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Spring Valley Asset Management, LLC  ® All Rights Reserved.

An investment with Spring Valley Asset Management, LLC is speculative, involves a high degree of risk, and is designed for sophisticated investors only. Prospective investors must meet specific qualifications, as well as be able to bear the risk of losing more than their entire investment. Past performance is not necessarily indicative of future results.​​



With the prolif­eration of data and exponential growth in computing power, researchers are virtually guaranteed to find something that performs very well despite not having any useful predictive ability. It merely fits idiosyncrasies, or noise, in the underlying dataset. In machine learning, this is called overfitting. Indeed, overfitting is now believed to be responsible for the failure of discoveries made in empirical finance to deliver in practice. Since expected returns and volatilities are unknown quantities and must be estimated from historical data, differences in performance between models can merely be the result of estimation error. Therefore, it is advantageous to combine the models. In machine learning, this is called an ensemble. Ensembles pool the predictions from many different models. If the models are imperfectly correlated, the combination can result in superior predictive power.