Ep 2: Why Hedge Funds Outperform for retail market? (w Jeff)

Welcome to the show. Would you classify what you are doing as an algo trader, as in use algorithms or, you know, it’s all human intervention?

Jeff: Yeah, so what we do is more of discretionary than systematic or quantitative in that sense. 

Sato Shi: What does that mean? 

Jeff: So discretionary, we will basically look at the macro trends in general and see how the market is actually moving. Then make a decision. So there’s a lot of human intuition that goes into it, and a lot of, say, your macro knowledge that you have to understand and delve in deeper itself. Yeah. So basically that’s kind of what we do. But if you look at, say an algo trader, or quant trader, then they usually have a rule-based system, or they look at some form of mathematical models to try to understand things a bit better and very little human intervention to try to get in and out of risk itself. Yeah, that’s what I would say. 

Sato Shi: Then can I just ask your opinion? Because you know, you’re speaking for us humans. Do you find a particular way superior? Is human intervention superior to that? Will humans get phased out in the future? 

Jeff: I wouldn’t think that humans will get phased out in the future. I think that’s the worry of a lot of industries as well. Particularly for trading, I think one thing to take note is that you are going to have to be able to think of how the different market participants are actually playing out this huge game or a puzzle even. Yeah. So yes, you might be doing some form of systematic trading or you may be doing some form of algo to try to understand a bit better  of the markets by looking at this data, to see how you can find some form of alphas, which we will kind of go through later as well when we talk about a hedge fund strategy. 

And at the same time, of course, when we look at, say, on the discretionary front of things, we also try to automate some of the processes because when we look at things, there’s a lot of information that comes in and out. So we got to streamline certain things. We got to only take in the information that’s essential to us and look at those, then make a decision from there. 

So I think eventually, what will happen is that things will become more of like fundamental in that sense where you still have to use some form of fundamental data to look at things from a different angle and use the quant methods itself to help you to better craft your own decision. Like maybe if you think about it, like your transaction cost analysis or even say, at which point do you try to put a trade in or get out of a trade? Yeah. So things like that will actually matter in the near future. 

Sato Shi: And I mean, from a layman point of view, when you talk about fundamental, you’re referring to market events, am I right to say that?  

Jeff: Yeah, market events. Or maybe your accounting. Like your 13F on the SCC filings and things like that.

Sato Shi: Sure. So this is what you mean by a  fundamental and quant — can you just give us a insight, you know, like for quant, is it like, you know, candlesticks or?  

Jeff: From the client perspective itself, a lot of it, they look at, like I mentioned, mathematical models. So it can come in the form of, say, your factor-based model or statistical arbitrage, or maybe some form of trend-following strategy.

So I think one of it is — momentum is a very big thing that people look at and mean reversion as well. Yeah. So all of which will rely very very little human judgment with respect to trading decisions outside of this model. So you basically are paying a lot for this quant analyst to try to be very intelligent models, to predict what to trade next and when to trade next.

Sato Shi: I see, and the model will give you the answer, am I right to say that? 

Jeff: Yes. That’s right. 

Sato Shi: Will model like give a probability or is there like a firm answer most of the time?

Jeff: It depends on how you build it. So if you look at, say, statistical arbitrage, we usually see things from a pair trading perspective. So, say, for example, if I’m going to trade Pepsi and Coke. Then it depends on the market events that goes around or the corporate actions that goes around these two different companies itself. So maybe for whatever reason, there’s an event that’s going to cause a Coke price to soar. And we know that the demand for the Coke will definitely increase.

So we expect that, yeah, for sure that the Coke stock price is going to increase. So why not just buy into it? And then we short the, yeah, we just short Pepsi altogether. And so in that sense, you have a distinct output. Yeah. But if you say you looked at factor based modeling, you, you get more of an overview of this stock universe or equities universe, then you see whether you want to invest in some of these different equities. That is when maybe some form of discretion will have to come in, or maybe you can even build a model to determine the portfolio composition and see how you can further implement these trades ideas as well. 

Sato Shi: I see. I see. So would you say that you are employing some sort of factor-based modeling on your end because you are discretionary, am I right to say? In factor-based modeling, I think it comprises of discretionary elements. 

Jeff: Yeah. I wouldn’t say that I do a lot of factor based modeling because factor-based modelling means that you have to look at some form of regression models as well. 

Sato Shi: What’s a regression model? 

Jeff: Yeah so, like back in high school, we all learn like y = Mx + c…

Sato Shi: Okay, so more of like algebra and very complex mathematical equations. 

Jeff: Yeah. So on my end, very recently, we had the Trump and Biden US election. Very, very recent. So I will look at it and see, oh, like, what are some ideas that we can generate our base? Like, is there some of the, maybe in the credit space or say in the fixed income space, is there things that we can try to leverage upon depending on the movement of the markets?

So it comes to a point where you actually think not just what you would like to do, but what the other participant would also be trying to do. So you want to be on the right side of the trade. Not on the wrong side, ’cause after all like I mentioned earlier, one should always try to get out of the position as risk-free as possible. 

Sato Shi: So all this comes from yourself, am I right? There is no model telling you how to think? Is this all Jeff, like, or is there like a computer program, you know, guiding you through? 

Jeff: Yeah. So I do look at a couple of things. Like I build my own indicators to take a look. Some of it is like to get in and out of position, maybe you look at the technical analysis aspect of things. Other things will be relying heavily on what I learn in macro economics in school. So, thanks, Prof. 

Sato Shi: So your education is still helping you. ‘Cause most of the guys, you know what, they throw away whatever they learn in school, but apparently you are still employing, so I think your lecturers will be very proud of you. If I could put a number to it, in terms of the proportion, is it like 80% Jeff, 90% Jeff, or 10% you know, those tools are helping you? How would you classify it?

Jeff: I think I would classify it in more like 70% Jeff, 30% having to scrape whatever that’s necessary and just take a look at them, then just come up with a judgment and before making a decision itself.

Sato Shi: So, I mean, from an investment angle point of view, can you just give us an understanding, because I think you’ve been to the other sides already. You know, what do the hedge funds really do from that angle? 

Jeff: Okay. Yeah. So from that point of view, so I think before we even delve into that, then we really need to understand what a hedge fund is.

So a hedge fund is a regulated investment fund that is typically open to a limited range of investors who actually pay a performance fee to the fund’s investment manager. So as we will discuss later, so like every hedge fund will have their own kind of investment philosophy that actually determines the type of investment made and the strategies they actually employ . 

In general, so in the hedge fund community, it undertakes a much wider of investments and trading activities than say your traditional long-only investment funds like mutual fund ,  asset managers. And hedge funds also invest in a broader range of assets that includes long and short positions in equities, bonds, commodities, and yeah, even derivative. Yeah. 

Sato Shi: I think you just shared a bit about, you know, the definition of the hedge fund. But, you know, from a layman, you know, if you want to actually understand the hedge fund business… 

Jeff: Yeah, so the hedge fund business essentially is just trying to make profit with limited regulatory constraints on them as opposed to a bank. But the thing is that a typical investor, like a retail investor, will find it very hard to break into because of the performance fee that the fund actually charge. It’s going to be very expensive. So very commonly, if you try to invest in a hedge fund, then you see things like 2/20.

And you’d be wondering, right, you’d be wondering like what exactly is 2/20? So actually  most of the hedge fund work on this 2 and 20 manager compensation scheme. So it means that the fund managers themselves will get 2% of the assets and performance fee of 20% of the profit every year.

Sato Shi: That sounds extremely insane. 

Jeff: Yeah. So yeah, given the nature, right. The hedge funds often have very aggressive  goals, which allows them to be very lucrative in trying to produce all these strong profits. But the structure itself have been widely criticized by a lot of people, given that the hedge funds, say, for example, the hedge fund is going to lose money that year on profit, the fund manager is still going to make a cozy amount. 

Sato Shi: You mean, even when you lose, they still have to take their fee? 

Jeff: Yeah, because you’re definitely going to be able to gain a cozy amount from  that 2% of investment asset. 

Sato Shi: I mean, then why does, why do people even still invest in the first place? I mean, it doesn’t make sense. 

Jeff: Yeah, that’s right. So I guess the performance fee itself, that 20% that is put forth, is the defining characteristic of a hedge fund. So it actually motivates the hedge fund manager to generate superior returns and it’s intended to align the interests of the manager and the investors, more than just a flat fee, say, typically you have with a mutual fund or asset manager. 

So to simply just put it is that, hedge fund manager get rich if you generate superior returns and thereby making their own clients rich as well. 

Sato Shi: I see. But I mean, 20%. Wow. Okay. But of course they don’t earn the 20% if it’s a loss-making investment, am I right to say that? Just earn the 2%. 

Jeff: Correct. Yeah. Well, I mean, like I mentioned, it’s going to be very difficult for retail investors to break into this industry because high fees is one. So the people that can actually invest in it will have to be worth a net 1 million, US dollar. 

Sato Shi: Is this a regulatory constraint?

Jeff: Yes, this is a SSC constraint. Or actually have annual income of 200k. So even in Singapore itself or Hong Kong back in APAC right now, we do see such a fee structure put in place. So to be a investor, accredited investor itself, these are some of the basic components that you have to achieve before you can go about to put your money in the hedge fund.

Sato Shi: So yeah, you have to get a license la basically. To get the license, you have to show that you have a track record, am I right to say that? 

Jeff: That’s right. 

Sato Shi: So would you say that the, you know, the barrier to create a hedge fund is not … it’s not insurmountable because there are so many right now fighting? 

Jeff: I would say  that well, it’s not wrong to say that there’s a lot of hedge funds that goes around, but let’s just take a historical look at some of the mega funds, for example. Like you have like SAC Capital that actually reported a return of 30% per year, and that’s on a net basis. And you have like Soros fund management, they actually reported 20% year on year. And of  course the Renaissance’s Medallion Fund reported 35% ever since 1989. 

Sato Shi: And that is astronomical returns, am I right to say that?

Jeff: Exactly. So one thing is that if you look into it with this. Not just 100, I think like there’s over 1000. Like in the US itself, there’s over, I think over like 5,000 different hedge funds that goes around, but not every one of them are actually making money. They are trying to be the next SAC or next Renaissance that is up and coming, but yeah, just simply doing a computation, then you realize that this average return yeah, it’s actually unappealing when amateur funds are just struggling to just keep up with the performance. 

Yeah. But even if you account for like the survivorship bias in that sense, and you took the entire hedge fund industry and weighted it by AUM, you’re definitely going to find that the cap-weighted aggregate annualizes returns to beat the benchmark. Yeah. That’s for sure. And, let’s say, but if you simply look at any of this random hedge fund, like throw a stone, and you hit one of these smaller hedge funds. Yeah, you probably wouldn’t find any alpha there. On a whole industry-wise, definitely that’s some form of astronomical return. 

Sato Shi: But it’s only for, I mean, more of the big boys, am I right to say? 

Jeff: That’s right. 

Sato Shi: Because I think, you know, if they’re not going to make as much as what the big boys are earning, I think the small guys, they have to cut down on their fee structure already. Does that make sense? 

Jeff: Yeah. Cutting down on fee structure is one thing, but it’s also because it has always been more of a, I think, it’s  more of a ritual in that sense, right? Like you put in all this performance fee to actually try to incentivize your team to work harder, to try to seek more alpha in that sense.

But after all, alpha is a zero sum game, and it’s definitely very hard to find good alpha  managers. And there’s also very established pattern for distribution of alpha across a fund life cycle. But none of this is relevant in a sense if you just try to weight it by AUM in the whole industry. Then you’re going to see that even the most median hedge fund is going to have negative alpha. They’re never going to be able to make superior return. In fact, inferior returns. 

Sato Shi: Yeah, sure. But I mean, it only make sense that they’re ultimately  forced to exit the market. Am I right? Because if you are you know, having negative returns now, there’s no reason for your existence already. So how are they still around? 

Jeff: I guess sometimes some people get lucky. There’s a huge element of luck. And also it depends on the kind of strategies that you employ. Yeah. Like Vanda Capital in Singapore, the fund manager himself made quite a big bet prior to the COVID. He actually made superior returns through that one trade itself.

So you have such instance where people actually put on huge positions making a loss for a really long period of time before yeah, getting that positive alpha out there. And another one you can think of is Nassim Taleb. So he’s the author of Black Swan and Fooled by Randomness. So he has a fund as well, mostly focused on trading tail risk, and prior to COVID, he wasn’t doing very well , just decent returns here are there, but closer to COVID or rather during COVID, he’s actually making quite a bit because of him having to achieve these tail risk trade that he had put on really, really long ago.

So. I, I do think that if you have a good idea, if you think that you have something in mind it’s worth a shot, just trying to put a trade out there and see how things go. But of course, like through this whole life cycle of a hedge fund, there’s definitely going to be like operational costs and data is going to be one thing that is very expensive.

And the manpower that you employ trying to get the best fund manager, because everybody wants them. So, which is why the costs, that 2/20 costs is never going to be taken away. Yeah. 

Sato Shi: I see. When you perceive hedge funds, we think of them as very ruthless, very aggressive. Do you think these kinds of fee structures actually drives these types of culture? Like cutthroat in that sense. 

Jeff: Yes, I do agree. So Just for fun fact, I guess. If you look at why, like back in history, how hedge funds actually even come about, then we can look at, say, hedging out unwanted risk is actually a very common thing in financial markets for centuries, right. So in like 1800s, You basically have like commodity producers and merchants that start using forward contracts to protect themselves against future changes in commodity prices.

Yeah, so that’s some form of hedging in that aspect. Then you have this guy that come along in 1949. Yeah, so Alfred Jones, he created his hedge fund called AW Jones, a partnership with 4 friends. The main idea was because they wanted to pull money together to make some returns. So he actually invested US$100,000 in stocks, so using long and short position and the fund returned 17.3%.

So the idea itself caught on. And later on you have like people or fund managers like George Soros, Julian Robertson that comes on board to start your own hedge fund. And definitely one of the examples that makes things or rather rattled the market was Soros’ quantum investment fund, when he bet a 1 billion on the devaluation of the British pound. 

Sato Shi: I think they called the event “breaking the bank of England,” am I right?

Jeff: Yeah, exactly. So that actually caused Britain to try to pull out from the exchange rate mechanism and yeah, all the spiking interest rate. 

Sato Shi: All these stories, they actually, you know, add to the mystery and the legend of the hedge funds, am I right? 

Jeff: Yeah. So from a surface point of view, I agree that things can be really ruthless from that point of view.

But if you think about it, what they are doing is that they also try to increase some form of competition because after all they are really trying to serve a client, as opposed to say bankers because bankers are just trying to take in orders and make sure that you are financing the larger population itself. 

And hedge fund is basically just the modern sexier sibling of all the traditional mutual funds. And yeah, they are more opportunistic, a lot more nimble. And I would say a lot more, less risk-averse as well, as opposed to, say, your mutual fund, having to just make long-only investments. So in that sense, it creates that competitiveness. And once you get in the industry, you realize that, hey, ruthless, yes, one. But the competition, the education that you can get out of it, just having to think beyond what you already have, what you have learned in school or in fact, what you have learned at work prior to working in a bank, things get a lot more interesting. 

You get a lot more free play to see how you can try to generate some of these returns. Yeah. So if you ever think of trying to rig into a hedge fund space, yeah. Why not just do it? 

Sato Shi: Thanks for sharing. Okay. I just want to, you know, touch on a lighter point. Okay, have you seen the movie Big Short? 

Jeff: Yeah. 

Sato Shi: Okay, so for our listeners out there, I think Big Short is one of the, I think the most famous hedge fund movies out there, that actually,  you know, goes deep into how the hedge fund actually made money. And it’s based on a true story, just to very quickly ask Jeff . You know, how factual is the movie? Because I think it really relates to, you know, like you mentioned, like most of the hedge funds, they’re just lying low, trying to survive the operational costs until a big bad bet makes it, am I right to say that? Is it quite factual in your words? 

Jeff: Before I answer the question, I think read the book. The book is more interesting [laughs]. But for certain I think what they portray on the movie is quite accurate. In fact, prior to 2008, you have the big boys like Goldman Sachs, JP Morgan, Morgan Stanley, Credit Suisse, trying to come up with their own hedge funds as well.

Because at that point in time, Volcker Rule wasn’t in place. So prop trading was a thing that can actually happen. So the traders can put on positions on their book to run their own portfolio, and things like that. 

So proprietary trading would mean that instead of just doing market-making, like what I mentioned earlier on, you can put on some positions in your book and take a certain direction such that you will be able to make some returns if it goes in favor.

Yeah, so what happened then in 2008 is that because of all these bets that goes on, people are actually looking at a lot of, say, your relative arbitrage strategy to see, especially in the fixed income space, so they are trying to see that, hey is there certain things that we can try to restructure, look into it and come up with some form of derivatives that we can sell to the mainstream market, the people on Wall Street? Then they realize that, hey, there’s this new product called CDOs: collaterized debt obligations. So it’s just having to put different junk bonds together, basket them into one and then selling this time bomb. I call them time bomb because essentially they are one that actually caused the whole financial crisis at that point in time to happen.

So the hedge fund space at a point in time had no limits, basically. They had all this free play to use different products and to just pass on all these different risk and try to make superior dense. But today, we definitely don’t have that as much luxury as we used to, because in fact, like the Fed or the different central bank across the world are actually looking at it and see like, oh, can they try to limit some of these are hedge funds’ ability to, you know, make risky bets that actually will move the market.

Sato Shi: So regulation has stopped this kind of behavior from reoccurring for now, until something new comes down the line. 

Jeff: Correct. 

Sato Shi: Regulators, you know, because it’s how dynamic and how profit oriented the whole industry is, they’re always one step behind, am I right to say that? Because everybody’s trying to find that next big thing. 

Jeff: One step behind, yes, for sure. I think the most evident one you can look at , say, during COVID. So there was a lot of distressed debt hedge funds, they were trying to put on trades during the COVID period. And one reason is that, yeah, you have a lot of potential fallouts from the corporates. So essentially people are trying to put on positions and they were getting really very big in that sense.

So if you look at the different credit matrix, then you see that, hey there’s potentially going to be a lot of defaults that happens. So what happens if these hedge funds actually collapsed, not having to honor some of these trades that they have already put on? It’s going to be a huge problem for the central banks itself and considering how constrained they already are right now because of low interest rates and whatever that’s going on, having to do some form of monetary stimulus. So it’s going to make their job very, very difficult. So, which is why they are going hard on hedge funds as well. And the banks, looking to see how they can try to minimize all this structure risk that goes on deeper in the markets.

Sato Shi: Definitely, definitely. And you know, while we are sharing with regards to that, I think you heard of the term, you know, the term of too big to fail, am I right to say? Will you say that that applies to hedge funds? I think when you refer to too big to fail, you’re referring to banks in general and we’ve seen, you know, bail outs, you know, it happen before already. Would you apply the same thing to hedge funds? In your own words.

Jeff: Yeah. So in fact, I have a really good example with regards to this. So if you look at say, Long-Term Capital management in the past, which was actually founded in 1994, by John Meriwether and advised by the creators of Black Scholes Model. So Myron Scholes and Robert Merton. So actually the LTCM collapsed in 1998 due to a Russian default that happened on 17 August, 1988 when the Russian government defaulted on its domestic local currency bonds. 

So LTCM actually put on a lot of investment strategy that were based on hedging against a predictable range of volatility in currency as well as bonds. So on that very fateful date, on 17  August, 1998, so Russia actually declared that, hey, I’m going to devalue my currency and I’m going to default my bonds. There’s nothing you guys can do. Yeah. Then the event itself was beyond the normal range that LTCM  had actually estimated. So by 31st August, the Dow Jones Index actually dropped by 13% and investors were actually seeking refuge in treasury bonds, which actually caused the long-term interest rate to fall by a full point.

As a result, so because LTCM was heavily invested in highly leveraged products, these all started to crumble. So by the end of August, 1998, it actually lost 50% of the value of his capital investment. Since so many banks and the pension funds have invested in LTCM, right, its problem actually threatened to push most of them to near bankruptcy. 

And Bear Stearns dealt the final blow in September. So the investment bank managed all of LTCM’s bond and derivative settlements. It caught for over like 500 million payments and Bear Stearns was so afraid that it will lose all its considerable investments and LTCM was out of compliance with all its banking agreement for three months, to the point that the Fed had to step in to try to rescue the market for the week itself.

And actually if I didn’t remember wrongly, the Fed actually  pumped in US$ 9 billion to try to rescue the whole market. So in that particular August, or rather September, 1998, there wasn’t a crisis. A crisis was averted. And only because the Fed realized that LTCM is too big to fail. Yeah.

And the Fed actually forced them to liquidate all the assets and close shop for good. 

Sato Shi: Well, I mean, that’s a really amazing story, so thanks for that. I just want to touch on one more last point before I let you go. It’s been very interesting, so probably we’ll take this offline. Could you just share what is a common, you know, sort of like hedge fund strategy and, you know, you, you mentioned like hedge fund returns like 30 over percent for George Soros.

What is the kind of common hedge fund strategies that they use, and that’s why they can actually you know, lead them to actually perform better than the market? 

Jeff: Yeah, sure. So there’s a couple of different elements that they actually look at. So like Stow, that’s one. They probably will look at, say, global macro, directional, event-driven, arbitrage, and so on and so forth.

Then what kind of markets do you want to try to tap on? So it may be equity, it may be fixed income, commodities, FX or alternative investments even. And what kind of instruments like your options, your swaps, your long shot equity. Maybe even exposure, say, like market neutral, taking a form of direction and what sector, health care industries, and so on and so forth. 

And last but not least, diversification. So it may come in the form of say, multi manager, multi-strategy, multi-fund, or multi-markets. So I think one of the more common strategy that is being employed is global macro. So what it means is that these hedge funds actually invest in bonds, stocks, futures, options, and sometimes currency in hope of trying to maximize the changes in macroeconomic variables. 

Sato Shi: Okay. What is a macroeconomic variable? 

Jeff: Yeah, so it can be like global trade, interest rates, or some of the central bank policies that goes on. So one example of a fund that does this is Brevan Howard. Yeah. So usually the investments that they do are highly leveraged and highly diversified.

And back to the question that you were asking me about systematic trading and discretionary trading. There’s a lot of macro funds that are actually implementing systematic macro as well. So it has been taking off because it looks into mathematical models and software instead of discretionary models.

And in fact, a lot of hedge funds are looking into doing multi-strategy so incorporating different strategies into one, they try to gain some of these superior returns that we talked about. 

Sato Shi: Would you say that, you know, a hybrid model is the most common, so there is no one size fits all, like, you know, you just take the best of everything for a particular strategy.

Jeff: Yeah. So if you look at, say, Millennium Capital, yeah, they have different trading pods. So they work with different PM’s that comes in. They work in silo in that group itself. So PM may have say, 3-4 traders, junior traders, or execution traders, and maybe 1 quant as well as maybe 1 research guy. So this form one pod.

And in that particular pod, maybe he focus on macro strategy and maybe in another pod, then he may be looking at a long shot. So essentially what it means is that the manager themselves, he will try to invest in undervalued stocks and speed up investment between the investing in long, in stocks, while shorting other stocks.

So the fund could actually have like 60% of his funds invested in long and 40% to short stocks leaving a net exposure of say up to the equity markets of 20%. So in that sense, it’s very interesting to see how all these different pods play out.  And then you see, when we classify all the returns into one, when Millennium reports their return, it’s just 1 number. 

Sato Shi: Okay. So there’s a lot of things that lead up to that one number la. 

Jeff: So, if you look at, say, like Point72, they are more of a long shot hedge fund, so they focus mainly on long shot, and then you may have to, say, like AQR or Lint asset management, where they look more of relative value arbitrage strategy, where they typically try to buy securities that is expected to appreciate while simultaneously selling short a similar product.

In fact, fixed income-based, relative value arbitrage actually posted a narrow gain in October as the interest rates increased, thanks to the fed and all your central banks led by U alternatives and your comfortable arbitrage exposures. So that’s quite interesting. 

Sato Shi: So I think, I mean, in a nutshell, I think there are many different you know, hedge fund strategy.

I don’t think there’s a common one because it seems like every hedge fund, you know, it finds their own way. Yeah, at the end of the day, I think it’s very important that, you know, they reach the promised land, which is that high return that they are promising their investors [laughs]. 

Jeff: Yeah. So I think one of the, like, one of the biggest funds out there would be say, your Renaissance Technologies, DE Shore, yeah, they are particularly more interesting in that sense because they are quantitative hedge funds, mostly focusing on algos and systematic strategies to come up with their trading positions. 

The funds that I mentioned previously, I call them more of the fundamental hedge funds. But both fundamental and quantitative hedge-funds use fundamental information such as economic data, accounting, financial data, but what makes the quant funds very, very different is that the quant analysts will look at things in a very systematic and automated way, so they may be looking at, say, like tens, if not hundreds of types of different data, to try to predict a single output. So it’s basically just rule-based trying to see which asset to sell, which asset they buy. 

And they wouldn’t even care as to whether it has to be equities only, it has to be fixed income only, or stuff like that. So long as they can find a certain alpha or a certain correlation in the different asset classes space, and it can be statistically explained, they will just go with it. 

Sato Shi: Oh, okay. So whichever works. There’s no doctrine. There is no dogma. At the end of day, whichever works. So they’re agnostic about the kind of strategies that they’re using. So I mean, wah, it’s been mind-blowing, this entire session.

I think I myself, I learned a lot, you know, over the past episodes. Maybe I just want to get into a more personal question. You know, to probably round off this episode? Okay, so personal question to you, Jeff, if you had the means. I’m not trying to say you don’t have the means. But if you had the means, would you put your money in a hedge fund? 

Jeff: I would definitely do that. I would put a sizable amount to see how things go, but I think what’s more interesting for me is to try to understand what the investment philosophy that this particular hedge fund is adhering to and whether it resonates with what I think. That’s something that I really would like to know.

And a lot of times you don’t want to put your money in a black box, right? In a sense where at the end of the day, December comes, or the end of financial year and they tell you like, eh, your portfolio is making 15%. Wonderful for sure. But the question will be whether they can continuously sustain these returns going forward. And there’s something more important to me. 

Sato Shi: So I take it you’re agnostic as well. I mean, it could be a hedge fund, it could be a bank, as long as it’s a sustainable return.

But if we’re talking about hedge funds, we’re talking about 30 over percent returns, do a bank even promise that kind of returns? 

Jeff: No, I wouldn’t think a bank would promise you like 30 over percent. Like if you look at, say, private banking like Credit Suisse, UBS, or any of the different banks, right. They don’t even promise, say, like up to 10%. Yeah. Maybe at most like 5-7%. 

Sato Shi: Because they want to hedge their bets also, right? 

Jeff: Correct. So from that point of view is that if you’re looking for very superior returns and you have a liquid asset to, you know, to burn in that sense then hedge fund is the way to go. 

Sato Shi: So I mean it’s been a very interesting session. I think you also really answered the question, whether, you know, a hedge fund, you know, you explain why they actually outperform the retail market and, you know, if you had an opportunity to actually you know, invest in a hedge fund itself, I think you are a great — how do I put it — ambassador [laughs]. In a sense. Yeah. So ladies and gents, we have Jeff over here. Jeff, thanks for taking the time to be a part of this and thanks for sharing your knowledge and insights. 

Jeff: Yeah, no worries. Thank you. 

Sato Shi: So arigato, my friends, and my deepest appreciation for joining me on this journey. Please reach out to us on The Financial Coconut socials and Telegram group. Everything can be found in the description below. We would love to hear from you and discover which other sectors of finance to demystify. Until then, ciao!