Yes, I’d like to learn more! Please contact me to answer my questions.

 


 

 
Patrick Schwerdtfeger is a motivational speaker who can cover algorithmic stock market trading at your next business event. Contact us to check availability. The full transcript of the above video is included below.
 

Full Video Transcript:

 
Would you like to incorporate algorithmic trading in your investment strategy? These technologies historically have been reserved just for large banks and hedge funds, but today they’re increasingly available for individual traders like you and me. In this video presentation, we’re going to share with you six success factors that are absolutely essential when you’re evaluating algorithmic trading providers, and we’re going to go a step further and actually look at five actual algorithms that trade in concert with each other. We’re actually going to share the equity curves of each one of these algorithms including drawdowns and full financial results for you to evaluate as well.

But before we get into that, I want to take a look, a little bit of a broader look, at technology trends in general, technology trends which are reshaping our world, and probably there’s no better example than these two guys right here. The guy on the left, his name is Brian Acton and he graduated from university in 2009, started applying for jobs. He applied, among other places, at Facebook but Facebook turned him down. He wrote a tweet about it which said this: “Facebook turned me down. It was a great opportunity to connect with some fantastic people. Looking forward to life’s next adventure.” And what might that be? Well, he got together with a friend of his and started WhatsApp, which he built over the following five years and sold to none other than Facebook for a cool $19 billion.

Now, there are a bunch of different ways you can look at a transaction like this. One way is that at the time of the sale the company had 55 employees, so by that measure Facebook paid $345 million per employee. Another way to look at it is that at the time of the sale they had 450 million active monthly users. So by that measure, they paid $42 per user. But regardless how you look at a transaction like this, it’s an awful lot of money.

And maybe the most important thing to look at is that over the course of just five years, 55 employees built a piece of technology that engaged over 450 million people around the world. And that really speaks to the leverage in technology, and in fact, there are increasing amounts of leverage in our economy in general. So when you hear all the news stories on the news media outlets and on the Internet and so forth about the division between rich and poor, what they’re actually referring to is this leverage. There are some people in our economy who are figuring out how to leverage these various technologies and to grow their businesses, to become increasingly profitable, and meanwhile the vast majority of people are actually being leveraged by these same trends. So which side are you on? Clearly, the people who are doing well in our economy are figuring out how to take advantage of the leverage in the system.

And there’s leverage all over the place. Software is just one example of leverage. You can leverage software to be more profitable, to grow your business. The cloud, when people refer to cloud computing, the cloud is a form of leverage. You can leverage the cloud to become more profitable and to sustain new business models. Robotics is another form of leverage. In fact, this here is the Tesla factory in Fremont, California. The entire thing is automated. There are only a handful of people who work in this factory. The only reason it’s even possible to manufacture cars in California, here in the United States, is because they’re leveraging robotics to do so.

Well, algorithmic trading is just one more example of leverage. Algorithmic trading is a technology that allows you to take advantage of leverage in the system and to leverage it to become increasingly profitable and get more consistent returns. The future is already here; it just isn’t evenly distributed yet. This is one of my favorite quotes and it’s so true. These technologies already exist. There are people already taking advantage of these technologies but they’re few and far between. The vast majority of people aren’t even aware that these technologies are available for individual investors. In fact, we’ve all at one time or another seen a graphic that looks something like this. It’s referred to as the Law of Diffusion of Innovation. And it has the innovators and the early adopters on the left-hand side, and then in the large part of the hump here you have the early majority and then the late majority, and then finally the laggards. But when you look at something like automated trading and algorithmic trading, we are just getting started. We’re just here on the left-hand side. And if you’re watching this video, you are most likely an innovator or an early adopter because the vast majority of people, in fact the vast majority of financial advisers, are not actually even aware that these technologies are now available for individual investors.

Just to reassure you, there will be no sales pitch on this video. In fact, we don’t even have a way of taking payments, so rest assured there’s going to be no sales pitch. In fact, what we’re going to do is I’m going to tell you a little bit about my story so that you know who I am and why I’m doing this, and then we’re going to go straight into those six success factors that we mentioned before and as well we’re going to go into those five actual algorithms. At the end, we do have a special offer for the people who wait until the end, but that’s something for you to evaluate after this video is over.

So this is me, my name is Patrick, and I got interested in the stock market back in about year 2000. And at that time, I met a guy by the name of Ray—this is a picture of Ray here, I met him on a hiking trip—and he had done extraordinarily well trading stock in the stock market. And I was fascinated immediately. Of course I knew about the stock market, I wanted to figure it out, but I never knew anyone who was actively trading stock themselves. So I asked Ray to recommend some books that I could read to learn more about what it was he was doing and these are the four books that he recommended to me, and I bought them all that very day. I read every page of every one of these books and, in fact, I bought many, many more after that to learn about this new opportunity to trade stock in the stock market. These books are fantastic. I would recommend these books to anybody.

And I really became a student of the markets. I tried to figure it out. This is the Standard & Poor’s from 2000 to 2003. And I really started actively trading in 2001, and in a sense it was an easy time to make money in the market because the trend was so clearly down. I remember I made 19 trades in 2001 and 17 of them were short. I only traded long twice the whole year. And I actually did quite well. I did quite well. But it was frustrating and it kept me awake at night. It was stressful. I was taking large positions and using my margin to trade stock short. It was a stressful thing to do.

So I started looking at ETFs, which stands for exchange-traded funds—iShares is a provider of ETFs—and I looked at that as a way of diversifying and to reduce my risks somewhat. I moved my money over to TD Ameritrade. This is their think or swim platform. When I first got started I was trading on E*TRADE, but I moved it over here because it was a more sophisticated platform and I could take advantage of the indicators that I was learning so much about, and I became a student of technical analysis.

This here is a chart of the Standard & Poor’s 500. It’s a much more recent chart, so you may recognize the action here. This happened not too long ago. And this particular chart shows the five-day simple moving average and it also has the 50-day moving average and it also has the 200-day moving average. And see, the problem is that everybody’s following different lines. It’s like some people the five-day, some people follow the 50 or the 200, so at every one of these lines you have essentially a cluster of buy orders and a cluster of sell orders on either side of each one of these lines. And of course, there’s much more than just moving averages. There was a trend line here but then of course that one was broken, and so then there was a new trend line which wasn’t nearly as steep. And then there was this resistance up here that we were butting up against, and just a little bit below that it was this support line, so it was trading in this channel. And here’s another support line, and of course after this big drawdown here we have yet another trend line, and it’s difficult because everybody is watching different indicators and there are little clusters of buy orders and sell orders at every one of these lines, every one of these indicators, and it’s difficult to make money.

And I did make money in those early days but the reality is that 90% of traders lose money, and over a period of time I ended up in that 90%. I started out in the 10% but I now realize that that was basically beginner’s luck, and then as I got deeper into it it was really difficult to get consistent returns. I would get good returns for a while and I’d think I’d really figured it out, and then all of a sudden I would make a bunch of mistakes and lose a bunch of the money that I just made, and it was frustrating and so I started looking for other options.

And this is a market timing model. I actually have a lifetime membership. I purchased a lifetime membership to this particular model and it kicks out buy-sell signals in the stock market. This is a very long-term timing model, but there are others in the market as well and I looked at so many of these. I looked at a bunch on Portfolio 123, which is a platform where a number of different developers all had their own models that they had. You could subscribe to different models. And actually on two different occasions I bought a subscription to TimingCube, which is a fairly well-known timing model, and in fact what I did, I used their Turbo Model and what I did is I combined their buy-sell signals with leveraged ETFs. So ProShares is a company that provides leveraged ETFs. So in my case I was trading the TQQQ. That’s the NASDAQ-100 with triple leverage on the long side. So when the model kicked out a buy order, I would buy the TQQQ, and then when it issued a sell order I would immediately sell the TQQQ and then buy the SQQQ, which is the NASDAQ-100 with triple leverage on the short side. But of course, that caused problems as well because there’s a three-day settlement period that you have to abide by, so once you sell the TQQQ and buy the SQQQ, now you can’t make another trade for two days because the first one has to settle, and in some cases the model kicked out another buy order in a shorter period of time. So I was running up against one roadblock after another and really having a hard time finding a way to trade in the stock market and be profitable on a consistent basis. That was the problem, is being consistently profitable.

And that’s when I started looking at algorithmic trading. And I did a lot of research on it. I actually bought some books on Amazon. I read a bunch of books on this topic. I read dozens of articles and blog posts online about it to try and learn how it worked, and I even downloaded the white paper that TradeStation provides and I learned their script for writing these automated algorithmic trading platforms. So I really did a lot of work to try and understand what I should be looking for, and that’s when I came up with these six success factors. And if you’re doing research to look for an algorithmic trading platform for yourself, you have to look for these six factors. So let’s get started.

Success Factor #1: Multiple Algorithms

Factor number one, you have to have multiple algorithms. There are a lot of different providers out there who are selling algorithms, but they just have one algorithm. No one algorithm can be all things to all people. It can’t cater to every different market situation. Sometimes the market’s going up. Sometimes it’s going down. Sometimes it’s consolidating. You have to have a suite of algorithms that work together so that each individual algorithm can specialize in certain market conditions and they can get the returns during that time while other algorithms get the returns when the market conditions change. It’s very important that you find a provider that has multiple algorithms.

Success Factor #2: Uncorrelated Returns

And essentially correlated with that is you have to have uncorrelated returns. So like I said a second ago, sometimes the market is going to up, sometimes it’s going down, sometimes it’s consolidating or maybe it’s bottoming or maybe it’s topping. You have to have a program that can be profitable in all market conditions, which means that its profitability is uncorrelated to the market in general. That correlation coefficient is very, very important and I’m going to talk about that a little bit later on, but you have to find a program that’s uncorrelated with the market.

Success Factor #3: Extensive Back-Testing

Next up, this is very obvious, I’m sure most of you know this already, but you have to have a program that’s been extensively back-tested. Back-tested means you take the algorithms and you test them as far as back as you can possibly go depending on the asset class that you’re trading. The further the back-testing goes, the more reliable those results can be because you’ve seen how the algorithms perform under different market conditions.

Success Factor #4: Walk Forward Analysis

The back-testing is very important but it’s not as important as factor number four. Out of the six, this is the most important one. Guys, you have to write this stuff down because, if you’re doing the research later on, these six factors are critically important when you’re running your research and doing your analysis. The walk forward analysis looks at your entire data set and it splits it up into two different timeframes.

So let’s say, for example, that the data set is 2001 to 2015. Well, a walk forward analysis means that you split that timeframe into two, so let’s say you take 2001 to 2007 and then you optimize your algorithms for that time period, and then you use the algorithms, you essentially walk the algorithms forward into the second time period, which is 2007 to 2015. Then you go back and do it a second time where the split takes place in a different time. So let’s say it’s 2001 to 2005, you optimize your algorithms for that time period and then you run the algorithms from 2005 to 2015. And then you do it a third time, 2001 to let’s say 2011, and then you walk it forward from 2011 to 2015. And what you end up with at the end is a matrix of results and optimizations. So you have optimized it for different timeframes and seen the results that come from those optimizations, and by doing that you can find an overall optimization package which has the highest probability of continuing to work in the future because it’s been walked forward multiple times within your existing data set. If you are looking at a program that has not done extensive walk forward analysis, don’t look at that platform. This is critically important to see if your algorithm in future market conditions.

Success Factor #5: 100% Mechanical Execution

Factor number five, mechanical execution. Historically, these models were executed on TradeStation, for example, platforms like TradeStation, where the person, you as an investor, had the ability to turn the algorithms on or off at your own discretion. So if something crazy was happening on the news, let’s say North Korea was doing something crazy or Russia or who knows, some crazy news item, all of a sudden people would get scared and they would turn the algorithms off, and then lo and behold, perhaps the algorithm would have a great month on the short side during that particular time period so then they would turn the algorithms back on, and of course Murphy’s law says that that’s when you end up having a flat month or even a down month. Having mechanical execution takes that possibility out of the equation. We’re talking about having the algorithms executed by a computer without any human intervention, not you and not anyone at the place that’s hosting your account either. And that’s what allows the algorithms to do what they’ve been tested to do, which is provide returns under different market conditions. Mechanical execution allows you to have a hands-off approach and let the algorithms run on your behalf without you having to do anything along the way.

Success Factor #6: Transparent Company

And factor number six if you’re doing this type of research, only look for companies that are transparent with when they were established, where they’re located, who the developer is. It’s astonishing to me how many different people are out there trying to sell algorithms but they basically hide who they are and they don’t say where they’re located and they have some sort of a PO box and no phone number, and you can’t find out any information about the company. If you’re going to affiliate yourself with some company that’s selling algorithmic trading programs, make sure it’s a transparent company that you can investigate on your own and do the research and see what it is that they’re all about.

And it was precisely this research that led me inevitably to algorithmictrading.net, and this is a pretty interesting company. And I’m not an employee of theirs. I’m actually a 1099 contractor for them. I’ll tell you a little bit more about that in just a few seconds. But I came across this company and I did a lot of research on this company. I did a lot of research on many companies, but this was the one that really stood out and they are listed on the Better Business Bureau. They have an A rating there and a bunch of reviews. Also, there was quite an extensive review listed on tradingschools.org and they gave them also a very good review, which was incredibly rare. Most of their reviews were horrible but this one was very good. And the company also has a YouTube channel, and of course you can find all of these things on your own, but I dug into their YouTube channel and watched some of the videos, and that’s really what kind of convinced me that this is a great company and this is a company that I want to work with myself.

And the videos were all made by their primary developers, guy by the name of Richard…I’m going to tell you about him in just a second. And he’s a low-key guy. He’s kind of a soft-spoken guy. He’s an engineer. His name is Richard Metzger and this is a picture of him here. He’s as electrical engineer by education. He’s a logic designer. That’s what he did when he worked for some large companies, technology companies, HP and Intel and Qualcomm, with a particular emphasis in advanced mathematics. This guy writes algorithms. This is what he does and he does it very well.

So I was sold. I was convinced and I signed up myself. And you can see the date here. I pulled this from my Bank of America online banking platform. I signed up on May 28th, 2015. I paid $10,000 for my first licenses to trade these algorithms with my own money. So I’m a customer of theirs and, frankly, I’m a happy customer. It’s 100% automated execution. I don’t have to do a thing. It happens all on its own.

And every evening they automatically send me a PDF statement with all the activity that happened that day. So any trades that took place or if I have any open trades that are currently in the account, it tells me all that. Every single night I get these PDF statements that show up in my email box. And it’s been awesome actually because, see, I don’t have that obsession with the stock market the way I used to. I used to check all these websites and check the volume and what’s going on and advance-decline and all these different new sites and I was obsessed with it. And I find myself, now I’m probably saving an hour a day just because I’m not constantly checking the stock market and I’m letting the algorithms do what they do, and so far the returns have been fantastic. In fact, my best days were the days just recently when the stock market had really massive selloffs, like significant selloffs, and it was those three days in particular that were among the most profitable days for me. So I’ve been really happy and very excited and I’ve shared my excitement with my friends. I’ve actually had a number of my friends express interest and some of them, actually a couple of them, are now doing this program as well.

And so I ended up reaching out to Richard directly, and I contacted him and I said, “Look, I’d like to help you promote this. This is something that I’m a happy customer, I’m sold, I’m a believer in the product, and I would like to help spread the word.” Because you see, I’m a professional speaker. That’s what I do for a living. Historically, I’ve earned over 90% of my income in speaking fees. And I cover business and technology trends. That’s what I speak about. So this technology and what they’re doing here is exactly, it’s precisely in my wheelhouse. It makes a lot of sense to me. It’s something that I’ve studied and I speak about at business events and conferences all around the world. A few years ago I had an opportunity to speak at a TED event in Sacramento. I covered the topic of learned intuition, and of course you can find this very easily on YouTube if you wish. But the bottom line is that this is something that I’ve been looking for for years and I’m excited about it and I want to help spread the word, and so I asked Richard if I could do some webinars and create a video—like this is the video right here that you’re watching right now—and he agreed, and he said, “Sure, let’s do it.” And so I’ve put this together and I’m very happy to share my own experience and to tell others about what’s possible with algorithmic trading.

Back-Tested Results

So let’s look at some of those results right now. Now, if we’re going to share results, there are a number of disclosures and disclaimers that we have to provide. It’s very important when you’re sharing information like this. We have to do these disclaimers. So all of these disclaimers, the white copy here, it’s all on the website so you can read it in detail for yourself, but I’ve summarized each of five paragraphs. This is the first paragraph and basically it says, “Large potential risks. Don’t trade money you can’t afford to lose. Future performance is not guaranteed.”

Here’s paragraph number two. This is a long one but, if you summarize it, it says basically, “Results are based on back-testing the algorithms, not from live accounts. Live trading began in 2013.” So algorithmictrading.net, they’ve back-tested their algorithms as far back as you can go with back-testing futures contracts, which is 2001. So they’ve back-tested from 2001 but the company only started live trading in 2013. So keep that in mind.

Here’s paragraph number three, “Simulated trading does not account for some market conditions like lack of liquidity. Results may vary.” So what are they talking about? They’re talking about commissions and slippage, and slippage in particular. So when we’ve done the back-testing, and again, we’re going to show you the equity curves of all these algorithms just in a couple of minutes from now, and what we’ve done is we’ve incorporated an allowance for slippage and commissions. So in the case of the Standard & Poor’s futures contract, we did the commissions plus one tick, and for the NASDAQ futures we also did one tick plus the commissions. And then the treasury, the 10-year treasuries in the bond market, we did two ticks and the commissions. So it’s actually a pretty generous allowance, but the bottom line is you can’t guarantee slippage. It depends on the liquidity in the market, and liquidity changes all the time. So there’s no way to guarantee slippage. We’ve got a fairly generous allocation here but can’t guarantee slippage.

Number four, we have real statements posted from real customers on the website, and they are from real customers but they have not been audited by any sort of an accounting company, so individual results may vary. It’s important we have these disclosures.

And the fifth one—this is the one you’ve heard probably many times before, very important—we are not registered investment advisers. Richard is what the SEC refers to as a third-party developer. He is not an investment adviser. I am a professional speaker. That’s what I do for a living. I am not a professional, a registered investment adviser. Consult with your financial adviser before investing in this program or any other program.

And last but not least, here’s the big one, “The following financial results are presented for educational purposes only.” So we’re trying to be really careful with our disclosures to make sure we don’t break any rules.

Alright, we have to cover a couple more things as well. First, the minimum account size. When you’re trading one futures contract in each of five algorithms, well, there’s a minimum account size that you’re going to need in order to do that because the futures contracts cost a certain amount of money each, so potentially all five algorithms could possibly execute on the same day, so you have to have enough money to do that. And you also need to have a certain margin account, margin balance, if you’re going to hold those trades overnight, and some of these algorithms do trade possibly overnight. We have two options. You can either invest in the S&P 500 where you’re trading the ES—that’s the futures contract—or you can trade on the NASDAQ. It’s entirely your choice. The minimum account size for the Standard & Poor’s is 17,000 and for the NASDAQ it’s 15,000. That’s to trade one contract in each of five algorithms. And of course, as your account size grows, then you can scale up and add a second contract and a third and a fourth and a fifth, but the minimum is that for every contract you’re trading you have to have at least 17,000 or 15,000 in your account to trade that number of contracts.

Algorithm #1: Burst

Okay, algorithm number one is the burst algorithm. Let’s take a look at the equity curve. Here’s what it looks like. Pretty amazing. Now, it starts here at 15,000, and technically I could start much lower than that because a $15,000 account for the NASDAQ could trade all five algorithms simultaneously and we’re just looking at one algorithm in this particular equity curve, but I’ve started at 15,000 for each one of these and then I’ll show you how they all stack together once we’ve gone over each individual algorithm on its own. But the burst algorithm just on its own, this one contract, turns a $15,000 account to more than 50,000 between 2001 and 2015.

Now, let’s take a look at some of the features. This algorithm is most effective in sideways and slightly upward-drifting market conditions, but it does well as well as in the downward-moving markets. It’s looking at 120 minute candles, and again you can trade in either the Standard & Poor’s or the NASDAQ. If you look down here on the bottom, again, it’s trading 120 minute candles, so you can see when the entry points and it exits either when it’s stopped out or when the target is hit, and it can trade overnight in some cases.

Algorithm #2: Overnight Gap

Next up, algorithm number two. This is a fascinating algorithm. This is the overnight gap algorithm. Let’s take a look at it. This one performed even better, taking a $15,000 account and bringing it all the way up to over $60,000, just this one algorithm on its own. So you already start to see what happens when you stack all these together.

Let’s take a look at the features. This is an extremely effective algorithm during bull market conditions, but there are gap-ups as well during bear markets and it takes advantage of those as well. This thing trades on a 389-minute increment. It buys in one minute before the market close if the market conditions are right, and then it exits the next day if it’s either stopped out or if the target is hit, so obviously it can trade overnight as well.

Algorithm #3: Breakout

Algorithm number three is called the breakout algorithm. Let’s take a look. Here’s the equity curve and I want you to take a look at this right here. This is a two-year period where the algorithm traded sideways and drifted down. Two years. This is precisely why you need multiple algorithms. This can happen to any algorithm. It just depends on market conditions and sometimes the combination of the market condition and the algorithm, and the algorithm just doesn’t perform for a certain period of time. That’s exactly what happened here for two years, and then as well up here for one year it basically went sideways and drifted down. This is a perfect example of why you need multiple algorithms.

Let’s take a look at the features of this one. It’s particularly effective during down markets. Wait till you the next one, by the way, but this is a very low-risk trade. It gets in in the morning and it gets out at the close with very tight stops, so it does not trade overnight, which means you need a lower margin requirement for this one as well. You can see here at the bottom that it gets in at 9:50 a.m. if certain conditions are present, and then it comes out at the market close unless it’s stopped out before that.

Algorithm #4: Breakdown Short

Algorithm number four, this is the breakdown short. Listen, this is the most fascinating algorithm. I really want you to pay attention to this equity curve. Take a look at this. Here we have at the beginning, we have six years of sideways drifting down action, six years of nothing happening. And then, as soon as the market starts to crash, this algorithm exploded and had practically vertical and just caught the entire move, and then again up here later on, again we had four more years of sideways action. Four years of sideways action. This is why you need multiple algorithms. This particular algorithm had its best year in 2008 when the market was crashing and in fact the entire suite of five algorithms trading together, they also had their very best year in 2008 and this algorithm was leading the charge. So this is exactly why you need a suite of algorithms. No one algorithm is going to be able to catch all these different moves, but if you have a suite of multiple algorithms, then you can let this—this algorithm basically treads water and does nothing for most of the time, but then as soon as you have a market crash, the thing explodes and starts delivering the returns you’ve been waiting for. And just recently we’ve seen the stock market sell off, and yet again, this algorithm is starting to deliver when it’s chopping up here at the very end.

So let’s take a look at the key elements here. Obviously, this algorithm is really just designed exclusively for those bear market conditions when the market is crashing. It had its best year in 2008. Again, it gets in right in the morning, right close to the opening bell about an hour later, or rather, not even, 20 minutes later, and it gets out at the market close unless it’s stopped out first.

Algorithm #5: Push-Pull

Algorithm number five is the push pull. This is the workhorse of the entire program. If you’ve been keeping track of the numbers on the left-hand side, this one is the most extreme. It takes a $15,000 account and grew it to over $110,000 according to our back-tested data. Unbelievable. This is an extremely profitable algorithm, but even this algorithm had a three-year period here where it did almost nothing, sideways action, and then as well up here, this is another 18 months to two years of basically sideways action. Guys, this is the best algorithm in the whole suite. This is the most profitable algorithm in the whole package and, meanwhile, even this algorithm had sideways action where it did not perform. This is why you need to have multiple algorithms working in concert with each other.

Key features. This one is actually very profitable in almost all market conditions. It maybe does slightly better in downward-moving markets but it does well in other market conditions as well. It’s also looking at 120 minute candles. You can see the entry points here at the bottom and it gets stopped out. If it’s stopped out, that’s one thing, or if it hits its target, then it gets out there as well, and this is also an algorithm that can trade overnight.

Alright, so let’s stack them all together. This is astonishing. Here are all five algorithms stacked one on top of the other. Look at the results. It’s astonishing. So you’re starting with a $15,000 account in 2001 and if you held that the whole time, according to our back-tested data, by 2015 your account would be almost a quarter of a million dollars. Really astonishing the kind of leverage and the kind of returns that are possible here.

And even better, they’re trading futures contracts as you’ve heard, and that has some very important implications from a tax perspective. The U.S. Tax Code treats futures trading differently than trading regular securities under Section 1256, and what it says is that futures trading is taxed at 60% long-term, 40% short-term capital gains rates, which is much better than if you’re trading ETFs like I used to be, or even just individual stocks, when you’re taxed at the much higher short-term capital gains rates. In this case, you’re taxed in what they call a blended rate where it’s 60% long-term rates and 40% short-term rates. So if you look at the rates currently, and these are the highest rates, so obviously most people aren’t in the highest tax bracket because you have to be making a lot of money to be up in that high tax bracket, but even if you were at the highest tax bracket, the capital gains rate for long-term capital gains is 20% and the short-term capital gains rate is currently the highest bracket, is 39.6%. So if you take 60% and 40% of those respectively, the most you will ever pay in taxes for profits of futures trading is less than 28%, which is a significant tax advantage from investing just using the short-term capital gains rates, which is what I was doing myself.

Now, by the way, I actually have two different accounts that are trading these algorithms. One is an IRA where I obviously don’t have to worry about taxes at all, but the other is a personal trading account. So in that case, I’m paying a much lower tax rate than I would pay otherwise if I was trading regular ETFs or individual stocks.

Let’s look at the back-tested results. Since 2001, the average monthly return has been 8.71%, the average annual return has been 109%, but they vary dramatically, so let’s take a look at that next. The best year was 2008 when it returned 220% in one year. That’s not doubling your money. That’s tripling your money. If you have a 100% return, you’ve doubled your money. If you have a 200% return, you have tripled your money. In 2008, it more than tripled the account size. It’s astonishing. The worst year was 2005 where it had only a 3% return, so let’s take a look at that. Here’s 2005 right here. This is an unbelievably profitable and successful suite of algorithms, but even with all five working together it had a year where it basically went sideways, and that is the risk that you have to be aware of. So if you had a $100,000 account size and you had an average year considering our back-testing, you would have made 109,000, and so at the end of 12 months you would have had 209,000. And obviously you can continue to trade your algorithms into the future as long as you want, but just looking at the first 12 months you would have taken 100,000 and ended up with 209,000. If you had the best year that we had, your 100,000 would end up as 320,000 just 12 months later. And finally, if you had 100,000 in our worst year, 2005, then you would have had 103,000 by the end of the year. So again, we’re just trying to give you a really clear picture of the variance and where you’re likely to be. Based on our back-testing, you’re probably going to be anywhere from 3% to 220% over the course of 12 months.

Now, let’s look at the drawdowns. The worst drawdown we ever had in a single month was 23.2%. That happened in March 2002. So it’s only happened once at that level, but you need to be ready for a drawdown potentially in one month of, say, 25%. It has happened before, not quite 25 but close. The number of months where we had a drawdown of 20% or more was four. There were four months over the course of those 14 years where the drawdown was 20% or more. The number of drawdowns in one month of 10% or more were 13 months in the 14 years, so roughly one per year. Of course, four of those were the 20% drawdowns that I just mentioned. So, on 13 occasions. It’s amazing. Over the course of 14 years, there were only 13 months where we had a drawdown of 10% or more. So that gives you, again, an idea of what the worst-case scenario looks like based on our back-testing.

Again, past performance does not guarantee future results. We’re doing this to be compliant with the SEC and give you every disclaimer that we can. So we’re trying to be transparent and give you an idea of what you can expect. And if a program like this is maybe a good fit for you, maybe you’d like to try this with your own money, but we’re also trying to be very candid about the limitations of the system, the limitations of the back-testing and the performance results that we have been working towards. But this is an amazing set of results.

Now, one thing that’s very important to point out here is that during this entire 14-year period, we are still just trading one contract in each of five algorithms. So even on the far right-hand side of this chart, in 2015 when the account value was almost a quarter of a million dollars, we were still just trading one contract in each of five algorithms. So in that case, in the most recent case here where the account value is 250,000, we’re talking about 90% of the money is just sitting there in cash doing nothing at all. Well, of course if you want to, you could scale up, and every time your account value got up to another 15,000 or 17,000 you could add an additional contract and trade two contracts, and then three and four and five and six, and scale up along the way. That’s what I want to do myself. That’s what in fact I am doing, and I have bought enough contracts, enough licenses, to scale up as my accounts continue to grow.

So I wanted to show you what those results look like according to our back-testing and it is unbelievable what’s possible here. So what I’ve done is I haven’t scaled right at 15,000 increments or 17,000 increments; I gave a little bit of an extra margin and scaled up every time we got to an additional $20,000 increment. I scaled up with an additional contract. And as well, you see, if you continue to scale up indefinitely, by the end of the 14 years you would be trading in excess of 4000 contracts, and that’s not realistic because at that stage you would actually move the market. So it’s not realistic to trade 4000 contracts. On the Standard & Poor’s, you could probably trade 300 to 400 contracts and be okay, but what I have done for this chart that you’re looking at here is I’ve capped it at 100 contracts. So at $20,000 increments, you would get to 100 contracts when the account size reached $2,000,000, and it looks like that happened right here at the end of 2009, the beginning of 2010. So from that point on, it’s just 100 contracts. It’s not scaling up anymore. But even still, the equity here at the end if you did this, according to our back-testing, your account value starting from $15,000 at the end of 14 years would be in excess of $12,000,000.

Guys, this is what I am trying to do myself. This is why I’m in this program. I’m 44 years old, so I don’t have the time, frankly, to see regular returns guarantee a safe retirement for me and a comfortable retirement for me. I have 20 years left to get from where I’m at to where I want to be by the time I retire and this is the strategy that I’ve chosen, is these algorithms and scaling up at $20,000 increments. This is precisely what I plan to do with my own account.

And this is the leverage that I was referring to at the beginning. Guys, this leverage exists in our system and it is available, and very few people are aware of it and in fact a lot of people are afraid of it. A lot of people are afraid of the risks. They don’t fully understand the risks or even how these algorithms work and they’re afraid perhaps that they’re going to lose all of their money. They don’t understand how the whole system works and that’s why I wanted to share with you what the actual drawdowns look like over the course of 14 years—12 months in every single year, so we’ve got whatever that works out to be, over 150 months involved here—and the biggest drawdown we’ve ever had is 23.2% drawdown, and overall the average return in a given month was 8.7% and that average includes those periodic drawdowns. So the leverage is astonishing and the results are impressive.

So we do have a special offer. I told you that I would provide this for you earlier in the video. The regular price if you contacted the company, just on a regular basis they sell one contract for $5000, so the special offer here, they will sell five contracts for $15,000. So that’s obviously, in that case, you’re spending $3000 per contract as opposed to $5000 dollars per contract, and the special offer here is there’s a coupon code on the website where you’re watching this video, there’s a coupon code which will give you an additional 10% off. So you can get five contracts for just $13,500, which is an excellent deal. That’s less than $3000 per contract.

So again, I’ve been looking for a program like this for years. These are the back-tested results of these five algorithms traded in concert with each other. If you scale them as I mentioned before, the returns are unbelievable. Truthfully, the returns are pretty spectacular either way, but when you scale up the number of contracts as your account grows you really get some unbelievable returns. It’s taxed at a lower rate than you would get taxed if you’re trading regular securities. And of course, the fees that you pay for the licenses are tax-deductible as well. It does depend on your income, so you want to touch base with your account, but it is tax-deductible so of course there will be some tax savings associated with the $13,500 that you pay for your first five contracts to get started.

Again, the special offer, regular price is one contract for $5000. If you contact the company, that’s the deal that they’re going to offer you, and they will offer you the deal as well, five contracts for $15,000. But the coupon code which is on the website where you’re watching this video will give you an additional 10% off, so when you contact them…in fact, on the website there’s a contact form and, if you fill that out, that email’s going to come to me and I’m going to contact you myself to make sure that I answer your questions.

And again, I’ve gone through this process myself and I have two accounts right now. I have my trading account and I also have an IRA. If you have an IRA, by the way, and you’re trading futures contracts, you need to have what’s called a custodian. So we have to jump through a couple of extra hoops there to make sure that we get you set up. And again, I’ve done it myself, it’s not that much of a big deal, but there is the company and we have to get involved as a custodian of your IRA account so we can actually get the trading started. And I’d be happy to walk you through that process and get your questions answered as well.

So I’d like to thank you for taking the time to watch this video right through to the end. This is a program that I’m very excited about and I hope that we’ve done a good job of giving you the information you need to evaluate this for yourself. I encourage you to share this video with your loved one or your partner. Or, if you need somebody’s opinion about what we’re presenting here, we’ve done our best job here, our best effort here to try and provide a transparent and informative presentation of what this program is all about.

Thanks again for watching the video. Please fill out the contact form on the website. And I look forward to speaking with you on the other side. Thanks again and bye for now.
 


 
Patrick Schwerdtfeger is a keynote speaker who has spoken at business conferences in North America, South America, Europe, Africa, the Middle East and Asia.