@book{JRC32230,
	editor = {},
	address = {Castellanza (Italy)},
	year = {2005},
	author = {Strozzi F and Zaldivar Comenges J},
	isbn = {},
	abstract = {In this work, we have applied state space reconstruction techniques to estimate state space volume and its variation. These values have allowed us to define a trading methodology by considering a sort of acceleration in a high-dimensional state space system as a kind of momentum indicator similar to those used in financial technical analysis. Our interest was to develop a general trading strategy to determine and quantify the amount of predictability in these time series. This trading methodology has been applied to high-frequency currency exchange time series data from the HFDF96 data set provided by Olsen & Associates. The time series studied are the exchange rates between the US Dollar and 18 other foreign currencies from the Euro zone; i.e. Belgium Franc (BEF), Finnish Markka (FIM), German Mark (DEM), Spanish peseta (ESP), French Frank (FRF), Italian Lira (ITL), Dutch Guilder (NLG),
		and finally ECU (XEU); and from outside the Euro zone: Australian Dollar (AUD), Canadian Dollar (CAD), Swiss Frank (CHF), Danish Krone (DKK), British Pound (GBP), Malaysian Ringgit (MYR), Japanese Yen (JPY), Swedish Krona (SEK), Singapore Dollar (SGD), and South African Rand (ZAR)
		},
	title = {New Trading Methodology for Financial Time Series},
	url = {},
	volume = {},
	number = {},
	journal = {},
	pages = {},
	issn = {},
	publisher = {Carlo Cattaneo University},
	doi = {}
}