<b>http://www.elitetrader.com/vb/showthread.php?s=&threadid=76744&perpage=6&pagenumber=1</b> Our "backyard party" is meant to cover a bunch of different how-to or educational topics that apply to many (if not most) traders. The first topic of discussion concerns efficiency in management of a trading account in general = individual traders in particular. It was suggested by a friend (<b>Version77</b>) that we offer this out as a unique thread. Excellent suggestion. Here it is!
<b>"Optimal-A"</b> Traders of all markets and methods tend to fixate on the entry, exit and management of trades. Obviously that part is critically important⦠lest there be no further progress from there. Once a trader gets the hang of their chosen approach, attention is usually turned toward how much money to risk, how many contracts to work, etc. There is absolutely nothing wrong with just a static, linear approach to managing trades. Pick a number of shares or contracts and go. Simple as that, right? Well, it can be and thatâs just fine. But itâs not an optimum use of capital at all. I realize this basic info below is old hat to many traders here. I also expect it is all brand new to a number of traders as well. Very seldom is this type of stuff covered in public, versus the old clichéâs of trade four contracts, peel three off at x-partial profit and let the fourth run for distance, etc. By no means do I want to talk down towards the veteran traders, nor do I want to talk over the heads of others. Weâll try to cover the basics first in this installment, then build on from there. <b>%Risk Scale</b> First thing we need is a trading approach that works. Our trading approach for this optimal money management must have a positive expectancy, i.e. it needs to make money. News flash, right? If we donât have that, the remainder of this exercise is futile. #1: In addition to that, it needs a win/loss ratio very near 50% (or better) accuracy. #2: Needs to win roughly one out of two trades, and the distribution of such should be fairly balanced. If our method wins 60% of trades but frequently endures ten-trade consecutive loss sequence , thatâs not nearly good as a method which wins 48% of the time but seldom loses three trades in a row. Now, logic dictates that a 60% correct trading approach would not have drawn-out drawdowns. Iâve seen it happen, especially in mechanical systems. Just pointing out the fact that such strings of sustained losing trades can exist in a high %correct approach. #3: Our trading approach must have at least a 2/1 profit to loss ratio result. A negative profit to loss trade size scale is unsustainable over the course of time in my opinion anyways. For managing accounts in optimal fashion, we must have a positive balance of profit to loss results per trade. Iâve been told by way more than a few traders they were taught (and use) tactics such as +2pt ES target / -2.25pt ES stop or worse, a +10pt YM profit / -20pt YM stop for scalping tactics. Those dogs will not hunt over the course of time: try that scale of profit to loss long enough and total ruin is inevitable. Period, end of story. The higher our profit to loss ratio is, the better. That said, itâs pretty tough to beat a 2/1 ratio in ES and possibly 3/1 ratio in ER. Just 2/1 ratio of profit to loss is fine, with balanced distribution of win â loss results being equally important. <b>Risk 101</b> To recap, itâs critical to know your average win â loss patterns of distribution AND what your average profit/loss ratio is. Mechanical system traders have this data compiled in their reports. Method = discretionary traders need to figure this data out manually or spreadsheet fashion. Sounds like a lot of work? Who ever told you making money thru trading is easy? (laugh) Hereâs where we begin our lesson with hypothetical data for sake of discussion. <b> ET Method Of Trading Symbol: $ET emini futures (fictitious) Value: $100 per index point Trading Exchange: EliteTrader.com :>) </b> If we are accomplished $ET emini traders, we already have our data points to work with. We know that over any long period of time thru all market conditions averaged out our win/loss ratio is 50% and our profit/loss ratio is 2/1. The worst-loss string of consecutive trades ever was five, although we know it could be more in the future. O.K. so far? Ya with me? Great! Our initial trading account balance is $10,000. I realize thatâs paltry change to many of the big-gun traders here, but it took some of us rednecks quite awhile to save this much up. Had to sell a few of our coon hound pups and some of the antique Skoal can collection, plus our granddaddyâs coin collection to raise the cash. The coins fetched $9,400 from that dealer in the big city, good thing we had those pups and antique Skoal cans to make up the difference. So⦠weâve got $10,000 to work with and we donât want to risk more than 5% on any given trade. That would be -$500 per trade initially, and the dollar risk amount decreases if our account goes backward. By the same token, the dollar risk amount increases with account growth. We are trading $ET emini futures. They move in $100 per contract increments, and we use -$100 per contract initial stops on each trade. With -$500 per contract as our designed risk, we can trade five contracts (five at -$100 each on a stop) with the $10,000 initial balance. If our account balance goes to $12,000 from there, we trade six contracts, If our account balance goes to $15,000 from there, we trade seven or eight contracts. Should we hit a string of losses and account balance goes from $15k back to $12k, we drop our trade size down to six contracts again. If the balance slips to $10k, we scale back to five contracts there. <b>Sliding Scale</b> What does this all accomplish? It keeps us working our capital to max efficiency per the selected level of initial risk. We reduce position size when account is declining, not increased risk like so many traders do. When account size is growing, likewise is the trade position size. Now, adverse risk is mathematically contained, to a degree. First & foremost we must be sure our trading approach is what we believe it to be. Gotta have a rather smooth win/loss sequence and favorable profit to-loss-ratio for this scale to work well. The scale will not work if our profits are small and losses large, relative. The scale is designed to reduce overall capital risk during adverse periods for our protection. Sticking with a static number of contracts with account balance at $30,000 and $15,000 alike is far from optimal. Somewhere in that curve, we had too many or too few contracts at work. Imperative to long-term success is adherence to the contract scale, never over-riding contract size to make up for losses during drawdowns. The contract scale will take care of that for us⦠and helps protect (never eliminates) risk of ruin. <b>One Component Only</b> This part of managing an account is critical to rapid, methodical growth. It can be detailed as specific amount of contracts (shares) traded on each turn with each new equity point in the curve. It can also be more generalized, like trading five contracts per $10,000 balance and seven at $15k, ten at $20k and fifteen at $30k respectively. There are some inherent and a few personal self-management points one needs to be aware of. Weâll cover potential downside, pitfalls and limitations in the next visit here. Letâs all digest the basics, first. In order to trade a small â modest or even large account with most efficiency, correct application of trade size is vital. Along with the contract scale discussed above there are others aspects of managing dollar risk while maximizing weâll add on ahead. This is not the entirety of a mechanical, managed account method I use. It is the basis from which to build on, further details to follow. <b> Hope this helps! Austin</b>
Copyright (c) Technical Analysis Inc. Stocks & Commodities V. 23:2 (60-63): (Reprinted by author with permission) <b>Partial Profits = Fiscal Folly? (Part One)</b> Had I known that my career path would wind its way into professional trader status, I might have studied advanced mathematics with much more enthusiasm. After all, math is an exact science that does not lie. The way we assemble and interpret numbers to compile trading data may be subjective, but two plus two always equals four⦠or does it? Somewhere along the way, many traders have been led to believe that taking partial profits, that is, exiting some part of a trade before the necessary profit target is hit while letting the other part ârunâ is a viable tactic. Reasons for this boil down to basic human emotions. Some followers of this practice suggest that partial gains taken early in a trade reduce stress and allow the trader to ride out the remaining contracts, while others suggest that taking partial profits protects against drawdown (maximum loss), should a trade reverse early to halfway through its execution. <b>Not As Appears</b> On its face, taking partial profits may look like a professional tactic. The concept certainly has great appeal to new traders entering our game. But is it really as beneficial as it appears? If we can agree that math is an exact science, why donât we take a few words here to compare partial-profit exit tactics with the straight exit of trades? Assuming each tradeâs win/loss results happen in random fashion, weâll look at three hypothetical trading methodologies whose results (over the course of time) have win/loss ratios of 80%, 50%, and 40%. Finally, we will assume our profit target to initial stop-loss ratio is always +2 / -1. The math used in this article is meant to serve as an example only. <b>Breaking Down Numbers</b> Using the Standard & Poorâs 500 e-mini contract as the standard symbol of comparison, letâs target a four-point profit exit while using a two-point initial stop for the sake of discussion. Some traders attempt to scalp for a point here or there; I personally trade intraday for ES four ~ five point profit (or greater) moves using trailed stops to reduce max risk when trades move some distance in favor. Using three different probabilities of trading success (80%, 50% and 40%), we can build some simple tables to see how the various exit plans would fare. Trading two e-mini contracts in a method that results in a 50% success rate for a win ratio, any ten trades taken at random from a larger sample should yield $2,000 profit as a result. Simple math: half the trades gain four points, or $400 per-position profits. The other half loses two points, or $200 per position. Net result? We gain an average of $200 per trade over the course of time. What happens when a trader exits half of a position at âprofit target #1â (or whatever fancy phrase) for a two-point gain? Well, the average winning trade on a partial exit only yields $300 per position instead of $400 on a full exit approach. The stop-losses remain static at $200, but earning power has been effectively cut in half by the early exit for partial-profit gains. Taking this approach one step further, Iâve seen exit tactics touted whereby the trader scales out in stages on multiple contracts. One such popular method is to exit 25% of an e-mini position at a one-point gain, another 25% at a two-point gain, and then the remaining half of the position at a four-point gain. How might this method fare compared to making straight entries and exits? <u>50% Win Ratio Using Two Contracts</u> Two ES contracts: 50% win ratio +4pt profit target = both contracts: $400 -2pt initial stop = both contracts: ($200) Average winning trade: $400 Average losing trade: ($200) Average trade: $200 Ten average trades: <b>+$2,000</b> Two ES contracts: 50% win ratio +2pt profit target = one contract: $100 +4pt profit target = one contract: $200 -2pt initial stop = both contracts: ($200) Average winning trade: $300 Average losing trade: ($200) Average trade: $100 Ten average trades: <b>+$1,000</b> We easily see that scaling out of trades at different stages results in worse performance than the straight exit strategy. === <u>50% Win Ratio Using Four Contracts</u> Four ES contracts: 50% win ratio +4pt profit target = all contracts: $800 -2pt initial stop = all contracts: ($400) Average winning trade: $800 Average losing trade: ($400) Average trade: $400 Ten average trades: <b>+$4,000</b> Four ES contracts: 50% win ratio +2pt profit target = two contracts: $200 +3pt profit target = one contract: $150 +4pt profit target = one contract: $200 -2pt initial stop = all contracts: ($400) Average winning trade: $550 Average losing trade: ($400) Average trade: $150 Ten average trades: <b>+$1,500</b> The result of scaling out of trades is much worse in this scenario. (to be continued...)
<b>Part Two (...continued)</b> In each case the straight exit produces better results than scaling out. We see results fared even worse than the simpler two-stage exit profiled earlier. This time, the overall expected results went from one-half to roughly one-third of a straight exit at the expected profit target. Perhaps thatâs just an anomaly for systems or methods with a 50% correct profit expectancy. Maybe results are far different when it comes to trading methods with a higher percentage of accuracy? <u>80% Win Ratio Using Two Contracts</u> Two ES contracts: 80% win ratio +4pt profit target = both contracts: $400 -2pt initial stop = both contracts: ($200) Average profit per trade: $200 Average profit x eight winning trades: $3,200 Net loss x two losing trades: ($400) Ten average trades: <b>+$2,800</b> Two ES contracts: 80% win ratio +2pt profit target = one contract: $100 +4pt profit target = one contract $200 -2pt initial stop = both contracts ($200) Average profit per eight winning trades: $2,400 Net loss per two losing trade: ($400) Ten average trades (total):<b> +$2,000</b> Four ES contracts: 80% win ratio +4pt profit target = all contracts: $800 -2pt initial stop = all contracts: ($400) net Average profit per eight winning trades: $6,400 Average loss per one losing trade: ($800) Ten average trades (total): <b>+$5,600</b> Four ES contracts: 80% win ratio +2pt profit target = two contracts: $200 +3pt profit target = one contract: $150 +4pt profit target = one contract $200 -2pt initial stop = all contracts ($400) Average profit per eight winning trades = $4,400 Average loss per two losing trades: ($800) Ten average trades (total): <b>+$3,600</b> Scaling out exit tactics with high % win achieved are nearer the straight exit results than examples in 50% accuracy methods, but still inferior. Worse yet are the standardized results for traders who are working too hard at getting out of performing trades in stages for too little net gains. Is there any reason to use partial-profit exits? Perhaps the true magic of this approach lies in systems or methods with less than a 50% correct profit expectancy? Care to guess how those raw data results might calculate? Two ES contracts: 40% win ratio +4pt profit target = both contracts: $400 -2pt initial stop = both contracts: ($200) net Average profit per four winning trades: $1,600 Average loss per six losing trades: ($1,200) Ten average trades (total): <b>+$400</b> === Two ES contracts: 40% win ratio +2pt profit target = one contract: $100 +4pt profit target = one contract $200 -2pt initial stop = both contracts ($200) net Average profit per four winning trades: $1,200 Average loss per six losing trades: ($1,200) Ten average trades (total): <b>$0</b> === Four ES contracts: 40% win ratio +4pt profit target = all contracts: $800 -2pt initial stop = all contracts: ($400) net Average profit per four winning trades: ($3,200) Average loss per six losing trades: ($2,400) Ten average trades (total): <b>+$800</b> Four ES contracts: 40% win ratio +2pt profit target = two contracts: $200 +3pt profit target = one contract: $150 +4pt profit target = one contract $200 -2pt initial stop = all contracts ($400) Average profit per four winning trades: $2,200 Average loss per six losing trade: ($2,400) Ten average trades (total): <b>(-$200)</b> These results are the worst by far. Why? The reason is simple: maximum profits are essential to overcoming the greater net percentage of unprofitable trades. Cutting profits short in a system or method that wins less than 50% of the time will actually accelerate losses. The worst possible scenario is a multiple-contract trading approach based on a strategy of partial profit exit levels <b>Presumptions</b> The basic math used in this study fails to account for several factors. First of all, it assumes every trade reaches either its initial profit target or initial stop-loss. In reality, we know that failed trades and trailing stops will create an unknown percentage of trades that are exited between initial stops and profit targets. This would naturally skew average trade size, but in which direction is debatable. With those scenarios in mind, Iâve stuck to the idea that traders have one initial stop and one desired profit target in mind. If we try to balance a 2/1 profit/loss ratio over time, we must let the profitable trades reach their initial target in order to preserve that balance. Using a two-point stop in the S&P mandates that we let every trade possible run to our target or beyond. <b>Internal Weakness?</b> Using the same +2 profit / -1pt loss ratio balance assumed in the exercises above, there is nothing wrong with traders exiting part of their position at a four-point profit target and then letting the balance ride, using tightly trailed stops. That approach is far different from taking partial profits before reaching the initial target... just to âbook somethingâ and somehow benefit emotionally. If a trader uses two-point stops for two e-mini contracts while taking profits at one point and then at two points, what has that trader essentially done? He or she has taken a 2/1 profit-loss ratio and made it a 1.5/1 ratio instead. Has he done anything to reduce the loss size of -1? Absolutely not. What a trader using scaled-out tactics has done with this âpartial profitâ logic is to remove any upside leverage in his favor. Keep in mind the reality that slippage, commissions, and personal income tax do exist, and they will mean the difference between hypothetical results and cold, hard cash in our trading account. With all due respect, taking partial profits seems to be a crutch for emotional weakness. A trader using a hasty exit tactic seems to lack confidence in his or her overall trading method, the market, in oneself, or some combination thereof. Non-performing trades will hit our initial stops; this is not something we can control. However, performing trades move in our favor in many different ways. Sometimes itâs a fast, straight path to intended profit targets. Sometimes it is a slow, tortuous grind from the initial entry to our profit goal. Those are the times when lack of conviction in your method or yourself can cause you to seek early exits. <b>Conclusion</b> Iâll readily admit these basic mathematical examples could be flawed. Iâm open to any other traders out there who can demonstrate just why scaling out of trades for partial profits makes fiscal sense. I can easily build a case for why scaling into trades with multiple lots will give you upside leverage and downside protection, but thatâs an entire article in itself. If any active traders in the market with real money at work can demonstrate other examples of partial profit tactics that work mathematically, Iâll be the first to embrace their logic :>) <b> Best Trading Wishes, Austin P</b>