DislikedOK...I give up. I think I'll join Craig as well. I asked a simple question at the beginning of this thread. Is there some reason NOT to trade in this fashion.
Other than incurring minor transaction costs...which are clearly paid for in the method, I have not been convinced NOT to trade this way.Ignored
While the ability to hedge is an appealing feature, traders should be aware of the various factors that can affect their accounts. Spreads may widen, causing margin to diminish, potentially leading to the danger of a margin call. Pip costs and rollover may also cause a decrease in account equity, adversely effecting hedged positions.
QuoteDislikedThe market is NOT made of calculators, it is made of people. With few exceptions, most of those people do NOT think or trade in terms of math accuracy or formulas. They trade with their emotions and thus do not and will never consistently react in the way the math forumlas say they should. If that were the case we'd all be rich...the math guys first of course.
These are short-term bets. Very short. The founder of Tradebot, in Kansas City, Mo., told students in 2008 that his firm typically held stocks for 11 seconds. Tradebot, one of the biggest high-frequency traders around, had not had a losing day in four years, he said.
A more recent article said that he had finally had three losing days in a row But still no losing week EVER.
And from Oanda http://www.olsenblog.com/wp-content/..._Trade_5.2.pdf
For full disclosure, I need to add another remark of caution. Human traders cannot compete successfully with sophisticated quantitative trading models, which systematically process every tick of market data. Why do I say this? Human traders can be compared to a physics professor in an airplane about to take off: in principle, the professor knows all the principles of aerodynamics that are put to work in the airplane, but he cannot explain and compute all the equations on the fly. Quantitative trading models have a competitive edge; they are based on algorithms that aggregate the know-how that researchers specialized in a number of disciplines have brought together, and deploy this embedded knowledge in a systematic and consistent manner; quantitative algorithms do not miss a price tick; they do not need to sleep, eat or go on holidays.