- 3 years ago
Kaiju ETF Advisors builds, trains, and employs robust artificial intelligence (AI) and machine learning technologies designed to improve fund management decision-making. By empowering these innovative technologies to curate and provide direct management of our ETF, we’re striving to go places no Registered Investment Advisor has gone before.
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NewsTranscript
00:00 (upbeat music)
00:02 - What is up Zinger Nation?
00:04 Welcome back to another episode of Benzinga Live.
00:06 Happy Tuesday, everybody.
00:08 (upbeat music)
00:10 Ryan, how are you doing today?
00:16 - Good, how are you doing, Aaron?
00:17 - Good, you have a good weekend and Monday and everything?
00:20 - Yeah, pretty restful.
00:21 I mean, we had some wildfire smoke that blew through
00:24 and that choked things up a little bit,
00:27 but I think that's where everybody has been this summer,
00:30 frankly.
00:31 - Yeah, a lot of smoke, a lot of weird weather,
00:34 certainly this summer.
00:35 I mean, hopefully that's not just like the new normal
00:38 is that every year we're gonna get more and more,
00:40 you know, natural disasters and weird weather patterns,
00:44 but it kind of seems like that's where we're headed.
00:47 - Yeah, fingers crossed, right?
00:49 - Yep.
00:50 And then yesterday, I mean, it was a Monday,
00:52 but as you know, talking here on Benzinga,
00:55 it didn't, I mean, in terms of Mondays,
00:57 it felt like a pretty good Monday,
00:58 at least if you were long tech or long the general market,
01:02 the S&P 500, the NASDAQ composite each finished up
01:06 more than a percent, which, you know, might not be,
01:09 you know, it sound like the most, the best,
01:11 but over the past few weeks where there's been a lot of red,
01:14 it certainly felt good.
01:16 - Yeah, green morning as well across the board today,
01:18 generally, so that's always a nice way
01:20 to start your day, right?
01:22 - Yes, sir.
01:23 All right, well, Ryan, let's get into it.
01:24 Before we start, just again,
01:28 in case there are any new viewers with us today,
01:31 you wanna give us just a general overview of Kaiju
01:34 and of the DIP ETF?
01:35 - Sure, so globally, Kaiju is an ecosystem of companies
01:41 that have been working in AI for a long time,
01:45 at least by current standards.
01:48 And we build AI curated and directed trading strategies
01:52 for private funds that we run on the private side.
01:55 And then just last year, we launched Kaiju ETF advisors,
01:59 which is pushing those strategies that are appropriate
02:03 in the 40 Act space out to the broader investing public
02:07 via ETFs.
02:09 And the DIP ETF is our flagship ETF.
02:12 It's designed to capture low to high mean reversion
02:17 in S&P 500 components,
02:20 uses some weighted large cap indexes as well
02:23 when it needs to.
02:24 And we really designed it for investors
02:27 that like the strategy of buying the DIP,
02:31 but had sporadic performance with it.
02:35 They were identifying some authentic DIPs
02:37 and misidentifying others.
02:38 So we thought, all right, why don't we just build an AI
02:42 around finding authentic DIPs
02:44 and push that out to the marketplace.
02:47 So if you like that strategy,
02:49 this is an easier way to do it.
02:51 And it's something that AI does well.
02:53 AI doesn't do everything well,
02:54 as we've talked about many times, Aaron,
02:56 but these types of patterns, it tends to do well.
03:00 - Yeah, so I'm curious, backing up from the DIP ETF
03:04 and just talking about Kaiju in general.
03:06 I mean, do you guys have a particular philosophy
03:10 or vision that drives you and what you guys are doing?
03:12 I mean, I know it's hard enough to get staff to buy
03:16 into this type of company vision,
03:18 let alone an AI algorithm.
03:21 So what are kind of these philosophies that drive Kaiju?
03:25 - Yeah, I mean, if I had to sum it up,
03:27 the term that we've been trying to use recently
03:31 is responsible AI, right?
03:33 Because with this explosion that's happened
03:36 over the last eight months,
03:38 you have shops like ours that have been using this
03:41 for like half a decade,
03:43 and then you have all kinds of new players
03:45 that have rapidly entered the space.
03:47 I mean, you've seen AI applied,
03:49 that term applied to apps in the app store
03:52 that you know are not using AI.
03:54 You've seen it applied to like light bulbs
03:57 that you can buy in the hardware store.
03:58 You're now with an AI layer, you know?
04:01 And so it's how do you separate yourself
04:03 from getting tossed in the bucket with all the hype?
04:07 And from our perspective, it's always been responsible AI.
04:11 What do I mean by that?
04:12 I mean that just because AI can do something
04:15 doesn't mean we use it for that
04:17 and certainly doesn't mean we let it run wild, right?
04:20 I mean, there are a lot of guardrails we place on it.
04:24 That often comes at the expense
04:26 of nose bleeding performance,
04:28 which you can get with black box AI directed strategies,
04:32 but you can also get like 90% drawdown
04:35 and nobody wants that.
04:37 So instead of just looking at the mountain peak,
04:40 it's like the route there.
04:42 And I think that is something
04:45 that's widely embraced internally at the company.
04:47 And then obviously the glue that holds everyone together
04:51 here is the belief in the usefulness of this technology.
04:55 Like it's not just AI for AI sake.
04:58 It's like, let it do some heavy lifting for you
05:00 so that you can focus on things that it doesn't do well.
05:04 If you're focusing on everything,
05:06 you're not really getting a break.
05:07 If you let AI do some heavy lifting for you, okay, fine.
05:10 I'll let it be responsible
05:12 for all the technical trading that we do.
05:14 - Great, super.
05:15 So you can look at global macro,
05:16 you can look at earns plays,
05:18 you can work in these spaces
05:21 that AI is not very good at forecasting or working in.
05:24 - Yeah, and I think that makes a lot of sense
05:27 in the way you put it, Ryan,
05:28 is that AI is good at some things,
05:30 not great at all things, at least not yet.
05:33 But I mean, so the underlying strategy of dip
05:37 is to buy the dip.
05:39 Is there something particular about AI
05:41 that makes this strategy something
05:44 that it does, that the AI does effectively?
05:47 Do you foresee a point in the future
05:49 that the AI will eventually be like a black box type thing
05:52 where it's creating its own strategy
05:54 and you guys are more hands off?
05:56 - The shorter answer is not really.
06:01 What makes buying the dip a good strategy for AI
06:07 is that, I mean, let's back up and just say,
06:12 we're talking about artificial dips, right?
06:14 Artificially oversold conditions, we call them, right?
06:17 It's not every pullback,
06:19 and this is what investors struggle with, right?
06:22 Every time a stock sells off,
06:24 it's not necessarily a buying opportunity.
06:26 That could be the mean reversion.
06:28 It's hugely over-speculated, it's overvalued,
06:30 reality settles in,
06:32 and it comes back to its fair market value.
06:35 And it may stay there or drop lower.
06:37 It may be rolling off a high
06:39 because of fundamental problems
06:41 with the company or its leadership.
06:43 So there's good reasons for a lot of the pullbacks,
06:46 but some of them are large institutional player,
06:50 I should say, caused by large institutional players
06:52 that are predating on specific liquidity opportunities.
06:57 So there's, you know, the spread blows out,
07:00 there's low liquidity, and there's an opportunity
07:03 for like an HFT to hit a stock like a freight train.
07:06 You look at Chipotle intraday,
07:07 you got a huge global company,
07:09 but intraday it can be pretty illiquid.
07:11 ISRG, same thing, pretty illiquid.
07:13 During the day, and these are monster companies.
07:15 And so someone can hit that,
07:18 artificially depress the stock,
07:20 cover lower, buy back, buy in, whatever.
07:23 Eventually it's gonna hit an institutional buy zone
07:25 that will absorb all that flow and send it back up.
07:28 And so there's a pattern there that you can look for.
07:31 And that's it, right?
07:32 Like we're not buying
07:33 and then we're holding for the next three months.
07:36 You know, we're buying
07:36 and we're holding for one to seven days, right?
07:39 We're just capturing this little piece of price action
07:42 over and over again.
07:43 So it's really good at doing that.
07:46 In terms of where it goes in the future,
07:49 yeah, there's a machine learning layer there.
07:51 You look at like the last 30 days of its performance
07:54 and we've been asked repeatedly,
07:56 including on your show a couple of weeks ago,
07:58 like, what is that?
08:00 That's machine learning in real time, right?
08:02 And so the power of AI is exhibited right there.
08:06 But it's still working within this rules framework.
08:09 Yes, it's able to rewrite part of its code
08:12 to optimize how it picks these dips,
08:16 how it identifies them,
08:18 the weighting of the criteria that it uses,
08:20 it can adjust that,
08:21 but it can't just decide to go do something else,
08:25 which is why, you know,
08:26 when we were asked by the Wall Street Journal recently,
08:29 like why it didn't pick the stock,
08:31 specific stocks for the big AI tech boost in the spring.
08:35 Well, none of them were in dips
08:36 and it's not designed as a Momo algorithm,
08:40 it's designed to find dips.
08:42 So it's gonna keep doing that.
08:43 So black box, no.
08:45 Optimization and increased efficiency, yeah, absolutely.
08:49 - Got it, that makes a lot of sense, Ryan.
08:51 So I understand that you spent some time briefly
08:56 some years ago as a retail trader
08:58 before becoming a professional trader and then fund manager
09:02 and now the global chair of Kaiju.
09:05 You know, I'm curious what were like the things
09:08 that you learned mentally,
09:09 kind of some of the psychological tricks
09:13 as a retail trader, like did you bring?
09:15 - Yeah, I think the big shift for me
09:27 was in the mental game, right?
09:31 I mean, you sort of, you start out
09:33 and you're thinking about, you know,
09:35 how am I gonna make money?
09:36 And the lack of information out there
09:39 is pretty shocking, right?
09:41 What do you have?
09:42 You have chat rooms, you've got some blogs,
09:44 you know, not access to quality information.
09:47 You don't, when you're starting out,
09:49 you don't really know any professional traders.
09:50 If you do, they wouldn't really talk to you
09:51 about how they run their businesses.
09:54 So, you know, it can be a question
09:57 of the blind leading the blind.
09:59 And for me, the biggest shift was starting to learn
10:05 from some kind traders, starting to learn
10:10 that it was possible to increase performance
10:16 just based on rules, application of rules.
10:24 That's the biggest difference.
10:25 You know, I, like everybody else thought
10:26 that there were tools that were needed.
10:30 I didn't have the right software.
10:31 I didn't have the right broker.
10:32 I didn't have that, but that's not the case.
10:34 Really what it came down to was the mental game
10:39 and understanding the standardization
10:42 of capital deployment, you know, across your strategies
10:47 so that you weren't like investing based on emotion.
10:51 I like this one, I'll invest more.
10:53 I don't like this one or I'm worried I'll invest less,
10:55 et cetera, et cetera.
10:56 And, you know, so applying that number one,
11:00 we've talked about that before.
11:02 And really realizing that you needed to let the law
11:07 of large numbers and probable outcomes work for you.
11:12 So the more you cherry pick, the more you skew
11:15 based on an emotional read, the more you pick and choose
11:19 within like a series of possible candidates
11:22 that you feel really strongly about,
11:24 the more you're gonna randomize your outcomes.
11:26 And then you're gonna feel that like as a trader,
11:30 you might have periods where you're just on fire
11:32 and then periods where you're like,
11:33 I can't do anything right.
11:35 And that can be really difficult.
11:38 And so going that systematized trading route
11:42 makes all the difference in the world, really.
11:44 That's where I came at it from.
11:46 - Got it, and Ryan, I'm here with the audio only.
11:48 We had our camera froze up,
11:49 so we're getting that restarted right now,
11:51 but I'm here with you.
11:53 So, you know, as we kind of wrap up today
11:56 and head toward the Kaiju kicker, before we get there,
11:59 I wanna ask kind of a follow-up question on your point there.
12:03 So what are some of the things I guess
12:05 that as retail traders, like things that we can kind of take
12:10 from a professional strategy
12:12 and try to implement in our trading?
12:14 - So as I think we talked about it maybe last show,
12:21 maybe the show before that,
12:26 the easiest ways to see an increase in performance are,
12:31 as I just said, standardize your allocation
12:33 across all your trades.
12:35 Because if it's standardized,
12:36 it's gonna highlight the areas
12:39 in which you're making good decisions and you're not.
12:41 Because you're probably not just trading one strategy.
12:44 You've got a handful that you like,
12:46 you're looking for specific signals.
12:48 I don't know if you're using indicators
12:50 to help you identify these signals.
12:52 But if you are standardized across all of them,
12:56 if all of your bets are the same,
12:58 whatever it is, 50 bucks, 100 bucks, it doesn't matter.
13:00 Then you can identify signals that are working for you
13:03 and signals that are not.
13:04 And that leads into take notes.
13:06 Like I don't know any professional traders that don't keep,
13:10 I mean, we have to do it for regulatory purposes,
13:13 but you want to make a note.
13:15 Most analytics software, certainly,
13:19 I mean, you can use Notepad or you can use Notes
13:21 if you're on a Mac.
13:22 Like make notes on why you picked this stock,
13:27 why you executed this trade.
13:30 Saw this, this looked good, feel good about that,
13:32 got this here, did my homework, et cetera.
13:35 And then you need to go back and review those
13:38 and see whether or not there's consistency
13:40 in the wins or losses.
13:41 Like when you lose, is there something you keep seeing
13:44 that doesn't pan out that you think will?
13:47 And that's a really important part of it.
13:50 And finally, you need to trade every opportunity.
13:54 Again, if you see 20 opportunities
13:57 and your position size is too large,
13:59 and I can't say it enough, small position sizes,
14:01 small and more of them.
14:03 So if you keep your position sizes small,
14:05 you can trade as much as you can within what you're seeing
14:09 from an opportunity perspective,
14:11 then you're going to be picking like the whole cohort
14:16 instead of a subset, because it's totally possible
14:19 that out of 50 opportunities that you're evaluating
14:23 and you decide you're going to trade 10,
14:24 you could easily accidentally randomly pick the 10 losers.
14:29 40 winners, which means you're awesome,
14:31 but you picked the 10 losers.
14:34 And that's tough for a trader to take on.
14:37 It's like, oh, I pick all the losers.
14:38 Okay, so stop doing that.
14:40 Within your strategy, with a collection of strategies,
14:43 you have a number of opportunities, trade all of them.
14:47 And then let the law of large numbers work for you.
14:50 Fine, you'll have the 10 losers
14:52 and you'll have the 40 winners.
14:53 And if you have your asymmetrical return on risk,
14:56 you'll make money right there.
14:58 And again, it's mental.
14:59 It's not tools, it's not access to information.
15:02 It's just rules and discipline, really.
15:04 - Got it.
15:06 Well, I'm going to turn it over to the chat
15:09 to see if we've got any questions from our audience today,
15:13 in general about Kaiju, about the dip ETF.
15:16 But Ryan, for the Kaiju kicker,
15:17 I was thinking we can do a quick review
15:20 over some different tools and whatnot
15:22 that for us retail traders to use in terms of
15:26 what you use for charting and analytics software,
15:31 what's the most important things to consider for a broker,
15:34 how much money do you really need to start with
15:36 if you want to make some money trading?
15:39 And do you prefer maybe, and explain this one out,
15:43 but options versus common stock,
15:46 especially for maybe a retail trader?
15:48 - You picked like a highlight reel here.
15:51 That's a lot to sort of blast through,
15:53 but I'll do my best.
15:55 - We'll do rapid fire.
15:56 - Rapid fire.
15:57 I'll do my best to answer those
15:59 without boring people to death.
16:00 Okay, so first one, analytics package.
16:03 We use a number of different packages, obviously here.
16:08 If I had to pick a general package, and again, caveat,
16:12 I am not compensated by saying this,
16:15 in any way, TC2000, Worden,
16:20 is I don't actually know how they make money.
16:24 It's a monster package for what it is.
16:27 It doesn't cost very much money.
16:28 It has real time data.
16:30 I think they even have a brokerage now.
16:32 I think they clear with Apex.
16:33 So it can be like a one-stop solution,
16:36 but from an analytics package,
16:37 it's the one retail package
16:39 that a lot of professional traders use.
16:41 It allows you to make sure your candlestick charts
16:45 are black and white on a white background,
16:47 which we've talked about before is so important.
16:50 Please don't trade red and green candlesticks
16:52 on a black background
16:53 unless you like being 30% less profitable.
16:55 Your brain is just not trained to read those patterns.
16:58 It has really powerful scans built in
17:02 and that you can create and customize.
17:04 And it has a PCF module,
17:06 so you can write your own indicators
17:09 and then layer that under a chart.
17:11 So it's like shockingly powerful.
17:13 I would go that route.
17:14 So there's your trading software.
17:16 What to look for in a broker.
17:18 I mean, everyone's gonna say commission fees
17:21 and should say commissions and fees.
17:25 And from my perspective, inventory, right?
17:29 Access to borrows.
17:30 If you're only trading the long side,
17:32 you are trading like half the market
17:34 and it will be harder for you to make money
17:37 in all market conditions.
17:39 Learning how to short, when to short,
17:40 what are the strengths, pros and cons of shorting
17:44 is one thing, but you also need the borrows, right?
17:46 It's not your stock.
17:47 So you have to have access to the stock
17:49 to borrow it and short it.
17:51 And some brokers have access to crummy inventory
17:54 and others have great inventory.
17:55 I don't know if IB still has the best short inventory,
17:59 but they used to.
18:00 That was sort of a go-to.
18:02 On the, how much money do you need
18:06 to make money in trading?
18:07 Okay, I've been asked this about a thousand times
18:09 in my career, I guess a popular question.
18:11 So the short answer is, if you're just starting trading,
18:15 you really don't need any money.
18:17 Something like TC2000 or your brokerage account
18:21 probably has a paper trading account.
18:25 And I can't stress this enough.
18:26 You should paper trade whatever strategy
18:29 you think you're going to do for a minimum of six months
18:32 before you put live cash on it.
18:34 If you are not profitable after six months of paper trading,
18:38 there's something fundamentally wrong with your strategy
18:40 and best that you don't lose your hard earned money over it.
18:43 If you can't exercise the discipline
18:46 to paper trade six months, I'm sorry to say this,
18:50 but you don't have the discipline
18:51 to be a professional trader.
18:52 I mean, like that's the minimum, right?
18:54 Patience, six months of paper trading,
18:57 you're profitable, let her rip.
18:59 So you don't have to have any.
19:03 When you're starting, you got the different tiers.
19:05 You could start with a couple grand,
19:08 whatever your broker will let you open an account with.
19:10 Some of the prosumer brokers like IB,
19:13 I think it's a $15,000 minimum.
19:15 Okay, so you have that.
19:16 You're gonna have a hard time with position sizing.
19:20 Fractional trading is an option.
19:22 I'm not a huge fan.
19:23 That's a subject for another episode.
19:26 But you're then going to fall into the tier
19:30 of pattern day trader, right?
19:32 So you have this round trip trade limitation
19:34 under whatever it is, $25,000, $26,000,
19:39 where you are going to be restricted
19:41 to the number of round trip trades you can do a week.
19:44 And that's gonna limit you to the type of trading you do.
19:47 So swing and momentum trading will be really difficult
19:50 if you only have five of those puppies during a week.
19:52 You're probably going to start
19:54 with more position trading, right?
19:56 You know, you're quarter on quarter there.
19:58 If you can be over $25,000, you'll skip the PDT rule
20:02 and you're off into regular trading,
20:04 but your reg T margin, which means you're going
20:07 to have less capital efficiency
20:10 than if you were over a hundred grand
20:11 and you have access to portfolio margin.
20:14 Again, better calculations, better leverage,
20:17 topic for another day.
20:18 So short answer, you don't need anything to start
20:22 and determine whether or not this is something
20:23 that's gonna work for you.
20:25 And there is a way to work with each capital level.
20:28 Last, your last question I think was stock versus options.
20:33 - You had a good memory.
20:34 - Yeah, well, I probably would not be very good
20:36 at this job if I didn't have a good memory.
20:39 That's a key skill right there.
20:42 You kind of need to,
20:43 it needs to be borderline photographic at times.
20:46 So stocks versus options.
20:47 Options, if you don't know how to trade options,
20:50 you really should educate yourself
20:52 because it's the biggest bang for the buck.
20:54 It's the best capital efficiency, right?
20:56 If you've got 10 grand in your trading stock,
21:00 you know, it's gonna be very hard for you
21:02 to make enough money to make a dent in your life.
21:05 You know, give you a little extra spending money,
21:07 pay off bills, get you half out of your job,
21:09 whatever it is.
21:11 With options though, you know, like a 50% return,
21:14 100% return per trade, 20% return per trade,
21:18 that's not impossible or crazy.
21:20 That happens all the time.
21:22 In stock, that's crazy, right?
21:24 You're gonna get that once in a blue moon.
21:26 But options, that happens a lot.
21:29 And your risk is predefined, right?
21:31 It's limited to the premium that you purchase
21:33 if you're long options,
21:34 which is what you're gonna do in the beginning.
21:36 So you can't lose more than you bet.
21:39 You know, you don't even really need
21:42 to put a stop loss in there
21:43 if you've properly sized your position.
21:45 And there is really good free education
21:48 for options trading.
21:49 I think there's a guy named Kirk Duplassie.
21:53 He used to be a Goldman's options trader.
21:56 He started this business online,
21:58 I don't know how many years ago.
22:00 I hope it's still running 'cause I'm gonna say it.
22:02 I haven't seen it in ages.
22:03 I think it's called Option Alpha or Options Alpha.
22:07 And there's like, he's created this enormous library
22:10 of educational videos that are free.
22:13 I think you get slightly more if you sign up
22:15 for whatever service he provides.
22:16 But like, there's this huge
22:18 beginner, intermediate, advanced library
22:21 that he offers access to.
22:23 Like, if you have no idea what options are,
22:25 how to trade them,
22:26 you're like walked by the hand through this.
22:27 So you got that.
22:28 And then Tasty Trade, Tony Batista and Tom Sosnoff,
22:33 Liz and Jenny, these are all former SIBO floor traders
22:38 and market makers.
22:40 And they have, I think it's like a free TV show.
22:43 It's like a web show like Benzinga Live here.
22:46 And they talk about options all day.
22:48 It's option specific.
22:49 And again, an enormous library of free education.
22:53 So that's low hanging fruit.
22:55 If you don't know how to use it, go check those two out.
22:58 They're good folks.
22:59 And I mean, SOS and the bat are like legends
23:03 in this business.
23:04 So you are getting it from the top tier
23:07 of options traders here who have like long retired
23:11 and just doing this for fun.
23:14 On the stock side, okay, I'm an ex equities trader.
23:17 I hope all my Volarb guys that are watching
23:20 appreciate my support of the options market.
23:22 But I'm an ex equities trader.
23:24 That's kind of my specialization.
23:28 So I obviously lean that way,
23:31 but it requires a much larger capital base.
23:34 If you are gonna go that route,
23:36 please don't go the day trading route.
23:38 Nobody does that on the professional side.
23:40 We're not like in and out on the tick level.
23:44 It's just with your cost of trading,
23:46 you're gonna lose money doing that.
23:47 Like close to close, yes.
23:49 Momentum swing, absolutely.
23:51 No question.
23:52 I'm a huge fan.
23:53 That was my bailiwick.
23:54 But intraday, please don't do that.
23:57 It just, it very rarely works out.
23:59 So there I hope I covered it all.
24:01 - Yeah, you did.
24:02 You covered all the bases and in order
24:04 and remembered all of them too.
24:05 So extra points for that.
24:06 But yeah, maybe next week for the Kaiju Kicker,
24:08 we can kind of maybe extrapolate
24:11 on that last point a little bit
24:12 and break down the different types of trading
24:15 versus day trading, swing trading, momentum trading
24:18 and why maybe professional traders
24:20 or investors employ certain strategies and not all of them.
24:25 - Happy to do so.
24:26 - Awesome.
24:27 Well, Ryan, it's always a pleasure to get you on.
24:29 Guys in the chat, if you wanna learn more about Kaiju,
24:32 about the dip ETF, I'll drop that link in the chat
24:36 that you guys can check it out.
24:37 Or of course, just the ticker is DIP, pretty simple enough.
24:42 Ryan, thanks again for hopping on
24:43 and looking forward to chat next week.
24:44 - Always a pleasure, Aaron.
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