Algorithms Taking Over Markets (w/ Howard Morgan)

Markets in general move down faster a sharper than they move up You In the markets there’s something known as the wiseguy effect which is you know If somebody if you have an algorithm that works and other people start figuring it out. I think one of the secrets of Renaissance is That it’s not a static model. It’s not they built a model in 1989 and they’re still trading that model It’s every month. There are changes made There are new signals put in signals taken out new awareness of what’s happening and most other people who build models and built systems Have one thing they have one our one-trick ponies and that lasts for a year or two years and then it goes away there are very few groups some like to Sigma and maybe Andy Shaw that have the discipline to Continue to evolve their models Constantly as opposed to simply saying Oh, I got something that works and then all of a sudden it doesn’t work and they don’t quite know why it doesn’t anymore So what worries you though when you when you look at this thing and and things trouble you what’s the basis of that? I think there’s too much Happened has happened is the Argos have acted as an amplifier Yeah so price discovery in general comes from information coming into the market and something usually humans up until recently saying Oh apples earnings are higher than we thought we should go buy Apple or Apple’s earnings are lower than then expected We should sell Apple and that causes some price discovery and they trade a hundred shares or a thousand shares now What happens is the few people who make that decision are then followed on by algos which? dramatically amplify the moose so the volatility and the the depths of moves and in any direction has been greatly Exaggerated and that’s not good for the market and it’s certainly not good for individual investors. And that’s why you get John Bogle Correctly telling people you don’t do this. This is not for amateurs And I think having algo trading beasts 50 60 70 percent of the market is is not a great thing but what’s been interesting to me is to watch this the rise of algorithmic trading against a backdrop of massively declining volatility Which is what we’ve seen and a lot of that I guess is because we’ve had this straight-up bull market for 10 years Yeah, and that for me is someone that doesn’t know anything like what you know about this stuff. That’s what concerns me Is that what happens when the momentum shifts in the markets path of least resistance is down as opposed up. How do these momentum chasing strategies affect the market a no idea Well, I think they’re you know markets in general move down faster and sharper than they move up I think we saw a few days and weeks after the Trump election. We saw this last December that The normal trend followings did terribly most of the quant funds did pretty badly last year Because they didn’t realize that if they were built in the last five years on Five years of history. They were in a constant bull market and those models are not good enough You need things that understand that markets. Don’t just go one direction and so they all got killed the other last year, but we’ve had this we’ve had this period for you you say entire trading desks that I’ve never seen down markets haven’t seen interest rate hikes haven’t seen any of this stuff and Yet the data to your point Is there going back you know? 40 50 60 years really granular data that suggests that there is a whole other world that we haven’t seen there is and and there the the best players the the Renaissance to Sigma D sha have data going back that far and run their models in both up and down markets and try to see what’s going on and The young people who come by my office for how to me to see their quant funds which I do On a regular basis come by with two years of data and say look I’ve got something that works and then I have to tell them well, are you sure it works? First of all, let’s try the following we run your simulation But put a random variable and on whether you’re filled or not on your orders Let’s say you’re only filled half the time what happens and they do that in come back say when we lost And cuz that’s what house if you tell them to start trading real money there and they lose money They said I don’t know why I lost and I say I do know why you lost probably You probably didn’t get filled. You probably had more slippage than you expect Did you all of the real market things that that screw up somebody’s wonderful little algorithm? It works in theory and on, you know, pure data where you get every order you want and so on That’s just not the real world, but it’s funny. Isn’t it? Something as simple as not getting your order filled? You can screw one of these things up completely. Yeah, and the and these are these are everyday codes is not not metaphorically These are everyday occurrences Yes it so you know I’m always amazed that some of the models that I’ve heard people talk about are so simplistic and so reliant upon a Very defined set of variables that we’ve really only seen in the last three four five years that it almost feels like It’s dangerous to allow these things to go anywhere near the market not just for the people who’ve staked them Right, but for the markets themselves Well, I mean, I think it’s always good for the market. They have more players participants and so I like that part of it, but it’s definitely true that They don’t have understanding of the real market dynamics and the fact that if they found an anomaly Probably a few other players have found it as well and may get those orders faster The other thing that I find is that they don’t understand the importance of their time horizon The markets are not quite a zero-sum game Because when a high-speed Renaissance model sells a share of stock to warren buffett and It goes down in in 20 Microseconds Renaissance has made money on the short side And if it goes up in 20 years Buffett’s made money So both can win its it can be win-win if the time horizons are different And when I the first question really I asked about for these people is what time ERISA you trading you’re taking microseconds milliseconds intraday, you know weeks months and The further out you go the harder it is to build good models And the exciting thing about Renaissance is they built high speed models and medallion which is relatively short or focused and they built the Renaissance the institutional equity fund which is you know, Multi-year focused and have done successfully at both ends of that spectrum So if we if we free ourselves on the bounds of capitalism, is there anything that you would look to do to maybe? Contain the power of these machines given where we are in the cycle. I Don’t know. I I you know, the the the truth is that We’ve gotten rid of some of the worst excesses the portfolio insurance kind of gems that exacerbated the 87 crash And I think that having the models there does really provide more liquidity of the markets so that when people want to trade I do think That some of the new efforts to make sure that every there’s a level playing field in terms of you know People getting an edge by being three meters closer to the rights to the trading volumes and that micro second level stuff I think is good. I think that would be a good thing. And I know the US market regulators are thinking about You

6 thoughts on “Algorithms Taking Over Markets (w/ Howard Morgan)”

  1. That's why I polish my skills and new skills that may compliment my skills, so that if my other skills has a machine to work on it. I still have other skills to earn money.

  2. I have a very simple solution to that… go back to having one central trading location for a single issue. The deregulation has caused a lot of these problems.

  3. Its feels pretty comfy knowing how to do manually (recognizing the proper extension ratios by which price distributes), what quants and algos do in a massively inefficient and roundabout way.

  4. Recently came across all of these machine learning trading strategies on GitHub

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