The world of quantitative trading is vast and rich in opportunities for sophisticated investors. One strategy that is attracting a lot of attention is fund picking. In this article, we'll explore this strategy, its importance in algo trading, and how it can be used to enhance returns.

Fund selection is the process of choosing the right mix of asset classes based on expected risk and return characteristics over the holding period. Historically, past fund performance has been used to predict future returns. However, this approach has been shown to be fraught with pitfalls.

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Contrary to popular belief, past fund performance has often been a poor indicator of future success. In addition, high management fees have often eroded superior gross returns. Without complete information and a sufficiently long track record from the fund manager, it is difficult, if not impossible, to make a robust fund selection.

The True Measure of a Manager's Talent

Studies have shown that the distribution of a manager's returns across his portfolio can reveal his talent. If a single asset is responsible for the majority of outperformance, this is likely to be due to one-off luck rather than genuine skill.

Research has identified additional indicators of managerial competence to complement traditional factor analysis. These indicators include the way funds are distributed, the time distribution of returns, and other factors that may indicate a competent manager.

Unfortunately, many investors tend to chase past winners rather than focus on the quality of the fund's underlying management. This is particularly true of closed-end funds, where investor preferences are often biased.

One study revealed that 76.6% of active funds have no alpha, i.e. they do not outperform the market. Only 2.1% of funds showed positive performance. This suggests that most funds do not offer added value to their investors.

There is evidence to suggest the existence of momentum in mutual fund returns. By selling the most overvalued funds and holding the most undervalued funds relative to their net asset values, it is possible to achieve significant returns. However, this strategy generally requires shorter holding periods.

Fund selection is a complex field that requires a well-informed approach. While past performance can often mislead investors, an algo trading approach can offer a better perspective. By using quantitative tools and in-depth analysis, it is possible to identify the funds most likely to outperform the market in the future.

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