It means to remove a set of factors from the signal - or the returns of the signal, which would impact its performance or exposure, and are not meant to be captured by the signal.
Imagine a "I have no preference" signal which gives a weight of 1/n to each asset of the portfolio - you have 100 stocks in your basket, you give 1% to each. If you would compute its performance, you would see that this portfolio would roughly make 10% average returns over 20 years. That seems good right?
Well no it's not, because these 10% don't come from anything meaningful that your signal did. It came because you gained exposure to the market, and that exposure "carried" your signal performance.
> What do the need to do to the software to “residualize” it?
Well residualizing overall just means that you want to regress your signals on a set of factors that would carry its performance for no justified reason. In practical terms, you could start by doing a linear regression of your signal against such factors (say beta, country, sector) and only keeping the remaining residuals (alpha).
Watched every video of them, I am okay with math. Thank you very much!
Btw, since quant industry is full of secrets - is there any source on some actual money figures - how much firms make, what are the sums that are required to be shuffled, what are the frequencies of trades, profitability figures? Anything to get a slight glimpse into inner workings of this. Unfortunately googling turns out nothing or scams
> is there any source on some actual money figures - actual money figures - how much firms make
Yes there are a number of public sources, especially for UCITS funds that have some regulatory requirements to post publish their portfolio composition.
But you probably won't be able to make much sense of these figures, as it needs to be interpreted relative to the orientation of the fund.
See, a hedge fund is not selling "performance" per se, it's selling a reward for assuming a specific kind of risk on your behalf. Lots of people don't understand that nuance, and that's where you see all these messages like "haha my index fund outperformed hedge fund X".
Say you're a super wealthy company, idk, let's take an insurance company for the sake of the example. You have 1 billion dollar lying around and you would like to earn some passive money on it.
You can't just give that money to whatever hedge fund manager will give you the most performance, simply because you, as an investor, already have exposure to a bunch of factors. You cannot afford to have that money exposed to the same risks.
- Suppose your insured clients are mostly from Europe, it would be a bad investment to place that money on something that is exposed to the European economy. It would mean that if some bad macroeconomic factor impacts the European economy, thus making Europeans companies at risk, your dear investment would fall at the same time.
- You probably will need to be able to withdraw a part of that money at some point. Even if not, you will need to have some sort of balanced books to keep track of. Something along the lines of "the overall company reserve should cover 20% of the insured goods of clients". That means you cannot invest on whatever yields good performance, you also have to make sure the volatility of this investment won't put you at risk.
There are thousands of considerations like that, each client will have a different set. This leads to a bunch of different "orientations" of funds. Each client will typically have some kind of preferred allocation that he will balance between multiple funds accordingly.
Some examples:
- CTAs (trend followers) will provide good performance, at the expense of a strong market exposure and volatility.
- Market neutrals will provide pure alpha (no market exposure) but with lower volatility and returns.
- Arbitragers will provide very good returns, very low volatility, but with very small capacity.
- Macro funds will provide returns uncorrelated to the market, but suffer very low vol in certain circumstances.
There is no point in comparing the returns of different orientations of funds. Even comparing the returns of same kind of funds is not really relevant, to have a full picture you would need to k ow exactly what this kind of fund is supposed to deliver in terms of volatility, exposure, returns, etc.
> what are the sums that are required to be shuffled
Usually this is an output of your strategy, not something you decide a priori. Quantitative funds win "on average", so you want to trade as much as you can for the law of large numbers to kick in, until the trading costs catches up.
> what are the frequencies of trades
That completely depends on the kind of fund, and the regulatory enveloppe with which the fund is sold.
Typically that will go from a few microseconds for the best arbitragers to weekly/monthly rebalancing for large fundental funds.
Imagine a "I have no preference" signal which gives a weight of 1/n to each asset of the portfolio - you have 100 stocks in your basket, you give 1% to each. If you would compute its performance, you would see that this portfolio would roughly make 10% average returns over 20 years. That seems good right?
Well no it's not, because these 10% don't come from anything meaningful that your signal did. It came because you gained exposure to the market, and that exposure "carried" your signal performance.
> What do the need to do to the software to “residualize” it?
Well residualizing overall just means that you want to regress your signals on a set of factors that would carry its performance for no justified reason. In practical terms, you could start by doing a linear regression of your signal against such factors (say beta, country, sector) and only keeping the remaining residuals (alpha).