[0.2] I've realized something about trading.
[2.1] Average people who are trying to do day
[3.8] trading, even all the way up to
[5.0] professionals doing trading, they do it
[7.5] completely different than how hedge
[9.6] funds do it. Now, I want to tell you
[11.3] something that I've learned recently
[13.0] that completely shattered my view of
[15.0] trading. And that is that quants are not
[18.4] using trend lines and indicators on a
[21.4] chart to make their decisions. And you
[23.6] might be thinking, well, how on earth do
[25.4] you do it then? Well, that's exactly
[26.9] what I'm going to show you in this
[28.2] video. In the depths of trading Twitter,
[30.4] I found a thread by a person called
[32.2] Rowan. He is a quant. He makes tons of
[35.4] money as a quant. And he's laid out on
[37.5] the table all of the secrets that these
[39.7] hedge fund quants use that get them the
[42.3] results that they do, which outperforms
[44.2] your normal trader and is far more
[46.1] consistent but significantly more
[48.7] complex. I've gone through all of his
[50.7] work on what's called the hedge fund
[52.8] method and I've simplified it into a
[55.2] single video and that's what you're
[56.7] watching today.
[58.2] So, in this video, I'm going to give you
[59.8] a few things. Number one, I'm going to
[61.8] share exactly what the hedge fund method
[63.8] is. Number two, I'm going to convert all
[66.2] of that hedge fund method into a format
[68.5] that is understood by AI. And then
[70.7] third, I'm going to give you an exact
[72.6] copy and paste prompt that you can put
[74.9] into your clawed code or any LLM right
[77.3] now and have this whole method installed
[79.9] into your own trading strategies. And if
[82.5] you're using clawed code, you can use
[84.2] this prompt as a skill in your AI. So
[87.4] anytime you have a new strategy, it will
[89.8] automatically apply this method on top
[91.9] of it. And by the end of the video,
[93.4] you'll have all the tools necessary to
[95.2] operate like a hedge fund quant. And
[97.3] right after you subscribe, let's get
[99.6] into it.
[109.4] In this video, we're going to go over
[110.8] the 10 elements that make up the hedge
[113.5] fund method. And after all of that has
[115.6] been explained, I'm going to give you a
[117.3] couple of prompts. One is going to be to
[119.6] install this onto your Claude code or
[121.8] any LLM that you use. And the other one
[123.9] will be a visualization that you can put
[125.7] onto your Trading View chart using
[127.4] Pinescript. I want you to know that
[129.0] these prompts are entirely free for you
[131.8] to copy and paste and take. I don't even
[133.8] want your email. You can find those
[135.1] prompts on my GitHub link in the top
[137.3] line of the description.
[140.5] The first thing to understand is that
[142.2] these hedge funds and the quants are not
[144.2] operating using the same data that you
[146.6] and I are. I think for the most part you
[148.6] and I go on vibes kind of like feeling
[151.4] our way around the investing like I've
[153.4] got a good feeling about Bitcoin or I've
[155.3] got a good feeling about Palunteer and
[157.0] it's all about feelings. Quants and
[159.1] hedge funds do their absolute best to
[161.9] quantify these feelings actually put
[164.2] numerical values to them. And it's a bit
[166.1] like going outside and saying, "Oh, it's
[167.8] windy today. I'm going to make this
[169.3] decision as a result. Whereas if a quant
[171.5] or a hedge fund went out there, they
[173.0] want a numerical value. How strong is
[175.0] the wind? What direction is it pointing?
[177.1] And then with those numbers, they can
[178.6] make decisions. So I want to introduce
[180.3] to you something called states. Every
[182.6] hedge fund and quant will operate with
[184.9] these states. There are only three
[186.6] states. There is a bull state, a
[188.6] sideways state, and a bare state. Now a
[190.9] bull state is defined as the last 20
[193.8] days. When you add up all of the returns
[195.8] of the last 20 days, are they at 5% or
[199.3] more return? For example, if you had a
[201.4] 1% gain every single day for 20 days,
[204.3] that would represent a 20% gain and
[206.9] obviously would be in a bull state. If
[209.0] you had 15 of the days as a 1% increase,
[211.5] but five of the days were a 1% decrease,
[214.4] then overall you would have a 10% gain
[217.3] over that 20-day period, which would
[219.4] again match the criteria for a bull
[221.6] state. Now if the last 20 days were a
[224.6] negative 5% or greater meaning -5 - 6 so
[229.0] on and so forth then that would be
[230.6] classified as a bare state and anything
[232.8] in between is a sideways state. I know
[235.2] this sounds very elementary but wait
[237.1] until you see how they use this
[238.6] information. And so the next step of the
[240.2] process is obvious. We need to figure
[242.4] out what the state is currently. What is
[245.0] today's state? And so what they do is
[247.4] they go back over the course of the
[249.4] entire asset history. Let's say it's
[251.4] Bitcoin. And they actually run an
[252.9] algorithm for every single day of the
[254.9] history of Bitcoin and label each day
[257.3] with its state. So, if you can imagine
[259.0] now, you've got the entire price history
[260.6] of Bitcoin or any asset. And every
[263.0] single day starting from the 20th day
[265.4] cuz that's the first time you actually
[267.0] have a 20-day looking back period all
[269.5] the way through to today has a label.
[272.6] And each day is a specific state. And
[275.4] this brings us to the third rule that
[276.9] they use as part of this hedge fund
[278.3] method. And it's something called the
[279.8] mark of property. And it's this whole
[281.9] idea that the market only moves to the
[285.1] next place as a result of where it is
[287.8] today. And this goes completely against
[289.8] the way that traders view things. They
[291.8] kind of look back throughout history and
[294.2] try to determine what's going to happen
[296.3] tomorrow. But the Markoff property
[298.2] focuses solely on today. So let me give
[301.0] you a bit of an analogy. Let's say
[302.6] you're driving from Little Rock,
[304.4] Arkansas all the way up to New York
[306.4] City. The route you take to get to New
[308.8] York City will entirely depend on the
[310.7] starting location. This might sound very
[312.8] obvious, but let me make it even
[314.2] clearer. The way you get to New York
[315.9] City from Little Rock, Arkansas, is not
[318.0] the same way you get there from
[319.5] Nebraska. And it goes without saying
[321.2] that as you make your way on that
[322.9] journey, let's say you get to Ohio, for
[325.0] example, the journey to get to New York
[326.9] City from Ohio is also different. The
[329.6] journey to New York from Ohio is
[332.2] entirely unique. It doesn't matter at
[334.5] all that you started in Little Rock if
[336.6] you're in Ohio trying to get to New
[338.6] York. I hope I've made that quite clear.
[340.5] To summarize, the past doesn't really
[342.9] indicate where the future is going to
[344.7] go. And you might be thinking, "Well,
[346.0] Lewis, didn't we just do like the 20-day
[348.2] thing back in history throughout the
[349.7] whole history of Bitcoin? Why would we
[351.3] do that if the past was irrelevant?" And
[353.8] maybe I was a bit extreme there, but the
[355.8] Markoff principle really is looking at
[358.3] today. Today has the most weight. And it
[361.4] brings us to this thing called the hedge
[363.4] fund matrix, which before this video, I
[366.0] had no idea this thing exists. And it
[368.2] makes all the sense in the world. And it
[370.6] brings everything we've talked about
[371.7] already together. Now, with all that
[373.4] data that we've got from the entire
[375.2] history of Bitcoin, there are moments in
[378.2] time where the state shifts. So we might
[381.4] go from a sideways market to a bull
[383.8] market or a bull state and we might go
[385.7] from a bull state to a bare state and
[388.0] each one of those transitions is counted
[391.0] and logged. So what they do is is that
[393.3] they look back in time at every time
[395.5] that transition took place between a
[397.4] bull and a sideways market for example
[399.7] and they tally them all down. So we have
[402.3] now a complete record of the transitions
[405.8] that have occurred and how many times
[407.6] they occurred. So, the amount of times
[409.7] we went from bear to bull, bull to bear,
[413.1] from sideways to bull, sideways to bear,
[415.8] bear to sideways, bull to sideways,
[417.9] every single combination, we've now
[419.5] tallied them all down. And we can put a
[421.5] numerical value on the amount of times
[423.6] that it happened. Now that we've got
[425.4] those counts and that tally, we can turn
[427.8] them into percentages. And that brings
[430.0] us to this very simple 3x3 grid. And
[433.2] it's kind of difficult to explain, so
[434.9] I'm going to show you on screen right
[436.3] here. What you're seeing on screen are
[438.3] three rows that represent today's state.
[441.3] The three columns represent tomorrow's
[444.2] state. And every row has to add up to
[447.4] 100% because something does have to
[449.6] happen tomorrow with 100% certainty. The
[452.7] market does have to end up in one of
[455.0] those buckets. And so you'll notice that
[457.4] there is a most probable outcome for
[460.2] tomorrow's price. And this is where we
[462.1] get the whole concept of the trend is
[464.2] your friend. If you're in a bare state,
[466.2] the most likely outcome for the next day
[468.8] is also going to be a a bare state, but
[471.4] it's not 100% certain. There are other
[473.5] outcomes that can take place. But the
[475.7] hedge funds and the quants are
[477.6] specifically using probabilities to
[480.6] determine what the next day's moves are.
[482.3] And that's moving and progressing every
[484.3] single day as it looks back at all those
[486.4] transitions, all the tallies, and all
[488.0] the probabilities that they can see what
[489.8] the outcome of the following day is most
[492.2] likely to be. So you'll see on the
[493.9] screen right now that we have a diagonal
[496.2] line of cells running from the top left
[498.5] to the bottom right. And these three
[500.3] cells represent the market staying
[502.2] exactly the same. That would be like
[504.2] bull state into bull state, bare state
[506.3] into bear state, sideways into sideways.
[508.5] And the reason I highlight this diagonal
[510.2] is because it shows something called
[512.5] persistence. And that persistence brings
[515.0] about a word called stickiness. And
[517.4] every state has a stickiness score
[520.2] essentially. How sticky is a bull
[522.3] market? Well, if we are in a bull state
[524.8] today, accounting for the last 20 days,
[527.2] it's more likely for it to be another
[529.7] bull state tomorrow than it is any of
[532.2] the other states. Bull states tend to be
[534.4] quite sticky states. And also, bare
[536.3] markets do as well. And so, at all
[538.3] times, there's a live matrix scoreboard
[540.9] determining the likelihood of the
[542.7] outcome of tomorrow. And this is what
[544.8] the quants and the hedge funds use to
[546.8] determine where to place their bets
[548.4] today. So if you know that the
[550.0] stickiness score of a bull state is 80%
[553.4] for example, well then you can quite
[554.9] easily hedge your bets on tomorrow also
[557.1] being a bull state and as a result going
[559.4] long. They're not saying tomorrow will
[561.4] be a bull state. They're saying there's
[563.4] an 80% chance there's an 80% probability
[566.6] that it will be a bull state tomorrow as
[568.5] well. And just to make this super cool
[570.2] and amazing for you, I've actually
[572.2] created a pine script for an indicator
[574.7] that shows the matrix on a chart that
[577.0] you can use right now. So, when we get
[578.5] to the tutorial element of this video
[580.0] where I explain how to do it, I'm going
[581.4] to show you exactly how to install this
[583.0] Pine script into your Trading View. And
[584.9] you can see this 3x3 matrix on your
[588.5] chart for any asset you want. How cool
[591.0] is that? I think it's about time to
[592.5] subscribe, don't you? So, to summarize
[594.4] what we've covered so far, we've talked
[597.0] about what is a state, so we know what
[599.0] the states are. We've also decided
[601.5] today's state. That's the calculation
[603.1] that the hedge funds do to determine
[605.3] where we are today based on the last 20
[607.1] days of movement. We've talked about the
[608.6] markoff property. That was number three.
[610.6] Number four, we've talked about this
[611.8] transition matrix here that the hedge
[613.7] fund is using by that 3x3 grid. And
[615.9] number five, we talked about this
[617.2] persistence, the diagonal line that I
[619.2] showed you there, the stickiness score
[621.1] of the asset. But number six is kind of
[623.4] an interesting move which I never
[625.0] expected. And it is what if we don't
[627.4] just want a one day forecast? What if we
[630.7] want to look further in the future? How
[632.7] do we use all this mathematics and all
[634.4] the and all the information we've
[635.6] gathered so far to determine a more
[638.3] far-reaching prediction of the future?
[640.5] Well, there actually is a calculation
[641.9] for that, and I'm going to show you. And
[643.4] it's something called squaring the
[645.0] matrix. The great thing is is that you
[646.8] don't need any new mathematics. You've
[648.6] already got it already. So, all you have
[650.4] to do is simply multiply the matrix by
[653.8] itself. So, if you want a 2-day matrix,
[656.7] you square the matrix by itself. If you
[659.3] want a three-day forecast, you cube it
[662.0] against itself. And don't worry, I'm
[663.6] going to show you an example of this
[664.8] with real numbers. But it goes on and on
[666.7] and on depending on how far away you
[668.5] want that prediction. And of course, as
[670.5] you keep squaring and cubing against
[672.7] yourself, the number ultimately of
[674.9] percentage, the probability percentage
[676.7] is going down over time. So let's do a
[678.9] three example and I think by the end of
[680.3] this you'll understand it. So path
[681.8] number one would be like going from bull
[683.9] to bull. So from the example we used
[686.1] earlier, there's an 80% chance that if
[687.8] we are in a bull state now, it will be a
[690.0] bull state tomorrow. But the chance of
[692.2] that bull state remaining for the the
[694.5] following day is essentially 0.8
[698.1] representing 80% times by 0.8. We're
[701.2] tsing it by itself, which leaves us with
[703.8] 0.64, which is 64%. So, we've got our
[707.4] 2-day forecast predicting suggesting
[709.9] that there's a 64% probability that in 2
[713.0] days time we will still be in a bull
[715.0] state. And so, by doing that calculation
[717.0] for all the different combinations, you
[719.1] end up with the ability and a basically
[721.0] a way to kind of show on a huge matrix
[723.6] with percentage probabilities all
[726.1] perfectly laid out what the chances are
[728.2] that that asset will be in a specific
[730.5] state in a specific amount of days. You
[733.1] can see how different this is from doing
[734.7] trend lines and stuff, right? This is
[736.6] mathematical and equationbased. And this
[738.6] is what quants are doing. This is how
[740.2] the people who understand this as
[742.4] college kids end up landing jobs that
[744.5] are $650,000
[746.2] a year out of college. And that's true
[748.4] and I am making a video about that. But
[750.2] if you extrapolate this idea out quite a
[752.6] bit, instead of looking 2 or 3 days
[754.2] ahead where we're doing nice cute little
[756.2] squaring and then cubing these numbers,
[758.8] let's say you wanted to do a 28day
[761.6] forecast. Well, now we're getting into
[763.5] something where we're now multiplying
[765.0] the matrix by the 28th power. And these
[767.6] numbers start to get mind-boggling. And
[770.3] actually, if you look at it on a chart
[772.3] to see the kind of distribution of
[774.2] percentages, you'll see that it all
[776.0] basically converges into a single
[778.2] slither. And that slither represents how
[781.6] the probability of any of these outcomes
[784.0] is so small that there's no meaningful
[785.9] signal that you're getting from it. You
[787.4] know, for example, it might say, you
[788.7] know, in 28 days time there's a 0.2% 2%
[791.3] chance of this outcome. There's a 0.2%
[793.9] chance of this outcome, this outcome,
[795.4] this outcome, this. They're all going to
[797.0] be uniform, like 0.2%, but there's going
[799.5] to be so many outcomes and so many ways
[801.4] to get there that there's not really any
[803.2] point in using that projection down the
[805.8] line. And that is number seven, the
[807.9] stationary distribution. And so, how do
[809.8] you actually extract signals from all of
[812.4] this to actually make some trades? Well,
[814.4] it requires a process called signal
[816.5] generation. And that's number eight.
[818.2] Because when I'm thinking about this,
[819.2] I'm like, okay, all this maths is good,
[820.6] but what do I do with that information?
[822.8] Well, despite all of the calculations
[824.6] and all the equations that have come to
[826.7] this point, the calculation is
[829.2] incredibly easy. And that's what I found
[831.5] with the way the quants operate. They do
[833.4] lots of complex things in the background
[835.4] only to simplify it with that
[837.6] foundation. So, what they do is is one
[839.8] simple calculation of this thing minus
[842.3] this thing. And so, let's talk about it.
[844.6] Basically, they're looking at tomorrow,
[846.4] the probability of tomorrow being a bull
[849.0] state. And what they do is is that they
[850.8] subtract the likelihood of it being a
[853.1] bare market tomorrow from the bull
[855.3] market probability. And here's the
[857.1] genius part. The larger the number that
[859.6] you get as a result, the more money you
[862.1] will put into that trade. So the
[864.3] differential between the bull and the
[866.1] bear in this case determines how big
[868.2] that trade is going to be. So you're
[869.8] managing risk that way as well. So let
[871.8] me give you a concrete example. So,
[873.5] let's say the chance of a bull state
[875.2] tomorrow is 65%. And the chance of a
[878.0] bare state tomorrow is 20%. And of
[880.6] course, because we have to add up to
[881.8] 100, there's a 15% chance that we're
[883.9] going to be in a sideways state
[885.2] tomorrow. So, to extract your trading
[888.0] signal from this, all you do is take 65%
[890.9] which is the bull probability tomorrow,
[893.5] minus 20%, which is the bare probability
[897.0] for tomorrow, and you're left with 45%.
[900.0] So we've got the direction because it's
[901.9] plus 45%. So we know that the idea is
[904.8] that we're going to go long. So each
[906.5] quant and hedge fund will have their own
[908.1] calculation for you know how strong is
[910.6] 45% and how much will they put on that
[913.1] trade. I'd imagine that every hedge fund
[915.0] is going to be slightly different in
[916.3] that way. You know some people might
[917.8] look at a plus 45% as a really strong
[920.4] signal and put lots more into that trade
[922.3] and others might look at that as a
[923.8] little bit weaker and put less in. But
[925.5] the point is it's giving you the
[927.0] direction. And you might be wondering,
[928.4] well, how could that ever be negative?
[930.7] Well, you're doing the same calculation.
[932.4] You're taking the bare percentage away
[934.2] from the bull percentage. So, if the
[935.9] bare percentage is a larger number than
[937.8] the bull percentage, then you're going
[939.3] to end up with a negative number. And
[941.0] so, the signal is to go short. And the
[943.0] degree to which that outcome uh is
[945.4] revealed is the degree to which you
[947.2] enter that trade. And so, this is far
[949.4] from the idea of like Bitcoin feels
[951.3] bullish today. It feels good today. This
[953.4] is like far away from that. This is
[955.3] calculations to say, you know, this is
[957.5] how bullish I am or this is how bearish
[959.3] I am and this is how much money goes in
[961.2] as a result of that. It's calculated.
[963.8] It's simple but complex. It's truly
[967.0] amazing. So now, as we move into step
[969.6] number nine of the 10 that we're going
[971.2] to go over in this video before we get
[972.6] into the tutorial, the tutorial is
[974.2] relatively quick. I've just got a copy
[975.6] and paste prompt for you. So cool. In
[977.5] step nine, we're going to do something
[979.0] called walk forward back testing. Now,
[982.2] this walk forward back testing has taken
[984.1] me a lot of time to try and comprehend,
[986.2] and I'm not entirely sure I still do,
[987.8] but I'm going to explain what I do
[989.2] understand, and hopefully it will make
[990.7] sense. Now, when you're trading, often
[992.9] times, we'll create a strategy, and
[994.9] we'll do a back test on it. That back
[997.0] test basically takes all of the data
[999.4] that has happened in the past and
[1001.0] applies the strategy to all of that
[1003.0] history. So the issue is and this is
[1004.9] where people come into a problem
[1006.8] especially as retail traders is that you
[1009.4] take that strategy with all the
[1011.1] information it's learned from all of the
[1013.2] all of the data right and you take that
[1016.0] strategy and implement it into let's say
[1018.9] 2020. Now it's not a good back test
[1021.7] because the data from 2020 has already
[1024.3] been baked in to the entire back test
[1027.7] and you're applying it back in time.
[1029.9] This is really complex, but it's not a
[1032.0] good back test because it's already
[1033.6] learned from the future. If you're
[1035.4] placing the strategy into 2020, for
[1037.4] example, it already has the future
[1039.8] outcomes baked into the strategy. And
[1042.1] so, it doesn't make any sense. If we've
[1043.9] got all the data right now as of today,
[1046.2] that means it's learned from 2020. It's
[1048.4] learned from 2021 already. And so, this
[1050.7] walk forward back testing thing is a
[1053.4] mitigation against that. Now, it's
[1055.4] massively computationally heavy, or at
[1057.8] least it was before AI. Hint hint. But
[1060.7] every single day has to be entirely
[1063.4] recalculated. So, the whole matrix has
[1065.6] to be entirely redone. So, we never have
[1067.8] that issue of having a strategy that's
[1070.4] learned from all the data applied to the
[1072.6] past and it just doesn't work. From my
[1074.7] understanding, that's how it works. And
[1076.2] if you don't understand, you kind of
[1078.2] don't need to because it's going to be
[1079.7] in the AI to do this for you. Now, we're
[1082.3] at number 10, and things are about to
[1084.1] get mind-blowing, okay? And so, prepare.
[1086.4] Earlier on, we talked about defining a
[1089.1] state. Like, what are the numbers that
[1090.9] define a state? We said, you know, 5%
[1093.4] and up means a bull. Negative 5% and
[1095.8] down means a bear. And anything in
[1097.8] between is sideways. But that's
[1099.6] subjective. Like, who decided that? We
[1101.7] decided that. Humans decided that.
[1103.2] That's a subjective interpretation of
[1105.5] what a bull and bear means. And
[1107.7] obviously then we come into this natural
[1109.8] flaw of the system doesn't work now does
[1113.0] it? How can we have these subjective
[1115.1] opinions and everything else is kind of
[1116.8] calculated and mathematical but we're
[1119.4] still left with the weakest link which
[1121.5] is our subjective view. And so step
[1123.7] number 10 closes all of that out and
[1126.2] solves that problem. Solves that
[1127.9] subjective behavior that ultimately
[1129.8] allows us to really determine what bull
[1132.4] means, what bare means, and what
[1133.8] sideways means. And this is called the
[1135.7] hidden marov model. And this is a part
[1138.2] of the process that looks back over all
[1140.6] of the price history of the asset we're
[1142.5] looking at. All of the transitions, but
[1144.6] all of the states and the labels that we
[1146.6] attached to them earlier have been
[1148.7] removed. So it's not learning from the
[1150.9] labeling of states anymore. It's
[1153.0] actually doing a whole pass through the
[1154.8] strategy of pattern recognition itself.
[1157.7] It's looking at details like the
[1159.2] continuation of the price going up or
[1161.0] the price going down. is looking at a
[1162.6] whole load of different data points
[1164.8] without the labels. And so to make this
[1166.7] like super simple to understand, it's
[1168.7] almost like a babysitter. They come into
[1171.1] the house and there's a whole bunch of
[1173.0] children in there. They don't
[1174.2] immediately know, you know, this child
[1176.2] has ADHD. This child sleeps all the
[1178.9] time. This child is crazy and violent.
[1180.9] You know, they don't know any of that
[1182.2] stuff. And so a few days later though,
[1184.6] once they've sat there and they've
[1186.1] observed the children and the way they
[1187.8] act and the way they interact with each
[1189.8] other, you can determine a whole bunch
[1191.4] of things about each child and assign or
[1193.8] prescribe a personality to each child.
[1196.0] But it takes time to kind of analyze and
[1197.8] sit back and watch. And that's what this
[1199.8] hidden marov model is doing. And after
[1201.8] all of that, now let's determine the
[1203.5] personalities of the children. It'll
[1205.5] actually put a label on the children
[1207.9] like ADHD, violent, sleepy. it will do
[1211.8] that across all of them. And it's doing
[1213.8] the same thing across the data of the
[1215.8] chart. So it's now actually prescribing
[1218.7] a bull state, a bare state, and a
[1221.5] sideways state without any labels
[1223.6] existing previously. And so when you
[1225.7] overlap the two of those where you've
[1227.5] got the you know the 5% is a bull
[1230.2] negative 5% and below is a bear the the
[1232.7] subjective labels that we gave and also
[1235.1] the hidden marov method labels that were
[1238.0] generated you can overlap them and see
[1241.1] where they are confirming each other and
[1243.8] when they confirm each other that gives
[1245.7] you the green light to move ahead right
[1248.1] now that we've understood all of that
[1249.5] and I hope you have that was all 10 of
[1251.7] the elements that make up this hedge
[1253.4] fund method but it's all kind of useless
[1255.5] to you as just information. We need a
[1257.9] real way to apply this into our own
[1260.0] trading strategies and specifically
[1261.8] using AI, get this onto our computers
[1264.2] and running for us. So, you're going to
[1266.0] get a couple of things here. The first
[1267.4] thing you're going to get is a Claude
[1269.5] code skill. This skill you can install
[1272.5] into your computer, especially if you're
[1274.6] using Claude Code. If you're not using
[1276.2] Claude Code and any other LLM, you can
[1278.2] actually take the oneshot prompt and it
[1279.9] will just learn it on your system
[1281.6] regardless of whether it's Claude Code
[1283.1] or not. But this skill, this system will
[1286.2] be applied to any trading strategy that
[1288.7] you ask it to apply it to. So if I've
[1291.2] got my strategy for Bit Tensor and all
[1294.1] the subnets like I actually do in real
[1296.0] life, I can copy and paste this prompt
[1298.4] into my Clawude code. It can learn it
[1300.7] and determine what needs to change about
[1302.6] my strategy to go in accordance to this
[1305.4] hedge fund method. That'll be a copy and
[1307.4] paste prompt that will take you through
[1308.9] from beginning to end very simply
[1310.9] regardless of how much experience you
[1312.5] have with AI or with trading. And then
[1314.5] as a little bonus, I've created a pine
[1316.5] script. As I mentioned earlier, this is
[1318.1] a way to visualize the 3x3 grid of
[1321.2] probabilities on your chart inside
[1323.4] Trading View. This will be a separate
[1325.0] copy and paste that you can go straight
[1326.6] into your Pinecript editor on Trading
[1328.6] View and paste it in. So with that,
[1330.9] let's get into the tutorial.
[1334.2] All right. So, first things first is
[1335.9] you're going to go to the first line in
[1337.8] the description of the video and you'll
[1340.3] be brought to a GitHub page. The GitHub
[1342.2] page is going to give you all the code
[1343.6] of everything I've worked on so far.
[1345.3] It's going to give you the pine script,
[1346.5] the oneshot prompt for you to install on
[1348.5] your Clawude code or any LLM for that
[1351.0] matter and I'm going to walk you through
[1352.6] how to do that. So, you've come over to
[1355.0] the GitHub right now and you can see a
[1357.0] series of things. Uh if you just kind of
[1360.0] come down and see, you can see the two
[1362.4] elements of this. The on camera build
[1364.3] that we're doing right now. This is the
[1366.0] Marov hedge fund method. If you click
[1368.6] that, it will open up a link in another
[1371.4] tab. And we're also going to click the
[1373.1] pine script bonus as well if you're
[1375.3] going to use this for trading view. So
[1377.3] here is the hedge fund method skill that
[1379.9] you're going to install into your AI. So
[1383.0] you're going to copy it from this moment
[1384.6] onwards all the way down. It's going to
[1387.1] this is all the information that I've
[1388.8] kind of put together so that you can uh
[1392.3] create this skill in your system. So,
[1394.4] I've copied it. You're going to come
[1395.7] over here. You're going to click paste
[1397.3] and click enter. There's then going to
[1399.1] be an onboarding process that you'll go
[1401.1] through where it's just going to install
[1403.2] this whole thing into your computer. If
[1406.2] you're on claude code, it's going to
[1407.4] create a skill. So, anytime you have a
[1409.4] trading strategy, you can just say,
[1411.0] "Hey, can you do the Markov run the
[1413.1] Markov skill here?" here and it will go
[1414.5] through the whole process to make sure
[1415.8] that the strategy is, you know, beefed
[1418.0] up. So, it said I'm going to install the
[1419.7] mark of hedge fund method skill into
[1421.9] these this file about 90 seconds on Mac
[1424.6] and Linux and up to two to three minutes
[1426.2] on Windows. You don't need any keys or
[1428.4] accounts or admin passwords. Great. This
[1430.7] is Rowan's framework on Rowan Chain, an
[1433.1] observable marov regime model that
[1435.4] builds a bare a bull bare sideways
[1438.1] transition matrix from any ticker.
[1440.6] Great. So if you're ready, you just type
[1442.2] go and it will start the process.
[1446.0] And it's basically done with the process
[1447.6] now. We've been about 2 minutes and 21
[1449.6] into this. And you can see that phase
[1451.5] four of this whole process of the
[1452.8] onboarding. It says it's going to run a
[1456.0] um a marov reggime basically on the spy
[1459.8] 10-year chart. And this is just a demo
[1462.3] to show that it does in fact work. You
[1464.9] could also then after this just say,
[1466.6] hey, run it on Bitcoin, run it on
[1468.1] Ethereum, whatever you want to do. And
[1469.8] it will apply the Markov regime,
[1471.7] everything we've talked about today to
[1473.5] that asset. And it really can be an any
[1475.8] asset. And just like that, the whole
[1477.8] Markov hedge fund method skill has been
[1479.8] installed. So whenever you want to use
[1481.9] it on a strategy, you just type forward
[1484.0] slashmarkov
[1486.0] and you can see hedge fund method. You
[1488.0] type that there and then talk about your
[1490.0] strategy or whatever. And that's how it
[1492.3] works. Next, we're going to just talk
[1494.5] about how we can apply the Pinescript
[1496.7] into our uh trading view. And all you do
[1499.4] is come over to the Pinescript page that
[1501.3] we talked about earlier. Click copy raw
[1503.5] file right up here. Then you can go over
[1505.8] to your trading view. I've already got
[1507.5] mine installed, but I'm going to delete
[1509.0] it so you can see it all work. On the
[1511.5] right hand side, this is on the desktop
[1513.7] app, by the way. We've got a mountain
[1516.0] looking icon. That is the pine script
[1518.3] icon. You can click that. And sometimes
[1520.6] it helps just to bring this out a little
[1522.2] bit further. Uh we can do control A or
[1526.2] command A to select everything and we
[1528.2] want to delete that. Then we're going to
[1529.7] click commandV which is paste. This is
[1531.8] the pine script right here. And all we
[1534.2] want to do is click the play button here
[1536.0] which is to add to chart. We can now
[1538.2] close this and we wait for it to
[1539.6] populate on the chart. And remember this
[1541.7] is the Bitcoin chart. And there we go.
[1543.4] The Markov regime has been uh laid on
[1546.3] here. This will work for any asset
[1548.3] because it's just doing the calculations
[1550.0] automatically. And the one to look at,
[1552.1] obviously, we've explained the nine the
[1555.0] nine kind of card uh view, but the long
[1558.3] run mix is the the one that I like to
[1561.0] look for. So, if we look at the bull
[1563.0] percentage for tomorrow, it's 29% chance
[1567.4] of tomorrow being a bull run. Tomorrow
[1569.5] being a bare market is 42% chance and
[1572.4] 29% chance of it going sideways. And so
[1575.1] that that bare market being the highest
[1577.0] percentage, the highest likelihood is
[1579.0] because we have bare behavior um uh
[1582.5] recently, right? It's just it's a sticky
[1584.8] state as we talked about. So that's how
[1587.1] it works. It all works here. I'll
[1588.6] actually go and change the the chart.
[1590.6] Maybe we do let's say XRP for example.
[1594.6] And again, it applies the numbers for
[1596.7] XRP as well. And you can do really
[1598.7] anything here. Um I don't know what else
[1601.0] I can kind of show. Stocks, Tesla. There
[1603.4] it the mark of regime works for that as
[1605.8] well. All right, so I hope you've got
[1607.5] tremendous use from this. This is one
[1609.6] part of a potential series on the topic
[1612.6] of quant strategies that we can use AI
[1615.0] to implement. If at any point you're
[1616.9] doing this process and you hit a
[1618.3] roadblock, you can always uh get in
[1620.6] touch with me on 01 systems. It's the
[1623.7] second link in the description. That's
[1625.5] the only place really where I can
[1627.0] provide feedback and help people with
[1628.5] issues and bugs that they have along the
[1630.5] way. So check that out if you're
[1632.4] interested and I'll see you in the next
[1633.7] one.