# Tag Info

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If there are no arbitrage opportunities there is no dominant hedge or long position. Why would there be an arbitrage opportunity if everything was priced correctly? There may be arbitrage opportunities even if there are no dominant hedges or long positions. Put-call parity doesn't depend on a badly priced long position it depends on a badly priced ...

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See Evidence Based Technical Analysis by Aronson: http://www.amazon.ca/Evidence-Based-Technical-Analysis-Scientific-Statistical/dp/0470008741 Stochastic Oscillator backtest: http://systematicinvestor.wordpress.com/2013/07/19/stochastic-oscillator/ The above blog has a lot of TA backtests with code, warning that the authors code masks base functions. ...

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Please clarify rigorously what you mean by each term. It is not true that no dominance is a consequence of no arbitrage. Think of the put-call parity: $C-P=S-K$, assuming $r=0$ since it's inconsequential. If there is no short selling then we can have: $C-P \geq S-K$ without arbitrage but No Dominance would not hold. If you think very deeply about this, ...

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High Frequency: Seconds, Milliseconds, Nanoseconds Medium Frequency: Minutes Low frequency: Hours, Days, Months, Years

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As mentioned above, your post is very broad and therefore difficult to answer. However, I have had a lot of fun trying to reverse engineer some strategies, from back when RentASignal.com was in business. My general conclusion where that the strategies for rent where optimized for a great back test, the developers then set the strategy up for a forward test ...

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In the case of application in finance, usually, GARCH is used in estimating realized volatility of returns based on the weight we would like to give to each past observation. Ultimately after estimating (calibrating) the parameters of the model to an existing time-series, GARCH is used for forecasting multi-step ahead return (future) volatility. Different ...

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From my understanding I believe you will calculate conditional variance with GARCH. You would then need to take the square root of the variance to calculate the standard deviation/ volatility. One key aspect in GARCH is that you can calculate the "persistence" , I.e. How likely is the asset to "persist" to its long run variance

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