Factor alignment problem in portfolio optimization

External question — Quantitative Finance Stack Exchange Author: geonhwa Original post: https://quant.stackexchange.com/questions/61217 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. I'm taking a course 'AI for trading' in udacity, and there is a part I really want to make sure. The lecture keeps teaching me that there are alpha factors (driver of return) and risk factors (driver of variance) and it also says that alpha factors can turn into risk factors. I've heard that there is a joke between quant 'Your alpha factors are my risk factors' As I study more about factors, it seems that there is no difference between alpha factors and risk factors. Because, by taking risk factors, I mean by making ourselves exposed to those certain risks, we are getting risk premium which is 'alpha' itself. It seems that risk factor and alpha factor are like 2 sides of a coin. It can be flipped anytime. Momentum, Value, Quality factors which were thought to be alpha factors are labeled as 'risk factor' by BARRA. I cannot understand why they keep distinguishing alpha factors from risk factors. However, it seems that what I'm confused about now also made other people confused in the past. I read the paper 'Do risk factors eat alpha factors?' by JH Lee and D Stefek in The Journal of Portfolio Management, Summer 2008 and it discussed the potential problem we can get when we use similar factor both as alpha factor and risk factor. And the problem was called 'Factor Alignment Problem (FAP)' there. Is this a problem which should be dealt seriously when we try to divide factor into alpha and risk factors? How does this all procedure work in real world? I wonder if quants even really use the concept 'alpha factors' or they just think the only factor is 'risk factor'. Moreover, do they concern about 'Factor Alignment Problem'? As an undergraduate student from Korea, sorry if my grammar is bad and hard to read. But I really want to make it clear. Thank you

External answer — Quantitative Finance Stack Exchange Author: Dhruv Mahajan Original post: https://quant.stackexchange.com/a/61244 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Your argument breaks in this line Because, by taking risk factors, I mean by making ourselves exposed to those certain risks, we are getting risk premium which is 'alpha' itself. Market won’t always give you a premium over risk free rate for taking any kind of risk. Some factors have a researched premium attached to them, some don’t. A perfect example of this is High Beta Stocks , it was a long held belief that stocks with higher beta aka higher risk, will in the long run provide you with a premium over the market. But that’s not true always, there has been quite a few studies on premium of the Low volatility factor, which essentially says the opposite. Also I believe the treatment of risk vs return factors is on the discretion of the investor. AQR uses value as a return driver, but some other hedge funds treat it as risk, I think it comes down to the investor whether he wants to diversify away from the more “crowded” factors. Also if you’re charging 2/20 and your portfolio is mostly driven by the common factors like value or momentum, why would anyone pay you fees when they can get the same exposure from factor indices