Interview with Tadas Viskanta of Abnormal Returns

Tadas Viskanta sat down for an interview with our Growth Hacker Simon Burns on what he sees in the future for financial blogging, the effect of Twitter data on markets and the move towards democratization of algorithmic model creation among other things. Tadas is a prolific blogger at Abnormal Returns, author of Abnormal Returns: Winning Strategies from the Frontlines of the Investment Blogosphere and long time market commentator. His views, analysis and projections for algorithmic trading, HFT and markets in general are insightful and blended from experience, extensive market reading and his own research. Enjoy our interview with Tadas Viskanta:

Simon Burns: Thank you for joining us. So before we get started, I’ll give you a little introduction on QuantConnect. We have a software solution that is all C# and allows your average investor with basic coding knowledge to build an algorithmic trading model. Very much unique and in a sentence, we like to say we are democratizing algorithmic trading or algorithmic model creation.

I’ve been reading a few a few of your pieces recently, broadly on the financial blogosphere and how its “death”, maturity or some form of development has occured. I’d be interested in hearing your thoughts, or maybe contrasting this development with the rise of twitter as a market force and for crowdsourcing investment advice.

Tadas Viskanta Interview with Quant Connect

Tadas Viskanta had a conversation with QC’s Simon Burns on the future of HFT, the effect of Twitter on markets and what his optimism on the democratization of markets.

Tadas Viskanta:  I think that Twitter and Stocktwits are definitely taking share from the blogosphere. I don’t think there is any doubt about that. But you know, I do think they are big market segments and some of what used to happen in the blogosphere has shifted over to Twitter. For widgets they are the appropriate form. Also short form, quick messaging, one to many sort of messaging..has all been taken over from the blogosphere. But I think anything that gets beyond 140 characters, the blog is still the proper format. If you think about anything quantitative you need to go to the longer form, there is really just not the space in that short form communication to make that sort of argument. Certainly just from my blogging perspective, I’ve been on Twitter and Stocktwits for a long time and I still see people join that weren’t there before joining. I think it’s all part of growing communication, it’s not better or worse just strengthening the entire pie.

Simon: In the second stage of development in financial blogging, you talked about quantitative analysis. Do you think that long form quantitative analysis is ideal for blogs and Twitter is taking the place for other forms of investment content, is there a dichotomy there?

Tadas: Sure, I mean anything quantitive with linear equations or regressions or anything with that sort of frame, you have to go to that long form. I don’t know if blogs will take more share or move more in that direction. I think there is certainly a vibrant sub-culture of quantitative blogs. Like there is anything else there is kind of a wide variety of interests, skill levels…different markets being analyzed on different time frames. So I don’t think I say anything one thing, but a variety of things are spreading out.

Simon: Of course, are you saying that Twitter and the rise of Twitter. As it has taken share has it pushed blogs to be more quantitative? What will blogs move to to retain an innovative edge?

Tadas: I don’t know that it’s pushing the blogosphere to be more quantitative. I don’t know if that’s necessarily the case. I don’t know about that..but people who are still motivated and interested in writing long form’s a reluctant group and I think you are getting more substantive sort of pieces in that regards. Anyone looking for market chatter, can be pretty well served by Twitter and by Stocktwits. Somebody who is looking more in-depth analysis will be better served by long form blogs.

Simon: I think we would be remise to talk about the rise of Twitter for investment advice or for market chatter as you put it. I think market chatter is a much better term than what I’ve been terming “investment advice”!  So the AP tweet and subsequent market crash, from your expertise and perspective being a long time follower of market chatter…What’s your take on it? And what do you think of Flash Crashes going forward?

Tadas: Well it’s interesting because I missed it entirely! I was away from my desk. You know I just saw the aftermath. What’s interesting is that this has happened hundreds of times in history. It’s not always a hack but there have been fake accounts, set-up accounts that have tried to generate rumors and things like that. So in that regard, it’s not really anything different than what’s been happening for hundreds of years. People have…market participants have not only been talking about markets but have been generating rumours, passing on rumors and things like that. Now with the acceleration of data and information…it’s almost, in a perverse sort of sense there has been some sort of growing sub rosa rumor mongering going on! Although this was also obviously something that was corrected quite quickly. You know the market reversed almost instantaneously on the realization that that news was incorrect. But you know for market participants you have to take account that this can happen, and if your strategy is something with open orders or limit orders you have to take that into account. I’ve seen more talk from traders who realize this and are much more reluctant to have strategies that have open orders. A rational thing would be to stand out of the way of these flash crashes or market disruption, I don’t think we’re ever going change that out though. So everyone who is participating in markets has to really think about that and take it into account when building and running a strategy.

Simon: Great answer! I think your next blog post should be entitled something like “The evolution of sub rosa in the Twitter Age”..

Tadas: (Laughs)

Simon: I like that sub rosa reference.

Tadas: Yeah, there probably is room for a blog post on the financial history of flash crashes based on rumours! I think we could probably do a pretty good job at that…

Simon: Absolutely, so lots of people when they are talking about the AP market crash they were talking about how even though it was a fake tweet it was a good thing for markets in that the news was dissected much quicker by algorithmic trading models than it would have been by humans. So that the true market valuation, even though it was a fake market valuation was shown right away. Is that something you would you align yourself with? Or there are some on the other side of the debate, like say Mark Cuban for example, saying that: the fact that algorithmic trading models acted so quickly was bad for markets and that a human would have been able to tell the difference. What’s your take on that, is it good that markets are being evaluated and revalued so quickly? Or is it bad that there is not a human there to slow it down and make sure the valuation is in line with the proper valuation?

Tadas: Well you know there is two points to that, on the valuation side. I think the algorithmic approach leads to areas where that might be helpful. In situations like real events, like natural disasters or things like that. These algorithms can source from Twitter faster than any sort of news organization. And this is a subset of that. I think a proper news algorithm is looking for confirmation of an initial source. And if it doesn’t find confirmation of that, it quite quickly dismisses the initial tweet as invalid or false or bogus. So I think in the way that algorithms are tools, algorithmic news processing is certainly a useful approach to crowdsourced data.

The second question is really a market question, to what degree should quantitative traders be using algorithmic news output and that’s for every to decide on their own. If they have confidence in their algorithms they should link them up. But that’s up to the market. But we should be somewhat heartened to the fact that the market turned around as quickly as it did. There is a lot of issues of HFT that are not related to this specific event.

Simon: So moving right into broader issues with HFT. On the aggregate, do you think HFT has made markets more efficient?

Tadas: Um I don’t know about more efficient markets…

Simon: One way to analyze efficiency would be volume or liquidity. A second way would be with algorithmic trading no news goes without bringing re-valuations. So you can take that from either angle.

Tadas: I think like anything else it’s a bit of a mixed bag. For small traders it has brought tighter markets. But for traders who aren’t trading more than a couple hundred shares, I don’t think it’s been much of a boon to them in that regard. The quotes on their screen are at best indicative of a what the deeper market is.

I’ve probably turned a little bit on HFT. Having learned a little bit more about it and having read a little bit more about it. I think that the system that we have today is kind of an accident of history and I don’t think that it’s really been for whatever reason, largely political will, been optimized for markets in a certain sense. So in that regard, I think there is still probably a lot that can be done to make markets more fair and operate better.

Simon: That was a really great line about the markets today being an accident of history. Can you elaborate on what accidents in history you think are most relevant and still having the most impact and driving markets?

Tadas: Scott Patterson’s book Dark Pools is a history of electronic trading and goes back all the way to the 1980’s. Where really the initial cheerleaders of electronic trading were trying to democratize trading. If you think about the era back then, it was a time of market makers, stock traders on the phone or specialists on the floor. And their desire to open up markets was a really interesting one at that time. Over time it became something entirely different. A lot of the activity we see is the maker-taker model. You know trying to get in front of the other person to earn their fees. In that regard, if you were going to create the market from scratch its probably not something you would build into the market structure. So I think in that regard we have probably gotten a little off track. And it a lot of ways these issues are pretty obscure and a lot of market participants really don’t understand them. It comes back to the Scott Patterson book that is really great. Anybody that is interested in markets and market structure would be well served by reading it.

Simon: Let’s take this back to the effects on small traders, how do think HFT is impacting them, their trading habits, their profit margins. Can you take a stab at that?

Tadas: My best guess is that you are seeing a broad shift away from the shortest time frame trading into more intermediate time frame strategies. It’s sort of a rational move. We talk about the HFT and it’s effect on volume but in effect we’ve seen volume go down. A lot of the hardcore traders have adapted to survive, if they want to continue they need to adapt. I don’t know if I agree with Mark Cuban in that markets are turning people off. Maybe some interest has shifted to the forex market where you have a handful of crosses you can look at and, for lack of a better term, is more of a pure trading play then you might see in the equity market.

Simon: Very interesting, do you see it as a long term trend that small traders are moving to the “pure trading play” in forex markets?

Tadas: I don’t know, I think that whatever shift that has occurred is the extent of it. The rise of forex traders has run. But if you look at U.S. equity market and the number of securities, the number of securities that are small cap. Small cap stocks where there may be an informational advantage to a small trader, the number has gone down. And it has been shirking for over a decade now so I think part of this and the rise of the ETF as a substitute to the trader of 10 years ago who used to trade Microsoft or Cisco is now trading triple Q’s (QQQ), SPY and IWM and things like that.

Simon: Let’s move our conversation over to something that’s closer to QuantConnect’s business model, so what we are looking at is allowing the democratizing and creation of algorithmic models quicker than ever before. So in theory that will allow people to invest in other people’s models, to share models and in theory it will take on an industry that has been historically in hegemonic institutions and taking it to the people. We’ve seen similar movements with social trading with social forex brokers, synchronized trading, mirror trading and otherwise. What do you think the effect of social trading or mirroring will be for algorithmic trading? And maybe take on what will be the effect on innovation in algorithmic trading once a substantive movement takes place.

Tadas: I’m all for the democratizing of information whether it be trading models, earnings estimates or even things like market costs. That’s all for the good and I don’t think you can point to a downside to that. More information can provide plenty for trading individuals and that’s all for the good. The overall downside might be that whatever democratized marketplace or a richer set of models will not fix all the issues. There will still be emotional trading, even quants have to deal with the psychological challenges and dealing with the performances of different models. So it doesn’t necessarily mean that models overall will perform better. So it’s sort of a two pronged argument. I don’t’ know if more information is a bad thing, but when the rubber digs the road and decisions come down to what models to use, when to use them, when to scrap them, edit them I think all those sorts of things re-enter the domain that individual traders have been dealing with for hundreds of years. I think that challenge is still there and will continue to be.

Simon: So a summarized form of what you outlined could be, right now investors are emotionally trading individual securities and your worry or prediction is that in a system of democratized and social algorithmic model creation. The emotional component might also be attached to choosing models, switching models, changing models. So we’re trading emotionally on the derivative rather than the original security. Would that be accurate?

Tadas: You’re still going to have performance chasing and people will try to hop on hot models or hot trends and often democratized or easier trading as led to more speculation.

Simon: Great answer. So looking at HFT, on our side we tend to lean away from HFT as for small traders it is difficult for them to build competing models, difficult for them to compete on timing and quotes and other information biases. Like you said we are seeing small time traders move towards forex and other places due to this “historical accident” which you referenced eloquently. In terms of fixing the issues inherent to HFT, fixing that historical accident. What are some strategies that you are reading about? What are some bloggers talking about on the blogosphere that you find interesting for fixing the systematic issues to HFT? And maybe as a side question, how do you bring Mark Cuban back to the market?

Tadas: You know it’s funny, as much as the SEC has become involved I don’t think anyone really has come up with a full solution. There is a lot of talk but not a lot of action. The exchanges are pretty well entrenched in their current model and I think they are going to resist anything that will put their business models at risk. I don’t think you are going to see anything going to change that anytime soon. Even though a lot of market activity can be traced to market structure. You know markets are going up and people are pretty happy. So these market microstructures which are not a problem get pushed to the side. I don’t think there is a whole lot of political will intent on changing anything anytime soon so from my perspective I think anyone looking to trade on that timeframe will be running up against the status quo.

Simon: I saw a piece recently by Barry Ritholtz recently on limiting the period of time of each trade to a certain number. Sort of to limit the race to the bottom and reaching a lowest common denominator. What do you think of that sort of solution? Are there comparable or better implementations?

Tadas: I think that is a perfectly legitimate solution. That’s a pretty easy implementable solution thing you can do that would really optimize markets and obviate the advantages of collocated servers and things like that. It’s a perfectly reasonable response as we are moving the maker taker incentives for high frequency traders. That solution would start to get at the issues involved but I don’t’ see it happening anytime soon.

Simon: For the last part of the interview, let’s talk about projections. On that last issues of implementable policy options for high frequency trading, whether the limit be a thousandth of a second, hundredth of a second or whatever arbitrary number is decided. What effect will it have on small traders?

Tadas: I think you would be a lot of high frequency traders out of business. I think that would be the biggest outcome. But I mean you have already seen a slide in profitability in the last few years. Numbers out of the night trading business exchanges were down recently and show that a take away from HFT is going on. I think it’s a great question of what would happen. Would we see real order flows return to the market? There is some talk about widening tick size on small cap security trading from 1 cent to a nickel to try to get more people to provide liquidity. I think it’s a great question and I don’t think we really know. I don’t think we realize that electronic trading, algorithmic trading and high frequency trading…there is really no going back and I don’t think we know what would happen if we were to try anything. There is a lot of capital in these technologies and there would certainly be some adaptation on their part to try and again become profitable and work in a new framework. So I think it would change, how necessarily I don’t know but would certainly begin to give people a sense that there is a level playing field in the marketplace.

Simon: Fantastic answer. As you were talking there I was struck by how strange it is that no exchanges or private markets have been established with limits, with policies that you talked about and a market that is level for small traders. As you and I both seem to agree that there is a demand for a market that is egalitarian. To push out HFT traders and let small traders trade on that specific market, sort of a self-regulatory model. What are your thoughts on a model of that sort?

Tadas: I think it would be interesting experiment

Simon: Of course

Tadas: but I don’t think you will see any of the incumbent players try anything like that. I think they are wedded to the high frequency traders for fees, volume and I don’t think anybody, absent a regulatory model, move to that model anytime soon.

Simon: Let’s move to some more broad projections, let’s take algorithmic trading and what will it look like in 3 to 5 years?

Tadas: Oh I have no idea! (Laughs) I think you have a lot of smart people putting a lot of capital into models of all kinds and I think that you will continue to see the evolution and even the acceleration of those models. I think you will start to see non-market data being pulled in and I think that’s the biggest sort of open opportunity for algorithmic traders is using non-market data and integrating that into their systems.

I think social media data, that’s certainly one way to do it but there are challenges to generate some signal from that noise and that is the challenge to refine the responsiveness of models. I think people will come on with more data and more testing models in the non-market data space.

Simon: Final projections, financial blogging in 3 to 5 years? Tadas in 3 to 5 years? And if you are feeling ambitious, markets in 3 to 5 years?

Tadas: Oh I have no idea about markets! And I have no idea about blogging! Actually I don’t really know about Abnormal Returns!

But when you look at writing, financial writing but really all writing. There is always a distinct minority that is the content creators. There are a large segment of consumers of content, a smaller segment who interact with that content and a small minority that create that content. And I think there is always going to be a portion of the community that is interested in writing and teaching and getting feedback.

I think if its blogs or some other technology there will always be that segment that decides to communicate thoughts.

Simon: Well Tadas you’ve been an excellent communicator of thoughts and ideas, thank you for working with us. As a side note, at QuantConnect we are working on bringing Twitter Sentiment Data into our system shortly to facilitate that innovation you are talking about so we’ll keep you in touch with those developments.

Tadas: That would be great, thank you!

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Simon Burns

By: Simon Burns

Quant Development Intern