Search results for "volatility"
showing 10 items of 245 documents
Carbonyl compounds of Rh, Ir, and Mt: electronic structure, bonding and volatility
2020
With the aim to render assistance to future experiments on the production and investigation of chemical properties of carbonyl compounds of element 109, Mt, calculations of the molecular properties of M(CO)4 and MH(CO)4, where M = Rh, Ir, and Mt, and of the products of their decomposition, M(CO)3 and MH(CO)3, were performed using relativistic Density Functional Theory and Coupled-Cluster methods implemented in the ADF, ReSpect and DIRAC software suites. According to the results, MH(CO)4 should be formed at experimental conditions from the M atom with a mixture of CO and He gases. The calculated first M–CO bond dissociation energies (FBDE) of Mt(CO)4 and MtH(CO)4 turned out to be significant…
Forecasting Stock Market Volatility: The Gains from Using Intraday Data
2016
There is evidence that volatility forecasting models that use intraday data produce superior forecast accuracy as compared with that delivered by the models that use daily data. However, this evidence is still sparse and incomplete in the stock markets. This paper extends previous studies on forecasting stock market volatility in several important directions and comprehensively assesses the gains in forecast accuracy provided by intraday data. First, we use an extensive set of intraday data on 28 single stocks and 23 stock market indices. Second, in our study we use forecast horizons ranging from 1 day to 6 months. Third, we compare forecasting abilities of several competing models. We find…
The Limits to Volatility Predictability: Quantifying Forecast Accuracy Across Horizons
2018
Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities. Still, little is known about how far ahead one can forecast volatility. First, in this paper we introduce the notions of the spot and forward predicted volatilities and propose to describe the term structure of volatility predictability by the spot and forward forecast accuracy curves. Then, by employing a few popular time-series volatility models, we perform a comprehensive empirical study on the horizon of volatility predictability. Our results suggest that, whereas the spot volatility can be predicted over horizons that extend to 35 weeks, the horizon of the forward volatili…
How News Affect the Trading Behavior of Different Categories of Investors in a Financial Market
2012
We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the exogenous factors we use are the total daily number of news and a semantic variable based on a sentiment analysis of news. Linear regression and partial correlation analysis of data show that different categories of investors are differently correlated to these factors. Governmental and non profit organizations are weakly sensitive to news and returns or volatility, and, typica…
Multi-step ahead electricity price forecasting using a hybrid model based on two-layer decomposition technique and BP neural network optimized by fir…
2017
In the deregulated competitive electricity market, the price which reflects the relationship between electricity supply and demand is one of the most important elements, making it crucial for all market participants to precisely forecast the electricity price. However, electricity price series usually has complex features such as non-linearity, non-stationarity and volatility, which makes the price forecasting turn out to be very difficult. In order to improve the accuracy of electricity price forecasting, this paper first proposes a two-layer decomposition technique and then develops a hybrid model based on fast ensemble empirical mode decomposition (FEEMD), variational mode decomposition …
Volatility-Managing International Equity Risk Factors
2018
Recent research (see Moreira and Muir, 2017) suggests that volatility-managed portfolios take less risk when volatility is high produce large alphas, increase Sharpe ratios, and produce large utility gains for mean-variance investors. We extend this literature by investigating the profitability of volatility-managing the Fama and French (2017) local risk factors in international equity markets. Our general findings indicate that volatility-managing adds value for local risk factors in Europe and Asia, whereas in Japan we find no such evidence. Confirming earlier studies, we find that a risk-based story is unlikely to explain our results.
Essays in Macroeconomics: Growth, Macroeconomic Volatility and Currency Unions
2011
Essays in Macroeconomics: Growth, Macroeconomic Volatility and Currency Unions Essays in Macroeconomics: Growth, Macroeconomic Volatility and Currency Unions
Volatility transmission patterns and terrorist attacks
2009
The objective of this study is to analyze volatility transmission between the US and Eurozone stock markets considering the effects of the September 11, March 11 and July 7 financial crises. In order to do this, we use a multivariate GARCH model and take into account the asymmetric volatility phenomenon, the non-synchronous trading problem and the crises themselves. Moreover, a graphical analysis of the Asymmetric Volatility Impulse-Response Functions (AVIRF) is introduced, which takes into consideration the crisis effect. Results suggest that there is bidirectional and asymmetric volatility transmission and show the different impact that terrorist attacks had on both markets. El objetivo d…
Exchange Rate Volatility and FDI in the EMU Neighborhood Countries
2008
The purpose of this paper is to analyze the role of exchange rate volatility in explaining the evolution of FDI inflows in the EMU neighbourhood countries. Examining the question in the framework of an empirical model that considers the major macroeconomic determinants of FDI, the results of the paper suggest that the effect of exchange rate volatility on FDI crucially depends on a country’s degree of openness. In fact, while exchange rate volatility has positive or null effect for relatively closed economies, it has a negative impact on economies with a high level of openness. This result is particularly relevant for transition economies (Emerging Europe and CIS) and is robust to the use o…
Forecasting Exchange Rates Volatilities Using Artificial Neural Networks
2000
This paper employs Artificial Neural Networks to forecast volatilities of the exchange rates of six currencies against the Spanish peseta. First, we propose to use ANN as an alternative to parametric volatility models, then, we employ them as an aggregation procedure to build hybrid models. Though we do not find a systematic superiority of ANN, our results suggest that they are an interesting alternative to classical parametric volatility models.