 The following is a presentation of TFNN Trading Hour with your host David White. Call now toll-free at 1-877-927-6648 internationally at 727-445-1044. Now David White. And welcome all to another excellent edition of the Power Trading Hour with me, your unbelievable and squeezibly soft host as always. We'd like to come to you at this time. Did you hear that? It seemed awful quiet on this side. Maybe we can get that to figure out why that is. Options, system, okay. Lines are there. Oh no. Damn. Nope. Whatever. Hopefully it sounded okay. A little awkward. Anyway, I don't know why. Did everybody hear that? Okay. We'll have to find out later. Anyway, they were up 26 and a half points on the S&P cash. Dow's up 152. NASDAQ's up 92. Russell 2000 up 18 points. Crude oil up 12 cents. When we look to some of the other commodities, gold it's up 80 cents. Over up eight and a half cents. So half a percent move in that, but it tends to move a lot more than most. So anyway, as we start the show off, is there anything that I would really want to say? We talked about far too many shorts on Friday. I worry about a market when the shorts quit shorting because generally in the past, which is all we have to go by. When everybody quits shorting, that's generally a fairly good sign that we probably don't have any grist for the mill to go higher. We saw some extraordinary shorting on Friday. And in fact, can I, is that right? Let me see. See if this works. Okay. So here's the put call ratio for Friday. And we'll zoom in there a little bit. But since 1st of October, when the Fed really went hog wild over everything, we continue to see that the equity put call ratio pretty benign at about somewhere around three points or 33 percent, sometimes as a high as 42 percent. But it's pretty much in that range. It's not been significant. That's this blue line on this chart. The out of the money, which is the out of the money VIX options, those are the ones that you basically set the price of the VIX. That is how much premium is in those put call ratios went right back up to highs that we saw basically at the end of November before we rallied once again. So I think there's a fairly good indication, of course, I look at the daily short numbers for the actual equities and I've got a better look, but this probably the put call ratio from the CBOE is probably the best way of looking at this. Now I do it a little differently. The put call ratio could never be in my calculations, could never be more than 100 percent. A lot of people, and the one of the reasons I do that is that in any kind of formula or model, you can really, or almost all the models, we'll talk about other stuff later. Pretty much it needs to be scaled from a zero to a one. You don't want anything less than zero. You don't want anything more than one. In fact, for the most part, you don't want something anything less than 0.000001, right? You don't want a zero. So you've got to scale these things, of course, divide by zero is the quickest way to blow up a program because you can't divide by zero. And you won't be saved by zero, even though they had that horrible song in the 80s. But every time we've had these, it's led to a higher move in the market. Now, maybe we got it all out of our system today. I don't think so. I suspect that as soon as we got to around 3,200 on the, or when we get to 3,200 on the S&P cash, we're going to see nothing but a torrent of people that have been wrong the last four times they've gone after this market and they're going to add to it as a fifth. It reminds me of the joke that I cannot tell, but I think everybody has heard. And that is the one of the hunter that goes hunting for the bear. He comes back several times. Finally, the bear says, I guess you really don't come here to hunt, do you? And that's the question I have is, when do these guys give up? And it's almost always a great signal to short. We've seen no sign yet that the shorts are not ready to die on this ill literally once again. So anyway, beware shorts. They are always the weakest of the hands. And as soon as everybody gets short, it seems like the Fed is more than willing to use them for grist for the middle to go a little bit higher. Now, of course, we normally talk about, if I can find it here, talk about volume, so let's get to that. I've just got a bunch of stuff on my screen today, okay. Not as good as Friday, but I'm not surprised. We had about 4.7 billion shares on the CBOE consolidated tape. If you want to link to this page, and you're new to TFNN and my show, all you have to do is email me at pathpath at tfnn.com, I'll be glad to send it to you. We have about 1.45 billion shares as we started the show. Like I said, Friday about 4.7. We still didn't have enough volume when they came after the market. I think we ended up with like 7.5 billion shares on Friday. We've hit this high several times, and eventually you can chew through a high. We're going to look at some charts today. We've got a couple of stocks that have actually broken out probably today if they do close higher. The market, you can make a fairly decent case that after the third time back up at these levels that we do have a high that is higher than the previous high. The volume, other than one time before, has been significantly higher, at least of the previous time. It's not the first time, which was kind of a blow off top. I don't see anything changing. I don't see the end of the world. We were talking earlier with Basil Chapman, bringing it up on his show earlier at 9 a.m. And we'll talk a little about it a little bit more, but generally you want a lot of people that are all euphoric. We have about half and half people that believe the end of the world is nigh, the other people that they're just along for the ride as the market continues to go higher. We'll be back in a minute. If you're not currently using the TAS Profile Scanner when looking at setting up your trading opportunities, then your arsenal is short a mighty weapon. The TAS Profile Scanner is a standalone piece of software that instantly filters over 2,500 global financial markets such as stocks, ETFs, commodity futures and forex. Excited by Steve Dahl, TAS understands that in today's technological world, the use of top flight software applications and technical analysis expertise is essential to successful trading in today's market. You also gain access to the webinar that Steve Dahl and Tom O'Brien just hosted, the best way to use the TAS Profile Scanner to profit. This webinar archive is available for all subscribers immediately upon signing up. 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Details on The Tiger's Den are on the front page of TFNN.com. TFNN has launched our brand new website. You can still visit us at the same TFNN.com URL, but when you do you'll see a new and improved homepage with a much simpler navigation whether you're watching Tiger TV live in high definition or just accessing your newsletter subscriptions. We even have new pricing in six months and yearly options. Check out the new TFNN.com now and experience all the upgrades. TFNN.com educating investors. Now toll free at 1-877-927-6648 internationally at 727-873-7618. There's nothing but history repeating and on this day in 1773 in Boston Harbor, a group of Massachusetts colonists disguised as Mohawk Indians and I guess in 1973 do they have the Halloween shop down the street where you can get all the different accoutrements that you need? Did they actually give themselves Mohawks? Did they make a fake Mohawk? I always wonder. Anyway, the three British tea ships and dump 342 chests of tea into the harbor, the midnight raid popularly known as the Boston Tea Party, was in protest at British Parliament's Tea Act of 1970, 1773, a bill designed to save the faltering East India Company by greatly lowering its tea tax and granting it a virtual monopoly on the American tea trade. The low tax allowed the East India Company to undercut even tea smuggling into the Americas by Dutch traders and many colonists viewed the act as another example of taxation tyranny. And of course, I'm wondering if there are any Boston people left that would actually do it do this today? I don't know. They seem to all talk about having higher taxes until you actually give them higher taxes. We need a little bit more of that patriot spirit out there, Mr. Boston. But on this day in 1773, flames, a little ember of freedom coming to the colonies and throwing off the shackles of Mother England. Okay. What else do we have going on today? Oh, we were talking about, we're talking about, I think about shorting, was that what we were talking about? Oh, we were talking about Basil Show. And man, I hate it when I lose my train of thought and I'm standing on the tracks with a big train coming. There was a, I didn't bring it up too much, but there's an old parable and it may be apocryphal and maybe a story made up after it happened. But JFK's dad, Joe Kennedy, a notorious bootlegger and murderer, I always wonder if there's a little bit of sins of the father and what happened to all the sons. But he in 19, I think in 1929 said that he sold all his shares of stock and of course he was very rich at the time. He had all that monster, alcohol running money and had put it into the stock market and watched it grow. But his shoe shine guy that was down the street from where they lived in New York, or was it in Boston? Who knows? Anyway, he started telling him about what shares that he was getting into. And old Joe said that that was the sign of a top and he started selling shares that day in 1929 before the crash. This may have been late summer, but he did start selling shares. So that isn't that. The question is whether that truly happened or not. Of course, you never really know. A lot of people have a lot of stories on Wall Street. What it does say though is something that I've noticed and I think everybody else has and that is when everybody's screaming, then you have a pretty good sign of a top. When everybody's talking about buying and selling shares, you got a pretty good thing. When everybody's telling you the end of the world is here, you pretty much have a good low. But Basil was talking about talking to a group that he was with a few weeks ago and literally nobody was coming up with people saying you should buy this or you should buy that. And why we can't use that as an individual data point. We can kind of look at it and put it together with other things that we have. This is kind of more like a court case where it's the ponderance of the evidence that says whether or not people are euphoric. But when you don't hear them screaming about highs, then generally that's not a euphoric high. Now if I was to watch CNBC as I did at one time when I didn't like money as much as I did today. The thought is that you could get maybe something from those guys when they're all screaming at the highs. But as long as this continues, as long as I don't see a lot of people not shorting at the highs, I continue to think that this is a market that has not seen a high. If we see a month of people screaming and telling everybody to buy stocks and put everything in the stock market and haunt their house, I'll really think about a long term high. I just have not seen it, haven't heard it. I'm pretty good about reading the blogs about what does happen on financial infotainment TV. I again have not seen that much of it politically. If the elections for 2020 were held today, it actually looks fairly good for Wall Street. So I do not see anything that would say otherwise. There isn't a lot of belief right now that we'd have a anti-capitalist, probably the best way to put it, in the White House and or both houses under one rule. Democrats tend to really like gridlock for the most part, but us guys out in the unwashed masses, smelly Walmart shoppers as one executive in the Justice Department put us, we could do without it. But what else can you say? Okay, as we look into what is going on today, I got a lot of charts, did want to get into one, answer one question and to do, was that better, got a type here, had a question about what's going on in my machine learning work. But the question is just what is it? Kind of look at this thing as kind of a black hole, doesn't really say what is going on with it. But I thought I'd give a small demonstration of what happens because this little thing that I'm showing on right now is all the code, which is it fit on maybe one page, maybe one and a quarter pages with a lot of white space, you could get rid of that, fix it in there and a lot of comments out, it fit on one page. But this is the conical example as we go to the break, when we come back, we'll show what this is and then I'll be able to answer the question about why we haven't seen such huge results at the retail level for machine learning. We'll be back in a minute. The path of least resistance is David White's daily trading newsletter and if you're looking for active trading ideas, then now is a perfect time for a 30 day free trial to this powerful daily trading advisory service. David uses his years of trading experience to offer his subscribers his trading ideas each morning in his path of least resistance newsletter. 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Don't miss out on this incredible new piece of software. Get your copy of the art of timing the trade charts today by visiting TFNN dot com. This segment is brought to you by think or swim. For more information, just click the think or swim banner on the front page of TFNN dot com. Anyway, I had a question about why we haven't seen more success with machine learning in the stock market. And there's several answers to that. Anybody that's got my newsletter probably seen the results of buying lows over the last few years. And I've got something that uses kind of the wisdom of crowds that has been a huge boon for confidence in buying lows. There's nothing like having somebody have a loaded pistol aimed at your heart to quicken the mind when buying lows or trying to sell highs. The lows have been fairly accurate or forever in history. The highs have been somewhat tough to find. Although I'm making a lot of success in that and machine learning. But there are several answers to that. One, the ability to spend the kind of money that would be necessary in the previously in machine learning for an individual like me, even though I have domain knowledge in two things, programming and the stock market. You need somebody kind of like that. And again, a lot of the stuff is fairly new. It hadn't been around for 20 years. In fact, some of the well, I'm going to show you this, which is kind of interesting because it basically came along right when I started learning and trying to find out everything I need to do to start trying to use machine learning in software. But this is an example. In fact, I'll just run it while I'm talking about it of machine learning program. This thing uses the MNIST database, which is 60,000 examples of numbers in handwriting. And when I started, I think it took about eight to 10 minutes and probably more like 10 minutes in 2015 to actually have a program learn all of those handwritten digits and be able to what say you wanted to sort the mail at the post office. I'm going to run the program right now while we're on the air. Did I do it? Come on. Did I do it? PY. There we go. This is using TensorFlow from Google. They were the first to really work on handwriting analysis for things like zip codes and that kind of stuff. Although it had been around since the 90s, they were working at much better, trying to find much better ways of doing it. So I can be, in fact, if you look here, it may be a little tough. This is about 98 percent accurate. And it took about 11 seconds to go through 60,000 handwritten examples of digits. And then it went through 10,000 and predicted which ones that were right and wrong. And it was 98 percent correct. We could have played with this a lot more, got it up. They've got it up to about 99.8 percent correct. That's why most of the mail flies through anymore. But that I can do this at home. Why I'm on the air tells you a great deal and 11 seconds compared to the 10 minutes in the late 2015. The computers are now getting fairly decent at the kind of computational powers you need. This acceleration was made possible by NVIDIA cards. I've told a story before, but NVIDIA has been fairly good about supporting mathematical operations with their GPU cards or video display cards and using them for something that they were not intended for, not playing video games or showing some pretty pictures on the screen, but actually using each one of those GPUs, immense computing power for parallel operations. And it's all about how big a byte you can take at one time. The amount of memory that I have now on my cards is about eight gigabytes. That's compared to about two gigabytes when I started. So the amount of memory that you can put it, these things, how big a byte you can take at one time is a big issue. But it is there are a couple of things that are standing in the way of these things being widely adapted. First of all, you do need somebody that has domain knowledge in both and understanding in both programming. And, of course, in trading. The one of the problems is a lot of the stuff that is from machine learning, I'm going to say 98 percent of the stuff from machine learning is from PhDs, writing theses in colleges. And these folks are pretty much expected to use Linux or Unix style boxes because there's no licensing fee and they can share between all the people in that scientific community for machine learning. The other thing is that they've decided to do all the early work on a language called Python. That language is pretty much used by junior programmers and has a huge problem in scaling to enterprise applications. It's used a great deal on websites, but those things are fairly limited in the scope that it does not work very well to those larger programs. Generally, when you find people in the Fortune 500 companies, they'll use maybe Java or C sharp for Microsoft or a handful of other languages that are more adapted for writing stable programs. So you've got a lot of people that had a lot of experience. They picked this program, which is now or this language that's now just kind of become popular, but it's got its own problems. One, nobody really controls it. So it's kind of like hurting cats. And just to get what I showed you here up and running in 2015 took about eight hours. It was an example ready to go. And it still took eight hours. It's one of these things where even to get something that you know that works is horrifically bad. And that will probably continue for a while. I think the big next change in machine learning for stock markets is someone writing in a better language that's easier to work with. That's part of it. The other part is that almost everything because it's written in Python is a black box. It's very hard to debug. So you don't really see what's going on inside of it. In fact, some of the bigger discoveries or problems that machine learning has busted this year have let go have been on special versions of the software from Google that actually allows you to peek in under the hood while these things are running. But a lot of problems still exist. But I'm on the yeah, I got pillows figured out now I'm working on the highs and I actually have fairly decent grasp on those. I may be able to get a much better model before I come back in the early January. Anyway, just a little thoughts. Give me call 877-97-6648. If you're in the CD market and looking for a secure investment, the Tiger First mortgage program may work for you. 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And a question. Okay, who's this Pat asks what language are you writing in? It depends on what you're talking about. I traditionally write in C-Sharp and have for the last 18 years. It's kind of the version of Microsoft's version of Java from Oracle. Oracle kind of screwed everybody over. So I don't think there's a whole lot of people writing in Java anymore. They've all kind of, it's fairly easy to turn everything over to Microsoft and C-Sharp and the .NET community. So for the most part, the question I'm bringing or the statement I'm bringing up is that you can't write a lot of these machine learning programs in whatever you've learned before. You pretty much have to use Python. And why it's free, that's probably the best thing you can say about it, that it has nobody really running roughshod over what happens in the future. It becomes incredibly problematic. The tools are nowhere good as what you would get from a high level language from Apple or Microsoft. So there's a lot of hurdles and since all this stuff is pretty much in the public domain, there isn't a lot of money to be made. So you don't find people like Apple and Microsoft chasing after this stuff. They kind of leave Google and they're kind of the big guys. And a few people like Amazon that write stuff for themselves and make it publicly available. Of course Google's the real leader in that with a thing called TensorFlow, which everything that I just ran here is written for. But these are packages that have to be written to with Python. And again, Python has all its issues and you get kind of spoiled by Microsoft or some of the things like Swift from Apple. I'm not a Swift programmer, but a lot of those things just solve so many issues and take care of so many potential issues that you have that crop up in Python. Python is kind of like the Skunkworks making very sophisticated jets that they're going to make 10 of in the whole world or 20 of, right? Like a U2 or SR71. They get it going, but it's not pretty and it's not something that you want to try to mass produce and also have a lot of software built on. They make do. It's just not an ideal world. Eventually, some will come up with something that's really built as a 21st century language. But what else can you say? A little, probably too deep in the weeds for most people, but we'll get moving on here. Let me see. We've got a lot of charts I want to look at. American Eagle Outfitters. We might be finding some kind of low back to the sneezing. We'll answer that. Okay. Since I'll get into AEO in a second. So your holy grail is still further down the road. It may be as far down the road as the 1st of January. I'm testing all the stuff for the highs right now and it's very promising. But since I've had, it's kind of like the light bulb, they found a thousand ways not to make one. All they needed to do is find one way to make one. But I've got something that shows a lot of results that I'll be testing over Christmas, but I think it's there. Before I actually put anything into production or in the newsletter, I have one of my subscribers who's a statistician at a college in Tampa and he reviews it all. So I didn't make, he didn't find any glaring mistakes that would tell me that I'm doing something wrong. So I work at it fairly hard, make my models, and then hand him the data. He goes back through it just to make sure. That's probably why the lows work so well is that I had somebody that could go back and check all my work. He found, like I said, I think about 30 times, he found mistakes each time the program gets a little bit better. And we may have the same kind of iterate, iterative issue, but I think I got something that works. So it's basically refining it enough to go into production with it. But anybody that wants to get tiger dollars now, check out my newsletter. Every day in the newsletter, I've got about 20, five sectors and ETFs that have those sector oscillators in there. And you can see how well they pick out the lows and have for the last 20 years. So if you're trying to buy the lows and sell the highs, I have a lot of things that kind of work that I know that have worked for me in the past, but no automated way of buying highs. And as we talked about earlier, trying to sell the high has been problematic at best this year. Anyway, American Eagle Outfitters, got a little doji out here today, but it doesn't look that bad. You've got the low back here on September 4th, $13.53, 26 million shares. It got back into that four days ago on December 11th, with not quite half, but fairly close to half that volume. You got a little bounce out here. You probably get one more low and this thing goes sideways. But some of these retailers might be finding lows out here. Either the silver bullet or the holy grail. That's what everybody's talked about finding. And you won't find anything that works 100% of the time, but you might find something that works 70% of the time, and that makes all the difference in the world. And certainly when you find the right stocks, certainly makes a ton of difference out there. Okay, what else do I have? It's probably pretty close. Okay. Akamai. This did break out. It did break out with a sign of strength above the $86 level. That original first eye of 2019 came into play. You went above it on, what is it, 31st of July. You had some nice volume. You pulled back into the trading range, but the energy hasn't been all that much. You've got a valid breakout, but below the previous high, you popped back above it today. So that would be anything back above 86, 19 would suggest that you're probably going to go back up to 93 and then 100. So this kind of setting up for an ABC higher, but that may take into January. We'll be back in a minute. I'm certain you are or strive to be one of the best of the best at everything you do in life. It's the most common trait that we tigers and tigers share. If you're looking to become the best of the best when it comes to managing your money, let me teach you to do what most wealth managers tell you can't be done, which is how to time the markets. I'm Steve Rhodes, author of Mastering Probability. And for the last 12 months, Timer Digest has been tracking my newsletter signals, which have earned me the ranking as their number one market timer in the nation for the S&P 500 for the last 12, six and three months. Timer Digest also ranks me as the number one market timer for gold as well. The fact is markets can be timed and I'll teach you the exact set of tools that I use that has transformed me into one of the best at what I do. Sign up for Mastering Probability today by clicking on the newsletter tab on the homepage of TFNN.com and get immediate access to workshops where I take you step by step how to use an extraordinary set of tools as well as provide great market calls to sign up today. David White's newsletter, The Technology Insider is focused like a laser on finding the next big things in technology. If you had invested only $10,000 in Microsoft in 1986, you'd have been a millionaire by 2000. Disruptive technology like Microsoft's is the key to these massive long term profits and a tech insider is the vehicle from TFNN to capitalize on these opportunities. This is the go to newsletter that identifies, monitors and profits on mostly little known cutting edge companies with great long term prospects. David's experience is as an inventor of Emmy winning animation products for TV and Hollywood that propelled a company public. Match that with 14 years as a full time trader and he's uniquely qualified to guide you through the light speed world of ever evolving high tech. If you're ready to ride the next big technology market for less than $40 per month, log on to TFNN.com and get your two week free trial to the technology insider. Get in on the ground floor of the next big thing today. Since 1984, Basil Chapman has been using the Chapman wave methodology to advise traders of his expert market opinion. While originally hand drawing charts from the late 1970s into the 1980s, Basil noticed that prices under most circumstances virtually always had a certain number of legs to the upside before declining sharply. Later, Basil found that computer software which included the standard market technical indicators enhanced the degree of accuracy in calling price turns as well as market trend calls. Thus was born the Chapman wave sequence. Using the Chapman wave methodology along with other indicators, Basil Chapman advises his subscribers of his expert market opinion each market day with his opening call newsletter. Right now you can get a two week free trial to the opening call Basil's daily trading newsletter by visiting the front page of TFNN.com. Cancel at any time during that trial and pay absolutely nothing. Get your two week free trial to Basil's newsletter the opening call today by visiting TFNN.com. Catch Tom O'Brien, professional trader and educator, founder of TFNN. Also a special guest on CNBC. Tom will bisect and dissect the markets. The Tom O'Brien Show next on TFNN. And we've got a question on Boeing. What do we have going on down here? And that is possibly the a test well actually a test of this gap up that happened on the 22nd of October. Am I feeling that horrible about Boeing's long-term future? And the answer is no. I'm wondering if a lot of the articles written over the weekend about the impending Boeing stopping of the assembly line aren't self-serving. If you wanted to get a fairly decent price on Boeing, how much would it cost to pay off somebody? Or we'll say that you're in the company itself and you want to get options or you're on Wall Street and you want to buy options. Then you come out with a nice story that says they may, maybe they won't. No backup from the company. As far as we know it's a single source inside the company who may or may not be in a position to actually tell us the truth. From what I've been doing following it, I'd be very interested in watching this over the beginning part of the year. They get a new CEO at any point and you're going to get 30 bucks on the day. This has also kind of formed a uptrend line since the August 15th low. You've got what about five bucks higher on the October 21st low. You now got about five bucks higher on today's low. And the question is if this thing bases out volumes fairly light, I might be kind of tempted to be kind of tempted to be looking at calls early into next year. They get the 737 max back in the air and they hit pieces off. They still got 4,000 planes on backwater. So when you can, not when you have to, we will be here tomorrow. Same bat channel, same bat time.