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Turning Automation On

You’ve prepared for this moment, now it’s here. It’s time to release your strategies to the real world of live markets, real money. It can seem scary and daunting, but you are confident because you have done your homework, you have tested your strategies, you know your edge, and you’re completely comfortable with the process. Time to make money.

In theory, your systems should run completely autonomously, but this is the real world, and if it were that simple, then everyone would be doing it. But not to worry, because you know the drill, you know what to expect and what to do. We call these things SOPs, or Standard Operating Procedures. Every commercial manufacturing system has them, military operations revolve around them.

For example, once you turn your systems on, the clock starts ticking, and that’s because you’ve entered into a cycle we call a campaign. Kind of like a project at work, it has certain goals and a timeframe. But your campaign is way smarter than the typical corporate project plan, it’s an agile process designed for continuous improvement.

Standard Operating Procedures (SOPs)

The whole goal of your SOPs is to take the pressure off of you, so that you can concentrate on the really fun part of automated algorithmic trading, and that is coming up with creative ideas, modeling those ideas, then developing them into automated strategies that make you money. That process of development is in fact a SOP, just like back testing is a SOP, and the procedure you use to promote your strategies to live trading is governed by a SOP.

SOPs are like recipes. You start with the basic ingredients, follow the directions, and wha la! You’ve accomplished a very important step. The only difference between a SOP and a recipe is that you sometimes have to make choices that follow a prescribed path, where you have to make a decision, like is it worth continuing with this strategy, or should I scrap it and move on to the next one.

Then there are operational SOPs like dealing with futures contract rollover. Every futures contract has an expiration date, and if you are in a trade and the expiration date is nearing, and you want your system to stay in that trade, then you need to roll the current contract that is about to expire, to the newly formed contract that the rest of the world is rolling to as well.

So, in this SOP there’s a few elements, first we need to know about that particular futures contract’s expiration policy, that will tell us the drop dead date, before we are obliged to take delivery of the underlying commodity. And believe me, you don’t want to take delivery…I mean what would you do with a tanker truck full of oil pulling up to your house?

But it’s not a big deal, you simply give yourself plenty of time prior to expiration. Perhaps you have a notification mechanism that tells you when a contract is coming near rollover time, or a mechanism that temporarily halts the trade until the rollover is completed. All of these are very simple to setup. And then there’s the act of rolling the contract, which is a super simple process. And then reuniting the contract with the strategy. Ok, that SOP is done, and your strategy is off to making money again.

Real World versus Hypothetical

When you are running a strategy in the live market and the strategy (a computer program) is entering and exiting hypothetical positions, the TradeStation system needs to maintain synchronicity between its hypothetical position in code and the real life position in the market in order to work. If that synchronicity is broken, in other words if the code has a position but there isn’t a corresponding position in the real market, then there’s a problem.



Fortunately TradeStation has a Position Match monitor in the TradeManager, that allows you to see if the hypothetical system’s position has a corresponding matching position in the real market. And so long as that is true, your strategy will look exactly like the real world position. But watching the TradeManager’s Strategy Positions monitor all day can be mind numbing. There are better ways, like an indicator on the specific chart where the problem has occurred.



This chart shows a big yellow bar where the position match has occurred. It’s easy to spot and effective. To get the position back in synch is an easy procedure. Go to Format>Strategies…, in the format window click the “Properties for All…” button, then the “Automation” Tab.  Then select the the options below to adopt a real world position. If the position is open, the strategy will use it, otherwise you may have to manually add the position, then the strategy will adopt it and all will be synchronized again.



Fully Automated versus Semi-Automated

When you release your first strategy and give it access to your real money, this can be difficult and a little scary because you have not yet developed the confidence in your ability to administer the system. So TradeStation provides you with two options, semi-automated and fully automated. Fully automated simply means that when your strategy decides to enter a position, it will do so without any further action by you.

The second option, semi-automated, requires your confirmation. You will be presented with a dialog asking for your confirmation to execute the trade that the strategy has initiated. I don’t recommend the semi-automated approach, unless this is part of your strategy, and you have a very good reason for requiring manual confirmation. Otherwise you are no different than a discretionary trader. If you love your strategy, you must let it go.

Here’s how you turn on Automation. Select Format>Strategies… from the menu, then check the Automation execution button, select the appropriate account, then turn off confirmation. Now you’re fully automated!


Running in fully automated mode at first can seem a bit intimidating, but once your strategy starts performing the way it did in your testing and curation, that intimidation factor will soon reside. And the more strategies you get running fully automated, assuming of course that they exhibit a low level of correlation, the easier it will become.

Multiple Non-Correlated Strategies

If you have watched any of my YouTube videos, or attended any of my webinars, then you know that this is my mantra. Successful automated trading is built around running “multiple non-correlated strategies.” This is the holy grail of automated trading if there ever was one.

You don’t need a rock star strategy to be successful. Besides, they are very difficult to come by, if they exist at all. One thing is for sure, even rock star strategies eventually stop performing. Developing them can take months or even years, and buying them, assuming someone would be willing to sell something that good, could cost a small fortune.

So why do it, when you could, with much less effort, build several simple okay strategies, that have a low degree of correlation between them? In fact, the best thing to do is create a process where you can continually churn out simple strategies that work. They don’t have to be perfect, just good enough. And that’s because when run together, the uncorrelated returns will have the effect of diminishing drawdowns and profits will add up. The result will be a combined system that is superior to the rock star system.

Diversification of strategies is the key to running a successful automated portfolio. Of course all of this can be easily accomplished through well established SOPs and a good plan.

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Life Cycle of a Trading Strategy in an Automated Portfolio

Creating automated trading strategies is being presented as super hard work, that takes incredible discipline, lots of brain power and testing, testing and more testing. And only if you follow the prescribe thousands of steps will you achieve success.

Well I say that’s a bunch of bunk!

Now let’s be clear, I’m not saying it’s easy as pie, what I am saying is that the emphasis and effort is all in the wrong place to make a trading system a profitable system. The emphasis should not be on creating the perfect rock star strategy, this is HUGELY wasted effort.

The emphasis should be on how well one strategy plays with the other strategies. Because a successful trading system isn’t about one strategy, it’s about a community of strategies that work well together. And the mind blowing thing here is that a bunch of average strategies working together the right way, that don’t take gargantuan amounts of effort to develop, will perform way better than one or two rock star strategies.

And the total effort to build these average strategies is orders of magnitude less to create than the rock star strategy or strategies. The rock stars can consume years or even a life time of effort. Simpler strategies can be churned out weekly. The difference is the playground in which you place them and how well they play together.

The key phrase here is, you should be running multiple non-correlated strategies.

So here’s the end-to-end process, the cradle-to-grave life cycle of a strategy. Don’t be intimidated, it’s not that complex. It’s all a matter of moving the strategies from left to right as they grow up and become better citizens.

Strategy Life Cycle

The concept is pretty simple. We want to produce a bunch of average strategies that have a low degree of correlation with each other. That simply means that they generate trading signals in ways that are not related. For example, one strategy might take signals based on seasonality events, another might wait for breakouts after an economic report, another might work on lunar cycles (not kidding), while another takes signals on significant pullbacks. And we can measure the degree of non-correlation with a simple Excel function called CORREL.

There are also fantastic tools that let you organize your portfolio of strategies into one consolidated performance report, that will show the correlation as well as the combined statistical measures. TradeStation has such a tool called Portfolio Maestro, and there are third party tools like PortfolioMerge.

Ok, so let’s look at the picture above. Our goal is to move strategies from the idea phase on the left, to the live campaign on the right. About one in twenty strategies will make it to the campaign. Not a big deal when you get my course as I provide you with a bunch of campaign ready strategies right out of the box.

Ideas to Development

Ideas can come from anywhere. I talked about this in previous emails, it’s not that hard once you get in the swing of generating ideas, as a matter of fact, this is the fun part of this process, the part where you’ll spend most of your time, perhaps 75% in total. This is where the magic happens. There’s a definite process and you build upon things that are known to work, and hopefully discover more things that work from time to time.

If an idea is a flop, then you scrap it. If it makes it through you initial evaluation, and shows some promise, it can go into the curation process. Your main job is to think of this process like a factory, where you need to develop lots of small ideas of reasonably high quality.

Strategy Curation

This is where your strategy goes through both in sample and out of sample testing. That simply means historic and live market data. The testing process is the key here, and the goal is to weed out the good from the not so good, so that after time a strategy shows its true colors and proves that it’s ready.

This is the boring part of the process, but perhaps the most important. You spend about 15% of your time here. Once a strategy has proven it works under lots of conditions and is robust and shows a low degree of correlation to other strategies in the live campaign, it sits and waits for the opportunity to join the game.

Live Campaign

Campaigns are like serial projects. This is where all the live trading takes place. A new campaign starts periodically, let’s say every three months. Thats enough time to evaluate how well the strategies are doing, and decide whether they deserve to stay in the game, or get replaced by a curated strategy waiting on the bench.

Not all strategies live forever. Sooner or later they loose their mojo, and with have to be retired permanently or put back into the curation process. Every once in a while, they can be recycled;ed into new strategies, which is not depicted on the graphic.


So that’s the entire process from end-to-end. There’s obviously a lot of detail left out for the sake of brevity, but in essence that is it. The key take aways here is that you don’t have to sweat over perfect strategies. Ok is good enough, so long as it’s non correlated with other strategies.

You scale your system simply by getting more strategies into the live campaign, and spreading the risk between them.

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Do More Of What Works – Finding An Edge In Systems Trading

There’s so much information out there for traders. You stick your finger in the air and get bombarded with advice, strategies, stock picks, analysts projections, and that’s all good for traders. The more information you have the better. So, the process of learning how to trade should be easy, right?

Oh, that is so wrong! The problem is everyone has an opinion, and shows like CNBC have at least 100 people everyday telling you what to buy. Fox business, Bloomberg TV, and all those Internet sites all offer you an opinion, which often sounds like statements of fact. Often you’ll here something like…oil is up due to the weak dollar, then within the same minute you’ll hear that oil is up due to the strengthening dollar. It happens all the time.

You can go on the Internet and look up trading strategies, and how to trade. But few if any of these bits of information are quantifiable. In other words there’s no backing study that shows statistical evidence of what works and what doesn’t. And so, you are left to figure it out for yourself. But most of us simply don’t have the time, so we rely on what we think are authoritative sources.

The problem with authoritative sources is that besides the fact that they may be peddling a bunch of bull, but let’s assume they aren’t…a lot of the data may be good for now, but a few months down the line, a year or two from now, it may all be worthless. Things change, for the most part. However, there are some things that seem to endure, basic principles that work. And so I’m going to list them for you here. Future articles will cover each of these points in detail.

  • Choose to trade short term (overnight to days, or weeks) vs intraday.
  • Buy pullbacks over breakouts, learn about hidden divergences
  • Buy after the market has dropped, not after it has risen (kind of like #2).
  • Stops hurt stock performance, the tighter the stop, the worse the performance.
  • Futures are more stop friendly, but dynamic exits are almost always better
  • Buy when stocks, ETFs and futures are above their 200-day moving average.
  • Buy when the VIX is 5% above its 10-day moving average.
  • Lock in gains when the VIX is 5% below its 10-day moving average.
  • Act on intraday highs and lows to increase your edge.

When you apply these broad principles to your trading, you will do better than had you not applied them. As a general rule, strategies that I have developed or are in the process of development, which lead to entries into the market, and my exit components, all follow these general rules. There are other very specific tools I use, that have held up to the test of time as well.

There are two specific indicators I use to help filter out noise and produce clearer signals. One is the 2-period RSI, the other is the rate of change of volume. These two oscillators are as close as one comes to the holy grail of indicators. Neither are standards, for example the RSI comes out of the box with most charting programs with a 14-period, and the ROC Volume doesn’t even exist in most platforms, the Chaikin Money Flow indicator is closest. But from a statistical point of view, these two clearly outshine everything else.

The 2-period RSI does the best job I’ve seen at identifying markets that are overbought and oversold, and the ROC Volume is the best leading indicator prior to a market move.

There is one other thing that I find curious, and that’s the need for traders to find a good shorting strategy. And while I’m sure there are some excellent ones out there, that probably work wonders in specific stocks, futures or markets. I can’t for the life of me find a universal principle to lay my hat dow on, that makes shorting a bit easier. So, as a general rule, I avoid shorting unless it’s handed to me on a silver platter.

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Automated Trading Strategies That Work

“Everything should be made as simple as possible, but not simpler” – Albert Einstein

Einstein’s job was to think of scientific theories that explained things we see in nature, it’s likely that he was paraphrasing Occam’s Razor. In other words, the best theory is the simplest one that still explains observations.

By the way, this was Einstein’s actual quote…

It can scarcely be denied that the supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience.

It seems that someone sometime later, paraphrased Einstein’s statement into one that was too simple to be understood!

Automated strategies should be simple as possible too. You should be able to explain the hypothesis behind the strategy in simple and easy to understand terms, so that your grandmother could understand. Not to knock grandmother’s, as mine was brilliant…but you get what I mean.

A strategy that is convoluted with lots of adjustable parameters, has little chance of working across multiple markets and multiple timeframes. A strategy that emboldens basic natural truths, that’s easy to understand, with few moving parts, has a great chance of success across asset classes, markets and timeframes.

All code samples are written in EasyLanguage by TradeStation, however, it’s so simple that it appears to be in a kind of pseudo language.

This first example is from observations that when there’s a really big bar after there being a bunch of small bars, by bars I mean candlesticks on a stock chart, then that usually precedes a big move. And if that bar is moving up, then the bigger move, or the momentum, is probably going up as well, so buy that. And then the opposite case…if that big move bar is going down, then sell it.


BigRange = rrange > (NumDevs*stddev(rrange, length) + average(rrange, length)); { resolves to true/false }

if BigRange and open[daysback] < close[daysback] then buy at the market; 

if BigRange and open[daysback] > close[daysback] then sell short at the market;

There are only two parameters to this strategy (days back, length). Hopefully that was simple enough to understand…and that is all of the strategy. Now we could get fancy and put money management around this, set stops and targets, etc. But the strategy in its purest form should work, and give positive results across markets and timeframes.

The next strategy is very simple, it’s called the simple breakout. It looks at the previous day’s close and the first bar that opens above that close and is going up, is assumed to be a breakout., So we buy that sucker, and hold it until the end of the session and then close the position. Now we could have gotten fancier and put all kinds of conditions on how far above is that bar than yesterdays close, or how big was yesterdays range, or should we put a trailing stop incase it decides to turn around, etc. But we don’t, let’s keep it simple.

BreakOut = close > CloseD(1) and close > open; { CloseD is a special key word that means yesterday's close }

If breakout then buy this bar at the close;

SetExitOnClose; {a keyword that closes the position at the end of the day's session }

Notice the brevity of the code and how simple it is in concept. This strategy is one of my best by the way. It works across multiple markets and timeframes.

I have literally dozens of such strategies, and developing more of them all the time in a continuous process that some people in the industry call the strategy factory. I like to refer to the process as more like being the owner of a major league baseball team, along with all it’s minor league teams that are used to primp up candidate players that might eventually be good enough to move up into the major league team when needed.

In other words, I have a set of starter players that have varied skills and all work well together, then I have a bunch of other players that are constantly being tested to see if they deserve a spot on the starting team. This too is a relatively simple concept, but depending upon the size of the team, and the size of the league, it can take a fair amount of discipline to keep the whole continuous improvement process going smoothly. But it’s a simple process, easy to understand.

So, that makes me the general owner, manager and coach of my trading team.


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Where Do You Get Trading Ideas?

Trading ideas are everywhere, you just have to look and recognize them. The best ideas are intuitive and easy to explain. A trading idea doesn’t have to be mind blowing to work, it only needs a sound premise. Cobbling together a strategy with a bunch of indicators and tweaking the money management isn’t an idea, even if it does produce a great equity curve after several optimizations, what you’ve done is created a strategy that works perfectly in the past, via curve fitting, but has little hope of working on markets it’s never seen.

Types of Trading Ideas

When you’ve been doing this long enough you start to catalog ideas, here’s some:

  • Trends based on some identifiable factor like the monetary policy of the Federal reserve. Trends are by far the most followed pattern.
  • You could exploit the relationship between two similar stocks or futures in a statistical arbitrage (pairs trade). Perhaps even an inter market relationship like the auto industry and platinum group metals (primary use is catalytic converters for gas powered engines), or soybean vs soy meal.
  • There are seasonal patterns, speaking of soy beans, in agriculture, heating oil; did you know 40% of heating oil price movement is influenced by supply-demand issues in the northeastern United States, and weather is a big factor. Airlines and resorts have seasonal patterns that are easy to sort out.
  • Selling premium up to a big announcement or earnings report, or buying volatility cheap after the earnings are announced and volatility has crashed.
  • How about turnaround Tuesday, or over the weekend patterns, or same time next month when funds redeem and add to their position.

I could go on, as there are an unlimited number of ideas out there that are exploitable and profitable, if it’s a sound premise and you see it, then figure out how to trade it. Until you put up the money, your ideas are just that, ethereal moments in time, but ain’t worth a dime.

The best way to get in tune with the market and the economy is to get yourself involved, trade geopolitical events, wait for zinger economic reports and fade the move, be early on the spot by monitoring juicy breaking news from web news sites like The Fly on the Wall. When you have your money on the line, working for you, your attention is attenuated and focused. This is when ideas are born.

Trading Ideas Matter

If you think you’ll do well in the trading business with your idea de jour, think again. Someday that idea isn’t going to work. A constant stream of ideas is what you need, in fact it is the very life blood of a successful trader to stay ahead of, and take advantage of opportunities in these constantly changing markets. So, how does a trader come up with new ideas, and not just rehash the tired old ones?

“I begin with an idea, then it becomes something else.” -Pablo Picasso

The big mistake traders make looking for ideas is looking in the same old tired places. The market is reflective of what’s happening in the world, so doesn’t it make sense to expand your notion of a trade to the real world? Maybe, maybe not, perhaps you have to jump to the non-real world. The point is, trade idea generation is exactly like any creative endeavor, there are lots of ways to do it, just google “how to generate ideas.” That’ll get you going.

Most creatives use a process for generating ideas, let’s apply that to trading.

Research is first, you should focus on a particular market, like Oil for example. Start by looking at key reports, such as the petroleum status report, which comes out every Wednesday, and the weekly Natural gas report on Thursdays…ask yourself what happens to the market after these reports, how about before the reports…do you see patterns. Study why investors care, perhaps that will lead to research around OPEC and what they are currently up to, both business wise and political.

Most events experience a half-life, that’s where the maximum intensity of the report will last a certain number of days, then fade away until the next report. Ask yourself, what’s the half life of oil inventory reports? Is there a reversion to the mean that’s noticeable, or are these the beginning of momentum plays. Look for secondary markets that confirm a change in price of crude, like gasoline, maybe there’s a trade there, or maybe just a confirming indicator. Are there seasonal influencers, or weather anomalies at play. How many oil rigs might be affected by a nasty tropical storm, what about just the fear of a big storm coming.

Do you see how each question leads to another?

Once you’ve identified a pattern, think about how you can turn it into a trade. What are the setups, the ranges in time and price, what’s the average duration of the trade, what can go wrong, what can intensify the effect…on and on, one idea begets the next.

Let’s Get Real

It’s all and good to throw hypotheticals at you, but how would you actually turn an idea into a real trade? Well, let’s do that with crude oil. Perhaps we can trade some behavior we noticed crude takes after an impactful report. Let’s first develop the strategy.

After a big move does crude oil tend to fall back in line or does it continue down a path. In other words, is this a reversion to the mean or momentum play? Will the path be a circle (reversion) or momentum (line). From my research, crude is definitely a momentum play, so we’ll want to look at the strategy as a trend follower, but relatively short in duration due to the weekly reports. So we’ll make the following assumptions:


  • 10-day loopback covers 2 weekly status reports and smoothes out noise.
  • A move of 4 to 5 standard deviations over 10 days is big enough to matter, and small enough to generate enough trades.
  • Giving price at least two days of pullback will allow us to stay in the trade, while providing the room to discover a trend.
  • Holding the trade for 20 days allows the strategy to catch bigger market moves

Here are the Rules

  • Enter Long when the close > close 10 days ago + 4 standard deviations
  • Enter Short when the close < close 10 days ago + 4 standard deviations
  • Reverse the trade after two days if there’s a new signal
  • Exit the trade after 20 days

Results and Next Steps

I have executed this trade 4 times so far this year with excellent results, all four trades were big winners. I did 2 trades last year that has similar setups, but this year’s trade represents a refinement. How did I refine the trade you might ask? I varied some of the assumptions by trying different loopback periods, and varying the standard deviation threshold. I also incorporated a confirming market, using Heating Oil and looked for divergences.

I noticed a profound inverse relationship between the difference in price between crude oil and heating oil, and the price of crude oil alone. I also noticed this same inverse relationship of the Crude-Heating pair versus the S&P 500. With major changes in the market usually having a 2-3 day lagging effect on my trade.

I will continue to study this trade, and see if there are further refinements that can be made, or other triggers that can help it, confirm it, or turn it into something completely different. That’s the nature of trade idea generation.

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How To Get Started AutoTrading

Don’t let anyone tell you that systems trading stocks or futures is easy. I’ve been speculating in systems trading for nearly 15 years. And it wasn’t until I serendipitously found my mentors, did I start seeing success. The following is what I learned, and I suspect it will work for you too.

Step 1. Have a Plan

When you embark on any project of sufficient complexity, build a house, start a business, run a campaign…you need a plan. The same is true for speculating in the stock and futures market. Your opponent has a plan…this is a competition, there are winners and there are losers. The winners plan well.

Step 2. Find a Strategy

This is the most difficult part of developing a trading system. Because most people think its about finding A super strategy that works. The reality is that it’s not about finding a killer strategy, it’s about developing a process for creating a continuous stream of adequate strategies.

Step 3. Curate, Check and Test

This is perhaps the most important step, because it’s the gate you open to running your money. You need to check and double check your work, strategies should be back tested, forward walked, and run in simulation mode against realtime data before you commit it to real money. If you can peer review it, that would be a very good thing to do as well.

Step 4. Execute Your Strategy

This is the big moment, when you pull the trigger and trade your strategy with real money. This is when all your planning comes together, you are now a fund manager. Don’t deviate from the plan, stick with it, at least for three to six month campaigns. Anything less then random chance could make a good strategy look bad.

Step 5. Monitor, Measure and Adjust

As soon as you start trading, it’s essential that you monitor your results. Your plan is not static, it’s about continuous improvement. Keep a trade log, develop relevant statistics, note all anomalies, then review the performance of your system on a periodic basis. Use what you have discovered as input to the next round, the next campaign.


Whether you know it or not, when you trade, it’s a business, and it requires the same kind of attention that any business that you intend to succeed at should have. These are the steps I have used and found success. It takes time to settle in and get everything running smoothly, but it will be worth it.

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Why Pairs Trading?

Trying to pick which way the market is heading is a fools game. Unless you have superior knowledge of future events, policies, economic data, scandals, or whatever might move the market in the future, then you are simply guessing which way the market will move. If you do have such knowledge, then you mnake get indicted for insider trading.

Basing your trading on indicators that evaluate historical price action is equally idiotic. It’s a flawed premise that you can predict the future based on things that happened in the past. The past has nothing to do with the future. Sure, you can ride an ethereal  momentum wave or draw imaginary lines on a chart and pretend the market will obey them, but this has been proven to be a losers game, as 90% of all traders who practice such bunk lose money.

A better way would be to develop a model that has a sound basis in a mathematical proof, something that is independent of market direction, and relies on the fundamental relationships of the assets you want to trade. This is where pairs trading can help.

Pairs trading is simply a strategy where you go long one security and simultaneously go short another. Of course there needs to be a good reason for choosing the pair, and which one you’ll go long or short. You should choose a pair of assets that have some close binding relationship, and look for a break in that relationship that you can take advantage of. Generally, you short the overperforming asset, and go long the under performing after they have diverged from their normal state by some significant degree, and you make money as they move back to their current preferred or mean state.

If you use statistical measures to determine when this divergence is significant enought to enter a trade, and again to determine when a regression back to the mean signals taking profit, then you are employing a type of pairs trading called statistical arbitrage.

So why is this a sound way to trade?

The premise is that like assets, things that share many things such as similar or identical markets, have deep ties that cannot be easily broken. These ties could be the sharing of resources, markets, materials, processes, people…all kinds of things. And ocassionally the companies behind the assets may experience temporary disruptions for any number of reasons, causing their valuation to fluctuate. But the fundamental relatioships don’t change, so any rift that might occur causing the relative price between the assts to diverge will likely settle down and move back closer to where it was before the disruption.

This is not just a feeling, there are ways to measure how highly correlated two assets are, and there are mathematical proofs that show when two like assets are highly correlated, there is a deterministic probablity that any divergence will result in a regression, that number is 75%. This statistical proof is an edge, but not the whole edge. There are methods you can employ that can drastically improve upon this situation. And that will be the primary topic of this blog.