Using multiple Trading Indicators to screen for trades? Do this instead!

Foreign.

Here from enlightened stock trading. And are you looking at charts with piles and piles of indicators trying to make your decisions about what trade setups to take for the next day? If your chart looks anything like.

This, then this is the video for you. Because if you're looking at multiple indicators like this, trying to make your decisions, I got news for you. This is really, really confus challenging and difficult to be consistent. And on top of all that, even if you do look at all of these great indicators, you don't really even know if you're going to be profitable. Right. So what I want to do in this video is I want to show you a better way. If you're looking at charts full of indicators like this, there's an absolutely a better way to trade. And I want to give you a sneak peek into it right here. So on this chart you can see I've got the price chart at the top. I've got a long term 200 day moving average, I've got 100 day moving average, I've got a Bollinger band underneath, I've got volume, I've got macd, I've got rsi, I've got Stochastics, I've got rate of change, I've got ADX and I've got the VIX just for good measure. I don't know why I've got the VIX on an Australian chart. But anyway it's there. And you know, you could look at all of these indicators and try and make a decision. Except sometimes half the indicators are going to be pointing up and the other half are going to be pointing down and then at other times it's going to flip and you're never really going to know for sure when, which way you should go. And so it leaves your trading very much open to subjective interpretation. And subjectivity when it comes to trading is an absolute killer. So what do we do about it? Well, what we're going to do is we're going to convert some of these indicators into objective rules that we can test over decades of market history to make sure that they are actually profitable. So let's, let's do an example. What I want to do, I'm just going to make this up on the fly. So what I, what I'll do is I'll put the chart here. Okay, we can see that. So on the left hand side I've got this big messy chart with all of these indicators and on the right hand side I've got my amibroker coding window and What I'm going to do is put some rules into this based on some of these indicators, and then we're going to test it and see if it actually works and decide whether some of those rules are profitable or not. So let's kind of go down the chart on the left hand side and what I'll do is I'll create some rules based on some filters or.

Sort of checklists that people typically use for their trading. So one of the first ones that people use is we want to trade when the price is above the 200 day moving average. That's a pretty sensible rule because we only want to buy when a stock is, is trending up. So we're going to say the close is greater than the EMA of the close over the last 200 days. So that's the first rule. So whenever the close is above this red line, this thick red line here, this system will buy. What's another rule that we can use based on this chart? Well, we've got Bollinger bands on this chart. And a common rule for Bollinger bands is to buy when the price breaks out above the upper Bollinger band. And on this chart I think we've got a 15 day Bollinger band with two standard deviations. So what I'm going to do is I'm going to make a buy condition that the price.

Crosses above.

The top Bollinger band and we'll just see 15, 2. Okay, so on a day that the price crosses above the top Bollinger band, we can potentially get an entry signal. Now what other.

Rules do we want to put in place here? Let's have a look down volume. Now, a lot of traders will say, okay, I want to trade a stock that trades more than a certain number of shares per day. My preference actually is to say my stock should trade more than a certain dollar value per day. And the reason that's important is because it's all about the liquidity of the stock. So we want to make sure the stock is sufficiently liquid to support our positions. So what I'm going to do is I'm going to require that the 20 day moving average of the close times the volume close times volume 20. And I want that to be greater than some meaningful turnover number. I mean, let's just choose a million bucks just to.

Because for most retail traders, liquidity or daily turnover of a million dollars is going to be sufficient to make sure you don't have too much slippage in commission. So now we've got liquidity requirements so the stock is trending up, it's broken out above the top Bollinger band and it's sufficiently liquid. Let's have a look at some of these other indicators. All right, so rsi, you know, some people might say, well, I don't want to buy a stock if the RSI is overbought. So let's say we want to have a filter that says the RSI 2 is less than, I don't know, some number 85. Because we don't buy when it's super over, when it's super overbought.

And some people might have a rule that says the ADX has to be above a certain value to be considered to be trending significantly. So let's put in a rule that says ad oops. ADX14 is greater than some value, let's call it 20. And some people also have an index filter. Let's say we want the index to be above a long term moving average. So first I've got to tell amibroker what index we want to use.

Foreign. And we're going to use the xao, which is Australian All Ordinaries Index. I'm just going to test this on Australian stocks, by the way, in case you're wondering.

Okay, so the index is the xao. And then for the index filter, we're going to say that the index has to be greater than the EMA of the index. Which EMA? The 200 day EMA. All right, so that's our setup rules. That's enough to start with. That's actually a lot of rules and I suspect we're going to simplify this down. But let's give it a crack and see what happens. Now, cell rules. One obvious sell rule from this chart and this setup is that the price crosses below the 200 day moving average. So let's say we're going to get out if the price crosses below or the price is below the 200 day moving average. Another exit rule might be exit if the price crosses below the lower Bollinger band because that would indicate that there was a significant sudden move down. So we can do that. And so what we want to do, I'm going to change that to the Bollinger band bottom. Okay, And I think that's probably enough. So we've got a bunch of exit entry rules in here, we've got a bunch of cell rules or two cell rules. Let's get rid of this down here. And now we've got to tie all these rules together and we're going to buy when Rule 1, Rule 2, Rule 3, Rule 4, Rule 5 and the index filter is true. And we're going to sell if Rule 1 or Rule 2 is true. And for the purpose of this exercise, I'm going to do percent of equity. Position sizing and risk have 5% of equity in each trade. There's no stop loss, there's no trailing stop because we've got the exit below the 200 day moving average, which kind of acts as a trailing stop. Anyway. We don't have a position score formula in here. Position score is the way we rank trades. So I like to buy stocks that are moving up fast. So let's call the position score the distance between the closing price over the EMA.

Seed. So the further it is above the 200 day moving average, the higher ranked it'll be and the more preference we'll give that trade when we've got limited capital. Okay, if you don't understand the code, don't stress about it. All I'm demonstrating is that we can take all of these messy indicators on the right hand side and we can create logic based objective rules that we can test. I've coded these into amibroker. I'm just going to check the code. Syntax is okay, it's all good. Now what I'm going to do is I'm going to push the code over into the amibroker window and I'm going to back test that code over all Australian current and delisted stocks from 1990 to today. This system enters next bar and open. Exits next bar and open. And I've got a 5%, sorry, a half a percent allowance for slippage and commission. Let's back test it and see what happens. Now I'm not expecting this to be a good system by the way. I've just taken a bunch of random rules, made them objective and put them into my backtest. This is what you want to do if you're trading with a whole bunch of kind of checklist indicators. You want to codify those rules. Put them into a backtesting platform like this and then combine them all and run a backtest to see if your checklist actually makes you a profitable system overall. Chances are your checklist is probably leaving a lot of money on the table and we're going to see that shortly. All right, let's go back to our backtest here and I've got a, the backtest report and let's have a look at the chart. And what do you know, it's ugly as hell. So if you'd have followed those rules over the last 20 or 30 years. You would have been really, really struggling. And this is what happens to a whole lot of traders because.

You know, you follow checklists based on logical rules that you read somewhere or you think were and, and they just don't actually work in practice when you test them correctly. Even if you've looked at your charts and found a few interesting trades here or there that were profitable, Maybe you found 20 or 30 or even 50 profitable trades and you thought, wow, I'm onto a winner. This is a great strategy. It's not enough. You actually need to test those rules over decades of market history, over thousands of stocks and generate many, many trades and see if they're actually profitable. So what I want to do now is have a quick look at the performance report and figure out why this wasn't profitable. So let's have a quick look. So we're 34% winning trades, which is pretty low but typical for a trend following system. But the problem is we've got.

14% average profit per winning trade. We've got 6% average loss per losing trade.

The average bars held is 73, so it's holding for a fairly long time. The average bars held of the losing trades is 23. So I think the big problem here is we're actually not letting our winning trades run. But we've probably also got a whole bunch of restrictive rules that don't really make, don't really help us. So what I'm going to do is I'm going to have a look at this code here. Let's come back to our chart. Let's have a look at the chart there. And I just want to simplify this down. I'm going to take out this second exit rule. I'm just going to make that zero so it never gets triggered. I also happen to not really like.

The rule for the RSI and the adx, so I'm going to remove those entirely. So let's get rid of that.

Instead of having the RSI rule. One of the things that I know is that often lower volatility stocks tend to trend better. So let's put in a rule here that says ATR divided by close is less than 0.06. So ATR, the volatility is less than 6% of the closing price. And then I'm going to get rid of rule by Rule 5 altogether. So again, I don't know if this is going to work. I've just taken out a couple of rules that I Don't like that. I see a lot of traders use. Let's send them over to the analysis window and run a backtest and let's see what happens. Now, incidentally, while I'm doing this, I'm not following the full backtesting procedure that you would learn in the Trader Success System. I have a detailed step by step process for developing and testing systems. All I want to illustrate in this video is that if you're trading with a whole lot of indicators on your charts, chances are some of those indicators are holding you back, causing problems, and some of them might have an edge, but you just don't know, right? So what you got to do is codify them into a backtesting platform like amibroker or Real Test or Wealth Lab or whichever one you want to use, codify them and then test them correctly over a universe of stocks, over decades of market history. So let's have a look here. I've got the performance report up. Let me zoom in so you can see and just by making a couple of simple changes.

It'S obviously not great yet, but we can see that the average, sorry, the annual return has gone up to 8.5%. We've still got a thousand trades, 33% winners. The average profit of the winners has gone up to 34%. The average loss of the losers is 8%. So the stats are getting much better. We're getting a much doing a much better job at letting our winners run and we're still cutting our losers off. And so this system is looking much more interesting. Obviously there's a lot of work to do. Right. But when we look at the equity curve, let's zoom in so you can see rather than it going completely flat and falling off from 2005 like it did last time, now we can see it's gradually rising. Obviously this is still not a system that you would trade. I absolutely wouldn't recommend it. But we're going to make one more change and then see what happens. So let's go back to the code and I want to just get rid of this Bollinger band and rule and I just want to replace that with today's close is the highest high value of the close over the last 200 days. Let's take, let's take a 200 day highest breakout and let's, let's see what happens. So again, just demonstrating that what we can do is.

Codify the rules that we've been using in a subjective way on our charts, codify them, test them, and if they don't work to our satisfaction, then we can brainstorm some improvements, some adjustments, try some different indicators, test those and find ones that actually give you the results you want. Now again, there's a whole testing regime that you would learn in the trader success system. All I want to do here is demonstrate the fact that if you're trading on charts manually, like subjectively with lots of different indicators, there's a much better way to do it where you can get much richer data. So here we go. Let's have a look. If we.

If we replace that Bollinger band breakout with a high side breakout average, the annual return goes up to 11%. We've got a much fewer trades. We've now got 43% winners. The drawdown is a little bit big, obviously. 43, a lot big. And the equity curve is starting to sort of flatten out a little bit. Now again, still, obviously a lot of work to be done, but if you can appreciate the concept of going from discretionary indicator based trading to objective rules based trading, you, you can actually test the results. And this is what I'm going to be talking about in my upcoming workshop this coming weekend called the Market Mastery Bootcamp. So if you want to learn more about how to trade systematically, how to remove the subjectivity from your decisions and make objective trading decisions that you can test, validate to make sure they're actually profitable, click the link in the description below and register for Market Mastery Bootcamp. I'll take you through the entire journey from launch to Mastery of Systematic Trading and show you exactly what you need to learn so that you can master systematic trading. And finally get the confidence and conviction about your trading rules so you can follow through and build the wealth that you want in the markets. My name is Adrian Reid. This is enlightened stock Trading. I'll see you at Market Mastery Boot Camp. Click the link below, register for Market Mastery Bootcamp. I'll see you there. Bye for now.