Poll: Is successful trading more dependent on skill than luck?

Quoting WTB

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I keep reading on these forums that exits are more important that entries. I dont agree. I would agree if, after scoring a 60% or better win/loss ratio, you're still not making money. In such case then yes, the problem is within the exits or money management.

However, most of the traders dont even score a 50% win/loss. I dont care what sort of money management or magical exit strategy you follow, if you lose more trades than you win, it's going to be VERY tough in the long term to keep afloat. VERY VERY tough. Proper entry-timing is as crucial as proper exiting if not more.

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Quoting hanover

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If there was no randomness in price movements, then prices would be 100% predictable.

And if trading was 100% skill, then the skilful trader would have a 100% win rate. Unless his system, or its implementation, is somehow faulty, then losses are "accidents" that happen, due to factors outside of the trader's control. What falls outside of one's control ultimately amounts to luck.

With trading there is risk involved. We are dealing with probabilities, not certainties. Within the realm of probability, anything - however unlikely - can happen.

David

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Quoting piccolo

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make 5pip TP and 40pip SL.. you will have over 80% win/loss with almost any system.

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Quoting melpheos

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Wrong, even the perfect pianist can play one wrong note or one out of rythm note... Even the perfect trader can lose some pips...

The difference between the skillfull and the not so skillfull one will be how the skillfull one will be able to get rid of his misses...

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Quoting WTB

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You missunderstood my post.

I was trying to say that newcomers should first try to focus on scoring a minimum of 50% win/loss (which many do not achieve) and THEN focus of polishing their exit techniques out. First things first, and there's little point in stressing over your exits as a beginner trader if you dont have the entry part figured out yet.

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Quoting hanover

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If there was no randomness in price movements, then prices would be 100% predictable.

And if trading was 100% skill, then the skilful trader would have a 100% win rate. Unless his system, or its implementation, is somehow faulty, then losses are "accidents" that happen, due to factors outside of the trader's control. What falls outside of one's control ultimately amounts to luck.

With trading there is risk involved. We are dealing with probabilities, not certainties. Within the realm of probability, anything - however unlikely - can happen.

David

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Quoting mbqb11

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I draw so many similarities from poker and trading so I very much agree.

You can get your money in with the best hand and lose(happens all the time), but when the probabilities are in your favor it is worth making that play over and over, because in the long run(which is what counts) you come out ahead.

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Quoting bluebuddha

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You can learn a lot from listening to Kenny Rogers

Personally one of my favorite books on trading psychology is Zen and the Art of Poker.

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Quoting hanz

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it's a SKILL!!!

like this guy he turns $300 into $8k in less then 2 days...

ok don't tell me i make this up or something...

i found it on moneytec

it's up 2 u to believe...

p.s: who says scalping doesnt work

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Quoting Andy12

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It is very impresive! Deffinetly skill!
EUR/GBP is good currency, because it is one of the most predictable currency. Moves on EUR/GBP more logical then on any other currency. I scalp and sometimes I scalp on EUR/GBP and results were always not only positive but also very predictable so far.

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Quoting Andy12

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Great post Hanz, it gives me energy, another prove that you can make it on Forex!

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Quoting svtnick

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Im going to be honest here, but I think most of you on here are better of putting your money into some managed fund then trade. If you dont understand that to make money in any market and to keep making money requires managment of RISK. If you dont....at some point YOU WILL LOSE IT ALL.. You can turn $300 into $1000 in a week by simply managing your risk. You can do it winning 3 out of your 10 trades. I think you know where Im going with this...and if you need to know the rules you need to figure them out for yourself or you will never learn. And for those you dont know, managment of RISK is SKILL.

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Quoting james16

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i agree s, risk skills and a rifle shot mentality versus a shotgun one when actually trading are the keys... if whatever/whichever way you decide to trade has not/did not go thru at least 3 to 6 months of consecutive profitable demo your not treating it as a business. people that dont treat this like a business dont last long...

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Quoting melpheos

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Wrong, even the perfect pianist can play one wrong note or one out of rythm note... Even the perfect trader can lose some pips...

The difference between the skillfull and the not so skillfull one will be how the skillfull one will be able to get rid of his misses...

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Quoting hanover

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one can never control how many losses will occur in any given sequence of trades. That is an area of risk that can not be managed. It falls outside of the trader’s control.

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Quoting Gwan

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how about martingale, averaging up&down, scaling, pyramid or thing alike, it chain link some trades into 1 loss or 1 winning result, i beleive we can imitate chain reaction on trading

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Quoting tdion

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Do you think successful trading is more heavily based on your own skills (discretionary/mechanical) or the random luck of the market?

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Quoting hanover

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Gwan, I think of trading as a game of expectancy. To win with any kind of consistency, we must have a system of entry and exit that provides a demonstrable edge that is capable of overcoming costs. Then, provided positions are sized modestly enough to preserve capital during a sequence of losses, and we maintain perfect discipline in trading our method, we are mathematically bound to profit. However, as with any game, just because the probabilities are in our favor, perhaps even handsomely so, does not offer an iron-clad guarantee.

When I started tinkering with systems, I wrote software to generate a stream of OHLC values, simulating different market conditions: trending, ranging, completely random. For example, if the last tick was upward, I could assign X% probability that the next tick would also be upward: if X>50, that is a “trending” market.

Next, I developed an additional layer, to simulate different entry, exit and MM algorithms. Then I had the software trade these methods over the generated price patterns, and tabulate profit, drawdown, number of wins, losses, average win size, longest losing streak, etc over 10 million simulated trades.

As best as I can remember, here are some of the conclusions that I reached:

1. In a trending market, bottom line is improved by letting profits run and cutting losses short. Hence trailing stops work better than scaling out by taking profits at pre-defined targets. The wider the trailing stop, especially when combined with the greater the trend factor, then the greater the overall profit. Scaling upward into a position exploits trending behavior one step further, and further improves profit.

2. In a non-trending market, exactly the reverse applies, i.e. one should take profits early and hold onto losses, because they are more likely to bounce back. Scaling downward into positions, and even increasing position size while doing so (e.g. martingale), further enhances profit. In fact, the greater the likelihood of price bouncing back, the more aggressive one can afford to be in sizing positions.

3. In a completely random market (i.e. no trend bias or counter-bias), the probability of profit and loss is exactly 50/50. If there are costs, then no system can profit indefinitely under these conditions. No matter what rules of entry, exit, MM are devised, eventual wipe-out is guaranteed. However, the smaller one’s position sizes, the slower the descent toward ruin.

4. Where no bias exists, setting tighter stoplosses will reduce loss size, but will reduce win rate, in almost equal proportion. Same applies to moving stoploss to break-even more quickly. Setting profit targets further away from entry improves win size, but reduces win rate, in almost exactly inverse proportion. Conclusion is that there must be a valid technical reason (i.e. market climate, or bias/inefficiency in price behavior) to support positioning of stoploss or profit targets (e.g. support/resistance), for exit to have any bearing on profitability. Anything less than this amounts to curve-fitting.

5. Same applies to entry. Unless there is a demonstrable underlying (technical or fundamental) reason that highlights inefficiency, we are simply curve-fitting.

6. The fixed fractional method of position sizing has the advantage that positions are sized smaller, in absolute dollar terms, as account balance decreases, and larger, as it increases, allowing a positive expectancy system to generate exponential gains. However, it does create the problem of asymmetric leverage, i.e. when one has lost (for example) 20% of one’s account, it requires a 25% increase on the remaining balance to claw back to break-even.

7. Everything else being equal, position size has no bearing on expectancy. All it does is magnify gains and losses in exactly like proportion. It can only be used to increase profit because conditions favor your system. Base expectancy is the product of entry and exit. Consequently, entry and exit ultimately determine the direction of one’s equity curve, and position size its slope. The true measure of system efficiency = dollars won for every dollar placed at risk, across a given time period.

8. The Kelly formula comes very close to optimizing position sizes, in terms of this efficiency, in the hypothetical situation where account wipe-out is not an issue. In other words, to maximize profit relative to drawdown, without giving wipe-out special consideration. However, given average win rate, win size and maximum allowable drawdown (which is subjective), a Monte Carlo approach is as good as any in calculating optimal position size.

9. Increasing or decreasing position size, depending purely on whether one is currently in a winning or losing streak, has negligible overall effect. However, increasing position size when conditions favor ones entry/exit algorithm (e.g. when using a trend-following method in a trending market), and/or decreasing size when conditions are unfavorable, has a hugely significant effect.

10. The larger the sample size, the more statistically valid the results. (However, this doesn’t take the possibility of obsolescence into account).

11. The corollaries of the above are valid. For example, if letting profits run and cutting losses short tends to lead to greater profit, then we may assume that prices are trending (see point 1) more often than not.

12. Where (hypothetically) costs are irrelevant, trading more frequently (i.e. shorter time frame) generates a smoother equity curve. Everything else being equal (and assuming a positive expectancy entry/exit method), this will leave return unaffected while mitigating risk. However, costs being a reality, the shorter the price moves being traded, the greater the edge necessary to overcome the costs.

13. Extrapolating point 12, trading simultaneous (or overlapping, time-wise) uncorrelated positions leverages time to increase return without affecting risk.

14. All technical indicators, even oscillators, lag price action. All are ultimately derived from OHLC and are therefore multi-collinear. However, the degree of correlation is reduced (i.e. greater independence is introduced) by comparing multiple waves (i.e. timeframes). For example, if H4 is capturing the next higher wave to M30, then phenomena in H4 offers more reliable ‘confirmation’ of M30’s behavior than simply attaching another technical indicator to M30’s chart.

15. All technical analysis makes the assumption that the patterns of the past are in some way, more likely than not, to repeat themselves in the future.


Of course I realize that the above amounts to nothing more than a mathematical model; in reality prices are driven by sentiment, by “commercials” hedging their businesses, by banks and institutions speculating, by the manipulations of market makers, and a host of other factors. But TA makes us the ‘promise’ that the sentiment of all of the participants is ultimately reflected in the current price. Viewed from the perspective of probability theory, price is merely a stream of numbers. It is also the value that we must ultimately buy and sell at, for sentiment can not otherwise be quantified.

Points 14 and 15 apart, much of the above is general in its nature and is relevant to many gaming applications. However, knowing all of this will not in itself make one a more profitable trader (I am living proof of that!). Why? In my experience, it is no easier to forecast imminent market climate (trending, non-trending, etc) than it is to forecast price direction. This is logical, of course, because climate is a product of price movement, and hence can change at any time, and without warning.

David

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