Stock Correlation Explained

everyone and welcome back to Mike and his whiteboard my name is Mike this is my whiteboard and today we're talking about correlation so we're gonna finish off the week with correlation and beta since they're tightly tied together which will pretty much conclude our five Greeks that we've discussed so far so correlation is pretty much a very good metric that we looked like to look at in terms of trading and how different underlyings are related to each other so when we're talking about correlation what we're really looking at is the mean of the underlying relationship so we're gonna be looking at historical movement based on any sort of time frame so we can look at one month six months one year it doesn't really matter but all we're really looking to see is how correlated an underlying is to a different underlying that we're measuring it against so when we're looking at correlation basically we've got positive correlation negative correlation or no clear correlation so a positive correlation if it's completely correlated it will have a positive correlation of 1.0 a negative correlation will be the opposite so you'll see a negative number and indo on the dope platform you'll see a positive correlation as a Green Square and a negative correlation as a red square and you can locate that by just logging into the brokerage account going to the trade page or the grid page and along the top of the trade page you'll see a panel and you'll see two arrows going against each other and that will enable the grid the correlation page if you just click on that and on the grid page you'll see that same panel but it'll be vertical and you can go there and view different correlations for different underlyings and what we're measuring it at is a one-month timeline so we're basically looking at the last month of historical data and measuring the correlation for different underlyings so without further ado let's get into what different underlying correlations might look like so along the y-axis we have a dollar value so let's just say this is the price of the stock and along the x-axis we have overtime so we're looking at pretty much the price movement over time so a strong positive correlation you can see that we've got a red line here and a blue line so the red line and the blue line are pretty much moving one-for-one so you might see a strong correlation with this so this would be like a positive number maybe like point nine seven or 0.98 something very close to one because you can see that there's some distribution here and deviations from the actual mean but they pretty much move one for one so when I'm talking about the relationship of their mean just imagine taking their average price and just drawing a line straight through it so you can see if I'm if I've got a straight line here pretty much all the movement is on the same side of the mean so when something has a strong positive correlation we're taking that mean value and we're looking at where the underlyings are in relationship to the other at some certain time frame so you can see if I drew a line straight through this pretty much the whole time that this these two underlines are trading they're on the same side of their mean so that is what gives them a positive correlation so what are some examples of this so some examples of this would be something like Facebook or Microsoft pretty much anything in the S&P 500 bundle of stocks is going to have a strong correlation because when they move together or when the S&P moves they're gonna move up and when the S&P moves down they're going to essentially move down so theoretically you're gonna have strong correlations with underlyings that are within a certain bundle of stocks so again things like any tech stocks Microsoft Facebook Twitter they're all gonna have pretty much a strong positive correlation now let's look at an the opposite version of this which is going to be a negative correlation so we've got the same thing here we're going to be looking at price action over time and you can see that the graphs are pretty much mirror images of each other so we've got the blue line above and the red line below and you can see when the blue stock goes up the red stock tends to go down and when the red Stockton's to go down the blue stock tends to go up so you can see that this is a negative correlation so what if I drew this line straight through where these two points meet much they're always on the opposite side of the each others mean so that's what gives them that negative correlation so an example of this right now would be something like spy and TLT so over the last month if we look at the grid or the portfolio page or grid page or trade page on the dope platform and you look at the correlation you can see that there's a pretty strong negative correlation between 20-year bond etf and SP y which is the sp500 etf now what's really important to note is that correlation can change because it's basically looking at historical data for a certain time frame and I keep talking about time frames so let's just break down to certain time frame so if I'm looking at a one-month timeframe of historical data I'm pretty much looking at the very close view of correlation so I'm just looking at one month but if I expand that to one year and I have a strong correlation now I pretty much know that over the past year this has been a very strong correlation so I know going forward I can probably assume that those two underlyings are going to stay correlated because they've been correlated or have had a positive or negative correlation for a long period of time so we like to look at it from different time frames we're looking at it for one month just because of our trade style with the 45 days to expiration pretty much meshes with what we're trying to do but it's good to know what different timeframes will give you in terms of results of correlation so we've got positive correlation we've got negative correlation now let's look at what something would look like if it had no clear correlation so the next graph here we're going to look at no clear correlation and I think it's going to be very clear that regardless of what one stock does and the other does there's really no trend with the other so you can see the blue line is spiking up but the red line is pretty much staying neutral and the blue line spikes down but the red line is pretty much unaffected so when you see something like this when you're comparing to historical charts you're going to see that there's really no clear correlation I can't really draw any sort of conclusion from the relationship of these two especially when I'm looking at the mean so if I'm looking at the mean of both of these sometimes when the blue is on is below I mean the red is above and sometimes when the blue is above the mean the red is below so there's really no clear correlation here so an example of this would be something like gold and Twitter if you go to the DOE platform you can see that there's pretty much no correlation I think it's point zero two so it's real close to zero so again when we have a positive correlation it's going to be a positive number anywhere from zero to 1.0 and if we have a negative correlation it's going to be anywhere from zero to negative 1.0 where negative 1.0 is the strongest correlation and positive 1.0 is the strongest correlation for positive correlations so if you see anywhere on that DOE platform correlation page anything close to a zero there's really no clear correlation here so what's really important about correlation is that it's very important when we're looking at number of occurrences so we talk all the time about number of occurrences and correlation and what we really want to do is make sure we're looking at non correlated underlyings because if I've got different positions in Apple Twitter Facebook anything that's very positive positively correlated regardless of how many occurrences I put on those trades let's say I've got three naked puts all at the same time those aren't non-correlated they're very correlated so if the Nasdaq or SP goes up then I'm probably going to see profits on all of those so what we like to do is trade non-correlated on belling's which is actually one of the takeaways here so let's talk about some other takeaways with correlation as well so just a recap correlation is essentially the relationship between the mean of the two underlyings so just think about drawing a straight line finding the mean or the average of the price movement over a certain period of time and then look at the two graphs and see where the correlation is so where they're at the same side of the mean or on opposite sides of the mean so again if they're on the same side of the mean that's a positive correlation if they're on opposite sides of the mean that's going to indicate a negative correlation so again negative correlation underlyings move against each other so since they're on opposite sides of the mean that means if something is going up and something else is going down when we look the relationship between each other that's gonna give us a negative correlation they move against each other and they're again they're on the opposite sides of they're mean and with positive correlation it's just the opposite so if two underlyings are on the same side of the mean at the same time then it's pretty clear that when one goes up the other should also go up and when one goes down the other should theoretically also go down as well so again the clear takeaway here is what we'd like to do is trade non-correlated underlying so that pretty much makes us very diverse in terms of what we're trading so we don't like to just stick with certain stocks we want to make sure that we've got different stocks and different underlyings and different sectors of the market so I might be long something in Nasdaq and short something in mining ore minerals anything like that so pretty much what we want to do is make sure we've got very diverse stocks and portfolios so that when we're looking at correlation we pretty much have non-correlated underlyings and we're pretty much not susceptible to big large moves in the market so what we're gonna learn about correlation is that it's very closely tied to beta and we're going to talk about beta tomorrow so this has been correlation if you've got any feedback or questions at all shoot me an email to support at doe comm or support at tastytrade comm or you can send me a tweet at trading at tastytrade or at doe trader Mike so again tomorrow is beta and we're gonna wrap everything together in the next segment of all the Greeks so thanks again for watching this has been Mike and his white board and my name is Mike what's up everyone thanks for watching our video click below to watch more videos subscribe to our channel and visit our website at tastytrade calm

Channel: tastytrade

Views: 13,136

Rating: 4.8303032 out of 5

Keywords: stock correlation, multiple stock correlation, correlation, stock market, correlation matrix, stock trading, technical analysis, investing, positive correlation, negative correlation, types of correlation, what is correlation, correlation coefficient, positive and negative correlation, no clear correlation

Id: MhysGTc0rxM

Length: 10min 52sec (652 seconds)

Published: Tue Feb 02 2016