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Frank Holmes - The Growth of ETF's, Development of Smart Beta and Machine Learning Investing
By Frank Holmes – Published in investing, Machine Learning, Smart Beta, on August 14, 2017
00:00:40 This morning is going to be one of those presentations, good. It's fantastic, if you have attention deficit disorder because every 20 seconds they're going to try to click through and wake you up on the changes are taking place in the capital markets. I was two weeks ago at the Salt Conference in Vegas. It's a predominantly alternative investments and hedge funds.
00:00:31 In this past week I was in New York. I was at a CEO Hedge Fund Presentation. At the same comment went to the big – I was shocked by it. The Bitcoin and all the crypto currencies and blockchain event in New York City and I was telling Jay that I was just shocked because it was -- Rick will remember at the Marquee Hotel, the Marriot. The show use do to be packed for the gold show. This is three times bigger.
00:01:00 I'm going to try to walk you through to understand how things are changing quickly. Regulations is a big part and how it moves and morphs capital. The hedge funds and the quant's and how they look at gold stocks is totally different in my trips going around visiting gold analyst on the sell side. What they think is working and selling there's no audience. The bulk of the money last year went into the GDX and GDXJ.
00:01:22 I would say something like $5 billion alone went to GDXJ and then recently they found that they were going to own more than 20 percent of 20 companies. They had to reposition and sell a bunch of juniors. The whole industry even if you had fantastic results last quarter it didn't matter. There was $3 billion dollars of headwind being sold into the marketplace. That provides you a good opportunity to understand why it's being sold down.
00:01:50 If you don't understand and you've become frustrated and you just blow your stock along with this sell side volume. That's how capital markets are switching and changing. Now we're going to start off with the Trump and dump Bot. This is happening in gold. This is happening and I've seen this and I'll articulate it more. Let's watch this little clip here.
00:02:08 NARRATOR: Any time a company mentions moving to Mexico or overseas or just doing something bad he's on it. He tweets the stock tanks. Tweet tank, tweet, tank, tweet, tank. Everyone's talking about how to make sense of all this. T3 thought the unpredictability of it created a real opportunity. Meet the Trump and dump automated trading platform. Trump and dump is a bot powered by a complex algorithm that helps us short stocks ahead of the market.
00:02:38 Here's how. Every time he tweets the bot analyzes the tweet to see if a publicly traded company is mentioned then the algorithm runs an instant sentiment analysis as a tweet in less than 20 milliseconds. It figures positive or negative. A negative tweet triggers the bot to short the stock. Like earlier this month his Toyota tweet immediately tank for stock.
00:03:02 The Trump and dump bot is out ahead in the market. It shorted the second after his tweet and as the stock tanked we closed our short. We made a profit, huge profit. Oh and we donated our profits here. Now when President Trump tweets we save a puppy. It's the Trump and dump automated trading platform, Twitter monitoring, sentiment analysis, complex algorithms, real-time stock trades. All fully automated, all in milliseconds and all for a good cause. From your friends at T3
00:03:36 Now this is happening in the gold space. It happens in seconds that they were able to take a look at a country's currency, the South Africa Ram versus the South Africa gold stocks versus the dollar and immediately a trade is being put on. It's predominate goes to the futures market and where most of the gold manipulation takes place is predominately through the futures market especially when there's a holiday in China
00:03:57 China is now the global gold price maker not the taker when it comes to gold. Recognizing how these capital markets change and form, in this past week there was a Wall Street Journal story regarding the quant's taking over. I mean we saw this article taking over Wall Street. No one here will Google it. Quant's overtaking Wall Street. Wall Street Journal, young kids never did anything in finance is a Russian immigrant wins a math competition and immediately his bid up and his base salary Rick is 700,000.
00:04:30 He's 21 years old. That's how this world is changing that they're looking for patterns. You take all this data and you try to take unconstructed data and then you look for a pattern. They can trade in a minute you know like basically a nanosecond. What they're looking at words and they're and they're analyzing such as Trump has three words he likes to say as a as a amplifying as adjectives is very, very, very and the other one is really, really.
00:05:41 The analysis of be done he says very, very, very three times as an analysis and he says really, really twice and most often he will say that it's because of a rich friend or an important friend is his evidence of why he you should listen to him. It's understanding that these quant's have turned around and done this data mining and it creates short-term volatility which can be to your favor if you understand why.
00:05:27 This is a fantastic book. I highly recommend it. It's how your brain can think quickly and think slowly, process has left and right brain. Daniel Kahneman as a noble Lord for his behavior of finance research. What's happening today? If information where the answer we'd all be billionaires and had perfect abs. It was a sarcastic part and in these presentations I've recently heard. What's happening to me is look at the data venture capitals have been spending you can see this number here.
00:06:00 It's almost a billion dollars two years ago going into artificial intelligence and machine learning. What is the difference I hope to walk you through. Machine learning is not about explicit programming processes. It's not like your bank account reconciles to a zero trial balance. It's more of a heuristic. When you were a kid and you learn to ride a bicycle. You didn't know the laws of physics to explain why you fell down.
00:06:25 You knew after time it's called the tacit knowledge you learn to balance yourself and 20 years later you get on a bicycle you can still ride your bicycle because your brain has been able to process and create the neurons based on heuristics. Now they're using this data and we all take it for granted when we look at GPS but GPS is all about using heuristics. It can't tell us exactly that Rick is nine feet away from me but he could turn around and say he is within 30 feet of me.
00:06:53 if they're able to track the GPS on your iPhones. It's recognized then they're looking at the stock market and data this way so your path to deeper insight is machine learning is used to build everything from voice recognition which you take for granted to cities, intelligent cars. It's a big part of your intuition. They are looking for as many case studies of great wins in the stock market and great disasters and they go back and analyze the words and all the press releases and because everything's gone to the Cloud the cost of processing stuff has falling 90 percent.
00:07:27 That's the big -- the advent of this breakout in artificial intelligence and Google's put a lot of money into it. It's because the capacity of looking at the data, unconstructed data and creating something constructive out of it. The ability to operate in complex systems without having to articulate the procedures like I said riding a bicycle so we operate. Most of us operate in a set of approximate rules known as heuristics. It's how we function.
00:07:55 Machine learning looks for patterns to produce approximation of rules. Machine learning requires a large, large, large set to produce strong intuition for complex system behaviors. The data is looking at every case study. To me is most fascinating that there is more research in America on energy in oil fields and gas fields and data than there is on health care. The most successful companies have been applying this technology and that's why fracking was able to explode is because America has been a leader in data analysis.
00:08:28 Now this is rolling into healthcare and why most of us will live to over 100 years old is being able to apply all this math to the data from all the food you eat, from your exercise et cetera. You think of this machine learning is designed to approximate your behaviors and come to imprecise but as you can see regarding words of the Trump bot and this is real that in it in 1/5 of a second it's able to go borrow from TD Waterhouse a stock and short.
00:09:01 The software they say is eating the world but machine learning is eating everything else. Now you take up for granted face recognition when you come through the airport or voice recognition and seismic imaging that are all using machine learning. This tacit knowledge along with inductive thinking and heuristics is where the world's changing in analyzing stocks words. It shocked me that 18 months ago Janet Yellen had to come out and make a press release, that the 250 page white paper had two words that were not supposed to be there and the market immediately sold off.
00:09:35 Now how could anyone here read a white paper 250 pages long, have a discussion and go out and buy the market. The market was rallying and one hour later she came out and made this change and immediately the market tanked. These machines are reading words and they're reading sentiment and they're noticing our patterns are changing quickly.
00:09:55 Amazon, Netflix, Azure, IBM, Watson, Google Predictions, they're all using this machine learning. We take a look. An example, how many here have a Amazon product? Anyone here? It's phenomenal isn't it? It's just shocking and prices just dropped again and the same thing how many here use their Siri with their iPhone? This is all machine learning and it's only advancing.
00:10:23 Right now it's only about 93 percent accurate and they believed the pattern is whenever you had this technology it goes through 95 percent the adoption process is now ubiquitous. It's everywhere in the world so forecasting of weather is improved dramatically with machine learning, prices and then we just saw patterns and recognitions. Also for hacking, it's all that machine learning is going in to prevent hacking and looking for patterns.
00:10:47 How does it work? You have a bunch of input data and you have algorithms that look for patterns. These patterns could only be three minutes and a lot of those high-frequency trading is actually behind it is really high frequency research that says this information is only good for eight minutes or eight hours or eight days. They call it the gamma, the information is as a very short shelf life.
00:11:15 It's important to recognize this is what creates a lot of the short-term volatility and it is very big in the resource sector. This is ANNI. It was called Advanced Neural Networking Investing. It's a rise of the Robo asset allocation. This is a process of driving down fees but basically it's able to take a look at your emotional temperament and everyone says oh I want to make 25 percent rate of return every year for the next 5 years. They won't say whether the volatility could be plus or minus 50 percent.
00:11:46 Well that's okay because I know I'm going to make 25 percent so then they start doing psychological profiles and ask how often you've gone from zero to 60 in three seconds. They ask you if you've done bungee jumping because you haven't done bungee jumping and you haven't done these other sort of personal experiences we can deal with volatility then you should not be taking those investments because you'll capitulate each time.
00:12:07 They now have to go through psychological profiles of you and ask the words and words and descriptions then they do patterns and they do grouping and then all of a sudden they'll say no you should not be doing this. You should be looking at this asset class. That's how it's morphing. If you take a look at a tree with no leaves on it's just like your neurons in your brain and so these seeing in all the sciences from biology evolution you're seeing every type of mathematical model on basic calculus and basic physics and basic biology and basic chemistry.
00:12:39 They're looking for with an exothermic and endothermic reaction. If a molecule, a positive and negative has a reaction does it give up energy or does it suck a way energy? How many of you been in to a room where you walk the way exhilarated because you felt the other person's energy and other times you've been in a room and you walk away with a headache because they took all your energy.
00:12:59 Well there are exothermic and endothermic reactions. They could turn around and take a look at data and that's how the world's changing. I think that this is what makes it exciting as long as you're aware of that. These are the classic examples of different types of neural networks. It's not one type of model with it. You have statistics, you have databases, you have all these type of powder recognition models that are out there today and they're upgrading every day.
00:13:23 Quant's are driving the gold stocks so in a week quickly see this Trump bot between gold the currency in the stock. We can show this when we take a look at gold has surged this year and why did not last year when gold surged 8.6 percent a lot of the gold stocks jumped on average 40 percent and the juniors advanced almost 100 percent. Why did that not happen this year because of the disruption of the GDX and GD XJ and also the currencies.
00:13:50 Last year the currencies were wiped out in emerging markets and this year they've had a rally. This is calculated and recalibrated every 15 minutes., every 15 minutes. For you and the whole purpose of this presentation for you to walk away that you're not intimidated by volatility it is your friend if you understand it and if you understand what's driving it. We can take this of Rubik's cube and look at production cash flow and reserves and relative value momentum and event-driven and look at words.
00:14:25 We've created a model that can process this faster than our competition. That's what we've done and you can go back and look at different types of words and press releases such as these types of words. This was basically a research that took almost a year to do. Now you can process this stuff in hours so if this word --- one of these words happens such as a project delay on average the stock would fall 20 percent.
00:00:40 It would take two weeks. Now it happens in two hours. Two hours, well who read it? How do they digest it? Where's it going? This is the world of the quant's This is a classic example that the GDX and GDXJ is $17 billion and the fun flows have not gone into Rick's open-ended funds. They're not going to ours even though we won all these awards again. In 2006 we had days of 50 million a day coming in.
00:15:20 We're lucky we get $500,000 a day coming in. that's how the market has shifted and everyone wants to be able to trade the GDX and GDXJ. Do you know what the dollar value of the triple bear and bull and the GDX and GDXJ trade every day? Does anyone know here? $3.5 billion every day, short, long, long, short. Who's in that space predominately? Not you. Not the average gold investor. It's the quant's.
00:15:48 It's recognizing they create this distortion in flows just the same as the ETF structure has created distortion in fund flows. When you look at the GDX and GDXJ it only cares about market cap. It doesn't care if this is a good property or a bad property, if this is good management or bad management, this is a safe country or an unsafe country or jurisdiction. It doesn't care. It's agnostic. It's just market capital and liquidity and so I found that a lot of these junior mining producers have become lazy.
00:16:40 They'd figure they'll get the money through the stocks will up because of GDXJ and they don't have to talk to you the investors. They've lost that sort of retail component that's so significant because in ecology of the ocean you just want to have whales like ourselves or institutional buyers you want to have minnows and you want to have tunas and you want to have -- sharks are out there. You'll want to have a complete ecology and what's happened now is this ecology has been morphed for many reasons.
00:16:49 Here's another example of looking quant data. This is looking at the massive dilution of the GDXJ underlying holdings. If we go back in the past four years you can see that the GDXJ has issuing shares at a faster rate than the price of gold has gone up. You've seen on a whole a 110 percent dilution so the either the price of gold goes up 110 percent or these stocks fall on a relative basis.
00:17:11 The quant's process this immediately. They make a decision that's immediate and they look for factors or everything's on a per share basis. They don't give a who about how big your production is or your reserves are. They care about your reserves per share. They care about your price to book value per share and it shows up in stock performance. This is a classic example of looking at the difference of you taking the top 10 holdings and comparing it how you did with.
00:17:39 This is another example we took the top 10 gold stocks with the highest revenue per share so the price of gold went up last year 8.6 percent. What about the top 10 gold that protected the value over 4 years not just one quarter. Those stocks you can see here doubled over four years but what are the GDXJ do? It fell 50 percent. How many here have experienced 50 percent declines in their portfolio in gold stocks in the past four years? Nobody?
00:18:06 Come on. I know it's Sunday morning. I'm not the Catholic priest. You don't have to do the Mea Culpa with me. It's the reality. The reality so that data says if a CEO of a mining company destroys the value on a per share basis you don't find more reserves of that cash or they don't increase the production then their stocks get destroyed. In the mutual fund world we have to have a minimum 21 names so it's hard to find so as soon as we start taking our data to go to 21, 25, 30 names it becomes very difficult to actually get great performance.
00:18:38 You're forced with this diversification rule but if you're an individual investor, a concentrated portfolio focusing like this you can have great alpha. You can do spectacularly well. This is looking at the 10 precious metal stocks based on the highest revenue per share and you can see Northern Star in Australia, some of the best performing gold stocks have been in Australia and they've had phenomenal runs phenomenal.
00:19:01 There's only two in the top 10 are Canadian then I take a look another factor is SGA, the revenue. What's your expenses to your revenue? The biggest significant factor that helps here is the currency so if you're producing in South Africa and the currency falls by 50 percent and gold is flat you're automatically going to have lower SGA revenue. Those stocks double. They went up 160 percent.
00:19:23 Why did they do that? I know 2001 were a number one gold fund. We were predominately in South Africa because the currency had half. This sort of thought process is so much more rapid now in the world of Quant analysis. Just look at revenue to SGA and just that we rebalance these top 10 names every quarter and as you can see in the first quarter or take a look at this period this is over 4 years that you have – what? 13 percent categories losing 8.6 percent a year.
00:19:56 Another way the Quants look at and rebalance is this is looking at all these different factors like cash flow return and invested capital. It's a key Warren Buffett tenet and you can see you still owe perform GDXJ and the GDX by a wide, wide margin if you focus on those key factors on a per share basis. The royalty companies have done spectacularly well because they have the highest revenue per employee and we've noticed that when we look at technology companies, we look outside of that those companies in any industry category that had the highest revenue per share attract more money.
00:20:25 The other thing that's interesting is that they also have rising price to book value. The quant's don't care about any of these. They don't care about any of these. Every gold stock analyst, what did they sell you Rick? Cheap NAV, right? This is a cheap relative NAV. They don't care. The fund poles are going to look for are you increasing your price to book in a relative basis?
00:20:47 This is a classic example of looking at the GDXJ and the dilution as of compared to the royalty companies and when the royalty companies go and dilute they immediately by something that has immediate cash flow. That's another reason why they outperform in a dramatic way. What I'm trying to show you here you can get all of these slides is that is the system has changed and the factors have changed and everything is about relative value on a per share basis.
00:21:15 You as investors have to ask the question what is these junior companies or producers to protect the value on a per share basis and no stocks in a rising gold market will out perform. This is a class example, showing a book value with the four years. You can see the royalty company's price the book has been rising whereas you see the other gold producers have been falling.
00:21:35 These are royalty companies showing superior stability, Franco Nevada, Royal Gold. Now we take a look at project rests and what we found is that most of these companies have NAV's that are saying well it's only 5 percent discount rate. This project that they say is that say a billion dollars. It's worth a $1 billion but if you had a 5 percent discount rates were 600 million. If you use a 15 percent discount rate it's only worth 250 million.
00:22:40 They wouldn't raise $600 million for something that really should be discounted a 15 percent rate and guess how much they wrote off? 600 minus $250 million dollars. That's what they wrote off. It's the Quant world doesn't care about discount rates. What's driving the price of gold? this is driving it. It's that love and fear trade and its predominantly the monetary policy and there's no change.
00:22:25 It all has to do with negative real interest rates. I repeat this over and over and over and Kitco has on their website to show you is that the dollar or the prices slight amount of gold is driving the price of gold. In the U.S. terms it is all negative interest rates. What's the number one thing that drives the Canadian dollar? Oil prices. It's a number one thing that drives through the Russian Ruble and the Norwegian kroner? It's oil prices.
00:22:48 It's recognizing what drives it. I just do this comparison a regular basis to show investors that when negative -- when we had negative rates of 300 basis points gold hit 1900 then they went plus 200 basis points and then went back. What is negative interest rates? Every month it gets recalibrated with a CPI number .
00:23:06 What is the government willing to attract pay you to buy my five or 10 your government bond? I duct the CPI number which comes out every month and if that return is negative the price of gold is rising. If that return is positive the price of gold is falling. That science shows up over and over and over.
00:23:23 Where are we in now? We're in a cyclical cycle for gold. Historically gold bottoms in at the beginning of Ramadan and we get a run until Chinese New Year. They'll be many corrections for so stay tuned for this. Understand that the volatility in the capital markets are your opportunity Understand that a lot of volatility is triggered by high-speed Quant research.
00:23:45 Now you know what the factors are looking for and I wish you all buckets of happy investing and I'll be speaking later today more detail about ETFs and how smart beta is applying some of this technology to look at investments. Thank you all for your patience and coming early in the morning.
Frank Holmes
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