derivatives have become very popular tools in weather risk management in recent years. One of the elements supporting their diffusion has been the increase in volatility observed on many energy markets. Among the several available contracts, Quanto options are now becoming very popular for a simple reason: they take into account the strong correlation between energy consumption and certain weather conditions, so enabling price and weather risk to be controlled at the same time. These products are more efficient and, in many cases, significantly cheaper than simpler plain vanilla options. Unfortunately, the specific features of energy and weather time series do not enable the use of …
Causalities between CO2, electricity, and other energy variables during phase I and phase II of the EU ETS
2010
The topic of this article is the analysis of the interplay between daily carbon, electricity and gas price data with the European Union Emission Trading System (EU ETS) for CO2 emissions. In a first step we have performed Granger causality tests for Phase I of the EU ETS (January 2005 until December 2007) and the first year of Phase II of the EU ETS (2008). The analysis includes both spot and forward markets—given the close interactions between the two sets of markets. The results show that during Phase I coal and gas prices, through the clean dark and spark spread, impacted CO2 futures prices, which in return Granger caused electricity prices. During the first year of the Phase II, the sho…
The Random-Time Binomial Model
1999
In this paper we study Binomial Models with random time steps. We explain, how calculating values for European and American Call and Put options is straightforward for the Random-Time Binomial Model. We present the conditions to ensure weak-convergence to the Black-Scholes setup and convergence of the values for European and American put options. Differently to the CRR-model the convergence behaviour is extremely smooth in our model. By using extrapolation we therefore achieve order of convergence two. This way it is an efficient tool for pricing purposes in the Black-Scholes setup, since the CRR model and its extrapolations typically achieve order one. Moreover our model allows in a straig…
Estructura de la bolsa española e introducción del mercado de activos derivados sobre el IBEX-35
2001
-Jose.E.Farinos@uv.es -Matilde.Fernandez@uv.es La controversia acerca de si la implantación y negociación de activos derivados afecta a la estabilidad de los respectivos mercados de contado perdura desde hace más de dos décadas. En este trabajo abordamos la problemática anterior desde una nueva perspectiva. Concretamente, analizamos el impacto que sobre la estructura del mercado bursátil ha podido tener la introducción de los mercados de activos derivados sobre el IBEX-35. Para ello, definimos e identificamos la estructura del mercado bursátil para el periodo de estudio, y, a continuación, analizamos el efecto que sobre la misma ha tenido la aparición de los nuevos mercados de derivados. Nu…
Volatility risk premia and financial connectedness
2014
In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. The…
Forecasting Weekly Electricity Prices at Nord Pool
2007
This paper analyses the forecasting power of weekly futures prices at Nord Pool. The forecasting power of futures prices is compared to an ARIMAX model of the spot price. The time series model contains lagged external variables such as: temperature, precipitation, reservoir levels and the basis (futures price less the spot price); and generally reflects the typical seasonal patterns in weekly spot prices. Results show that the time series model forecasts significantly beat futures prices when using the Diebold and Mariano (1995) test. Furthermore, the average forecasting error of futures prices reveals that they are significantly above the settlement spot price at the ‘delivery week’ and th…
Pricing of Asian exchange rate options under stochastic interest rates as a sum of options
2002
The aim of the paper is to develop pricing formulas for long term European type Asian options written on the exchange rate in a two currency economy. The exchange rate as well as the foreign and domestic zero coupon bond prices are assumed to follow geometric Brownian motions. The emphasis is devoted to the discretely sampled Asian option. It is shown how the value of this option can be approximated as the sum of Black-Scholes options. The formula is obtained under the extension of results developed by Rogers and Shi (1995) and Jamshidian (1991). In addition bounds for the pricing error are determined. Comparing with Monte Carlo simulation the pricing is found to be very precise.