DYLS Reddit Mentions | ChartExchange

There are a few different types that I can think of.
There's a group called factors (sometimes marketed as smart beta). These are simple academically researched rules that have outperformed. The major ones are small size, cheap value, momentum, quality, and low volatility. You'll find lots of these funds in ETF form including multifactor funds that combine a bunch of them together. You can do factors as long-only, meaning you hold the stocks that have that factor, or market neutral meaning you hold the ones that have it and short the ones that don't. Most funds you'll find do long only.
Small size was the first factor identified in the literature (besides basic CAPM beta) in 1981. ([more history](https://alphaarchitect.com/2017/02/03/factor-models-are-more-art-and-less-science/)) But since then its performance has been poor and decades later it's no longer considered to be an outperforming factor on its own. However it still [works](https://www.aqr.com/Insights/Perspectives/The-Small-Firm-Effect-Is-Real-and-Its-Spectacular) when combined with other factors.
Value has also been giving people concern recently. But since it's normal for these things to go through decade long periods of underperformance, we won't be able to tell for certain if it has stopped working for a long time.
Low vol is a weird one because it's the exact opposite of CAPM which says that riskier assets have higher expected returns. There's disagreement about why these factors exist, and low vol really perplexes the people that think these factors are motivated by alternative risks.
It's important to realize that backtesting and 'machine learning' are not enough to find an outperforming strategy. Sharpe ratio is a measure of risk adjusted performance. For reference the S&P has a sharpe around .4, stocks plus bonds around .5, and 0 means it has the same returns as cash with non-zero volatility. If you take 1000 random strategies that have a true sharpe of 0 and backtest them, you can expect to find one with a measured [sharpe of 3.26](https://mathinvestor.org/2018/04/the-most-important-plot-in-finance/)! This is the major problem in quantitative investing. Figuring out which strategies do well because they generate value and which do well just by luck is not easy.
I mentioned AIEQ already. It's an 'AI driven' fund. I just skimmed their website again and didn't see anything about their actual strategy or how they trained the AI. That says to me that it's just a gimmick.
There are various big hedge funds that are doing similar things. Some of them are really great. The very best is [Renaissance Technologies Medallion fund](https://www.afr.com/technology/inside-the-medallion-fund-a-74-billion-moneymaking-machine-like-no-other-20161122-gsuohh) which shows what can happen when you put a lot of ultra smart people in a room and tell them to make a ton of money. But it's not open to anyone but employees, and similarly, many of the other good quant funds are not looking for new investors (plus you need to be an accredited investor). On average the ones that you could get into are not going to do that well, partly due to high fees.
There's some market timing funds like DYLS, PTLC, GMOM. These switch between different assets based on how the market is moving. I know of other timing strategies that I haven't seen in fund form, such as vol timing (hold less stocks when vix or realized volatility has been high), valuation timing based on measures like CAPE, economic indicators like unemployment. You can see some of these in the bottom right of [this site](https://www.portfoliovisualizer.com/).
Kind of similar is managed futures funds. Again, the best ones are private hedge funds and I wouldn't really recommend the public mutual funds that do this because they have regulatory restrictions that make them harder to operate. But these use trend-following and other systematic tools to buy and sell commodity and financial futures.