Now that I have my alpha factor I backtest it and whatever. Since the mean of a zscore is zero, I know I'm market neutral, so (ignoring some stuff) my factor should have little exposure to the market.
If I think it's good, I add it to my other alpha factors and combine them somehow. Could be as simple as adding them all up, or maybe something like using random forests to figure out the best way to combine them, or whatever. Now that I have a bunch of alpha factors all combined, I can run them through the optimization engine.
The optimization engine will adjust the weights of my "ideal" portfolio in order to reduce exposure to various risk factors (thus lowering volatility). My optimizer will also figure out how often I need to rebalance. There's generally a bunch of terms in there that try to reduce trading costs and zero out exposure while not diluting the "ideal" portfolio too much (or else the alpha could be wiped out).
Now, after all of this, I'm ready to trade.
In short, what we're trying to do is reduce our exposure to as many factors as possible and just get exposure to our alpha factor. We don't want the market, price of oil, sex scandal of a CEO, or anything else affecting our portfolio. We are trying to dig up this latent, unearthed, alpha that exists in the market, but doesn't belong to one company or asset.
Thinking you can read Fama papers to take on quant funds, like smabie is claiming at several places in this thread, is like reading Commodore manuals to take on AlphaGo.
It's kind of like the theory that open source doesn't have serious bugs because so many people read it.
You know the saying that the market can remain irrational longer than you can remain solvent? If some people don't care about doing simple analysis, and others assume that someone else is doing it, and still others accept that it's useless to do it if other people aren't, it seems like a none-too-efficient market can be a stable equilibrium.
There's a reason why these factors are called "persistent." For systemic reasons, it is hard to arbitrage them away, mostly due to laws, and sometimes tax implications.
Of course, I suppose it would be possible if you discovered some amazing alpha factor. But if you did, you probably would be better just trying to get investors.
So in short, the answer is $0. For my personal portfolio, I run (only started recently) a variable leveraged beta strategy that can be described in my three part series:
https://cryptm.org/posts/2019/10/04/vol.html
It’s accepting that you’ll receive what the market gives you and not a dollar more, and that that’s the best you’re ever going to get.
If you aren't willing to put in the work, sure just hold an all weather portfolio or whatever. But I don't think it's super hard to beat the market on a risk-adjusted basis, especially as a retail investor. Most of all, it takes a passion for it (trading is a hobby) and also a reasonable amount of time dedication.
For example, there are a number of persistent factors that don't go away. Things like value, low-beta, size factors, etc. It's not super hard to leverage the tons and tons of papers that have been published to construct a portfolio that does really well. And, due to structural reasons, will do well until the laws change (almost all persistent factors exist due to some law).
Especially in the current market environment, it's really easy to make a killing. The market is moving purely on sentiment and day traders have had some really great opportunities to make stacks in the past couple of months.
Comments like this are why these "beat-the-market" threads are evergreen on HN. They do a disservice to the community.
Real estate is another area that is very typical for bubbles and when the bubble bursts the large majority of people who are overleveraged will be eaten alive by the big investers (much bigger than you) who make money off the poor in times of crisis like they always do.
Since it was very hard to lose money with cryptocurrency even if you tried, you had years where it was a good idea to invest. Who should you listen to? The one that got rich with a better scheme than buy and hold? or the one who sat on the side lines for years, made zero profit, and now holds a grudge at missing such a good investment?
Poor people should not go into real estate. There is enough for everyone. If you'd put some of your wealth into Euro, in the past months alone, you'd have made enough to buy a small apartment when the bubble bursts.
Good luck with that though.
https://www.aqr.com/Insights/Research/Journal-Article/Bettin...
https://en.wikipedia.org/wiki/Low-volatility_anomaly
I think your attitude of dismissing decades of academic research by Nobel prize winners is a little myopic.
Also I don't think you understand what "risk-adjusted" means.
You might be right; why don't you try explaining it for me? I suspect it is going to look a lot like a justification for why your strategy is fantastic even though it makes sub-par returns.
I can give you complete run down of persistent factors, leverage, risk-adjusted returns, etc etc.
That will lead you to the reasons why it is very possible to both beat the market and be incapable of scaling it up to billions of dollars.
tl;dr: Someone who has found a way to reliably arbitrage to 25% gains year over year on an inefficiency that will only fill about $100,000 is not going to be able to cash their system in for billions of dollars. But they will be reliably beating the market (on a risk-adjusted basis: assuming the system has risk equal to or less than holding e.g. the S&P).
You will find that firms which can actually reliably beat the market do tend to make their founders wealthy. But they can't scale it beyond the capacity allowed for by the inefficiency. All successful hedge funds and prop shops eventually reach a point where they can't reinvest the returns for the same gain.
[0] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2503174
But yes, picking stocks is probably not as effective for most people as buying an index fund.
I doubt he could without using or BH insider info.
I depend on an in-depth understanding of human psychology as one of my data sources. You can't turn something like that into data and input to a model. It is something learned through life experience and study.
I am not that familiar with forex market compared to equity market. But I expect forex to be impacted by changes in political and economic situational news of host countries of relevant currency pairs. All these need to be coded into forex trading strategies.
If trading based on just price was so simple , everybody would be doing it successfully.
if you really care to trade currency rates in a sane way, there are CME futures
1 http://www.forexscamalerts.com/fxcm-permanently-banned-usa-f...
A few months ago I tried to evaluate autoregressive behavior in stock returns. To my surprise it seemed strong on some periods, but then weak on others [1], and as you said not reliable enough to rely on.
My impression is that a lot more information aggregation and processing is required to obtain a sustainable edge worth tranding on than what a single developer can achieve in his/her spare time.
Top investment shops have dedicated teams of sw engineers just to deal with the infrastructure that support their data pipelines, financial model backtesting and deployment.
[1] https://thomasvilhena.com/2020/01/likelihood-of-autoregressi...
[1] https://en.wikipedia.org/wiki/Momentum_investing
[2] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2961979
(1) monitoring other people’s tomato transactions in as much detail as possible;
(2) spying on people who are about to buy tomatoes and rapidly make changes behind the scenes just before they make a purchase; or
(3) pointing voice analysis at The Food Network looking out for recipes that call for fresh tomatoes, tracking tomato tankers in major sea lanes, monitoring storm tracks in the top tomato growing zones, etc, and adjusting your position appropriately.
It sounds like you are trying (1) when (3) might be better, or even (2) if you are not jail-averse (or your local jurisdiction has institutionalized high speed market fiddling to the point of being legal.)
For non-native speakers, market has a specific meaning in US English. In the US a “market” typically means a small shop selling the most common fruits, vegetables, snacks, and household items.
In Europe a market is a larger and more general area for autonomous small traders, usually also trading food and household goods.
The autonomy and low barrier to entry make them a good analogy to a stock market.
(They also suffer from availability and quality issues. A large business can arrange to purchase and retail all of these goods on behalf of consumers under one roof — a supermarket.)
The secret is simply to have an edge.
If you're trading on behalf of clients. You don't care what happens to the market because you don't depend on the high or low to make money.
If you're buying or selling for yourself, same thing. Guess who's buying coal and oil, power plants and refineries and assimilated. They sell what they have and buy what they need.
If you're making money on arbitrage, making sure the New York and the London stock exchange have the same USD to GBP to EUR price and vice versa. You could make money but you better be faster than other corporations and more careful at the same time because you're not the only one doing that. Anytime you buy one side, the other side might have changed because you can balance out.
There are clear factors that drive many markets. When the weather is cold people consume more energy for heating. When it's hot, they go out to make barbecues and buy more sausages. When there is a drought or crop sickness, wiping agriculture exploitation, prices of food and meat go up. That's some examples that are easy to understand.
The stock market is not about speculation. It's about buying real items in the real world and providing services.
So inflation comes out at X% and then you try to jump ahead of other people reacting to the news.
Speaking very generally, you are looking for data that has information about future returns. So this may include past values of the time series (this is kind of complex though because a stock price does trend, that company is investing capital to earn a return which compounds in the price so stationarity is...complex) but may include other time series/their past values i.e. price of other stocks, economic data, etc.
So this could be responding to changes in liquidity, it could be seeing some repeatable behaviour by investors and jumping ahead of it, etc.
Quant is not about adding to the efficiency of markets though. They aren't using these models to determine the value of something, they are more about looking at the value of other things to determine the value of a given asset. So these strategies end up being correlated to liquidity in a lot of instances (but not all). This is a generalisation but...it is a very odd thing to have occurring in society...would this exist if investors didn't have an irrational demand for microsecond liquidity? Probably not.
Also, determining whether something is a real signal is just part of statistics, isn't it? This has definitely been an area where there has been quite a lot of innovation as increases in computational power has made non-parametric stuff more feasible (I am not an expert on this, it is just my understanding).
Btw, I should add I used to work in finance and I have some experience with this kind of thing as I do quite a bit of "quant investing" but in gambling (it is far easier to just copy what people do in finance and apply it to gambling then come up with it yourself). And just based on my experience, it makes most sense to employ a mixed approach. So learn about the business valuation, and then build a five-factor model...watch what it does, and then filter its picks with your knowledge. A lot of quant strategies are vaguely ludicrous if you have an understanding of the fundamentals of investing, like you are trying to use a computer to replicate a human...and people wonder why it doesn't work? It is an overcomplicated shortcut (to give you a concrete example, the blowup of value and funds like AQR was very obvious...you just had to look at the utter garbage stocks they owned). So I think a combination of human and computer beats either separately (one fund that does is Marshall Wace).
This makes me wonder what kind of trading systems can actually have any kind of edge, since some kind of autoregressive time series forecasting system seems pretty unreliable.
On a more general note, how do you move beyond it being gambling? Just because a system backtests well doesn't mean a phenomenon will continue to happen, especially if your system will significantly impact the market you're in. If you make a trend-following system, every time you trade, you're gambling that the trend is more likely to continue than not. If you're right, you'll come out ahead over many trades. If you don't have enough capital to withstand drawdown the way most beginners don't, you won't be able to last long enough for whatever phenomenon you've found to average out.
It takes a lot of time, effort and risk to do all this, so, this is a long-winded way of saying I don't think it's for me. If you build a SaaS product and it fails, at least you can talk about what you learned from building it and use that in future endeavors. If you lose money trading because your algorithm doesn't work, what do you learn from that besides that your algorithm doesn't work?