A concept central to trading is that of pattern and pattern recognition. Different approaches to trading frame patterns differently, but all focus upon relationships that are deemed to be meaningful. After all, any particular configuration among market elements can occur and reoccur through random happenstance. It is when patterns happen for understandable reasons that we find them meaningful. We may or may not be able to predict when that pattern will occur next, but that is not necessary for successful trading. If we become very sensitive to meaningful patterns and their myriad expressions, we can identify their occurrence as they unfold. A psychologist, for instance, might not be able to predict when a patient will next experience a depressive episode, but can become highly attuned to occasions in which depression is starting to set in. Similarly, when couples make progress in their counseling, they can recognize patterns to their arguments and circumvent those by doing something more constructive.
Many active traders look at a very limited number of markets--often, only those that they are trading or thinking of trading--and so they miss important patterns that occur *among* markets. These intermarket relationships often reflect macroeconomic factors that are driving the participation of large market players. Recognizing when those relationships are waxing and waning can provide important clues as to whether particular market moves are likely to continue.
I've been reading a large--and excellent--book from John Netto called The Global Macro Edge. It touches upon a number of worthwhile ideas, including the importance of viewing performance (one's own and those of markets) in risk-adjusted terms. One idea I particularly liked was the ongoing tracking of correlations in the price movements among markets as a way of identifying market regimes and shifts in those regimes. The same concept is valuable in tracking correlations of moves among equity sectors. When we see dramatic changes in correlations, those patterns can alert us to the emergence of important themes that are driving market action. For example, after the recent election, we saw dramatic co-movement among equity sectors (industrials and financials versus higher yielding sectors) and markets (US dollar, rates, developed markets versus emerging ones). New flows were coming into markets, and the patterns of correlations alerted us to the drivers of those flows.
Let's combine two of Netto's ideas and imagine a situation in which your dashboard is tracking the risk-adjusted returns of different markets (a way of tracking quality of trend behavior) *and* the correlations among markets. The combination would tell you when shifting correlations are manifesting themselves as growing trends. That would be sweet for trend-following macro traders. It would also provide useful alerts as to when markets are becoming choppy and less patterned. After all, it's the pattern of patterns that ultimately defines the opportunity set for traders.
Further Reading: The Greatest Mistake Losing Traders Make
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Many active traders look at a very limited number of markets--often, only those that they are trading or thinking of trading--and so they miss important patterns that occur *among* markets. These intermarket relationships often reflect macroeconomic factors that are driving the participation of large market players. Recognizing when those relationships are waxing and waning can provide important clues as to whether particular market moves are likely to continue.
I've been reading a large--and excellent--book from John Netto called The Global Macro Edge. It touches upon a number of worthwhile ideas, including the importance of viewing performance (one's own and those of markets) in risk-adjusted terms. One idea I particularly liked was the ongoing tracking of correlations in the price movements among markets as a way of identifying market regimes and shifts in those regimes. The same concept is valuable in tracking correlations of moves among equity sectors. When we see dramatic changes in correlations, those patterns can alert us to the emergence of important themes that are driving market action. For example, after the recent election, we saw dramatic co-movement among equity sectors (industrials and financials versus higher yielding sectors) and markets (US dollar, rates, developed markets versus emerging ones). New flows were coming into markets, and the patterns of correlations alerted us to the drivers of those flows.
Let's combine two of Netto's ideas and imagine a situation in which your dashboard is tracking the risk-adjusted returns of different markets (a way of tracking quality of trend behavior) *and* the correlations among markets. The combination would tell you when shifting correlations are manifesting themselves as growing trends. That would be sweet for trend-following macro traders. It would also provide useful alerts as to when markets are becoming choppy and less patterned. After all, it's the pattern of patterns that ultimately defines the opportunity set for traders.
Further Reading: The Greatest Mistake Losing Traders Make
.