Forecasting of Realised Volatility with the Random Forests Algorithm

The paper addresses the forecasting of realised volatility for financial time series using the heterogeneous autoregressive model (HAR) and machine learning techniques. We consider an extended version of the existing HAR model with included purified implied volatility. For this extended model, we apply the random forests algorithm for the forecasting of the direction and the magnitude of the realised volatility. In experiments with historical high frequency data, we demonstrate improvements of forecast accuracy for the proposed model

Analysis of market volatility via a dynamically purified option price process

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial ‘dynamically purified' price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggest several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX

Adaptive EAGLE dynamic solution adaptation and grid quality enhancement

In the effort described here, the elliptic grid generation procedure in the EAGLE grid code was separated from the main code into a subroutine, and a new subroutine which evaluates several grid quality measures at each grid point was added. The elliptic grid routine can now be called, either by a computational fluid dynamics (CFD) code to generate a new adaptive grid based on flow variables and quality measures through multiple adaptation, or by the EAGLE main code to generate a grid based on quality measure variables through static adaptation. Arrays of flow variables can be read into the EAGLE grid code for use in static adaptation as well. These major changes in the EAGLE adaptive grid system make it easier to convert any CFD code that operates on a block-structured grid (or single-block grid) into a multiple adaptive code

Underground transfer of carbonised organic residues to lithics during preliminary fire experiments: implications for archaeology

Using fire experiments, we investigate claims that black organic residues on lithics found in Stone Age sites are markers for heat treatment of rocks in the embers of aboveground wood fires. We buried sedges overlain with lithics and bone to replicate plant bedding sometimes found in archaeological sites. Small fires were lit over the material buried under a mixture of coarse- and medium-grained sand. Black carbonised residues formed on several lithics that were in direct contact with buried sedges that burned below the fire. FTIR, Raman and preliminary GC-MS measurements were made on dried and burnt sedge, burnt bone, and on a prominent black residue that formed on one quartz piece that had been in contact with buried fresh sedge when it was heated. Importantly, we were able to confirm the spontaneous and accidental transfer of organic compounds to lithics buried and heated underground in the presence of plant material. This means that carbonised organic residues are not useful markers for determining whether heat treatment of rocks took place above or below ground. Our preliminary experiments imply that further work should be done to investigate the causes of the residues formed on lithics underground