Don’t Trade Blind, Use Data

 Will McBride and Dmitry Pargamanik cofounders of Market Chameleon join IBKR’s Jeff Praissman to discuss the value of data in trading. This podcast is a follow up to their insightful webinar, “Linking Trade Data For Valuable Insights”.

Webinar Link:

https://ibkrcampus.com/webinars/linking-trade-data-for-valuable-insights/

Summary – IBKR Podcasts Ep. 137

The following is a summary of a live audio recording and may contain errors in spelling or grammar. Although IBKR has edited for clarity no material changes have been made.

Jeff Praissman

Hi everyone. Welcome to IBKR podcasts. I’m your host, Jeff Praissman. It’s my pleasure to welcome back the cofounders of Market Chameleon, Will McBride and Dmitry Pargamanik. Hey, guys, how are you?

Will & Dmitry

Hey Jeff, how are you?

Jeff Praissman

Thanks for coming by the IBKR podcast studio. We just finished up a great webinar. And it’s my pleasure to have you guys in and further discuss using data to gain valuable trading insights.

And for our listeners, if you’ve missed the webinar, there’ll be links in the viewing notes of this podcast to cross reference it. So guys, I kind of want to start off with, there’s obviously a lot of data out there, some useful and some probably not so much. What is the overall goal of traders with this immense amount of data available?

Dmitry Pargamanik

Actually a good question because I get this question sometimes where people look at all this data available and they say, okay, well, so what? What do I do with it? What am I supposed to do with all this data? And when we look at the raw data, we take that raw data and we try to analyze it by taking out the noise and getting some meaningful positive signals.

And the three main goals that we use the data for are, one, can we take the raw data, run it through a model, and get answers to important questions? And the questions could be such as, well what is the market implying about this or that? Or can we use the data and look at historically and answer questions. How often does this happen or what happens after a certain event? So that’s one of the objectives. The other two main objectives are can we take the data and create a model and price a certain asset? So, pricing an asset becomes very important, especially if you’re trading something and you could get a good price then that could indicate to you something might be undervalued or overvalued and trade around that price. And then lastly, we will use that data to try to help with risk management tools. So the risk management tools are just as critical as anything else. And using that data, you could try to see, how can I mitigate my risk? How do I manage my risk and what is my risk exposure? And those are the three main goals from a high level where we could take in data and use it for trading.

Jeff Praissman

The three of us have covered a lot of topics over the last few years. Obviously we mostly deal with options and this is going to be no exception, but I do want to kind of take a step back. Options are obviously derivatives and equity options clearly are derived from equity.  So I want to start with, what are some of the data points that are useful for trading equities?

Dmitry Pargamanik

When it comes to equities, the few most important data points would be probably financials, then ownership. And some of the data points that we look at for traders are the data points that are provided on the data feeds from the exchanges.

Because those feeds provide a lot more color and insights into what’s going on underneath the surface, what’s behind the volume and behind the trading. So the market feed data, at least to us, is very important. And also data points that will be meaningful to option or stock prices, such as upcoming events, earnings or important events. It could be the Fed meetings and so forth that could be a catalyst for a stop move. So for equity, there are lots of other important data points, but from a high level, those are the ones that we focus on the most.

Jeff Praissman

And I have to assume that obviously the data points used for equities or used to evaluate equities, they’re useful for options obviously, because you’re evaluating what the options are derived from.

But are there other data points that are more useful for options that don’t maybe apply to the equities themselves, but more specific to the derivatives?

Dmitry Pargamanik

Yeah, definitely. When we look at options, usually we express options as some kind of a derived value, implied volatility and we would run an option pricing model to help us out with that. And some of the important data points for an option pricing model are of course the stock price. You would need the reference price. Also the dividends are important data points. Interest rates and even the borrow rates to borrow and short the stock. Those are all important because what you want to do is be able to run those data points through an option pricing model and then compare them to the market prices to see well, is the Put-Call parity even in line? And if it’s not, what can the market be signaling? Or does it present an opportunity?

And of course, all these data points, they’re scattered. They’re not coming all from one source. So you would still have to go out there and compile them. Other data points, important for options, of course, are anything that could be a catalyst for a move such as an earnings’ FDA announcement. It could be a Fed meeting. You would have to have all that ready and take that into account when you’re trading options.

Then you do have other data points that could potentially help you with the trading if you could get access to the order limit book on the exchanges or the trade details or the time and sales. Because those offer you much more insights into the trading itself, where you could analyze the trades, see that these trades are part of a multi-leg trade, for example. Is it part of a spread or is it a single-leg trade? And this helps with the price discovery process. Where you could see where people are trading, where there’s a meeting of the minds and that also helps you plan your own trades.

Jeff Praissman

And from the all the data points you just went over, trying to think where an investor would  find this data, it seems like it’s probably a group of sources. My question is, is this data available for free or is there fees associated with it? Are there sites out there that can consolidate the data? Or is this sort of like all the above and just kind of up to the investor to track down and find out on their own?

Dmitry Pargamanik

It’s a mix of both. We have data sources that are free. You could access it, you could go to the SEC website and get financial data, ownership data, insider data. You could also go to company websites and look up their investor relations websites, if they have upcoming events, upcoming dividends, their dividend history. Interest rates are a big component in trading and option pricing or even valuing stocks so you could access that from the Fed.

 And then there are other data points where you would have to go and purchase, such as data feeds from the exchanges. Those are not public. You’d either have to go and purchase them directly or do it through a vendor. So there’s a mixture of data that’s available to the public, some that’s not available. You’d have to either go and purchase it. It’s kind of also very scattered and the challenge is bringing it all together.

Jeff Praissman

And with all this data out there, I mean, it would seem like, obviously you mentioned the SEC or the exchange. So if you’re getting the data from a primary source, it’s probably fairly safe to say that it should be accurate.

But what are some of the risks of using data? Is there a way that the trader or investor can, if they’re getting it from a secondary source, is there a way they can verify that the data they’re seeing accurate? I’m thinking like a service versus something they see on social media, right? That would be considered a source but it could unfortunately be very inaccurate, I guess.

Dmitry Pargamanik

Yeah, whenever you work with large data sets, that is always going to be a problem where you have outliers. You have certain data points that could be bad data points because even when we compiled data, a lot of these data points could be entered in manually by an individual, like for example press release. They could enter in maybe a bad date or bad number. That could happen, and the chances of that happening when you have large data sets is greater. So there there’s always that struggle with cleaning the data, finding outliers, finding exceptions. There’s sometimes problems with missing data points so that itself is a huge process when you take in the data and try to clean it and organize it and prepare it for data analysis. That itself takes up a lot of time.

Jeff Praissman

Dmitry and Will, how has the data availability to the general retail investor changed over the years? Are there more sources than in the past?

Dmitry Pargamanik

With the Internet, with advancements in technology and storage, a lot of data is now more accessible and available to the general public. Some of it is free, like you said, some you still have to go out there and purchase. It’s not always free and I think that it’s not just the availability or access to the data, it’s how does an individual retail investor.. How do you compile all this data yourself? How do you clean it and prepare it for analysis? How do you connect it together and create the tools to analyze it? That itself is not a simple process. That process alone is more time consuming, more costly than just being able to access the data.

And that’s something that we are trying to provide. Given those challenges, is it possible to compile the data, clean the data, make the data available for analysis with the tools to analyze it at a cost that’s reasonable enough for a retail investor, right? And I think that given the advancements in technology, the cost of storage and servers, I think that that is becoming more available to the retail investor.

Jeff Praissman

Is it a fair statement to say that the playing surface has probably come a little bit more level between “professional” traders and retail investors? As far as the data being available and what they have access to.

Dmitry Pargamanik

Yeah. So that part I think is becoming more accessible. And a little bit like you said, that the level playing field is becoming a little bit more fair. However, just having access to the data and the analytical tools won’t be enough. You still need the education, knowledge and experience to be able to use that data and distinguish yourself. That’s what distinguishes a good trader from a not good trader. It’s still the knowledge, experience and know-how that is important. However, at least having access to that data information and analytical tools is becoming much easier.

Jeff Praissman

Yeah, and that’s a really important distinction you just made. You can have access to all the data information in the world, but if you don’t know how to interpret it and use it through education and experience then it’s not worth that much to you.

Dmitry Pargamanik

The data alone will not do that. You still need to know what to do with it.

Jeff Praissman

This has been great. Any last thoughts you want to leave the listeners with as far as using data and having it go hand in hand with valuable insights for trading?

Dmitry Pargamanik

One of the common comments that I hear is that it’s become very easy to open an account and to execute trades. So people try to bypass this important stage. Critical to successful trading or to a successful trading plan is the data analysis and research. Behind the trades. That’s the difference between a good trading system and no trading system at all.

And when you try to bypass that, what you’re doing is then trying to trade on your intuition, right? Your impulse. I think Warren Buffett had a quote where it went something like any idiot with a plan can be a genius without a plan. So going into trading without a plan without the research, without trying to understand and analyze the data to be able to create the models that we were discussing for unique insights into the trading, modeling, pricing of assets and risk management tools, you’re going to go in there and most of the time, it doesn’t end up pretty good. It doesn’t end up well.

Jeff Praissman

Will and Dmitry, thank you guys for coming by. It’s always a pleasure to have you in the studio.

And for more from Market Chameleon, go to IBKR.com, click on Education, then IBKR Campus and select IBKR Campus Contributors.

For our listeners who want to do a take a deeper dive into how to use data to help make informed trading decisions, I highly recommend watching the webinar we just finished. The links are in the study notes. Thank you for listening. Until next time, I’m Jeff Praissman with Interactive Brokers.

Will & Dmitry

Thanks Jeff!