Summary
The main aim of this paper is to forecast gold and silver daily returns with advanced regression analysis using various linear and non-linear models. ARMA models are used as a linear benchmark for comparison purposes with established non-linear models such as Nearest Neighbours and MultiLayer Perceptron (MLP), and Higher Order Neural Networks (HONN) whose application to financial markets is quite new. All models are assessed using statistical criteria such as correct directional change as well as financial criteria such as risk adjusted return. The main aim is to find which of these models generate the best returns and if nonlinear models can be used for generating excess returns in the precious metals market. This is achieved by implementing a trading simulation where the forecast is translated into a trading signal. Profit statistics are calculated taking into account transaction costs. It is concluded that, for the January 2000-May 2006 period under review, non-linear models like MLPs and HONNs did outperform the linear ARMA models. In the end, the performance of both MLP and HONN models showed the presence of nonlinearities in the gold and silver prices as it was found that nonlinear models can be effectively used for generating excess returns in these markets.
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Extract
Quantitative Trading of Gold and Silver Using Nonlinear Models
1. Introduction
Gold and silver are two important traded commodities, with gold being used as a hedge against inflation (Ranson, 2005), a hedge against the variations of the US Dollar (Capie et al., 2004) apart from other uses in the jewellery industry, industrial uses, as an investment and a store of value. Since the breakdown of the Bretton Woods Agreement in 1971-1973 the official role of gold in the international monetary system has ended. After the de- linking of the US Dollar to gold there has been a wide fluctuation in gold prices. Since the start of 2000 precious metals prices have appreciated and there is speculation of further price rises. In the circumstances, forecasting the price of these commodities has important implications not only monetarily but also economically (Levin and Wright, 2006).Precious metals have an economic value apart from being commodities and particularly gold is considered as an alternate investment to the US Dollar and a 'safe heaven' investment. A rise in the value of the US Dollar will lead, all other things being equal, to a fall in the dollar value of gold so both assets exhibit a negative correlation. Economic indicators and political factors play an important role in the long run pricing of these commodities. Although fundamental analysis could be applied for the long term pricing of these metals, predicting daily returns is very difficult as argued by Baker and Van Tassel (1985) who also underline that there is a lot of speculati...See the full content of this document
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