So what is this magical thing called beat? And how can it improve our asset allocation. So essentially bita measures the systemic risk of a single asset versus an index, or for those of you that understand statistical modeling, it would be the line of best fit in linear regression analysis. So essentially, the chart that we have here is a five year beta for Apple. So, all those dots on the chart that's either a weekly return for Apple or the s&p 500 over a five year period. And what you want to see is you want to see those dots cluster close together, and that'll give you a high probability of what the beat actually is.

So let's say we have a company like apple, which this example is about, and we're measuring it against the s&p 500. What we want to find out is for every 1% move in the s&p 500, what's the relative price move in apple? In short, we would be talking Taking a company. In this example, we're using Apple. And we'd be measuring the returns of apple or their performance on a weekly or daily basis over a period of time versus an entire index. So we might be looking at the s&p 500, for argument's sake, and we'd be measuring the returns relative to each other to figure out which one has a higher beat or which one is more volatile than the other within the s&p 500.

There are 11 different sectors right, which I'm sure you're all very aware of. So that ranges from technology to financials to utilities, and each of those has a different volatility profile, versus the broader markets. So we can take financials for argument's sake, and we can calculate beta for the financial sector versus the s&p 500. And that'll give us really good insight into how we should allocate our portfolio. So taking a bigger picture, macro view and a top down fundamental perspective of an economy, we might come to the conclusion that we're entering a bull market, I would end a bull market, we want to be long hire beat on names. So we want to be taking full advantage of the move.

And we're quite happy with the extra risk. In other words, we're quite happy with the extra volatility. So we need to measure each of these industries or these sectors versus the s&p 500 to figure out where we need to allocate our capital and when. So what I've done is I've broke down the beat for every single sector here. So as you can see, from the left, we've got technology all the way to the right where we've got materials, and each one has a specific value. And what that value represents is, it's essentially the price volatility of that sector versus the s&p 500.

So first, we've got technology where it says 1.14. So for every 1% move in the s&p 500, we tend to have a 1.14% move in technology. Next we have healthcare for every 1% move in the s&p 500. It tends to be 0.96. On a very important caveat here is the beat up for each sector in front of you guys. That's a follow up Beat.

So that's given us perspective of price volatility over a five year period using the weekly returns profile of each sector. To give you a more practical view of what that linear regression analysis means is, if we have a look at the five year view of x lk here, which would be the technology sector, the s&p 500 technology sector, and we love God for argument's sake, we want to compare utilities so we can x Liu that'll give us the utility sector. And what we can see is over the same period, we have massive outperformance from technology. So if you guys remember the beat off technology versus the s&p 500 was 1.14. The beat of utilities was 0.31. So in a bull market, if you can do a top down analysis of the economy in a bull market, you want to be long, higher beat names in a bear market.

You want to be sure tire beat names, and you want to be long, lower beat names, and the idea would be that you captured this spread in the middle. And essentially, if I'm to show you guys what the s&p 500 looks like we put spy in there. Essentially, what we can see is that the spy comes somewhere in the middle there. So a lower beta name, you'd be capturing the spread between the s&p 500 versus x value, or the utility sector. So we go into a recession, you go long utility sector, you go short, the s&p 500, and you're looking to capture that spread in between. So it's a low risk trade off that we're making into a recession in order to make a decent return.

While broadly assets are falling, finding tops and bottoms is not that difficult when you put it into perspective, right. And that requires the right time horizon that requires overlapping a number of different aspects such as fundamentals, macro technical analysis, which is all available in the full course and will give you guys a fantastic overview of how we break all this down. But essentially, the more work we do behind the scenes, the higher the problem ability of the outcome for us. And finally, to demonstrate the view here, this is a very long term count of the s&p 500. Now we use Elliott Wave as a technical analysis tool in order to give us directional bias or pinpoint some sort of trend change in markets. That gives us a higher conviction using fundamentals and macros well.

So essentially, what we have here is just a couple of pointers to show where we would want to be in a higher beta name versus where we would want to be in a lower beta name. So if we were to go back to 2006 into 2008, we seen that the housing market started to roll over. And when you realize that housing or real estate is where the majority of people have their net worth, and that starts to roll over in 2006, as represented by the homebuilders, we recognize that there was something wrong. So in that period, you would want to be transitioning to a more defensive portfolio. In other words, we go back and look at what we just mentioned a moment ago with beta, we want to be long lower beta names. So we want to be long you utilities for argument's sake are long consumer staples.

And what we want to be is we want to be sure tire beaten names like technology, or maybe in this case financials. So we go back to the financials beta, the beta for financials is right up there with technology, both of them are the highest beta versus the s&p 500 a 1.14. So we would want to have been short financials because it's very sensitive to real estate, we want it to be long utilities. And so by measuring beat out, whether it's a single stock, whether it's a gold miner versus the gold price, whether it's Bitcoin versus the broader market cap of cryptocurrencies, it doesn't really matter what you're measuring it against. What it gives you insight into is how you should be positioning yourself during different market environments, whether it's in stocks, whether it's in currencies, whether it's precious metals, bonds, it doesn't matter. The trick behind bita is giving you insight into how you should be allocating your portfolio in that specific moment in that specific environment and it should be used as a tool in tandem with traditional technical analysis.

Whether you're using Elliott Wave or using support and resistance, it should be used in tandem with fundamental bottom up analysis of an economy macro top down analysis of a global view, if you will, whether it's a single stock that you're looking into, you want to have bottom up fundamental analysis, you want to know how to measure the valuations, liquidity on the balance sheet, etc. and that all increases the probability of you making money long term in the market. So beta is a fantastic resource very simple, and an extremely powerful tool to help you as an investor to generate consistent returns.