What are the factors that drive short-term returns in the stock market?
It's an important question for short-term traders obviously, but also for longer-term market participants, as the execution of one's positions ultimately has a significant role in determining profitability. This is especially true in situations where longer-term participants face a mandate to keep losses at a minimum. The demands of high Sharpe-ratio trading often necessitate shorter-term management of the price paths of one's trades, making entry and exit execution a meaningful part of trading returns.
I consistently find that traders do not think intelligently about short-term market returns. They either make the blanket assertion that short-term returns are random, or they attribute short-term returns to single sources without having tested those sources. So, for instance, short-term returns may be attributed to particular chart patterns or simply chalked up to loosely defined notions such as "trend". When tested, those explanations can be shown to be weak: very often, they apply to some market periods and not others.
As for the notion that short-term returns are random, that falls by the wayside when one has directly observed and worked with successful short-term market participants. They may be rare, but their superior returns can be documented across hundreds if not thousands of trades per year, year after year. As one of the few trading coaches that has worked for trading firms on a full-time basis, with full access to traders' returns, I can personally verify the existence of persistent market talent/skill among an elite set of short-term traders.
Here is where short-term trading can learn from the research into longer-term investment. That research suggests that longer-term market returns can be explained as the interplay of a number of factors. Bender et al identify six factors that explain longer-term market returns based upon considerable academic research. Capturing returns from these factors is an important principle behind asset management and can produce returns well in excess of active management.
The recent post on teasing apart buying and selling activity in markets suggests that buying and selling may separately account for two factors that account for short-term returns: momentum (the tendency of price direction to persist) and value (the tendency of price direction to reverse). I am currently operating with a third factor in mind that we can call "rotation". This is a factor in which trader/investor funds are shifted from some market groups to others with relatively little impact upon broad market averages.
The challenge of short-term trading is that all of these factors yield positive returns over time, but none of them produce positive returns across all market periods. Traders who identify with a single factor inevitably perform poorly when other factors are dominant, resulting in frustration. This is a great example of a situation in which a logical trading problem is mistaken for a psychological one. A worthy challenge is understanding the range of factors that impact short-term returns, so that trading style can flexibly accommodate those regime shifts in which one group of factors takes over from another.
Further Reading: The Momentum Curve
.
It's an important question for short-term traders obviously, but also for longer-term market participants, as the execution of one's positions ultimately has a significant role in determining profitability. This is especially true in situations where longer-term participants face a mandate to keep losses at a minimum. The demands of high Sharpe-ratio trading often necessitate shorter-term management of the price paths of one's trades, making entry and exit execution a meaningful part of trading returns.
I consistently find that traders do not think intelligently about short-term market returns. They either make the blanket assertion that short-term returns are random, or they attribute short-term returns to single sources without having tested those sources. So, for instance, short-term returns may be attributed to particular chart patterns or simply chalked up to loosely defined notions such as "trend". When tested, those explanations can be shown to be weak: very often, they apply to some market periods and not others.
As for the notion that short-term returns are random, that falls by the wayside when one has directly observed and worked with successful short-term market participants. They may be rare, but their superior returns can be documented across hundreds if not thousands of trades per year, year after year. As one of the few trading coaches that has worked for trading firms on a full-time basis, with full access to traders' returns, I can personally verify the existence of persistent market talent/skill among an elite set of short-term traders.
Here is where short-term trading can learn from the research into longer-term investment. That research suggests that longer-term market returns can be explained as the interplay of a number of factors. Bender et al identify six factors that explain longer-term market returns based upon considerable academic research. Capturing returns from these factors is an important principle behind asset management and can produce returns well in excess of active management.
The recent post on teasing apart buying and selling activity in markets suggests that buying and selling may separately account for two factors that account for short-term returns: momentum (the tendency of price direction to persist) and value (the tendency of price direction to reverse). I am currently operating with a third factor in mind that we can call "rotation". This is a factor in which trader/investor funds are shifted from some market groups to others with relatively little impact upon broad market averages.
The challenge of short-term trading is that all of these factors yield positive returns over time, but none of them produce positive returns across all market periods. Traders who identify with a single factor inevitably perform poorly when other factors are dominant, resulting in frustration. This is a great example of a situation in which a logical trading problem is mistaken for a psychological one. A worthy challenge is understanding the range of factors that impact short-term returns, so that trading style can flexibly accommodate those regime shifts in which one group of factors takes over from another.
Further Reading: The Momentum Curve
.