Quantitative Credit Strategy: Investment Approach
This is a unique quantitative credit strategy offered anywhere globally. The quantitative model is built around fixed income instruments that trade in public markets in the United States.
This strategy uses a deep learning neural network* to deliver its output. The model parameters are re-calibrated as per fixed schedule.
No leverage, indices or OTC derivatives are used, thus obviating the need of bank counter-parties or prime brokers.
This is a systematic strategy.
* Deep learning, a subset of machine learning, uses a layered structure of algorithms called an artificial neural network. Though humans design its architecture and select the network inputs and the desired output, the network — with the proper training — learns how to map the inputs to the intended outputs and make intelligent decisions on its own. Because of their structure and capacity, DL models can approximate much more complex functions than classical ML algorithms and can recognize nonlinear patterns in data that are too complex for humans to identify
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