Global equity indexes contain a significant amount of day-to-day price chop, but, due to the herding of market participants, they still exhibit longer-term trends. Traditionally, intermediate-term or longer-term trend following models (greater than 6 month lookback) are used to exploit these trends. However, because these models are designed to ignore the short-term chop of equity markets, they are susceptible to signal lag at market turning points.
The main goal of our credit momentum models is to capitalize on short and medium-term trends (typically 2 to 6 weeks) in equity markets. Our models rely on the lead-lag relationship between credit markets and equities to filter out short-term equity market noise and anticipate directional changes. They translate short-term trends in credit indicators (credit spreads, default rates, credit market liquidity, etc.) into signals that are implemented with equity index futures.
Because of the prolific amount of choppy price movements in equity markets, a short-term momentum model that uses equity price action to generate its signals is unlikely to produce consistent positive returns.
However, movements in credit markets contain less noise than equity price movements.
Therefore, our credit market momentum thesis can be broken into two main parts:
The best environments for the hybrid momentum models can be broken down into two major types: steadily rising markets and sharp selloffs.
Months with multiple direction changes often present the hardest trading environment for these models. These models will also struggle at the beginning of any trend change as they switch their signal to catch up with the new trend.
On average, these signals last 10 to 15 trading days. In times of heavy chop, they will be shorter in duration, while a smooth and steady trend can produce a signal that last up to several months. We expect this model to be long 50-60% of trading days, short 20-30% of the time and in cash the remainder.
