Beginner’s guide to (part-time) system trading · Kory Hoang

chat with traders episode 152 has backing from online broker and technology provider trade station now folks there's a good reason why TradeStation clean up when it comes to Awards because they know what traders need and they deliver from decent rates to powerful technology and analytical tools to helpful support trade station r1 broker you should not overlook learn more at trade station comm slash traders markets speculation and risk this is the chaplet traders podcast hosted by aaron Fifield hey crew what is going on your host aaron Fifield here coming up on this episode what you're about to hear is a conversation I had with Corey Kwang Corey is not a veteran trader he's not someone who has been doing this 10 20 years he's someone who's been doing this for only a few years but he's begun to make decent gains on his trading capital Corey is also not a full-time trader well let me be clear at the time we recorded this a few weeks back he wasn't but I've since been told he's handed in his notice and has taken the leap so the point being for the average listener there are quite possibly a few similarities between your situation and Corey's situation so how does he trade Corey is a retail systematic trader he's running numerous algorithmic strategies which he's developed all of which are fairly simple these run on various ETFs etienne's and even some crypto currencies join our chat we cover quite a bit but mostly his journey and how he's progressed to this point there was a moment I'm just going to throw us out there there was a moment around Midway where Corey did lose me a little bit if you happen to get lost - just stick with it because it will all click and I then take a moment to summarise his point also as Corey talks about a few strategy specifics I'd like to just mind you that you are entirely responsible for your own trading decisions okay enjoy the episode team this is Cory Wang where's a good place to start I mean it might be helpful if we just hear a little bit about kind of what you studied at University did you go to university yeah I went to the University of Washington I took a business degree and I major in finance and marketing okay and what did you do once you uh once you got your degree so while I was still in school to get my degree I actually took an internship at merrill lynch wealth management in Everett kind of by Seattle and that's where I really got my foot in the door in the financial industry and the investment industry in particular and that's where I learned a lot about you know stock market financial market trading and all that and you know became really fascinated to me ever since that day okay so what were you doing at Merrill Lynch while you were there which is an intern for three months during the summer in Derek Wells management division I was tasked mainly with basically shadowing other advisers there and you know one of the guys there I remember him to this day his name was Kelly I remember I walk into that office one time and he was in this big glass office facing you know this was on the 10th or 12th floor of a building and he was looking overlooking the ocean from the port of Everett and you know I look in his office and there was you know screens and charts and all these cool indicators and everything I knew from that day and I want to just be like that guy know so that obviously sparked your interest in trading that experience was was your internship there did you find that to be any help once you started to get into trading yourself it did help me get kick-started in terms of you know finding out what's a research you know what kind of stocks to look at you know what for example stock sectors market sectors are and things like that versification then you know a lot of you know basic beginner stuff for investing in general so that did help me get started in the right direction and from de niño which is basically self research and you know looking up information online reading books and figuring out the rest from dara on my own okay okay so just to put this in perspective when did you actually start to get interested in trading or actually start trading so a person was a few years back right yeah so my internship Merrill Lynch was actually three years ago and that was the same time that I actually started trading you know I was still in college that time I had a little spare money just a couple grand I started to trade you know technology stocks high gross stocks I remember this one time I bet money on KND eye candy technologies is with it it was a Chinese clean energy vehicle company but a long story short I made some good money on it initially made a couple grand off of it but then you know that company it just didn't do really well and then the stock kept tanky and I just kept trading it and didn't go well at all and so start losing money and had to take a break after a while so what what we basing your decisions to buy and sell on back then like was there any methodology to what you're doing or did you just have like a a good feeling the stock was going to give you a nice return yeah to be honest back now is really just gambling yeah to be honest um it's just basically seeing what's what's moving today you know what's the top market movers and what are the major themes in the market today one of the things I was researching back then back in school was clean energy and electric vehicles and you know so I thought I venture into that space and bet on a couple of stocks from that sector so there wasn't really any methodology really I mean I did look at charts a lot but I never really found them to be extremely effective okay so why did you feel as I was was gambling I know you said they let you feel like you were probably lacking a bit of methodology but um was that the only reason or was there we bet him too big I know you said you made some profits and one it was a candy or something like that and then it went right back against you just kept holding I mean what was some of the reasons why it felt like gambling in the beginning well I felt like gambling because I did not follow a system I mean I would think that I have a system but I would not follow it rigidly and you know it wasn't it wasn't a scientific process a scientific process mean that you come up with an observation and then you create a hypothesis and then you go out and you do your experiment you collect your evidence and from then you analyze the result and make a decision you know is your hypothesis supported by evidence or not that wasn't exactly what I was doing what I was doing is akin to what a lot of traders that I see you know when they just start out and trading or investing they just have some sort of ideas some sort of intuition or maybe they heard someone say oh this is a good stock or maybe they read somewhere that you know maybe they should buy a stocks when the RSI goes to oversold and they would just have some sort of idea of how to trade and they would you know think it'll make sense and they would go with it without really testing out that idea you know may perhaps through a back test or for testing with paper trading or something like that they just go right at it it's just like Emily okay and I just want to ask you before we go too much further what were your expectations like when you started out trading like did you feel as though this could be an easy ride and an easy way to make money you know initially I thought I could really date try and make just 1% a day you know and I'll be good for the rest of my life and it was just really you know naive beginners thought process that I'm sure a lot of people went through when they first started trading but yeah expectations were high and sure enough it was soon crushed by the reality of trading in the market mmm now what caused you to start getting interested in algorithmic trading I feel as though you may be touched on it before when you started to talk about having more of a scientific approach to the types of strategies who trade but you know you started out as a discretionary trader you started out just trading stocks and sectors that you knew a little bit about what caused you to start gravitating towards algorithmic trading it was in 2015 and there was a TED talk with Jim Simon's from Renaissance Technologies and I was very intrigued by that TED talk because here we have you know someone who's a mathematical genius he's you know had a great career in academics and not only that he used his knowledge from there and went into the financial industry started a hedge fund and managed to crank out you know the best returns that anyone ever seen in the market so and he did it all by using algorithms and following rules Bey processes so to me that was what I needed to do because I saw that as you know a scientific process that he was doing and to me he was a scientist and he was tackling trading and investing in a very scientific approach and I figure you know if I started imitating that process myself I would hopefully be able to achieve the same sort results yeah I have seen that talk actually it's a really good one and I'll dig up a link to that and put it in the show notes if anyone wants to also watch that it was that the first time you'd heard of Jim Simons yes that was the first time I heard Jim from Simon's ok wasn't the last time he came up India he came out in the news you know many times that dad how you know about how his medallion fund is like the best performing hedge fund of all time it's just insane the kind of returns that he cranks out yeah there's a really interesting article on Bloomberg about the medallion fund I presume you've probably read that it came out probably as a few months ago earlier in the year so you've watched this talk you've realized that you kind of like the approach that Jim Simons has taken you know very algorithmic rules based as you described what did you do from there like what resources were helpful for you to begin learning about algorithmic trading I would say the most useful tool that I ever came across was quanto peon for you know some people who don't know what Quinto peon is it is an algorithmic trading platform there's open source actually it's not a trading platform anymore they disabled live trading recently but you can still do a lot research on this platform it is based on Python and you can code your own algorithmic trading strategy there and they have a forum where a lot of wants and a lot of people who pursue that subject pose a bunch of you know algorithm and things that they come up with and we will share idea and collaborate together on strategies so it was a great place to learn and I started out learning just like everyone else who doesn't know how to code you just kind of like copy and paste and put thing together and just kind of like making a Frankenstein algorithm and you know run a backtest on it and see if it would work and you know you do that day up today week after week some months after months you start to get better and better at it and at the same time quanto peein offer a course they had lectures on how to build Python based trading algorithm and you know it it's literally like a full university course on quantitating that's my impression on it I know to some people it might not be very advanced but no to someone who did not really have that kind of exposure it was a lot of help and it kick started my journey into algorithmic trading a lot yeah their lecture series is very top-notch I mean I would consider certainly some of the topics there to be quite advanced yeah and I love that feature about canto P and how you can like just clone other people's algorithms and then play around with them tweak them try change a few things and you know see if you can improve on it and yeah and they also have a really good forum as well I mean I don't normally I'm not really much of a fan of forums generally but quanto can have a really quality forum like you can you can find some interesting insights there so did you know how to code in Python prior to this because as we know quanto pians platform only takes python as the input language I mean had you had any experience coding in this language before absolutely not before I discover quanto pian I did not KO it at all I mean the closest that the coding was using Excel spreadsheet and back in college most my courses were mainly business and finance courses none of it was for programming so I could go back to school I was probably one thing that would change to take some programming classes absolutely I mean that's one thing I wish I would have picked up a lot sooner is they only had a code hey we are but yeah so with absolutely no coding experience I just kind of dive head in and you know it took weeks and weeks before I finally figure out how to get basic features running like running a fallback test and factoring in commission & slippage and how to change stock symbols and all that stuff it took a while the learning curve was you know a little bit steep at first but you know this was something that was really passionate and that I really enjoy doing so to me it wasn't really you know something that was strenuous it was something that you know I was looking forward to doing I I remember staying team you know 2 or 3 a.m. I'm just coding algorithms and learning how to use the platform yeah it can be kind of addictive in some ways right yeah certainly what because you know once you understand the capability that this tool can offer you and all it takes it for you to learn it and get better at it you know you just kind of get into that mindset and just push yourself to do it yeah yeah totally man now were you using corn soybeans which the learn Python as well or we like doing some other online courses and classes etc from other places on the net I did take be a course from you to me but I never really finished up with it so my experience with Python so far is you know I'm not like the average typical programmer who who knows Python and can't code like an app or you know some sort of interface for you so I'm not that kind of guy i strictly know how to use python on the quanto peon platform only and my break really came when I discovered tradestation because tradestation uses a much simpler coding language called easy language and TradeStation has like charting platforms and interfaces that you know I was much more accustomed to quanto Pierre was very much tech space and code base and very little charts and I mean you can coat them yourself but for me to do that at that point what it was a huge learning curve so when I found TradeStation and I've discovered you know the ease of coding in easy language I started playing around with that platform a lot more and I started migrating my trading over to TradeStation okay and I presume it points throughout this whole process there's been there's been points where you've kind of got stuck or hit a wall and got maybe frustrated because you can't work something out what are you doing those sorts of scenarios well what I usually do when I'm stuck at something is I find someone else who can help me figure it out someone who actually know how to code at first it was a bit difficult because usually the people who knows finance don't know how to code and usually the people who know how to code don't know finance so to find someone who has some sort of quality of both was very difficult I remember trying to work with programmer who have no financial knowledge and you know it was ok and I try to teach them you know what I did know and you know my what I wanted my strategy to be and you know try to guide him through the process but it was very difficult you know is it's basically another learning curve for them that they had to tackle on and for the amount of money that was paying them they obviously were not interested in pursuing that route so but you know eventually when when you have a forum like quanto peon you can find collaborators fairly easily and you know when I start using the forum there to reach out to people to coders to help me with my strategy that's when I really found that's when one of my first breakthrough really came when I found someone to help me implement one of my strategy that I had in my head it was just a concept and he helped me lay it out in Python and I was able to observe like how the Python code was structure and I basically reverse engineer and learned it back from there okay yeah I mean that's that's any smart way to go about it in the forum you know a lot of people really helpful there so you know if you have questions is a good place to find some answers how long did it actually take you to go from doing back tests and different forms of analysis to actually starting to run some real money through your strategies so I began coding strategy and you know trying to back testing since a thing 2002 start 2016 and from then it took me all you know about six seven months to finally get comfortable enough throw some money at the algorithm that I have code it and you know it wouldn't be a lot of money I'll just be like five or $10,000 and I wouldn't even trade the whole amount you know just make the algorithm take very small portion of that money but you know it was enough to test out my idea to do some walk-forward testing and from then on you know it helped me build more confidence because you know I can see that my money's being put to work by this machine that I built myself and knowing how this machine works and seeing it in action after you know weeks and weeks and weeks build up your confidence to the point where you realize that you know this is this is real you know like I always read about that's always heard about this and you know now I'm actually experienced experiencing it so right do you remember your first automated trade you know to be honest I can't remember the first one but I remember my first biggest win from automated trading it was Andy yeah it was in the summer of 2016 I forgot what happened but that week my algorithm bought XIV and inverse volatility ETN I bought it you know at a really good time and I saw it you know about week later and make some good money on that and from that on where you know I was hooked yeah yeah now it's a good feeling man so when did you feel confident to actually go live with this first strategy because you know I presume there was it of course it wasn't the first strategy you tried you tried to like in what's it without trading real money right so like it backtest in different ideas and tried different things but this particular strategy which you decided to go live with you obviously felt confident in that like what gave you the confidence to go live with that particular strategy I see when I when I first created a profitable algorithm I knew it was profitable because it was a very simple algorithm it's literally a moving average crossover but you know the asset and the timeframe that I was using is for it just work out perfectly and you know so just just because I understand how it works and the simplicity behind it it gave me a lot of confidence that you know start going forward okay and I know some people I think probably freaked out about the idea that a computer is trading their money for them right was that an issue for you like did you struggle with that aspect of it just let taking your hands off and letting the computer take over to be honest I think I had it easier down a lot of people because when I started building my strategy and creating my algorithm that's was when I started researching into you know market anomalies and taking you know really quantitative approach and research into you know how to figure out what assets and how to trade them and you know I think it was luck perhaps but the framework I develop it ended up working out really well and I'm still using it to this very day and you know all the algorithms that I built and create are from this framework that I use and it is rather simple if I really break it down to you due to its simplicity it is very robust and you know it's been more than one-and-a-half years of walk-forward testing and live trading now so it's giving me a lot of confidence to keep moving forward this is something this episode of chat with traders is brought to you by trade station when you become a tradestation client you're putting yourself in a position to better analyze and trade markets especially as a retail trader as traders we have enough challenges as it is so roll with an online broker who understands what traders need TradeStation equipped their clients with awesome commission rates and professional grade analysis tools which you won't find being offered by other brokers just as an example tradestation allow you to create your own custom indicators and your own custom strategies then back test these ideas on 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chat to get your free quote how many systems or strategies what are you gonna call them a running nowadays like at the moment so where do i do things days I have two different type of algorithms that I run the first one is my binocular so this is an algorithm that I develop based on my observation and research into market anomalies I call it my price anomaly detection algorithm so what this algorithm would do is it would scan all available securities in the market and based on a proprietary metric that I developed it would classify which asset at which time interval exhibit price anomaly meaning this has mean reversion properties or if it has momentum or trend persistence properties and of course this system would also tell me this algorithm would also help me identify assets that random walk and according to my framework I don't trade random walk assets my algorithm indicates to me that about 96 95 percent of the available assets and time interval was out there are random walk and it is not profitable for you know you for most people to come in and trade those assets because they don't have any edge because they're random you can tre something does you know random but about 5% up stuff out there they do exhibit certain trends and anomalies that show up time over time and it's those assets that you want to focus your trading on and this is when I start using my second set of algorithm these so the first one was the binocular the price anomaly detection algorithm the second set of algorithm I call them my rifles so this is when after I have identified my prey like a hunter I would take my rifle some very simple rifles at time then I would go and I would hunt down my prey to put to put it in a you know in a simple to understand way okay okay now I just want to go into a few of those things you said there okay so I guess the first one being framework you know you've used this word a few times I just want to make sure that we're clear on what you're actually referencing when you talk about a framework so what are you referencing okay all my research so far ever since I started investing trading 3 doing 1/2 years ago indicates to me that the market is mostly efficient if you study you know French and Farmer Modern Portfolio theory they say that prices asset prices are efficient because the market discount all available information into prices almost instantly so you know the best thing you should do out there is really just buy and hold on index fund and just let it ride so my internship Merrill Lynch kind of had me subscribe to that idea for awhile until one day I realized that you know perhaps that's not the whole truth out there perhaps there are certain pockets in the market where inefficiency still exists and so you know it was at that point I realized that efficient assets a random because when they are efficient there are no extractable alpha or there's no edge in trading them therefore that's why they are efficient and they are random you can't predict these things however certain assets out there are inefficient meaning there are repeatable patterns that keep showing up and people are not exploiting them at that pattern or what I call anomaly is large enough for you to explore yourself they just definitely do it so that's basically what my framework is about you know I used the price anomaly detection algorithm to scan all available asset you know my butt inoculator to find my praise the ones that that are random and you know that can't be hunted down I disregard them and I don't trade them but the ones that do show a high level of anomaly that you know is exploitable then I would come in and trade those assets with my more optimized algorithm okay so in some ways this binocular algorithm I guess you could call it that doesn't actually take any trades it's purely just a scanning tool essentially essentially yes so what this algorithm does is it uses an oscillator a technical oscillator to measure the expectancy of momentum or mean reversion for any particular asset at a certain time I'm interval for example I can use this algorithm to scan for scan all ETF on a daily interval and at the end to scan it would produce many a market map this market map it looks like an x and y plot the x axis would be for momentum expectancy and the y axis would be for mean reversion expectancy so in the middle up the pot where the two axes intersect is zero so in the bottom left quadrant it's the random walk zone nests where 95% of assets tend to end up because they're random and unpredictable however and the top left quadrant and the bottom right quadrant those are the quadrant where you would find momentum and mean reversion anomalies where assets would exhibit certain trends that are persistent throughout time and assets that fall into those zones I would assess them and find a 1/2 off for me the highest risk reward ratio and then I would go in trade just those asset only maybe four or five of them and these ten these usually tends to be ETF so you know it's been pretty good for me following the system that I develop now the price anomalies that you're talking about can you give us just maybe an example of one anomaly which you might use certainly so when I'm talking about anomaly I'm actually just talking about two and its momentum and mean reversion matter of fact that how I got started thinking in this direction is when I went to quant con hosted by quanto peon in 2016 I think was April in New York so I flew out to New York and I met up with some people there and you know we went and we saw a couple of lectures and talks by some of the best you know people in the industry some of the brightest quant out there and there was a there was a person who came all the way from India his name was Manish Galan of I think SG analytics yeah and he came all the way from India chips to give a talk at Kwan Khan and so I you know I I figure I'll go to his talk and see what he has to say and it was at that talk that he opened my eye to price anomalies it wasn't really you know fully a hard percent clear to me at that point but you know afterward after went home and taken to consideration what he talked about during his lecture there I finally understood what he meant and from then on I developed the rest of my framework from there so when I was in that talk he showed me what a topic that he touched I was you know figuring out how to trade certain assets and certain style like you can't use the same trading style for every single asset and so he put up on the projector a picture of an RSI oscillator and so he I look at the RSI you know everyone's familiar with the RSI indicator and so I look at the RSI and he said if I was to buy when the RSI is over Seoul and sell when the RSI is overbought what technique that is used and you know for a while everyone was like stumped and then he said that is a mean reversion technique and I thought about it I was like you know what that makes sense you know if you buy when it's over so and you wait for it to bounce back when and then sell it when it's overbought you're waiting for it to mean revert and then he also said what do you think a momentum technique would be I first I couldn't figure it out but then it was very simple he said a momentum technique would be to buy when it's overbought and so when it's oversold the exact mathematical opposite of mean reversion and so from my experience from that lecture there I went home and thought about it and I realized that you know what he is right and I started doing some more research and trying to come up my own evidence and support you know what he had to say and in the course of looking for these evidence I stumble upon these anomalies that is momentum and mean reversion in the market certain assets you can use momentum technique on them and it would work really well but what that means is if you use mean reversion techniques on these assets you're gonna do very poorly and so forth cert also for certain assets neither mean reversion of momentum technique would work well on them and you know those asset tends to be random walk because you know they don't show a persistent trend neither a momentum a mean reversion trend for you to follow so that is basically what my entire framework is based on identifying which assets shows momentum properties in which asset shows mean reversion property identified a1 that exhibit the highest level of those anomaly and trade those asset only meanwhile avoid trading all the random walk assets okay now don't want to confuse things here but the example you gave about the RSI between what makes what might be a mean reverting characteristic and what might be a momentum property or characteristic you said if the RSI is pointing to overboard and you sell that that's a mean reversion type of trade if you you can look at it the opposite way and it's a momentum type of trade so how does that work because doesn't wouldn't it give you a signal to also go long as well as go short the same stock so this is where this is the part where you have to identify which asset exhibit momentum anomalies and which asset exhibit mean reversion anomaly for example I've done this myself so I know spwhy on a daily interval exhibit mean reversion property right now it does back in the 1960 it did not exhibit mean reversion properties in the 1960 have you bought the SMP today after it was it has gone up after it has gone positive and you hoe it and sell it the data it finally starts going down how you followed that basic momentum system you would have made I can't remember and I'm the number but you would definitely have outperformed the market many many times but sometimes around the 1980s and 1990s that system stopped working however the reversal of it started to work and that was mean reversion so whenever the market started the ESPY start going down the data I start going down how you buy it and then you sell it the first day I start going up that system when I started making you money so because I did this research myself and I saw it in the S&P 500 I figured this anomaly must also be it must also exist another asset and so I went out I scan all every single one of them and sure enough I was able to identify certain ones that have very strong momentum anomaly couple of them are inverse volatility products like xiv sv x y jr gold miners etf like GD xj exhibit very high momentum anomaly on the intraday interval also junk bonds this was kind of surprising but on the two our interval junk bond hyg the etf exhibits momentum anomaly so if you use a simple are size system where you would buy it when it is overbought and sell it when it is over so you would make decent money over time trading those assets now are you scanning this a scanning these different symbols every day or is this just what you've done in your initial research and then you've traded main reversion on that those particular names yeah right now i'm working on a system where it would be constantly monitoring it but for now I'm just taking a snapshot every quarter so at the start of each quarter I'll run the scan and I'll run it on many time interval for example run the scan on all ETFs on a 30 minute in devil in an hour and then 2 hour and then a daily interval and then perhaps weekly in OBO monthly quarterly at the most and so after every one to scan at each time interval I would get a bunch of result and so I would get that XY plot for every single time interval and on these XY plots on each time interval it which indicate to me which asset is currently exhibiting momentum or mean reversion anomaly once I figure out you know out of all those which one gives me the best odds then I go after him okay I think this is all starting to make sense and come together so just to summarize what we've been talking about here every quarter you run this scan through your binocular algorithm right and it determines which symbols which stocks or ETFs or whatever it is you're trading has strong characteristics of mean reversion or strong characteristics of momentum and then you take kind of the correct their strongest out of the strong and then that's what you trade your other strategies on so if it's it shows strong properties of momentum you're gonna trade those names with momentum strategies is that correct yes a lot of traders they tend to think that you know today the secret lies in a strategy you know in the perfect indicators and the perfect rules you know the perfect money management system I mean all that play a part in becoming you know in creating a successful strategy but from my experience that's not where the secret lies it's not in the system that you trade it it lies in the asset if the asset is random there is no way you can ever try to make it work for you I mean personally I have not found a way yet I shouldn't say never but you know personally I haven't found a way to trade random assets but when you found when you can find certain assets that exhibit certain patterns that keep repeating over time you know you need to be you know oh you got to be a really chicken a really big chicken so now go out and take your chance at that because they keep showing up over and over and over again okay yeah now this this makes sense I'm following with you I was a little bit lost for a moment there but ya know it's it's very clear to me now I might just say if anyone has any questions around this would you be open to answering those in the comment section of this episode on the website yeah so I wouldn't necessarily share all my secrets but you know I from my experience with quanto pian other people have been very willing to help me and help me get started to where I am today so you know I'm just trying to return the favor and doing the same it's who obviously I have a day job and I'm trading my algorithm trades on the side so you know I don't have a lot of time to cater to everyone but I try to answer it as many emails I can if that makes any sense of course ya know we obviously would be respectful of your time but I'm just thinking if this part wasn't clear to someone you know I don't expect you and I don't think anyone expects you to give away the secret sauce yeah just if they need a little bit of clarification around your framework there but anyway let's keep moving so let me ask you this how do you come up with strategy ideas okay so once you've classified different assets into either being having mean reverting characteristics or momentum characteristics how do you actually come up with the ideas for how to trade those assets now this is a little bit interesting because I draw from my own personal life experience to you know come up these strategies so just a little bit background with myself I I was born and raised in Vietnam I actually wasn't from the United State I came here in 2004 my family when I was 12 so for a good part of my life I was you know growing up under communism under a system that was you know a hybrid between communism and capitalism to put it that way and when I was in Vietnam I had the chance to learn a lot about the Vietnam War that was actually one of the major topics that you had to learn about in school and I had to learn about the tactics that were used during the war I don't know why they were teaching kids those kind of things back then but you know they did it anyway so you learn a lot about guerrilla tactics and what you know the Vietcong the Vietnamese communists used to against the Americans during the war and some of that theme it kind of stuck with me for the rest of my life throughout everything not kind of do guerrilla tactics that makes any sense so for example one of the things that a guerrilla would do during that war is they never openly confront the enemy who is superior to them in open battle right so that's kind of like me the end of a time trading I when I create strategy I don't create a strategy to try every single thing out there because I know that I don't have the capability or the skills to do that I want to focus my trading on you know things that I know that I'm really good at just like guerrilla tactics you don't go out you fight everywhere you focus your you know on the most vulnerable target and on the most the one that do the most damage and put the best bang for the buck and you know keep my I keep my strategy is very simple just like you know when during that war you know we had to side one was like technical technologically hundred times superior and the other side was you know fighting in jungles and using bamboo trap but you know we all know how that war ended up and simplicity at the end of day one that war I'm a idea of other reason so that's why I keep my strategy very simple I try not to over complicate it a lot of my strategies are bill which is a couple of variables just a couple of inputs maybe two three less than forty fifty line of codes at best it's working out really well surprisingly you know something so simple and you know not very complicated could deliver such robust result over time now most of these strategy art is revolve around indicators most of what I use is technical indicators and I don't use it like a lot of what people call technical analysts technical analysts tend to look at a chart and draw some sort of trend line or see some sort of patterns emerging or maybe they'll look at a technical oscillator and like the RSI and they would come up with some sort of a subjective idea about it now I don't want to say that that doesn't work or it won't ever work but in my experience when you follow that route there's a lot of subjectivity and a lot less science and it it becomes more an art than a science so when I use technical indicators I you know don't I also don't draw trend lines I don't you know see random patterns like you know bullish flag or whatever in my chart I use cycle indicators as basically triggers to initiate my traits for in very quiet and I use them in very quantitative manners for so for example if if I use the RSI I would only buy when the RSI hit a certain level and only said when I hit a certain level and that would be defined and I would follow that without fail every single time okay and what's the maximum number of parameters you'd feel comfortable including in a strategy let's say a number of parameters or conditions which must be true for you to enter into a position like I know you'd like to keep things very simple so just so we really get a grasp on that usually when I create strategies because I don't put too many inputs in there and you know overfit the strategy or data mine sometimes it tends to have very few inputs maybe I would say less than 10 inputs most of the time probably won't even get above five or six things you know those input with some it would be something like the length of the RSI or the length of the moving average and we're not I want to short sell or not or what is the person allocation portrayed and what the stop loss and profit targets are done you know not nothing too fancy nothing to complicate it it depends on how strong the anomaly is so for example on and you can go out you can verify this yourself on a daily interval if you look at s py and if you were to use an RSI a two period RSI and if you were to buy when that RSI is below 30 and so when it's above 70 that system produce very good result over the past 10 15 years I don't recall exactly what the numbers was but the Sharpe ratio was very high it was above 1 compared to just by and holding s py itself a matter of fact that system during 2008 managed to avoid a lot of the drawdown that s py experienced ok and when you say boy when these conditions are true how do you exit that position like is what's the what's the guard line there on certain system I would have a profit target but most of my system the exit condition would be based on my indicator so for example if the RSI is or so I would buy and if it's when it's overbought then I was self and I would not use any sort of stop loss or profit target because that system I just described there as a mean reversion system it's you tend to want to let mean reversion system have some room to jiggle before it mean revert back up so using stop loss can sometime cut you out a trade too early and a lot of time with you put in a profit target you don't capture the entire move of the trades and you would exit early so in my experience using profit target and stop-loss with only be reserved for asset and time intervals that offer lower intensity and momentum or mean reversion okay and I realized I just you'd already explained how to exit that particular strategy before I asked you exit when the RSI crosses 70 so ok so where are we here now as you have been live trading a few strategies now for how long has it been it's probably been about 18 months since she first started live trading with algos I see I think I've turned my first algorithm on July of 2016 so twelve years I mean 12 months and a bit yeah about 15 months yeah yeah have there been any times when you've you've stepped in and overridden your strategies a couple of times and I've learned that I should stop doing that because you know the time that you know I miss out the most was after the election of 2016 I after that election and when the market was still going up initially I thought it was kind of weird because I had my expectation was you know the market would not react well to a trump presidency for various reason so I decided to go against what I typically do which is to trust my algorithm to do to train for me because you know I already already identified the anomaly I already designed the system already tested it and it's working I should stick to it but for some reason after that election I had a little of doubt so I decided to turn my system up all for a couple of months and I did not turn them back on into March of 2017 and that was a really big mistake because had I had it on during that time I would have made you know close thirty forty percent during that period so lesson learned lesson learned so what sort of returns are you aiming for like you know what would you classify is a good year for you so according to the back test I'm running on my strategies I'm running seven different algorithm right now and when you put them all together in a portfolio each one of them is taking 15% of my account per trade so my account was not leveraged I don't use leverage at all I do short so but not on a lot of asset matter of fact only short sell on junior Gold Miner ETF and these system when you put them all in conjunction about working side-by-side each other I'm expecting the backtest tell me I can expect around 60 to 70% in annual return now I know that sounds really well but again I am trading inverse volatility securities and you know these securities have been shown to deliver incredible returns on certain years but also during other year they could produce very incredible disastrous result which is part the reason why I use algorithm to trade them and don't trust myself to do the manual trading yeah I mean I don't think that sounds [Applause] absurd you know what I mean like you're not trading 10 million dollars so you know - I mean for 60 70 % yeah I you know I think I don't see an issue with it now how do you monitor your strategies in real time like is there anything you do want a day-to-day basis to just check that everything's running smoothly as it should be yeah so you know I work a day job and I don't have the luxury of monitoring my strategies all the time but I host it at my home computer and I've remote remotely connected to my home computer every now and then to check up on my algorithm and see how they're doing see if all the trades are executed or the API still connected what a one of the big lesson I learned this year during the summer was I took a vacation it took about two weeks off to go to Southeast Asia to go back to Vietnam and travel and during that time I still have my algorithm on and they were running just fine and so it was a couple days before my trip was over that the API went offline for some reason and so for a while the algorithmic trading platform now I was using which is called multi charts was not connected to my broker and because I was oversea and did not have regular you know internet connection I was not aware of that and so by the time I found out you know I was already down I think five about 5% or so in max drawdown which you know wasn't a lot but you know it was a stupid mistake that could have been prevented had I you know decided to check on it more often so definitely learn a lesson there too you know even if your algorithm are automated and your strategies are doing a training by themself you still should check in every once in a while to perhaps daily if you can to make sure that everything is running smoothly because you know things can always go wrong you can't Bank on the fact that your strategy will keep on working perfectly a hard person at a time another lesson learned now how's it been for you to hold down a full-time job and do this I guess part-time you know like you do this after hours is that presented any challenges for you or do you find it's you know it's a good lifestyle it's been pretty good for me I mean my algorithms in total since I started um in March they're up close to 17 percent this year so far I know that's nowhere near the 60 or 70 percent market I'm aiming for but they spent a couple of times this year where I turned them off or did not you know let them run a hum percent of time so but the risk adjusted return is very good my Sharpe ratio right now is about 2.0 so and having that running just on a sigh while I'm working I find it to be incredibly easy maybe it's just because I'm not handling a lot of money right now it's just my own personal money and perhaps that's why it seems easy not to worry about you know your money being traded by a bunch of robots in a market but you know I go to my day job I take care of my duties perhaps I cleanse over to my algorithm at home to be a remote connect every 2 or 3 hours or so make sure that everything is running fine and get right back to work and at the end of day I go home and tell you you know how the algorithms performed today and you know if I made money and I lost money something most most imma go home and it's all green some days I go home is red but I've seen that so many times now that I'm not fazed by it anymore no I'm just like oh ok cool and then you know whatever else that I want to do and you know keep the algorithm running for the next day and repeat yeah and are you working towards going full-time into training or are you just happy to keep doing things as our for the time being I do in several different paths one of my plan is to eventually start a hedge fund and implement this D strategies that I've developed for the hedge fund but in order to do that I need to start building track record first so that's one of the first thing that I'm focusing on doing it right now and to us a little bit about you know there's something very interesting about you and that's the fact that you're donating a portion of your profits to charity so do you just want to tell us a little bit about what you're doing there yeah so I have a startup I it's called quant profit this is one of my startup projects Oh website is www.antakungfu.com tative investment strategies that we collect online from various sources like quanto PN and blogs and uh you know podcast even and books and we would sort of just collect all these strategies from online and we would go through them and make sure you know we picked the quality ones we remodel them test and test them ourselves and then once we have you know a third library we put it on our platform and we make it available for people to subscribe to so you know they see for example a gold trading strategy on my platform that they like yeah they can look it up see all the statistics of the trade signal that has taken in the path in the past and if they want to they can subscribe to that strategy and they would receive trading notification trading signal notification from it so as part of this startup we are also running a charity program call we call it trading for charity so what we're doing right now is we seeded the program with $30,000 in March and we hook it up to my trading algorithm system that I've been using and I began the year we in March we said that by the end a year we will take half of our profit generated by the algorithm and we would donate it to step up for Laos which is a nonprofit organization here in Washington State one of my friends he worked with Europe a university was up Washington professor I can't recall his name right now but he has a nonprofit organization here in Washington state called step up for Laos and he for $75 he creates a prosthetic limb and he sends it over to Laos where it is given to children victim UXO unexploded ordinance which is a you know a remnants of the Southeast Asian conflict 3040 years ago there are actually a lot of people a lot of children victim in Lao who step on land mines and you know get their limbs and lakes just torn off and it's a really sad situation over there so you know I'm personally from that region of the world and you know I kind of saw that that scene myself before in life and I decided if I'm gonna start business or start a project I might as well as some corporate social responsibility aspect to it and try to make a difference and you know at the end of the day if you're a trader you can't never have to the too much good karma so you know hopefully my do by doing this hopefully I will inspire other people to you know take the same approach take some of their blessings and winnings from the market and give it to the less fortunate because a little bit of your trading profit over here means a whole world to someone you know half a world way who who doesn't even make more than a dollar a day yeah now respect that man good on you that's that's really impressive well that's uh let's close this out Corey is there anything else you'd like to add I mean what if some wants to find out a bit more about you are you on Twitter and I you mentioned a website before where's the best place to go yeah so if anyone wants to contact me directly they can email me my email is H o ang dot k o ry at gmail.com so that's my personal email you can also reach me at info at quant profit.com okay and I'll also mention you are fairly active in the chat with traders Facebook group I mean that's the that's how I came across you I mean I wouldn't know about you otherwise so I'll just mention you hanging out in there as well if you know wants to join the chat with traders Facebook group its chat with traders comm slash Facebook that will redirect you directly to the group on Facebook you've just got a request to join there and of course I'll accept you in Cory I appreciate you taking the time to do this thanks very much you're welcome Aaron you've reached the end of this episode of chat with traders but rest assured there are more episodes loaded with real market insight and zero hype on the way soon so to stay updated with each great new release subscribe to the podcast in iTunes and we'd love it if you leave a rating and review we'll catch you next time on chat with traders [Music]

Channel: Chat With Traders

Views: 35,155

Rating: 4.8150287 out of 5

Keywords: systematic trading, system trading, algo trading, algorithmic trading, python for finance, quantopian, profitable day trading, day trading success, successful day trading, automated trading strategies, day trading strategy, momentum strategy, mean reversion strategy, how to trade stocks, stock trading tutorial, system trading podcast, bitcoin trading, bitcoin trading bot, automated bitcoin trading, pitchbook, tradestation, multi charts, interactive brokers, trading strategy

Id: Co_GYku903k

Length: 64min 3sec (3843 seconds)

Published: Thu Dec 07 2017