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hi everybody, this is shaun overton with onestepremoved.com and in this video i have michael halls-moore. michael's the owner of quantstart.com, a blog aboutalgorithmic trading. mike thanks for joining me



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sex education worksheets, mike, you have one more interesting stories about how you got involved in finance you want to tell us a little bit about it?yeah, i came out of postgraduate school and essentially,one of my friends actually


after going through a start up he actually said would you like to be involved in an investment of his which was essentially a quant fund, a prop funda nice guy to know. he's a nice guy to know, exactly. i became essentially they're systems developer or quant developer. and then with that we essentially traded for abouttwo months we really started from scratch.everybody has this impression of what a quant it is. you're a quant developer or quant trader


what is that?the quant word is overused quite a lot what i think what people really means is something that involves generally maths or statistics in finance and in a quite heavy fashion. it can mean anythingfrom the guy programming the trading structureright through to the the guy doing the hardcore trading research strategic back testing in a very computational and statistical mannerright it's very nerdy. you got the propeller heads. they're in the back room


exactly.when you're developing a strategy, how important is the actual rule for buying and selling? not as important probably as other aspects. i mean, you can think of it as one big whole system, right? you got you got pricing to deal with, data cleansing you've got the what they call the alpha signalgenerator right that you mentioned and then you have the whole execution and an exchangemodel and an execution process and each those areas has its own


unique challenges essentially. i see that sorta signal generators are one bit of a much larger system, which is not as the importance is on all of these systems working absolutely well rather than one signal. i get to use to signals not to highlight any system, but say have a moving average cross. something everybody knows you look at the signal and you think, "oh, if i would coulda should have done this then i would havemake loads money," but


that's not what funds or quants do at all. it depends on the frequency of what they're trading, which is a very important factor. it probably differs quite a lot from retail. retail is very much at the lower end of the frequency. there's still money to be made there of course, right? quant funds tend to be generally more of the higher frequency. a lot of what they will be studying is optimizing of technology and strategies that are really involved in market microstructures and like say of the


particular assets they're trading. that is quite different approach generally to "you know, i've seen that. i could've bought there. i might've sold there." it's a very different sort of approach. the signals are generated in quite different ways, i think. what is the typical timeframe? what's the difference between a retail trader a guy that just has a trade robot thathe bought off the internet and a guy that's developed it and he has a statistics background and he is a true quant?


depending on what you're trading it could be anywhere from the guy who has bought the robot that sort of guy would want to be checking himself making sure it's not doing anything stupid. and so, you really wouldn't want it to be doing more than a few trades every minuteprobably. that is the absolute cap?it's whatever you can cognitively handle. in the true quant sense the ultra high-frequency stuff will be microsecond and even nanosecond


kind of scale that obviously is not, you know, it takes three hundred milliseconds to blink. you can imagine the kind of latency that you have to deal with in that space is a verydifferent kind of mentality. it's all done with a computer. when you're competing against quants that are trading in microsecondsand your technology is cut streaming fromthe us to your broker server in the uk or whatever


how do you compete?you essentially don't. you are playing on a different playing field, i mean they're dealing with differences on these incredibly tinytime scales. they have their own little games going on down to that level and as a kind of longer-term, lower frequency trader, you're playing you aren't really hugely sensitive to latency. if you're trading once every week, latency is not gonna be your biggest problem having been on the inside and worked in funds


where do you think the retail trader hasthe biggest opportunity? ok, so there's as a retail trader, you could go for more a higher frequency style straetgy and there are plenty of spaces out there where bigger funds, because they got quite a lot to invest aren't able to compete at the lower scale of the money. as a retail trader, you can go there. you can make money even with a relatively sophisticated


strategy. but you do need to be quitecomputationally aware. you need to be good at programming and probably have a bit of a background in math and stats to compete at that end. when we talk about quants, for whateverreason, that is almost always associated with high frequency trading or even ultra high frequency trading in my mind anyway. there are plenty of quant funds who tackle lower frequency stuff. there's quantitative and there's automated. you can have a very low frequency, automated strategy.


it's just that quant funds by virtue of generally who they hire they'll be working at the higher endof the spectrum because that's generally where they have the skills to compete. why is that? why do all the funds focus on these short term strategies. get the money right now, real quick.i think it's because they take quite a scientific approach to how thetrade so they'll be actually trying to exploit physical inefficiency in the system, some of the time. it won't be


quite different from, as you say, coming up with a technical signal and going for it. they'll be saying, right, hang on the exchange works like this, they use thisinfrastructure can we exploit that somehow?so, it's just pure arbitrage? or something very close to it? there's lots of different strategies, one of them obviously being arbitrage there's lots of we know the infrastructure better than the other guy. it is done that way. you can see how it comes from very much a sort of hypothesis first


trade signal second mentality ratherthan, "oh, let's see what indicator gives me a buy or sell." it's done in a very differnt way what is your opinion? do you think you need the science background first and thenyou try to figure out trading or is it better to have the trading backgroundand then you try to develop a strategy i think you need a mix of both. you can't just be a nerd and have a ph.d. no. you can come up with the best


forecasting system in the world. if you don't understand risk management, if you don't understand position sizing you don't understand these core bread and butter ideas in trading, you're going to lose money. you won't have done any statistical analysis on your drawdown characteristics. or even know what drawdown is.or even know what drawdown is. you cannot, i think i believe you need to have a mix of both, frankly, to do well. before we


started recording, we talked a lot about risk management. what is that in your mind and how do youbest go about coming up with the best risk-averse strategy that makes money? i think retail and funds have a very different approach to how they deal with risk. in retail from my experience it seems kind of a secondary consideration to the the signalgenerator.in a bad way or good way? in a bad way. it seems like a dull, boring area of trading. you can see why that is.


you're telling me i can't make as much money as i possibly can. i have to dial it back.exactly. this really comes down to the differences in now retailers and funds operate. funds have institutional mandates what is that?that is, they have to generally present monthly performance for what they're doing. some investors will actually ask for daily performance or even real time performance. you're really under the magnifying glass a lot of the time. for that reason, the primary concern is


not losing money rather than gung-ho.this is for the institutions? yeah, this is for the institutions. especially for your larger institution like pension funds who the people are putting inwell, it's people's pensions.it's people's pensions. they're not going to just throw a hundred-million at you and say, "go for it." they will do an extensive amount of due diligence on you. years of due diligence in some cases. they will want to see very sophisticated risk systems in that regard. i guess a few examples would be they'd want to see exactly


how you go about leveraging up and downand what your actual mentality is for leveraging up and down. it's not just picking it out of the air. there's a protocol?very much a protocol and you know it when i see it idownside insurance policy would be in that regard. a classic put option to make sure your portfolio. they're stress testing you. yeah. you'll also be stress testing yourself.yeah, of course.all the time. there's the industry standard like var, the classic


stress testing. it's more a culture difference i think. it's a risk first mentality. you're always thinking how much is this going to affect my portfolio swing how much of mine is going to be the average volume that i'm trading. it's just constantly assessing risk. whereas in retail, it's mostly, "what's the signal, what's the signal?" exactly so if you are retail and obviously retail traders are primarily profit-driven


how does that change your approach? if you were in an institutional environment your risk management focused in terms of you want to make money every day, even if it's a fraction of the potential money but if you're trading your own money, within certain restrictions and you can only tolerate so much drawdown within that drawdown. you wanna make as much money as possible. how do you go about doing it? there's a couple of actual, specific ways. the classic is the kelly


criterion, which is a means of adjustingyour leverage based on the amount of account equity you have. it can get a bit mathematical so i won't delve too deeply into that. you can google it. the more conservative uses of leverage and cutting back on leverage. that would be very much controlling your drawdown and your growth rate as a sort of slide almost.you say, "alright, well i'm happy to reduce my drawdown at the expense of not gaining as much growth."


obviously, any trader doesn't want to lose their entire equity. that's called gambling.exactly. they'll all be fundamentally using some principle like kelly it's quite a common one. you can go anywhere right up to as i said, the put option mentality basically only half your account and then literally put 50% of your account aside if you lose your entire amount, you've only lost


50%. that in itself is actually quite a good mentality to have in some regard.if you... i've used kelly before and sometimes you have systems that havedone way too well in the past and you plug in the numbers and the optimalkelly is something like risk 30 percent of your account on some but i know from experience that's dumb. what do you do? how do you handle that?i mean you tend to have overlays on top of that. another actual mechanism that is used


a lot in quant funds is what's called leading risk indicators. especially in equities where you've got these new shiny exchange-traded funds popping up allover the place. some of them will be measuring very interesting things like the vix, which you've probably heard of this is the implied volatility index of the options on the s&p 500 and some people use that as a mechanismfor essentially saying what is the future volatility goign to be looking like. you would incorporate a lot of these. if you can imagine putting all of these different factors into a pot


and essentially saying well okay my overallleverage is gonna be this, it's not just dominated by kelly. it's notjust dominated by the vix. mixing them all together and getting a holistic view. you're mixing. you're not just saying here is my entry signal. here's my system that goes within the entry system to come up with the best trading size. the signal generator is piping information to a sort of more important risk management system that says


okay yes, okay no, or downscale by this much the signal generator is convincing therisk manager whether or not to do the trade rather than the signal generator being the be alland end all decision-maker the risk management layer is generally much more important and much heavier do you think you could make money if say that you're trading forex or equities or whatever and you're pushing through a hundredshares every trade and you have stop-loss of fifty cents


every time. do you think you could makemoney doing that? essentially, because stop losses they are quite a controversial thing to do in trading.are they? cause retail traders...in trend following definitely, they are a fundamental part of the strategy you have lots of little mini losses and then all of a sudden.the mega-winner. obviously, if that reverses, you don't want to lose it. that's the whole point of a stop loss, but in


mean reversion, they're a bit more difficult to utilize. even a lot of quant funds specialize in mean reversion they may or may not be using.so you have these huge institutions that are really prestigious and they're not trading with stop losses?i think you'd assess it in a different way/ you'd say to yourself, right, what is thekind of historical distribution of returns we've seen in our backtest. and then you'd say well i've seen a 50 percent drawdown


in the backtest. you might just say, let's get rid of the backtest and start again. but you you'll see some drawdown inthe back testing. you say ok, well in the future i'm likely to see that drawdown if not much worse you would essentially cap it in that regard. that brings up a good point because the signal works and you back test it. you feel good. unless you get really unlucky, it should work up to some pointin the future and then it stops you so that begs thequestion


how do you know when an algorithm isin a drawdown and when you need to turn it off? before you even begin trading, you've carried out the backtest phase. you would then say, right, i've seen a 30 or 25 per drawdown in my backtest, which to me would be pretty high. that's hard to ride through.let's just pick a figure - 25%. if i got anywhere near 25 percent in my in my walk forwards, in my actual out of sample test, i'd just turn it off. time to do some different?


the reason i would turn it off is not because i'm expecting a 25 per cent in the future it's because i'm aware that i do not know. there's this unknown unknowns that could creep in and it may even get much worse than that. you should be expecting worse drawdowns during the walk forward. yes a you might you should it beexpecting were stored and certainly in that raises a good philosophical point. you can't know that your strategy is going to make money in the future. how important do you think it is to try to disprove the strategy?


what's the value in that?i would actually come at it from the point of disproving it. i would use the backtest not as a means of putting something into production. i would use the backtest as a means to filter stuff. getting... imagine starting with 100 strategies. you can then use a computer to backtest the lot. you would filter 95% of them out immediately. just cause of drawdowns? drawdowns, you're not happy with the statistical properties for instance, you might not like the fat tails


as they would call them. it might be too much for you. you're always looking for a filtration mechanism. you want to find a reason to get rid of it always. if you if you're happy that you've not found any reason get rid of it then you'd put it in, as opposed to i've start with this let's try and find everything i can tokeep it. very different mentality you mentioned fat tails and we've talked about trends we talked about range trading. what's therelationship between those trading styles


and the fat tails? what are fat tails for people that don't know.fat tail would mean a lot of the finance is based on the assumption that returns aee normally distributed meaning they have relatively thin tales. there's relatively less extremes occurring then probably do inreal life you'd say they have fat tails. this is the kind of taleb approach.the black swan guy?the black swan, right. there's more extreme events than would occur than you would assume under a normal distribution. you would be


using a distribution that has much more extreme events more commonly.in the quant world because taleb writes scientific papers and he writes black swan in pop literature type stuff how how popular is he?he's a character, certainly. he has very interesting strategies that sort of exploit his belief that these fat tails occur more often than not. they are difficult strategies to carry out.how are they difficult? they are the opposite of what i would call the pennies under a steamroller


approach. you are taking, it's very similar to a momentum or trending strategy where you take lots of mini losses on selling these options, out of the money options and then every now and then, an extreme event will occur and these options will come into the money. he believes these options are mispriced such that you can make more money.do you ever know when you're due for a winner? no. you can only ever say


historically over this time period i've seen this amount and you know you can never be certain. you're trying it always to see if it fits the statistical distribution. you don't know what that distribution is in real life you can only sort of estimate as best you can that distribution and then hope for the best, right, in his case. in my opinion it's quite a tricky strategy.if you, let's say that you have a suite of range trading strategies and have a suite of trend trading strategies


what do you feel more comfortable within in the future? this is a discussion that goes very much goes back and forth depending on which year we're in, right? where am i making money?exactly. i would say quants tend to be... some quants are ambivalent. they will basically try and assess what type of market regime they're in and then apply do they do that quantitatively?they do. i mean this is quite a sophisticated area actually and it's a very tricky one to get right.


there's a lot of them filtering mechanisms that kind of machine learning technology that would be used to try and ascertain whether you're in a range-bound or mean reverting scenario or a trending market. there are lots of ways of doing that but you gotta say, "what time scale am i talking about? am i talking about years? am i talking about days?" when you have a market regime shift i mean it's an unknown unknown


in some sense you can have a kind of view on interest rates you can model interest rates, but that's kinda a purely random event in some sense. it's very difficult to keep it in mind. you'd have to kind of look over historically what the ecb had done and say how likely are they to drop rates? the more sophisticated firms will obviously be tracking all this fundamental data and be putting it into their models. in some sense they would have more of an edge


in that regard to be able to detect these things, but it's tricky. market regime detection is one of the hardest problems to solve in quant finance. for that reason, to actually be able to answer whether we're mean reverting or trending strategy is better at any time is very asset dependent and very dependant on which year you're in. it's a tricky one. with trading, it depends on what you're trading. with forex there's like twenty to choose from. but if you're trading equities you have the opposite problem. there'sfive thousand to chose from. how do you


pick one? i wouldn't be going and picking stocks in the traditional sense. i would try and find some kind of economic relationship between a pair of socks or a triplet of stocks in etfs generally because you can take a more...yeah, why are etfs so popular? they're really quite interesting because what they allow you to do is a company, the fund that sets them up can basically say, "we're doing this specific thing and we will thengive you an exchange-traded


instrument that does this so you mighthave a a possible gold stocks right now i'll settle at war you might have any shifts the triple levels up thenasdaq fortune minus triple letters the nasdaq or somethinglike that and say time you've got low sophistication to buy andsell the system is without having see and because they will exchange traded abase in stop-start celiacs time and see deborah may alsouse generally very very liquid the on on certainthings saying i'm sorry that take okay it might be thebiggest example i can think up with an


e.t.a and tracking error is uso yes the oil etf in the us market and i don't knowwhat it is now but years ago it was 10 percent two years enormous are etf's the dumb money for you knowthat they're gonna do something in you exploit it when they first came outthere was a heavy load index of charge not try to united special night live. the classics&p 500 and you know the st line 119 keep trying to exploitdifferences in that and


here that can still be done you'reyou're investing significant man you technology to do that you okay so what is the advantage in thecurrent market with the tsc i would say it's not so much the anykind of trolls on on that so much for the retailer lisa for talking so it's stability say well like a hand this etf has some peace of mind this issomething to do oil and there's fucking a fundamentalunderlying relationship between these two quantities


okay and the you you could come up witha clutch scientific hypothesis for why say a company that has a basketgold stocks plus another easy if that measures thespot price goal tracks as well for school put in some sense because places or youknow and you can exploit high correlation and and try to fix excuses is a muchmore scientific approach to you here you know basically take apunt on any firm you basically trying to exploit somekind is economic relationship that


should partnership the definition bts staythere okay so you aren't just running mathmodels you do have know what the market is and fbi mean youtube the euro is coming with economy'sfundamental idea is a your i it they're all she complains that hereally questionable may just literally from focus prices from prior priceswithout any concern about i'm fundamentals i mean my personal views you need to mix thetwo okay because these


black swan defense right i mean if ifthere's no you prior horrific volatility in the pricesreason new base model not been you know your pc isa you not to expect a pic downloadablesays the even a one may have just happened prize you look back period say its sam i think going so im prices a cases is a tricky one because you will youwere prolly hurt you in the future circa so we have do we talk aboutperformance


a lot of people have again quite veryhigh level it's got it's a sexy german financewhat's that highest-performing return that you've ever seen aninstitutional finance the highest public 1 i've ever heard of his love it thatthe very things one is renaissance technology they're thebiggest fund in the us ultra seeks is highs the bestmathematicians and statisticians and i tight concord i think they're casketthink women are things with the better i'm they have a huge but 35 percent return every year of fees onevery shot okay so that's where absolute


best the best with math phd's their mindthey're they're very they got a lot on the management processa to them to get back return with that my money is isincredibly impressive because you know it's quite easy to getmuch higher return if you think a small amount toinvestigate doing something in the car high-frequency space we talked a lot about i quants thatleave and they go manage their own money and their trading sixty your accountbalances which is a lot of money in real life


but in in finance it's not a lot ofmoney so a what kinda returns if they're reallygood care are possible on those kinda downturn with larry i mean you know you hittingthe grapevine and people doing twenty 20-25 percent i guess and probably youryet psas time be really wanna be looking at theirrisk characteristics as well as i suck figure cannot be created in isolation noof course not but everybody you know you see it here that use on howmuch money that i make exactly coming i would obviously one look at all to seecharacteristic is a mainland delaney


see how the shop rationing more not buttime i think you you could make a lot ofmoney but the next year you may blow up busy tight-lipped savior i i think thequestion really becomes what's the country's good return on a sensible the averagethat is likely lost long-term and i think you can gently 15to 20 few really good in exploiting something that is actual exploitation %uh the processrather than so the pub condition right so


with the with quants one thing thatcaught my attention is you don't have a magic algorithm like the one algorithmthat does everything for you guy was a sex act upset that you haveheart lies and lies about lindsay got plenty light is coming out as the academic would let some stuff thatyou can begin trading you can replicate its you tend to have struckyou are times where this thing loss to six months a year but then you'll know that newbie you beprepared for two dials you have to sort is


the act would you even consider it i'mcut off for a trading strategy night hunting in the woods hewitt's i'mgenerally keep it going into it's not forming disorders level youexpect in your why you would have a mandate you so youbasically hoping it doesn't politic off a cliff that is the case yet generallythey do you that the solution slightly lower ones do tend to just k like that okay the high-frequency ones can have abit of a cliff fourth and you can see why because they're exploiting thingslike underlying hardware you right now and ifthe exchange the size of greatness


hardware or some some other as incomes and concern seemsthat so that just immediately destroys your your house i heard that's a tough way towhat walk into the office and you're like oh our strategy doesn't work today hey i think that's why these highpreviously cuz he pays column icus suffer through the the the pain that is you know he's thesort six-month research periods where it just compete in the rugby put up fromthe room


he's just like it daily do these guyshave high-stress jobs i wouldn't someone i know been in theipcc's i'd say it's not much more high stress than any othergerman finance the hours on gonna be crazy because they need people to be able tothink rating right you know there's a list studies that saythat anything beyond a 40-hour workweek you come to the ability to missus prettyrapidly and they know that they allegedly dated june people say they'renot gonna make you work $89.00 weeks is


points not look different okay i'm well not only the investment no itknows that it's all here and i mean that you know can you be morehours than ever it's certainly been there with deadlines clearly but its you know it's much morethe the you know for the performance-drivenkind of environment where was getting things done be making moneyhe we're not gonna make you stay acls with dalian a height like yet know is i think about i thinkthere is an a just you know they worked


90 hours a week in a fly around theworld it's just that sounds cool but it's not yet tough gameyeah even matter the so that we'll with a quantitativetrait or be up at night thinking about oh god i got and i i'm only made percent half this month in my boss isexpecting to i mean its if they're a source smartfunds you gonna have monthly losses are somesigns this is the way it is i mean it and police at a lower frequency yespartly and you will it's difficult because you know in yourpractice the really expecting these


periods but as you said you see a niceup with a critique over some looks great in history but when youactually go through that process if you to follow the equity curve itself their periods in its is dropping a landand say in a wall while you're expecting thosethings troops it's still painful the time yes is what's going on what's happeningnothing may be happening because the statistical properties alright in school generally civil whatyou see in the back to assist you


going through the particular period withisrael so is deeds you look at these tests you getreally involved in and it's all scientific in it has a very mathematical approach are daequan summerpanic but your too funny i mean it's a youknow it's here because he was worried about what you don't know you haveincluded in the model this is the guy who are you see herewhere that you have not created the perfect model i think anyone you trusts that modelimplicitly is


probably not a not really thinking froma fully quantitative mines in another because it i mean by definition we couldbe a model is not reality say this silly things as miss was a a.m. and the same here as any proxy sothere's always things you don't need any incoming if this is the whole ethos behind thewall street crash 2081 in a salem it at the models had everything in therethe this probably would have been an issue but


but yeah they did and i mean it there'sreally famous examples like long-term capital management was one other the classics they the if they had and itwas a plus one hundred russian bombs right russian putting mein that sexually please him up i section group yeah exactly but you know that wouldhave been a model dave expected russia's the default missus is quite a black swan style event itsbut he probably wouldn't put it into practice


so does ok whatever get jumpy penny i mean it ends what you do you'reconstantly researching new models in your you very wears a performance allthe time continue the mission force for you youunderstand their draw down periods unitarians limine is on 07 investors some cities and those who don't you theywill understand if you can get you crazy drawdown but ok time it's never fun you know it ithink is she knows they really are lost money akid except it


concern you know and its you just you what you really wanna be saying sois the model doing something was not the right nowi'm not aware of is a lot is whatever's happening summits do theunknown unknown right or is it something that i'm just i'm just saying about period and that'sthe way it might think we're telling me as i can just come up with an algorithmand then move to the beach and forget aboutthere's no there's no sipping martinis early i mean i've had


but this is really funny annotate knowthe country quite funny needs two entities function right man in thedog than that in a day the the man is there to feed the dog andthe dog is there to make sure the man doesn't touch the computer let thistragedy and is that okay that's what i i mean that'sreally what i'm asking as i have this big red button theory where especially traders that by theserobots that i just hit the eject button at the moment something doesn't feelright dick wants to the same thing and there'sthere's a there's a very natural


tendency to want to interfere okay and is often the case theinterfering will generally have a net an adverse effects sewing i mean you the classic situationwould be you know you think you models not fullydealing with the antics in the market opened quickly okay and say you feel that ifyou wait say 10 minutes you might get a you might get betterexecution that's a that's a discretionary is awesome senatordiscretionary overlay and


its is this not hearing to the model imean you have to say to supplying me is is my model then accounting for these enough the the thatthe dynamics of the market open a shortened should i now be putting these into mymodels getting cool if you sensitive during that country's micro-management ithink it becomes you know gv is the best as the wordswhether you're actually running construction of the next year i told mike i think we're at a time yeti want to thank you for joining me yep


and everybody thanks for joining us i and i'm gonna cut their yeah done theme


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