Estimating conditional volatility with neural networks

It is well known that one of the obstacles to effective forecasting of exchange rates is heteroscedasticity (non-stationary conditional variance). The autoregressive conditional heteroscedastic (ARCH) model and its variants have been used to estimate a time dependent variance for many financial time series. However, such models are essentially linear in form and we can ask whether a non-linear model for variance can improve results just as non-linear models (such as neural networks) for the mean have done. In this paper we consider two neural network models for variance estimation. Mixture Density Networks (Bishop 1994, Nix and Weigend 1994) combine a Multi-Layer Perceptron (MLP) and a mixture model to estimate the conditional data density. They are trained using a maximum likelihood approach. However, it is known that maximum likelihood estimates are biased and lead to a systematic under-estimate of variance. More recently, a Bayesian approach to parameter estimation has been developed (Bishop and Qazaz 1996) that shows promise in removing the maximum likelihood bias. However, up to now, this model has not been used for time series prediction. Here we compare these algorithms with two other models to provide benchmark results: a linear model (from the ARIMA family), and a conventional neural network trained with a sum-of-squares error function (which estimates the conditional mean of the time series with a constant variance noise model). This comparison is carried out on daily exchange rate data for five currencies.

Volatility changes in drachma exchange rates

In January 2001 Greece joined the eurozone. The aim of this article is to examine whether an intention to join the eurozone had any impact on exchange rate volatility. We apply the Iterated Cumulative Sum of Squares (ICSS) algorithm of Inclan and Tiao (1994) to a set of Greek drachma exchange rate changes. We find evidence to suggest that the unconditional volatility of the drachma exchange rate against the dollar, British pound, yen, German mark and ECU/Euro was nonstationary, exhibiting a large number of volatility changes prior to European Monetary Union (EMU) membership. We then use a news archive service to identify the events that might have caused exchange rate volatility to shift. We find that devaluation of the drachma increased exchange rate volatility but ERM membership and a commitment to joining the eurozone led to lower volatility. Our findings therefore suggest that a strong commitment to join the eurozone may be sufficient to reduce some exchange rate volatility which has implications for countries intending to join the eurozone in the future.

Explaining volatility and serial correlation in opening and closing returns:a study of the FT-30 components

In this paper the performance of opening and closing returns, for the components of the FT-30 will be studied. It will be shown that for these stocks opening returns have higher volatility and a greater tendency towards negative serial correlation than closing returns. Unlike previous studies this contrasting performance cannot solely be attributed to differences in the trading mechanism across the trading day. All the stocks used in our sample trade thought the day using a uniform trading mechanism. In this paper, we suggest that it is differences in the speed that closing and opening returns adjust to new information that causes differences in return performance. By estimating the Amihud and Mendelson (1987) [Amihud, Yakov, & Mendelson, Haim (1987). Trading mechanisms and stock returns: An empirical investigation, Journal of Finance, 62 533-553.] partial adjustment model with noise, we show that opening returns have a tendency towards over-reaction, while closing returns have a tendency towards under-reaction. We suggest that it is these differences that cause a substantial proportion (although not all) of the asymmetric return patterns associated with opening and closing returns. © 2005 Elsevier Inc. All rights reserved.

Volatility changes caused by the trading system:a Markov switching application

An expanding literature exists to suggest that the trading mechanism can influence the volatility of security returns. This study adds to this literature by examining the impact that the introduction of SETS, on the London Stock Exchange, had on the volatility of security returns. Using a Markov switching regime change model security volatility is categorized as being in a regime of either high or low volatility. It is shown that prior to the introduction of SETS securities tended to be in a low volatility regime. At the time SETS was introduced securities moved to a high volatility regime. This suggests that volatility increased when SETS was introduced.

On the search for spillovers from foreign direct investment (FDI) with spatial dependency

This paper examines various specifications that are used within the literature to test for spillovers from foreign direct investment (FDI). Analysis provides significant evidence of externalities from inward FDI, but it shows that these externalities are more localized than has previously been believed. Further, the results demonstrate that the econometric treatment of issues such as agglomeration, contiguity and spatial dependence significantly changes the conclusions regarding local and national spillovers from FDI, and productivity growth more generally.

The importance of clusters for spillovers from foreign direct investment and technology sourcing

This paper examines the link between cluster development and inward foreign direct investment. The conventional policy approach has been to assume that inward foreign direct investment (FDI) can stimulate significant clustering activity, thus generating significant spillovers. This paper, however, questions this and shows that, while clusters can generate significant productivity spillovers from FDI, this only occurs in pre-existing clusters. Further, the paper demonstrates that foreign-owned firms that enter clusters also appropriate spillovers when domestic firms undertake investment, raising the possibility that clusters are important locations for so called technology, or knowledge sourcing activities by MNEs. © 2006 Oxford University Press.

Regional policy and spillovers from FDI in the UK

This paper tests one of the fundamental assumptions of regional policy makers over the last 20 years. Western governments, in seeking to attract internationally mobile capital have spent significant sums of public money on subsidies and grants. This is justified on the basis that the social returns to FDI are significantly greater than the private returns, due to productivity or technology spillovers from inward investors to domestic industry. However, this paper generates some estimates of these spillovers for both assisted areas and non-assisted areas in the UK, and questions the size of these social returns, arguing that productivity spillovers do not occur in regions where significant inward investment incentives are available.

Regional foreign direct investment and wage spillovers:plant level evidence from the UK electronics industry

This paper examines the extent to which foreign investment in the UK generates wage spillovers in the domestic sector of the economy using a simultaneous dynamic panel data model and focusing on the electronics sector, possibly the most ‘globalized’ sector of UK manufacturing. It finds evidence that the higher wages paid by foreign firms cause wages in the domestic sector to be bid up. This phenomenon is, however, largely confined to the region where foreign direct investment takes place.