My opinion on trading size… revised
Recently, trading psychologist Dr. Steenbarger, in a post at SMB Capital’s blog, recommended that traders think about scaling out, that is diversifying and adding more trade setups, instead of sizing up their best trades. On reflection, I was doing well on my TopStepTrader combine until I took every trade at max size. On the other hand, I have seen it is far more difficult to make money trading a single contract and not adding size to my best trades. First, obviously the amount of capital that is one is trading is important and generally larger traders will prefer to scale out because there is no sense to concentrate risk beyond a certain point.
But, in this post, I wanted to more fully elucidate the answer, as I see it to this question for the trader who is thinking about scaling up. The answer is to first understand for an intuitive discretionary trader, one’s confidence in a trade should correlate with quality or probability of the trade working out. A big difference between trading and gambling is that traders can add size and make more money off their best trades. On the other hand, gambling games tend limit the ability to bet more when the odds are better, this is caused either by negative selection of other players or the bet size is fixed. There are really two distinct differences in trading compared to gambling: in trading the odds are unknown and there is an ability to bet bigger when one’s perception of the odds are more favorable. In gambling, the odds are knowable, at least in theory, and it is generally more difficult to bet more when one has more favorable odds.
It is important make the distinction between absolute size and relative size. To be clear, a trader could be trading at relatively low leverage and still trading bigger on their best trades. Discretionary traders often like to put small positions on to see how a trade idea is working out. In addition, the ability to obtain an expert level, zen-like state of trading, requires accepting that every trade has an uncertain outcome. As such, it is much easier to enter a trade with smaller size and then to add additional size based on the changing market conditions. In fact, if this keen ability is perfected then one can trade on even the slightest intuition or hunch because the edge is in the trade management.
The ability to dynamically size positions can be an advantage for systems but is primarily a benefit for the discretionary trader. Systems can be programmed to be highly selective. Discretionary traders often find that they become analysis paralyzed if they become too selective and find it difficult to take action. As well, a high level discretionary trader should be able to profit from many more “average” market conditions. Because discretionary traders are in general taking more average trades, there is greater cost in over analyzing the situation. As an aside, there is one possible approach that might work for a discretionary trader to become more selective and that would be to trade a shadow simulated account.
Now, that we understand why traders want to add size: it is important to understand the risk and ramifications of dynamic leverage. First, if there weren’t any cost to trading then it might make sense to continually change size based on the changing market conditions. However, in reality, there is a cost to make a trade and in most cases, it is difficult to beat max risk or simply not acting. This is why that often trading systems that can not read the market very well still make money because they are employing max risk. In other words, there is a hurdle that must be overcome. Even if I think my trade may be going bad, I have to calculate whether or not the new information is sufficient to overcome the opportunity cost of being wrong and the transaction costs. While my confidence may fluctuate in a trade, in general if I am not very sure then I should default back to max risk unless I can exit for a profit or break even.
Because adding multiple contracts is risky, it must be placed into a comprehensive and defined plan. A plan might look something like: trade max 2 contracts while profits < 3k, trade max 4 lots profits < 5k, and so forth. Each level has a corresponding daily loss limit such as $700 < 3k, $1000 < 5k, and so forth. The ability to size up is based on the relevant real-time performance and a trader may need to move up and down based on their actual performance.
Beyond those considerations, it is relevant to understand that adding size does not work on every type of trade: even high probability trades. I have found that over leveraging good system trades while decreasing the stop loss to be ill advised. And, that leads into the second part of the solution: the trader must have a keen understanding of likely market path dynamics and specifics of the trade quality to understand when adding size is more or less likely to work. It is a cognitive bias for traders to assume that the trade will work out in a perfect fashion in every case. The trader must know that only specific conditions will allow for sizing up in a way that is less likely to increase risk and must be keenly attuned to those situations.
Below are some specific types of trades examples I have not had much luck with adding size on:
On the other hand, these are trades that are more likely to work for adding size
In summary, I still believe that for the discretionary futures trader that the ability to add size on one’s best trades is likely to positively skew the profits. However, the additional contracts must be managed within a comprehensive and defined risk management plan and with an expert understanding of the conditions in which extra size can be properly managed. More over, the trader must be aware of cognitive biases such as assuming that every high probability trade can sized up or the tendency to want to add size after a losing a max sized trade. In general, the ability to add additional contracts is a powerful tool but one that must be used in a strictly disciplined fashion: a little is often better then a lot.
Curtis is passionate about markets. He has developed top ranked futures strategies. His core focus is (1) applying machine learning and developing systematic strategies, and (2) solving the toughest problems of discretionary trading by applying quantitative tools, machine learning, and performance discipline.
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