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on Market Microstructure |
| By: | Jonathan A. Batten; Brian M. Lucey |
| Abstract: | We investigate the volatility structure of gold, trading as a futures contract on the Chicago Board of Trade (CBOT) using intraday (high frequency) data from January 1999 to December 2005. Apart from investigating the now familiar GARCH properties we also utilize a rarely used measure of volatility–the Garman Klass estimator – to provide new insights in intraday and interday volatility. This nonparametric measure incorporates the open, close, high and low price within a particular time interval. Both sets of results suggest significant variation across the trading day and week consistent with microstructure theories, although volatility is only slightly positively correlated with volume when measured by tick-count. |
| Keywords: | Garman Klass estimator; volatility; gold; intraday patterns; futures |
| Date: | 2007–06–25 |
| URL: | http://d.repec.org/n?u=RePEc:iis:dispap:iiisdp225&r=mst |
| By: | Ross Starr (University of California, San Diego) |
| Abstract: | General equilibrium is investigated with N commodities traded at N(N−1) 2 commodity-pairwise trading posts. Trade is a resource-using activity recovering transaction costs through the spread between bid (wholesale) and ask (retail) prices (quoted as commodity rates of exchange). Budget constraints are enforced at each trading post separately implying demand for a carrier of value between trading posts, commodity money. Existence of general equilibrium is established under conventional convexity and continuity conditions while structuring the price space to account for distinct bid and ask prices. Trade in media of exchange (commodity money) is the difference between gross and net inter-post trades. |
| Keywords: | General equilibrium, money, transaction cost, trading post, bid ask, commodity money, |
| Date: | 2007–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:ucsdec:2005-07r2&r=mst |
| By: | de Vilder, Robin G.; Visser, Marcel P. |
| Abstract: | Discrete time volatility models typically employ a latent scale factor to represent volatility. High frequency data may be used to construct proxies for these scale factors. Examples are the intraday high-low range and the realized volatility. This paper develops a method for ranking and optimizing volatility proxies. It is possible to outperform the quadratic variation as a proxy for the discrete time scale factor. For the S&P 500 index data over the years 1988-2006 this is achieved by a proxy which puts, among other things, more weight on the highs than on the lows over intraday intervals. |
| Keywords: | volatility proxy; realized volatility; quadratic variation; scale factor; arch/garch/stochastic volatility; intraday seasonality |
| JEL: | C65 C52 C22 |
| Date: | 2007–09–14 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:4917&r=mst |