POLL: Do you typically risk more money on a trade than you plan to make?

Discussion in 'Trading' started by Thunderdog, Jul 25, 2009.

Do you typically risk more money on a trade than you plan to make?

  1. Yes

    31 vote(s)
  2. No

    22 vote(s)
  1. Although it is conventional wisdom to risk less money per trade than you plan (or hope) to make, several ET members claim to do the opposite and risk more dollars per trade than they normally expect to make, by depending on high trade reliability.

    Although I personally don't adhere to a number of precepts of conventional wisdom, this is one that I embrace. I risk fewer dollars per trade than I hope to make. In my case, it's a very murky relationship, because I claim no ability to "predict" either the magnitude or duration of a move. Therefore, it should come as no surprise that I endeavor to risk relatively little per trade.

    What about you? Please vote and provide any relevant comment.
  2. This could be an interesting thread.

    Once of the things that is important to consider is the notion of "static" risk/reward profile vs. what actually happens in a live market - "dynamic" risk.

    For example, let's say a trader starts out with 1 ER2 (TY) contract. They risk 2 points or $200 (at $10 per tick)

    Let's assume they have a 65% win rate, not unachievable by any means (with good patient setups)

    Let's assume the final target is 1.5 points, but that after the market moved 5 ticks in their favor, they take 1/2 profit on the position and then move their stop up to .4 point from B/E. And try to let the rest run out to the target.

    When you consider the partial profit taking and moving the stop close to B/E on the remainder, you end up with a completely different profile of risk on the trade than it initially seems like because:

    -you are only exposed to the full 2 point stop for a brief period of time on most trades until you grab the .5 profit

    - it is a low probability that the trade will go the 2 full points to the original stop loss order before it goes .5 point to the first scale-out of 1/2

    - if the market has moved the .5 in their favor, then the probabilty that it will continue to allow for at least some additional profit on the second 1/2 of the open position increases significantly as it is statistically unlikely that .5 was the exact amount of movement before the market reverses and hits their stop.

    -then if they get stopped out on the second 1/2 of the trade, they break even on the whole trade. Moving the second 1/2 stop to -.4 to entry allows for the extra tick to cover commish if they took first 1/2 profit at .5 win.

    - this whole calculation is affected dramatically by the "win rate" on the trades over a period of time. An extra 10% in win rate really cranks up the actual net winnings.

    With only a decent win rate and an occasional T-2 winner on the second 1/2 of the trade, this strategy can have a very good expectancy - much better than it looks from a "static" perspective on paper where a trader would say "1.5 win to 2.0 loss? that can't work!"

    (I wrote this off the cuff without doing the actual calcs and you have to factor for some slippage but you can get the point)
  3. NoDoji


    I select higher probability setups with very clear price levels where a trade would be invalidated. Overall this should produce a win:loss ratio higher than 50%, so I'm satisfied with a minimum profit target that's equal to my stop loss. If the trade continues to move in my favor that's great.

    Also, because I choose these specific entry levels based on setups that should not reverse direction, I move my stop to b/e as soon as the trade becomes profitable. Occasionally, this stops me out, trade moves a little against and then eventually back in my favor. I often re-enter the trade when this happens rather than risk letting a profit turn into a loss.

    One of my trading roomies has a different approach. He has a minimum 2:1 profit:loss ratio and only moves his stop to b/e when the trade is pennies away from his target. He has slightly more losing trades than winning trades, but the 2:1 ratio has given him a very strong overall ROI of almost 40% YTD.
  4. i day trade and have a set stopout for the day and i try to make about 1/3 to 1/2 that through a series of about maybe 8 positions a night and i never close out a position as a loss unless i'm at my stop-loss for the day. so i guess you could say i risk 16x what i intend to make on a trade or more realistically like 8x, because usually i won't stop out from just one loser, day in and day out and that has worked for me.
  5. this is the way pros size positions:

    Kelly %

    The Kelly % statistic was developed by John Kelly at AT&T's Bell Laboratories in 1956. John Kelly's original work dealt with long distance telephone transmission signal noise. You can read his original AT&T paper on signal noise by downloading the PDF at the bottom of this section.

    Kelly's work is recognised today as being able to determine the optimal betting size which will maximise the growth of your portfolio over time.

    The formula for the Kelly % is:

    Kelly % = W - (1 - W) / R

    Kelly % = Percentage of capital to risk per trade for maximum gains.
    W = Historical Winning percentage of the System (trades).
    R = Historical Average Win/Loss Ratio (AVG Dollar Win/Loss).

    The Kelly % statistic can be applied to a system as follows:

    Peter has a trading system with a winning percentage of 50% with average profits twice the size of his average losses.

    From this brief description we know that Peter has a profitable System.
    Putting these figures into the formula for Kelly % gives us W = 0.5 and R = 2. Substituting this into the Kelly % formula gives the Kelly % as 0.25. The Kelly % tells us the amount of equity Peter should risk in order to obtain optimal profits is around 25%.

    It should be noted that this amount of risk can be spread over the number of trades on average the System will have open at any one time.

    It is common to use 80% of the Kelly % as the optimal risk that is tolerable to a trader. In the example above, Peter has a system that on average has 10 positions open at any one time. He can spread his (25% x .8 = 20%) 20% risk over his ten trades. For Peter to obtain optimal results from his system, he should risk 2% for each trade.
  6. If need be, hell yes. All depends on the events that happen AFTER I enter.

    Mkt gives me a signal, from there the mkt "chooses its own adventure" and I'm prepared to follow it with VERY specific rules for each scenario. Fucking works like a charm, can't explain it.
  7. Let us say that Peter is faced with the not so uncommon situation of a streak of 4 losers. Peter starts with X amount of capital.

    After 1 loser, Peter is left with: X(1-.25) = .75X
    After the second loser: .75X(1-.25) = 0.5625X

    If Peter is a fund manager he is already getting calls for withdrawls and a lot of heat from investors.

    After the third loser: 0.5625X(1-.25) = 0.421875X

    Now Peter starts to sweet really bad. He curses %kelly and everything that has the optimal designation on it.

    After the forth loser Peter is left with: 0.421875X(1-.25)= 0.31640625X

    Peter has gotten a margin call a long time ago but assuming he did not, Peter is in the verge of a nervous breakdown.

    Peter has started with 1M and he now has 316K in the account left. Optimal loser.

    Peter stays away from trading for about 5 years and when he starts again he risks a fixed 1% on each trade. He learned his lesson.

    Good paper on %Kelly
  8. intradaybill, that is some funny stuff. Not only did you not understand milimabuses' point you quoted but it's clear you didn't read/understand the paper you linked too either.
    #10     Jul 27, 2009