Hello and welcome to the session. This is Professor Farhad in which we would look at a single index stock market model This topic is covered on the CFA exam as well as essentials of investments I'm gonna try to keep the Statistics out of this as much as possible when I explain this model as always I would like to remind you to connect with me only then if you haven't done So YouTube is where you would need to subscribe. I have 1800 plus Accounting, auditing, tax, finance as well as Excel tutorial. If you like my lectures, please like them Share them put them in playlists if they benefit you It means they might benefit other people connect with me on Instagram on my website farhadlectures.com You will find additional resources to complement and supplement this course as well as your other accounting and finance courses I strongly suggest you check out my website. First, we need to do a quick review You just want to make sure we know the difference between systematic and firm risk because we need to use those terms in this session systematic risk Systematic risk is the macroeconomic risk that's affecting all securities not a particular company and not a particular product It's affecting the whole economy inflation interest rate the Federal Reserve so on and so forth firm Specific risk in contrast to the systematic risk it affect only one particular company or one particular firm or at most maybe a cluster of firms For example software companies now the index model that we're gonna be working with today. What is that? It's a basically a statistical model designed to estimate These two component which are what are those two component the systematic risk Which is the broad market risk and the firm specific risk as to relate to a particular security or portfolio So we're going to look at this model as a way to Study the relationship between a particular stock or portfolio and those two Risks systematic risk and firm specific risk. So why do we use this index model? Why don't we use morco? It's well, there's a reason why because of its practicality and we're going to explain this in a moment To construct an efficient frontier, which is we talked about the efficient frontier in the prior session From a universe of 100 securities only we need to estimate 100 expected return because we need to we need to figure out the return We need to figure out the variances and we need to figure out Obviously the most important is how did they interlate with each other the covariances? So we need basically 4950 covariances alone and we're only talking about 100 security. So if we are dealing with 1000 securities What's going to happen? We need to compute almost half a million variances 1000 expected return and 1000 different Factors, so that's that's that's that's impractical So the index model asserts that one common systematic factor Which is a market factor is responsible for all the co-variability of the stock return With all other variability due to a due to firm specific factors So what we're saying in this model look how a stock return varies It's we can measure this by Study in the relationship between that stock and the market itself rather than studying the stock All the variability but among the stocks just let's look at this stock and how does it vary within the market? So this assumption dramatically simplifies the analysis of what we are trying what we are trying to do So i'm going to try to illustrate this concept by looking at this diagram and going through the equation So again, i'm going to try to keep the statistics out of this as much as Possible as much as possible. So here we're looking at this diagram And each dot there's a 60 of them a few count them represent the monthly access return of five years for Ford Motor Company And what we have in addition to that we have the Access monthly market index. So this is the market index right here the x-axis And we have the access monthly return on ford on the y-axis Now how first of all, how do we read those dots because we have 60 of them? For example, if we take this dot january 2020 the return for Ford Motor Company because the return for Ford Motor Company on the y-axis is 15 0.9 percent. That's the Ford Motor Company And the market return for that month was 5.4 So this is where this point intercept 5.4 on the market. Let's assume the market the s&p 500 And 15.9, which is let's say 16 percent. So january 20 seconds. So this is how we read those returns So so basically you could look at this return this return this return so on and so forth now What else do we need to know? What else do we need to know is this? the The line this line right here line of best fit this line and we're going to talk about how we draw this line later This line supposedly passes in the middle of all these dots. So it is in the middle So this this line is the the line of best fit like in the middle of all these dots Okay, now this is a regression line And what does it show if you know anything about regression? We saw a positive relationship between Ford and the market I mean we can look at just look at the Look at the scattered and we see that as As we have more return as we have more return as we have more return for the market We have more return for Ford motor stocks. It means there's a positive relationship now. We're going to measure this positive relationship We're going to measure it and you look at the equation, but that's the first thing you want to know And also we have you remember every time we have a line we can we can show that we can compute the slope of the line And what's the slope of the line? Rise over run or rise over run So you could also compute the slope of the line. It reflects the sensitivity of Ford return to the market how much Ford changes with every one percent of change in the market again We're going to look at actual numbers, but this is what we can do from this information. Okay now Notice these points are scattered all over. Okay Now the more scattered they are so if they are scattered all over the place if they were scattered more than this Then what we can say is there is no relationship between Ford and the market So the more the closer they are to this line And if they all if they are if all these dots are on this line, what does that mean? Let's assume that all are on this line Okay, so it means with for example, this is two percent market return. Maybe this is two percent ford five percent five percent notice 10 percent 10 percent of all these dots so the closer to the dot it means there is a perfect relationship So in other words ford and ford motor company and the stock market or whatever market We are using as as as a proxy of the market. They work hand in hand the more scattered they are Okay, it means Ford has firm specific condition that explain the stock not the market So hopefully this is the overall picture now We're going to look at specifically about the equation that form this line and understand the component of it So let's take a look at it. Take a look at this. So how do we how we might determine the line of best fit? Well, we estimate the line using a single variable linear regression using this formula Now we need to explain everything in this formula So the return is a function of the alpha of i Plus the beta of i plus the risk premium for that particular period plus E of i and we're going to explain each one of them separately starting with rm this function here We use r of i to to donate the excess return. So the market index m has an excess return Which is the basically the risk premium. What's the risk premium? It's the risk the return on ford minus the risk free rate This is the risk premium for if we're looking at ford security. So this is this one here Okay, this one here alpha. What is alpha? This is alpha alpha of i alpha of i is the intercept of the equation You know, it's alpha of y and what's the intercept of the equation? This is so you can see it. Hopefully i'm sure you know what the intercept of the equation This is the intercept of the equation where this line hits the y axis and it's going to be negative point Approximately negative point nine, but this is what the alpha intercept is. What does it represent? It represent the security's expected return when the market access return Equal to zero think about it when this is when if this equal to zero if you take zero times beta even though You don't know what beta is this is going to give you zero. So simply put alpha alpha tells you what is the return On this stock. What's the return on ford motor stock if the access return is zero that means We cannot have any risk premium To can we still have some sort of return for this for the stock? So can be thought of as the expected return on the stock and access of the treasury rate above the risk free rate Beyond any return beyond above any return induced by movement in the broad market So simply put you want this to be if this is positive if this is positive That's good. Why good positive because what we're saying is although you have no And no access return because this is zero you still have some return The stock still earns something even without the risk premium Okay, so investors naturally will be attracted to stocks with positive value of alpha It implies a higher average access return without the cost of any additional exposure to the market So simply put you're gonna you're gonna earn you're gonna you have a return Even without any exposure to the market. So that's why you want this alpha to be positive So investors would always look at alpha but alpha overall in the market If we compute all the alphas from different people the the alpha market is zero Now, let's take a look at beta. So let's take a look at this function here beta Beta is the slope of the line beta is the slope of the line, which is again rise Over run. Hopefully we all know what how to compute the slope of the line It's the amount by which the security return tend to increase or decrease increase or decrease for every 1% increase or decrease And return on the index and therefore measure the security sensitivity to the market wide economic shocks Simply put when the market goes up 1% what happened to your stock when the market goes down 1% what happened to your stock So this beta Measures it so it's it's the beta is the natural measure It is a natural measure of the systematic of the market risk. How does the market risk affect your stock? What's the relationship between the two and the term is e of i at you know at monthly It's the firm specific surprise in the security return in the monthly. It's often called the residual Basically, this is the risk that's specific to the company itself Think about it. This is we said this is the market risk And this is gonna be the firm risk Okay So the greater the residual positive or negative the the wider is the scatter of the return around this straight line So if you have if you have greater residual risk Okay, the the numbers will be scattered. Why it means if you have a greater residual risk It means the this firm this firm risk is not based on the market This if this number is large at positive or negative it's based on the firm itself Therefore, it's not explained by the market and that's what we have to measure when we get the numbers We're gonna see the measurement of the numbers. Is it explained by the market or is it explained by the firm? This scatter reflect the impact of firm specific or what we call residual risk now Remember both residual risk and systematic risk both of the market and residual Contribute to the volatility of the return. Of course, that's the case, you know the stock your stock is Is dependent upon the volatility of the market as well as the volatility of the company itself of the of the news of the company itself So let's talk about this line and call it now the security characteristic line This is the line that we draw plot of the security is predicted access return given the access return of the market This is the return and for Ford Motor Company. What we have is Alpha is 0.98 percent, which is negative beta is 1.32 now. We need to know The risk premium plus This residual so this is what we can find out So to look at the security characteristic line It tells us on average that ford stock roses an additional 1.32 percent for every 1 percent in the market So 1.32 it means for every 1.32 percent it goes up for one for every 1 percent change in the market Ford will go up 1.32 percent. That's what it's that's what this beta is telling us If we take these numbers and plug the january in january when the market access return Was 5.4 so this is the market we would have predicted ford return to be negative 9.8 plus 1.32 times 5.4 percent which is equal to we would expect ford to have a return of 6.2 But ford had a return of 15.9 again. This is a formula What does that mean? It means the difference between what we expected and 15.9 Resulting in the residual In a large positive residual return of 9.7 so in this for the month of for the month of January we had a positive Residual return it means in january the stock was not influenced by the market The stock was influenced by factors maybe ford reported good numbers while the market wasn't doing well This is what we can this is how we can interpret this if we go back here and look at this number here And we notice let's take a look graphically at it because it's very important. We see it's far away It's far away from the market. Do you see this now if we compute if we compute for this number It's going to be closer So if we compute this number the residual Will be lower if we compute this number the residual will be close to zero for these numbers What does it mean residual close to zero? It means That that for that particular month Ford return was exactly Explain 100% if it's zero by the market return. There is no residual It means if if the market went up 3% if the market was up 4% the return for Ford was 4% do you see this it will be the same So the closer to the line those points are the closer to the line. It means they are the Systematic factors explain Ford's stock not firm specific and the wider they are From the line for those particular period It means there was something specific the Ford Motor Company There was something specific the Ford Motor Company that affected the stock price not not the market It's not explained by the market So this is this is this whole thing about this index model is to just show you the difference between those two Factors between those two factors So let's talk a little bit more about beta The average beta of all stocks in the economy is one the average response think about it If all the stocks are combined together and we compute a beta They all work the same like I mean they they cancel each other out The average response of the stock to changes of the market index composed of all the stocks is one to one If we combine everything so the beta of the market index is by definition one So what does that mean? It means when you compute your beta you can you compare your beta to one if your beta is one It means your stock works Perfectly with the market if your beta is higher than one. It's more It goes it's more it's on average It's more sensitive to the market if it's less it goes less than one It means it is it's a defensive stock So cyclical or aggressive stocks have higher than average sensitivity to the broad economy and therefore they will have a beta greater than one So they are on average. They have a lot of sensitivity The the market moves one point. They move 1.5. They move 1.7 Defensive stocks, they will have a beta less than one So the return on so when the market goes up one they go up by 0.75 They go up by 0.3 Now the best way is to show you actual beta because once you see the actual beta Hopefully it will make sense to you So if we look at the beta for amazon, and this is uh, what's the day's data at closing date august 7th The beta for amazon is 1.33. What does that mean? It means amazon moves More than the market now this is up and down when the market goes down. Also, it's going to move down 1.33 That's the relationship between beta amazon and the market if we look at walmart walmart for the same date The beta is 0.32. It means walmart doesn't move because walmart Comparing to amazon walmart is considered a defensive stock amazon. I don't know what it's considered technology stock E-commerce. I don't know amazon is basically everything. Okay, but it's definitely cyclical aggressive In comparison, hopefully we can all see this to walmart and beta clearly shows it now How do we compute this beta notice here? They took five years of data and they compare amazon to some index I don't know what the index is they could compare it to s and p 500 nasdaq I don't know they ended they did the same thing for walmart So this is how they computed beta and this is what they find out walmart doesn't move as aggressively as As as amazon and hopefully this makes sense The other thing we want to learn is about the variance because the firm specific component of the stock return is uncolorated unc Correlated with the market return We can write the variance of the access return as the stock s follow Basically, it's the variance of that formula except that basically alpha doesn't have a variance So what we're left with is the variance of the market Which is the systematic risk in the variance of the firm specific and I told you the total variance is the variance of The market plus the variance of the So why would your stock varies well because of market conditions or firm specific conditions? That's basically it therefore the total variance of the rate of return for each security is the sum of two Component what are those two component the variance attributed to the uncertainty of the entire market? Which is this component here, which is the systematic market? That's the systematic risk that's measured by the beta Measured by the beta and the risk premium and the variance of the form specific firm specific Which is the independent of market performance One more thing we could compute is r square and hopefully we all know what r square is is the correlation coefficient between the market And the stock return and this is a good measurement of how you know How can we explain the market versus the the firm specific? The dispersion of the scattered of the actual return About the regression line is measured by the variance of the residual So this is basically this shows us the magnitude of the firm specific risk And because they vary across different securities So one way to measure this is the relative importance of the systematic risk Is to measure the ratio of systematic variance to total variance remember what is total variance? Total variance. This is total variance systematic risk and firm risk So what we need what we need to know now is how much is the systematic risk in relationship to total variance? What we do is we take systematic risk And we divide systematic risk by the total risk, which is the variance the variance is Same thing as total risk and this is basically r square. So how much How much market risk explained the total risk? How much of the market risk explained the total risk? That's basically what we're saying explained risk, which is Systematic risk divided by the total variance now you could look you can look at the statistical formula But again, I'm going to try to keep stay away from those If r square equal to 1 it means there are no firm specific variants It means all the variance. So if we have a variance of 100 We have systematic risk of 100 100 divided by 100 equal to 1 So if we have r square of 1 and r square would goes from negative 1 to 1 by the way So if that's the case, it means this stock is works perfectly with the market It's all the risk is explained by the market. So the market explained the variance Low r square. It means market plays an unimportant role in explaining the variance and if we look at the the Ford the Ford stock in the january 2002 We can see if we computed most likely the the r square. It will be a low r square So the variance is firm specific the variance the risk is Because low r square. It means firm specific specific Let's assume an r square for a particular company is 0.3 for abc company It means 0.7 0.7 of abc is firm specific variance 0.7 If for example another company has an r square of 0.85 It means only 0.15 Is firm specific variance firm specific variance So which one is which one works more closely with the market? Obviously xyz more work Would work or based on statistical data or based on historical data Will match the market performance very much more much more closely In the next session we would look at an example that deals with a single index stock market As always if you like this recording, please like it and share it And I would like to remind you to visit my website farhatlectures.com If you are looking for additional resources to supplement or complement the scores Good luck and study hard


Hitchhiking is quickly becoming a lost art. I'm not referring to these apps on your phone and the websites out there that help you find a ride across state lines. What I'm talking about is the old fashioned kind of hitchhiking standing out on the side of the highway out on the exit on the turnpike at rest stops on the interstate thumbs out in the middle of nowhere. No sign except when desperate and even then all you write on it is home. It's the dangerous way, but it's always been dangerous. A stranger taking a chance on another stranger and that stranger taking a chance on them in return. I started doing it in the late 90s. At first hitting the road with my uncle and then by myself. By the time I was 19, I'd been coast to coast after spending the previous 18 years stuck in the same 10 miles of city. Most people hitchhiking don't use the old fashioned method. And I can't say I blame them, especially when I find myself in the rain with my last cigarette. I was smoking that last cigarette next to an exit on I five somewhere in central California.   I grabbed my backpack and my duffel bag and headed over to the waiting truck. I had a couple of knives in my pockets and a gun in the duffel bag. So I really wasn't too worried about anything. I get to the door and through the window, I see an older white dude graying and much to my happy surprise, smoking a cigarette. If you don't mind the smoke, you can hop on in for a stretch is what I hear after he rolls down the window. I find this agreeable and get in the car.  Roger, Roger McClintock coming up out of Iowa. How about you? He asks, I'm from here. Well, there, a little bit of time all over, I answer. He laughs at my reply and shakes his head a little fair enough, he says, and we travel in silence for a bit. Eventually we start up on small talk. This leads into Roger drooping slightly more personal stories. I don't reply with anything other than one I deem humorous. I ask for a cigarette when he lights one and gives me one as well. Did you know that once upon a time, stories were basically a form of currency? He asked me, I don't respond. And he continues, well, like if this was 100 or 50 years ago when we met in the middle of the night, you might offer to pay for that cigarette with a story. It seems to me if you're good at telling stories, then you're usually a good travel in companion. If you're good at telling stories, you can make friends in a bar pretty easy. I bet you got some good stories from the road. I hold my silence. My dad used to travel quite a bit for work. He hitchhiked when he was a kid, rode the rails too. He had stories stories like you wouldn't believe he could go all day. Like father like son, I ask he laughs. My dad used to tell me that stuff about stories, how they're important. He pauses for a moment. I'm going to tell you one of his stories. He looks at me, but I stare at the road. He lights a smoke and starts his story. My father was driving from Houston, Texas to Portland, Oregon. This was back in 1968. I hadn't been born yet. He hadn't met my mother yet. He was fresh out of college and heading to Portland to visit some friends. Well, somewhere along the way. He spots a man hitchhiking. What stood out to my father was the way this man was dressed. He was wearing a dark gray trench coat with matching pants. He wore a black cowboy hat with a red band on it. He was outside Texas by this point. He said it was a pretty cold night and the man was not adequately dressed and stood there with a stern yet blank look. He passed him, but the guy stuck in his head and at the next exit, which was almost 50 miles down the road, he saw the same guy. Now, there was no way this guy had gotten ahead of my father. He was sure it was the same man. For some reason, my father decided to stop. He stopped down the road a bit and my father sat there but didn't look back. He thought to himself, if he gets in, he gets in. Sure enough, the man came over, opened the door and sat in the car without saying a word. He turned and without any expression thanked my father and asked him if he could drop him off three exits up the road. There's a bit of silence before my father gets up the courage to ask the man where he's heading. Do you know what he says? Three exits ahead, I answer. He laughs and continues. That was his answer. Eventually, my dad lights up a cigarette, offers one to the man which he accepted. He started to talk to this man, despite him not offering anything at all in the way of talking. Every now and then a yes or no, but his tone was flat. It told you nothing of who he was, how he was feeling. My father said it was like he was blank. He was a blank void in the shape of a man. My father knew that made no sense, but it's what made sense to him looking at this man. When they reached that third exit, my father pulled over to let the man out. Before he got out, the man asked for another cigarette. My father shook two cigarettes out of the pack and gave him to him. One for now, one for the road, my father told him. The man takes the two cigarettes and looks at my father for a moment before telling him this. He says, if you see me again along anywhere along this road before you make it home, don't pick me up. The man got out of the car and my father drove into the night. He stayed in a motel overnight before heading back onto the road. He gets about a hundred miles into the drive when he sees that same man stand in there in broad daylight on an exit. The man looked at him with a blank stare. My father did not pick him up and he never saw him again. I asked for another cigarette. He gives me one and I light it before starting my story. As it so happens, this is also a story my father told me about something that happened to him out on the road. So this would have been about the late 1990s when this happened. My dad was working for an oil company down in Texas as a glorified courier. When confidential documents are payroll or probably bribes needed to be transported, my dad was the man for the job. He'd find himself driving all over Texas. He didn't like to sleep overnight when on the road and he'd push himself on overnight drives to get home to all of us faster. Sometimes he even took me with him, which was great, funniest times I ever had with my dad. We'd eat at roadside diners and burger stands and he'd smoke his pipe when the sun was going down and, well, anyway, he once told this story and he only told it to me once. He said that this happened on one of the trips I went with him on. I was sleeping in the back. He said a pack of wild dogs had started to trail his car, which wasn't uncommon on the back roads or even the interstate at night. He said it was about a dozen and a half of them and they were charging as fast as they could to try to keep pace. And eventually they ended up in the middle of the highway chase on the car. This kept up for miles and he'd never had a pack follow him this far. He tells me at one point he looks up in the mirror and he sees one of the pack stand on its hind legs and start running like a human after the car.  The pack quickly was left behind, but as he got farther away, he saw two or three more of the pack stand on their hind legs. It's like humans. He drove all night. And when I woke up in the morning, he told me about what he'd seen. I was about 10. I knew my dad to be a good, honest man. I could tell he was unsure about telling me, but his flat tone told me he'd already rehearsed what he had to say to me many, many times before I'd woken up. I never asked him about it after, but it always stuck with me. He was silent for a moment before he tells me, there's stranger things out here on the road that'll chase you through the night. Not all of them give up that easy either. I don't ask him what he means by that. I tell him he can drop me off any exit he feels good about. We don't say anything else until he pulls the car over about an hour later. He looks at me and I can feel him sizing me up. You've spent time on the road. You've seen things I can tell out here between places. It can be, well, things can get strange in the night. Be careful when you're walking these roads.  He takes two cigarettes out of the pack and gives them to me. One for now, two for the road. He says, we share a glance. I could feel a brief moment of sizing up, gauging. I thanked him and took the cigarettes and got out of the car. I watched him drive off into the night for a while. I stood there in the darkness.  I thought for a moment about what it could possibly mean before lighting one and sticking the other behind my ear. I walked to the roadside and stuck my thumb out for the next ride.


So this is the Samsung Q900R, the company's latest 8K TV. This is the 65-inch model, which I have right behind me. And welcome to our setup video. Yeah, it's a little bit of an unboxing in this as well, but you get to see how this TV's set up, how it functions, all that fun stuff. Now this is no review, but we've got a lot of fun content in this video. So don't forget to smash the subscribe button, like this video and let's jump in. The Q900R is a lovely TV set, although thicker in terms of width than most regular 4K TVs. Now sending the TV up is an interesting process because I started looking for the TV stands in the box and realized after about 15 minutes that it's actually mounted behind the TV, which is cool. So if you wanted to warm out this, you go ahead without even touching the mounts, but you can see how easy it is to just take off the stands for the TV and then connect them, which is just super cool. I love this really simplistic approach. Now you can do it a wide mount or of course a narrow mount, depending on what you want to do. I'm giving you a very nice flush look and I like the whole back array. Now that's where you wanna connect the cable, connects to the TV. We've got a path that you can wrap it around to make clean cable management so you wanna connect the box right here. This box is a little heavier because it's the AQ version, more processing power in here. As you can see just how it looks, it's pretty flush. You've got all the ports you need in there. Of course, you've got your power, your antenna. You've got your HDMI ports as well. You've got your LAN optical and of course the one connected port itself. Now on the side you've got USB ports, the USB 2.0, which was 3.0, but it is 2.0 here. So the TV, when you turn it on, Samsung QLED 8K comes up, this is the 8K TV. It upscales all your content into 8K. What I like about this setup process, this is one of the easiest ones out there, is that once you turn the TV on, gives you the language you're looking at, you can select your language, whichever one you use for your TV. But then it prompts you to use the app, the SmartThings app and you can do this either if you're a Samsung owner, you've already got it built in, you can download it on Android or iOS and you're good to go. It finds your TV right the way and then you start the process. So that's where you wanna put the TV in, home. It's my living room, I'm gonna add that next and then I'm gonna go through the process here. Now this is the cool part about it because what it does here is it gives you a PIM prompt which you go ahead and you type in that PIN and then it's so fast because as I'm talking you through this it's a relatively fast process of just setting up the TV and going through the process of basically syncing in and giving you everything you want. So right now the process is going on the TV so it's setting up through SmartThings and boom. Before setup TVs used to be so difficult and long and also a lot of processes that you have to actually go through to make it happen which this is not the case. So next up of course is accepting the agreements which you have to do for all devices nowadays so you agree to all that, hit okay. And then it continues to process here restricting your TV to Samsung account which I already signed into. So once you have your Samsung account there's certain things that will bring down. So in my case because this is of course a smart TV things like smart things will show up in there and then I also set up my TV settings as well. Go ahead and hit next there. I'm just taking this a little slower than it actually is really a fast process but I'm trying to make it as simplistic as possible. Also recognizes what connectors you have. So I have a few things on my Xbox was off. If it was on it would actually showcase as Xbox there on my PlayStation or even my Nintendo Switch. So I like that aspect about it and the process again is really smooth and fast. And here I'm gonna enter of course my zip code and from there you're signed in and you already have TV playing because TV plus gives you digital free high def content. And you can see you have the plethora of menus for the speakers, for picture mode, amplification you even now have a app management or OS management, which is new. I like that. It's different, sets it up well. What I like about this TV is how good it looks. It is vibrant. When you're watching content on this thing, it looks good. The stuff on, I'm watching here on Netflix which is upscale to 8K, looks really good. It's just really sharp and vibrant. YouTube content, 8K content on there looks very, very nice. You get to enjoy this TV to the fullest and stay tuned when I do my gaming video and also do my full review on this. You get a good idea. Gaming on here looks really nice. Now this is not recorded at 60 frames per second but it also has free sync built into the TV. So if you're connecting your gaming PC, which I'll be doing, you get a whole different atmosphere with this TV set. So anyway guys, if you have any questions or any comments, let me know. Otherwise, don't forget to like and share this video, favorite this video, stay tuned and let me know what you wanna find out more about this TV. I'll tell you in my full video review and also my gaming review of the Samsung Q900R 8K TV. So don't forget to smash that subscribe button, like this video, hit the notification bell and always enjoy your entertainment.