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242 THE DAILY TRADING COACH<strong>for</strong> example, consists of three kinds of trades: intraday trades with plannedholding times of less than an hour; intraday swing trades with planned holdingtimes of greater than an hour; and overnight trades. The short intradaytrades are based on short-term patterns of price, volume, and sentiment.The swing trades are trend following and are based on historical researchthat gauges <strong>the</strong> odds of taking out price levels derived from <strong>the</strong> prior day’spivot points. The overnight trades are also trend following and are based onlonger-term historical research that shows a directional edge to markets.These trades comprise different kinds of trades, because <strong>the</strong>y are based ondifferent rationales and involve different positioning in <strong>the</strong> markets. Forinstance, I can take a short-term intraday trade to <strong>the</strong> long side, but short<strong>the</strong> market <strong>for</strong> an overnight trade that same day.You can identify <strong>the</strong> inventory of <strong>your</strong> <strong>trading</strong> business by segregatingtrades based on what you’re <strong>trading</strong> and how you’re<strong>trading</strong> it.For o<strong>the</strong>r traders, <strong>the</strong> division of <strong>the</strong> <strong>trading</strong> business will be by assetclass (rates <strong>trading</strong> versus currency trades versus equity trades) or by <strong>trading</strong>strategy/setup (trades based on news items; trades based on openinggaps; trades based on relative sector strength). Relatively early in my <strong>trading</strong>career, I broke my trades d<strong>own</strong> by time of day and found very differentmetrics associated with morning, midday, and afternoon trades. That findingwas instrumental in focusing my <strong>trading</strong> on <strong>the</strong> morning hours. In o<strong>the</strong>rwords, <strong>the</strong> divisions of <strong>your</strong> trades should reflect anticipated differencesin <strong>your</strong> income streams. If <strong>the</strong> returns from <strong>the</strong> <strong>trading</strong> strategies or approachesare likely to be independent of one ano<strong>the</strong>r, <strong>the</strong>y will deserve<strong>the</strong>ir <strong>own</strong> bin <strong>for</strong> analysis by metrics.One of <strong>the</strong> breakd<strong>own</strong>s I’ve found most helpful in my <strong>trading</strong> is basedon tagging <strong>the</strong> market conditions at <strong>the</strong> time of entry. To accomplish this,you would tag each trade based on whe<strong>the</strong>r it was placed in an upwardtrending market, a d<strong>own</strong>ward trending market, or a nontrending market.You will want to be consistent in how you identify market conditions; my<strong>own</strong> breakd<strong>own</strong>s (because I trade short-term) were simply based on how<strong>the</strong> current market session was <strong>trading</strong> relative to <strong>the</strong> previous one. It iscommon that traders will per<strong>for</strong>m better in some market environmentsthan o<strong>the</strong>rs. For instance, based on a different breakd<strong>own</strong>, I learned thatI was most profitable in moderate volatility markets, as tagged by <strong>the</strong> VIXindex at <strong>the</strong> time of entry. When markets were relatively nonvolatile orhighly volatile, my returns were significantly reduced. This was useful tome in knowing when and where to take risk.

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