Podcast Transcript: Adam Iqbal on Carry Trades, Volatility and Trading Options

This is an edited transcript of our podcast episode with Adam Iqbal published on 28 January 2022. He is the Managing Director and Global Head of G10 FX Options Trading at Goldman Sachs. Prior to this, he was an FX Volatility Portfolio Manager at PIMCO, and he has worked as a vanilla and exotic FX options trader at Barclays Investment Bank in London. In the podcast we discuss, what risk premia strategies are, where currency volatility comes from, rules of thumb for trading options, and much more. While we have tried to make the transcript as accurate as possible, if you do notice any errors, let me know by email.

Introduction

Bilal Hafeez (00:01): 

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Now, onto this episode’s guest, Adam Iqbal. Adam is the managing director and global head of G10 FX Options trading at Goldman Sachs. Before Goldman’s, he was an FX volatility portfolio manager at PIMCO, and he worked as a vanilla and exotic FX options trader at Barclays Investment Bank in London before that. He is the author of two books, the upcoming Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory, and an earlier book, Volatility: Practical Options Theory. Adam holds a PhD in financial mathematics and economics from Imperial College London, a master’s in applied mathematics from Oxford University, and a master’s of science and bachelor’s in physics from Cambridge University. He has held a visiting academic position in Imperial College, London, and has guest lectured at the LSE. So clearly, a very smart person. Onto my interview. 

So, greetings, Adam. It’s great to have you on the podcast. I’ve been looking forward to this conversation. 

Adam Iqbal (02:11): 

Hey, Bilal. Thanks for having me on. Pleasure to be here. 

Bilal Hafeez (02:14): 

Before we jump into the meat of our conversation, which I’m really looking forward to, I always like to ask my guests their origin story. So what did you study? Was it inevitable you’d end up in finance? And your career journey until now. 

Adam Iqbal (02:25): 

Yeah. I started with an undergraduate degree in physics at the University of Cambridge. And when I think back to that time, I actually remember quite clearly not understanding why somebody would want to even study economics or finance or the subjects that I eventually fell in love with. At the time, it felt like the questions in physics were just so much bigger and more important, things like, what’s the nature of the universe? Where are we going? What’s the origin of time? And so on. But then over time, I naturally mellowed from that slightly extreme starting position. And I did explore this city in actuarial firms and accountancy firms in summer jobs, but I ended up concluding that it probably really wasn’t going to be for me. And I decided that I was going to try and become an academic. 

And so I realised that to do so, I needed to get a little bit better at maths. And so I went off to the University of Oxford to do a masters in applied mathematics. And it was really there that I got influenced by some very enthusiastic classmates that I met who were already super into financial mathematics, which is essentially the application of Stochastic calculus to price derivative securities. At this age, I still hadn’t even heard of what a derivative was, but I think their infectious enthusiasm rubbed off on me, and I ended up dropping into some of the classes. And when I got there, I was instantly hooked. I didn’t know at that time that derivatives would ultimately become a lifelong passion, a career, obviously, the topic of my first book, Volatility: Practical Options Theory, which I think we’ll get a moment to discuss later on today. But at that time, I was really most interested in them from a scientific inquiry perspective. If you think about what I’d been learning in science until then, you have maybe like a closed system, you have a starting point, you write down a model, and you make some deterministic or probabilistic predictions for where that system might end up. 

The difference here was, here, you have, a portfolio. The system is the portfolio. That portfolio contains a derivative security. But in this case, you have the human who constantly pokes this system in a process that we call dynamic delta hedging. And so what you have is this derivative that is written on a Stochastic underlying. It could be a derivative written on say the FX rate of the equity price or an interest rate, or a commodity price, and has a random payoff. You have a human constantly doing this delta hedging, and each one of those delta hedges has a random payoff. And somehow, the aggregation of all this leads to certainty. And that’s a super interesting concept when you first come across it. And now just to take that argument a little bit further, let’s say that certain number is minus $1 million that you end up with. The logic then follows that if you charge $1 million ex ante to enter into this derivative contract, that’s therefore the fair value of this product because your P&L will be zero with certainty at the end of this. 

So that’s obviously the famous, the seminal Black–Scholes–Merton and approach to derivatives, and I found that fascinating. Now, as time went on and the idea is, it took me a while to really understand it, and as the idea eventually settled in my head, I think I was left quite unsatisfied with the main confusion being, how was it possible that I and my classmates could be sat in the basement of a library in Oxford totally removed from the real world, how could we be writing down a formula that would tell you exactly how to perfectly replicate a derivative? 

If it was true that it was so simple to do that, then why weren’t investors just doing that themselves instead of trading billions upon billions of notional of these contracts every single day and across market? So why wouldn’t a bank or someone just market an algorithm that could do that delta replication for you? These things shouldn’t exist. I was in financial mathematics at that time, and financial mathematics starts to give you some semblance of an answer. It says that the reason is that some of the conditions that are required for this perfect replication, namely, that volatility is constant, volatility doesn’t move up and down. or that you can trade your delta hedges at every point in spot space, spot doesn’t gap from A to B, but it moves in a continuous fashion. That’s in the model, and in real markets, that doesn’t happen. And so those conditions are not satisfied. And then financial mathematics goes off to do a load of useful things. It goes off and models that Stochastic volatility models jumps in asset prices and does all of that, but it really falls silent, I think, on the questions that I was most interested in at that point, which were, why does volatility move up and down? Why do asset prices sometimes behave in a continuous way and sometimes in a jumpy, gappy way? What causes periods of high volatility? Where does volatility even come from? Why do asset prices move at all? And so, at that point, I realised that to answer those questions, I really needed to learn some macroeconomics and I needed to spend some time in markets. I couldn’t get onto a macroeconomics PhD programme because I had absolutely no background in economics whatsoever, but what I did manage to do was convince an economist and a mathematician to jointly supervise me on a PhD project that was somewhere at the intersection of financial economics and financial mathematics. And so I went off to Imperial College London to start on that PhD. And it was really during the PhD programme that I came across, let’s say the second topic that I’ve had another lifelong passion for, which is this idea around risk premiums. So loosely put, and maybe we can come back to this topic in a bit more detail, but loosely put, risk premiums are this idea that you never enter into a bet at its fair actuarial value, you always need a premium or a discount depending on how that bet is going to correlate with your own outcomes, whether it’s a recession or a boom period, whether it’s a period in which you have personal wealth or you don’t and so on. And that topic ultimately became one of the central topics in my new book, forthcoming, about Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory, which again, I hope will get some time to talk about today. But I kept on working on that project since. And then when I eventually got to the end of the PhD, again, I was unsatisfied. I’d spent a lot of time downloading data, doing econometrics on data, reading academic papers and so on, but I really didn’t feel like I had a proper understanding of markets or of derivatives beyond that level. And also, I mentioned earlier that I wanted to understand a little bit more about market microstructure and how markets actually behave. And so I ended up deciding to try and get a job. And I was fortunate to find myself on the… I applied for some jobs and I found myself at the FX options desk at Barclays Capital, as it was called at the time, in Canary Wharf. Now, it was amusing in some senses because they hired me as a graduate, as a junior trader. Whereas in my mind, I was there on a reconnaissance research mission. I wanted to just observe how derivatives worked and how market microstructure worked and all of these things so that I could eventually go back and write better papers on those things. 

But as these things happen, the trading floor is a super addictive place. It didn’t take long for me to fall absolutely in love with taking risk and trading. I think that there were a few things that really appealed to me, one, the intellectual atmosphere and the ability to discuss a huge wide range of topics were just people in your row, let alone the hundreds of other traders scattered across the trading floor. But the other one was, I just loved the productivity of the place. And by that, I mean that we would sit there and discuss a trade or an idea for maybe five minutes or 10 minutes, and then go and actually implement that trade, and go and take risk. And we’d make money sometimes and we’d lose money sometimes, and we’d learn from that iterative process, which compared quite favourably at the time to the three, five-year process of publishing an academic paper. It was mind blowing. And so I really enjoyed that. And then I was hooked. Since then, I traded options at Barclays, I was an FX volatility portfolio manager at PIMCO. And of course, I am currently at Goldman Sachs. And that is where I’ve spent the majority of my career to date and where I still trade today. 

What risk premia strategies are 

Bilal Hafeez (10:38): 

Great. That’s a great story. And I should just add all your opinions of giving this podcast are just your personal opinions, not of any institution you are affiliated with. And now, you have this new book coming out or has come out or was about to come out called Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory. I’ve read a draught version, Or at least half a draft version of it. It’s really quite good. And rather than me not talking about it, it would be good to hear your thoughts on the book. But before we talk about some of the concepts you talk about, especially risk premium, which I think is very important, especially for investors to understand, what was your motivation for writing the book? Because you didn’t have to write this book. So why did you write this book? 

Adam Iqbal (11:13): 

Yeah. I think on the motivation side, I guess there are two sides to it. There’s the consumer side, like what gap was I trying to fill by writing that book? And there’s the producer side, like, why would I personally want to sit down and do it? Let me start quickly with the what gap I was trying to fill there. I’ll say that there are really two gaps. One is, and you mentioned it a little bit already, this concept of the risk premium. We have had this idea in, let’s say in the academic space for many, many years, that the risk premium is actually the dominant component of asset price movements. I think that practitioners are really familiar with that.  

You go into work one day and equities prices are down and yields and US yields are lower, and the high beta currencies, Aussie, Kiwi Canada, Norway, etc, are weaker. The safer haven ones, the Dollar, Swiss, Yen, to some extent, Euro, are stronger. We would call that a risk-off day. And if the opposite is happening, we’d call that a risk on day. So practitioners have this loose idea about risk premiums, and they talk about them. Academics have this idea about risk premiums. But what I thought there was a real gap in was the academic approach to risk premiums, the more quantitative approach, introducing that to a practitioner audience. And by that, I mean, where do these things come from? They come from utility functions, consumption smoothing, investor optimisation behaviour. If you can put those ideas into practitioner language while practitioners already understand the concept, they can improve their trading even further by understanding the origins of that, the microeconomic origins of that concept. So that was something that I thought was a big gap in the markets. To give you perhaps a slightly more specific example to bring that point home a little bit more. if you think about, say the financial crisis. 

At the start of the financial crisis, it started as a US crisis. It was a US mortgage crisis. It was a period where the US was running substantial current account deficits 5-6% of GDP. By all fundamental economic analysis, you would conclude that the dollar needed to weaken on that, either from a growth perspective because it was a US crisis or because investors should be less inclined to lend money to the US. And so from a balance of payments perspective, your economic theory might tell you that the dollar should weaken. And we all know that the dollar strengthens substantially, and it did it again in the pandemic. And so that is the risk premium being the dominant component of the currency price movement over the economic fundamentals. I think that gives you some justification for really focusing your attention on the risk premium. 

Understanding risk premium through umbrellas and rainy weather 

Bilal Hafeez (13:48): 

And I think your book really does give us a much better understanding of that from both sides of theory and the academic side and the practitioner side. Now, this idea risk premium, we hear that a lot in markets. Many people, even if they don’t know the word risk premium, they talk about, “Oh, it’s a risk off day, it’s risk selling off.” And they intuitively know what’s going to go up or down in that scenario. Then equally, you get all these asset managers and hedge funds who put on risk premium strategies. The idea is that they find different corners of the market that offer what they call risk premium and then they implement that strategy systematically. So there’s a lot of either intuitive understanding of this or an explicit discussion of risk premium. So this tells me it’s very important, number one. But secondly, it’s not clear to me whether everybody really understands what risk premium is exactly. So good to hear how you define risk premium, and then maybe we can go from there. 

Adam Iqbal (14:40): 

Yeah, sure. So maybe the easiest way is if we do it by an example, maybe I can do a little game or a little bet with you, Bilal, to try and do the concept. So let’s do a little bet, so let’s say that we’re going to bet on a toss of coin. It’s a fair coin. If it’s heads, you give me an umbrella, and if it’s tails, I’ll give you an umbrella. Sounds like a fair bet, right? You’re happy, I’m happy, it’s perfectly symmetric, we go and do that bet. Now, let’s change it slightly. I turn on the radio and the forecaster says that there’s a 50% chance of rain tomorrow and 50% chance of sunshine. And I say, “Okay, Bilal, well, you are happy to bet umbrellas at 50-50 odds with me. So why don’t we say if it rains tomorrow, which it will with 50% probability, you give me an umbrella, and if it’s sunny tomorrow, I’ll give you an umbrella.” 

All of a sudden, you’re a lot less happy with that bet. You’re not going to do that bet with me now. That seems pretty unfair. So now, well, what can we do? I can maybe sweeten the deal for you a little bit. I can say, “Okay, you’re not going to bet with me like that.” That tells you that really, it’s not the actual odds of the bet that are your main concern, it’s the correlation of the payout with the state of the world. You don’t want to bet something where you are short an umbrella when it rains. So what we can do is we can sweeten in the deal a little bit for you. So I can say, “Okay, if it rains, you give me one umbrella, but if it’s sunny, I’m going to give you two umbrellas.” And that bet, you might now take it because you’ll say, “Okay, well, if I’m unlucky and it rains, I’m going to get rained on. But if it’s sunny, I get double the payout, I’ll get two umbrellas and I can use those umbrellas in the future on another rainy day, I might be able to sell one of them or trade one of them for something else,” and so on. So now let’s say you accept that bet. So now an actuary comes along and says, “Okay, well I know it’s a 50-50 chance of rain, but it’s trading at two umbrellas to one umbrella. So the market implied odds of rain are actually 66%, they’re two thirds.” 

Now, that difference between the objective probabilities, the 50-50 objective probabilities of rain, and the market implied probability of rain, that 66% chance of rain that’s implied by the rate at which you and I have traded these umbrellas, that is what we would call risk adjusted probabilities, or the risk premium or whatever you want to call it. It’s when asset prices trade away from their objective probability, the objective probabilities of the payoffs, and trade at some kind of premium. 

That’s where the equity premium comes from. The equity risk premium is very well known, equities return something like 8% on average since World War II. Why do they do that? Because we know that when it rains, equities go down. And so you need some compensation for that. And so they end up getting systematically under priced, we call that risk premium. But I think the umbrella example puts it into your daily life. 

Bilal Hafeez (17:19): 

Yeah, no, that’s a really good point. So what I’m hearing there is that if you just look at the odds of something objectively or in isolation, that’s one set of expectations of the price or probabilities, you could say. But then if you put that in relation to a state of the world and how you feel about that stage of the world, then suddenly, that introduces this idea of risk premium, where you’ll suddenly think, actually, the price of that now can diverge from this objective probability so that something that I think is more valuable to me in a bad state of the world could be worth more than something that isn’t helpful to me in a bad state of the world, for example. And then that starts to impact the price. 

Adam Iqbal (17:58): 

Yeah, that’s exactly right. And the microeconomic foundations of it are from essentially smoothing your utility over time. Like in this example, you having an umbrella when it rains, when it rains, you’re unhappy and the umbrella offsets that and makes you happy. When it’s sunny, you’re happy already, so being short an umbrella, that will dampen your utility a little bit, because obviously, you prefer having an umbrella, owning umbrella to being short one, but essentially you smooth that utility over time, and that’s the microeconomic foundation.Now, in the book, I talk about this in more detail. I used that utility function, consumption smoothing, and all of these things to derive the results a lot more formally. And I go on to give a few more market-based examples rather than umbrella based examples of the risk premium and how it impacts equities and FX just in betting markets and so on. 

Bilal Hafeez (18:46): 

But this really tells you that there is something real here. This risk premium is based on something real. It’s not something just made up, and it’s a way you can earn higher returns over time, but it’s compensation for something. There’s a risk there, you’re being rewarded for something. 

Adam Iqbal (19:01): 

Yeah, that’s absolutely right. It’s not just real, it is the dominant, in my view, and I would say the dominant thing in asset markets. The amount of time that spend on analysing say the fundamentals, say, we look at currencies and we analyse, “Okay, what’s European growth going to be and what’s inflation going to be and so on.” Whereas the bigger price movements are driven by the risk premium. And I bring it back to the example of the dollar at the start of the financial crisis, it shows that that was the case. 

Common risk premia strategies in FX markets 

Bilal Hafeez (19:28): 

And I guess that’s why so many funds, asset managers, focus on risk premium strategies, because they’re aware that this is the dominant source of making money over time, rather than trying to come up with a better view of fundamentals. 

Adam Iqbal (19:39): 

Yeah, exactly. 

Bilal Hafeez (19:40): 

And I was going to just ask, you said currencies there, so how does risk premium apply to currencies? Because we can see how it applies to equities. You want to be long in equities, but in bad times, equities really do terribly, so there has to be some compensation for that. How does that apply to currencies? 

Adam Iqbal (19:53): 

It’s a tricky one in currencies. The way I look at it is that I know that in bad times, the Dollar, the Swiss, the Yen, the Euro to some extent are going to strengthen, and Aussie, Kiwi, NOK, CAD, etc, are going to weaken in economic bad times and vice versa in good times. Now, reasons that happens are quite difficult. In the case of the dollar, people cite all sorts of things. So you’ll be able to read things like, “Oh, the dollar strengthens in pandemics or in financial crisis or in global recessions because the dollar is premier reserve currency, because it’s a premier currency in international payment and so on.” 

But then those reasons don’t really apply to the Yen and the Swiss to that extent. And actually, Yen strengthens more than the dollar and Swiss strengthens more than the dollar in typical global crisis periods. We saw that again in the early stages of the pandemic and so on. So I don’t know why these currencies are the ones. And again, we could probably come up with some reasons if we had to, but we know that they do. And if they do, then we need to ex ante price that into those currencies. 

If the dollar is ever trading cheap versus where it’s say fair value is based on some, let’s say some PPP or PPP adjusted model, you need to be buying the dollar, that’s too cheap for the dollar. You need to be paying a premium for the dollar. This is an old phenomenon. This is what Valery d’Estaing, the former famous French finance minister and then president called the exorbitant privilege of the dollar. The fact that US interest rates could be a lower than where they should otherwise be, that the dollar can be stronger than where it should otherwise be. Essentially, it’s a risk premium based argument. 

Bilal Hafeez (21:25): 

Yeah. So there’s this excess demand for dollars because of safe haven properties. 

Adam Iqbal (21:29): 

Yeah, exactly. That’s right. But that demand is there at all times. We know that the dollar, the Swiss, the Yen are going to strengthen in the rainy state of the world, and so we need to price those currencies at a premium in the calm state of the world as well. 

Bilal Hafeez (21:43): 

Yeah, absolutely. One popular way of thinking about this is the so called FX carry trade, which is a strategy that’s very common. It’s probably the most popular strategy in FX markets where you buy high interest rate currencies, which often are emerging markets, but also sometimes G10, look, Australian dollar or Turkish Lira or Brazilian Real is, and you borrow in the low interest rate currencies like the Japanese Yen or the Swiss Franc, then you end with this nice carry trade. And that I suppose is you are trying to capture risk premium there by investing in that carry trade. 

Adam Iqbal (22:15): 

Yeah. To some extent, I guess I would append that with what you should be doing is buying in the high real interest rate currencies rate and selling the low real interest rate currencies. And then depending on the relation of those currencies with the state of the world, you should then be adding on a risk premium on top of that, that real interest rate differential that you’re trying to capture over time. And the more the currency is positively correlated with say markets, the higher premium that you need to attach. 

Bilal Hafeez (22:42): 

Yeah, absolutely. I guess this leads to an associated question, which is, how do you determine whether something isn’t offering you a risk premium? Because you could fall into this trap where anything that goes up over time, just empirically, you’ll say, “Okay, that’s a risk premium, so I’ll implement that as a strategy.” How do you think about trying to distinguish between things that offer true risk premium and things that are just went up over time and there’s just data mining. 

Adam Iqbal (23:07): 

Yeah, exactly. Currency to have a bit of an anchor. If you think about a very stylised model, like a hypothetical model where you have two countries, let’s just call them US and China, they both produce goods and they happen to produce goods of identical quality, we’ll call them US widgets and Chinese widgets then. And let’s say also, we end up with a world in which you can try transport these things frictionlessly across the two countries with little transport costs, then that the real exchange rate needs to be at one in, let’s say, some forward,… Let’s say if I say, “Where’s the one-year dollar CNH forward trading?” And that needs to imply a real exchange rate at one. And so that would be the anchor point. Now, from there, you obviously- 

Bilal Hafeez (23:49): 

Just be clear, that’s a bit like the so-called Big Mac index, although the Big Mac’s not tradeable or iPhone index or something where we publish this iPhone index, where we look at the price of iPhones in different countries. And in theory, when you do the currency conversion, it should be the same price, but it’s not, maybe transport costs are different, tax, there’s all sorts of different reasons. But as you said, if you lived in a world where there were no transport costs, no frictions, no tax differentials, then the price should be the same. If it’s not, then there’s an arbitrage possibility and then that should just make sure people just buy it in the cheap country and sell it in the more expensive country. And that would because the currency to move in a way to equilibriate that all. 

Adam Iqbal (24:27): 

Yeah, exactly that. Now, the issue that you have is that in that model, actually, if there were genuinely no transport costs, then there actually is no risk premium. You know with like FX Net, real exchange rates never move, real FX rates never move because they just fixed that one. And if you know something doesn’t have risk, then there’s no risk premium. But, that discussion gives you the origins of this idea that the real exchange rate should be something around one. And then there are various reasons that it’s not quite one, and we can go into where real exchange rate volatility comes from as we move on and talk about volatility more generally. 

But we say, let’s anchor the real exchange rate at somewhere around one. And then we say, okay, well we know there’s risk around this real exchange rate because some of these conditions that we just mentioned like no transport frictions don’t hold perfectly. And so we say, okay, well the real exchange rate on the forward should start at one. But then we know that there should be a risk premium. And let’s say it’s US and China. Typically, the dollar is the one that carries the risk premium, so we need the dollar to be a little bit expensive. So the real exchange rate US versus China should trade in favour of the dollar by a certain amount. And let’s say if there’s a 5% risk premium, it should be 5% expensive. So you put in your inflation expectations in the US, you put your inflation expectations in China, you calculate where dollar CNH forward should be based on one plus, say, 5% risk premium, plus your relative inflation expectations. That tells you where the nominal forward should be. Then you use covered interest rate parity to discount that back down to spot. Obviously, the higher country sets its real interest rate, the stronger the spot is going to be on that discounting using covered interest rate parity, and you work out there for your fair value of dollar-China today, and that’s the process. 

Now, I go into that in more detail in the book. And I think that in some ways, the book is unique in doing that because many books will do PPP, they’ll do covered interest rate parity and those kinds of concepts. Most of the books that are written on risk premiums are actually written about, say like equity markets and so on. So I think the nice thing about Foreign Exchange is that, and Asset Pricing and Macroeconomic Theory, is that it puts all of those things together, covered interest rate parity, inflation differentials, real exchange rates, and the risk premium all into one coherent model and tries to explain those ideas. 

Bilal Hafeez (26:42): 

It is really, really helpful. And just to be clear for our audience who may not be familiar with some of these terms, when we say PPP, we mean purchasing power parity, and it’s a way of value and currencies based on, you could say like the Big Mac index or an iPhone index. That’s in principle based on that. And then covered interest rate parity tells you how you calculate the value of FX forwards, linking it to interest rates between different countries. So you can work out what the FX forward is. 

Adam Iqbal (27:06): 

Exactly. And what I’m arguing here is you actually do it the other way around. You work out forward price and then you use CIP to discount backwards to get the spot. 

Where currency volatility comes from 

Bilal Hafeez (27:13): 

Yeah, exactly. Now, you did talk about currency volatility there. This may be a really silly question, but where does currency volatility come from? 

Adam Iqbal (27:21): 

Yeah. Again, it’s a really good question. Ultimately, the discussion we’ve had already, we’ve already argued that… So the FX rate, you have the real exchange rate, and then on top of that, you have some kind of adjustment for inflation to get where the nominal exchange rate is meant to be. So there are two components to that volatility. And the discussion that we’ve had already, we’ve already said that ultimately, real exchange rate volatility has to come from the fact that we do have transportation costs across the world. We already said that if you’ve got the US and China, and they’re both producing widgets and these widgets are of, say, identical quality and you can transport them frictionlessly and free between the two countries, well, the real exchange rate can never move, it’s one forever with certainty. 

So that means that ultimately, it’s the fact that you can’t do a real good arbitrage in practise that allows real exchange rates to move. Now let’s think about an example of where that might happen. Let’s say the real exchange rate is one because we started in the world with perfect transportation, and then all of a sudden we impose massive tariffs, we go infinite tariffs, China can’t send any goods to the US, US can’t say any goods, China, there’s not going to be any more trade between them. Now, let’s think about what happens. So now let’s say all of a sudden, one of these countries suffers, not suffers, but gains a productivity shock. Let’s say China suddenly produces widgets, twice as many widgets. Big technological improvement, and suddenly produced twice as many widgets. 

Now, what would’ve happened before these big tariffs were enacted is that those widgets that would’ve been exported across out of China and the global price of widgets would’ve come down such that the real exchange rate stayed at one. But now widget prices in China come down because there are twice as many of them, and widget prices in the US stay where they are. And so what you’ve got is you’ve actually got China starting to look very cheap. The real exchange rate is moving in favour of the US because, one, US widget is the same price, but one Chinese widget is half the price of what it was. And now if you think about it, so this is something that just comes out of the models that we were speaking about earlier, these models of investors optimising their portfolios across countries and international economies and utility optimisation and so on, and the book goes into detail about those. But if you think about this model, it’s actually quite familiar, the outcome of this little discussion is quite familiar to a lot of economists. A lot of economists with a slightly orthogonal approach say may be say the Balassa–Samuelson approach to FX. And in the Balassa–Samuelson model, what we’ve done here is we’ve said that in the non-tradeable good sector, because we’ve made everything non-tradeable, so it’s the non-tradeable good sector, we’ve hugely increased productivity. And therefore, the currency should weaken. You normally think about that the other way around. You think about the Balassa–Samuelson model, an increase in the tradeable good sector, productivity causing currency to strengthen. So it shows the other side of the same coin of that model. And so again, it’s something that I really like about this invest optimisation approach. It gives you maybe some pretty intuitive ways to get to some of the conclusions that you might have had, or heard or heard from other models of effect in the past. 

Bilal Hafeez (30:27): 

And so, can you separate out the real side of things on the inflation side of things on the volatility side? So what you’ve said there is that through introducing things like transport cost, through introducing ideas of productivity, that suddenly would influence the real exchange rates and introduce some shifts in its value and introduce some idea of volatility. How does inflation come into this all? 

Adam Iqbal (30:48): 

Yes. The other extreme then, let’s say that the real exchange rate was fixed, so you could transport everything. So then how does FX move? Well, then it only moves from inflation because let’s say if the prices of US widgets double relative to Chinese widgets because US inflation is very high compared to China, then for the real exchange rate to stay at one, well, the forward price of the dollar therefore has to weaken. So the nominal price of the dollar has to weaken such that the real price of widgets will still trade at one for one. So that would be the component of volatility that comes from inflation. 

Now, if you think about this, let’s try and put this in to the real world perspective a little bit. I’m going to have a timeline that goes back, let’s say before the pandemic because the pandemic time changed things a little bit, but let’s say, the last 30, 40, 50 years prior to 2020. Really what we’ve had is a period of globalisation, transport costs have come down, barriers to trade have come down, tariffs have come down over that period. In 2019 and Trump and so on, we had a little bit of a blip in that secular decline, but that is the direction of travel. And at the same time, the volatility of inflation differentials has hugely come down, especially in G10 central banks have broadly become a lot better at understanding how to control inflation. And we’ve had very, very stable inflation around 2% or lower in many developed market central banks over an extended period of time. And so if you think about those two components of FX volatility that we’ve spoken about, they’ve just been trending down and down and down. And that’s really what you see in markets. If you look at where, say FX implied vol trades relative to equity implied vol or rates supply vol, it’s been on a downward trend more broadly. Now, it remains to be seen, but the components of the pandemic are potentially things that change that. 

In some ways, we had this long period of globalisation maybe, maybe, maybe we have some blip in that trend. We’re seeing a little bit of that already, but there is a potential for some halt in that decline. And we’re already seeing a lot more volatility and inflation. Now, it’s early days and so I don’t want to make any big claims that this is a turning point. But I think it’s good to understand these components of FX volatility and how they can be impacted by what we’re seeing. 

Bilal Hafeez (33:05): 

It is a really good point. By having this discussion about what drives volatility, it helps us understand the trend in volatility as well. And so I’ve been in markets for like 20, 25 years and as long as I’ve been in markets, people have always said, “FX volatility is too low. It should pick up, this will be the year it picks up.” But as you say, if you have some grounding and theory and fundamentals and understanding of volatility, you’ll see that, “Okay, you’re right, globalisation has made things easier to flow between countries so that stabilises the real exchange rate and inflation volatility’s been going down.” So on that basis, there should be a trend down in FX vol. But as you’re right, you point out, we could be at turning point right now, we’ll have to see, obviously COVID has brought lots of temporary factors so we’ll have to see what really sticks after that. But one question I did have was, if you look at inflation volatility or shifts in productivity or growth, or all of these sorts of things, the volatility of these variables or these indicators are not as high as market volatility, whether it’s FX volatility, equity volatility. And so this is often called the volatility puzzle or whatever you want to call it. Do you have a take on why our market’s more volatile than fundamentals? 

Adam Iqbal (34:12): 

You know what I’m going to say for that, it’s the risk premium. It just further supports the point. The whole point of the risk premium is that asset prices can move around even if economic fundamentals are not moving around at all. 

Bilal Hafeez (34:24): 

Yeah. Which goes back to the umbrella example, so we’re tossing a coin, the odds, it’s always 50/50, that will always stay the same. But the value is scientific, different state of the world could just fluctuate a lot and change and the weather changes. And so that will drive the price of the odds. 

Adam Iqbal (34:41): 

Exactly. Let’s do that example. So there’s 50/50, is fixed. That’s just a fixed number, that coin. But the more scared you feel, the more adverse you feel, the more that 66 number goes higher. And the better you feel, if you feel like on risk on day, you feel feeling good about things, that 66 number could come lower and the objective probability they’re not changing at all through that whole period. So you end up with a lot of volatility for a world where the fundamentals just don’t move that much. 

How to learn about options markets 

Bilal Hafeez (35:06): 

Now, we talk a lot about volatility, so we have to talk about options, and you are an option’s trader and that’s in your blood now. So I need to get some wisdom from you on this. You did write a book called Volatility: Practical Options Theory a number of years ago, which is an excellent book. One question I suppose is, why did you find there was a need for writing this book? Because there’s lots of options books out there already, what was your value added so to speak with this book? 

Adam Iqbal (35:29): 

Yeah, that’s right. I published the book in 2018. Think about it like this, the book is written backwards in the sense that, imagine you tried to learn about options theory through a conventional method. You took maybe an MSC finance or an MSC financial mathematics or something like that. What you would typically have would be maybe a 12 lecture course. That course would start with a Binomial Model, would go into some stochastic calculus, you learn about Ito’s Dilemma, you learn about Tychonoff’s theorem, you learn about some partial differential equations. You’d use the Feynman–Kac theorem. 10 lectures later, you end up with Black-Scholes valuation function. You then spend another two lectures differentiating that Black-Scholes valuation function to get the greeks. And by the time you finished all of those 12 lectures, you’ve ended up really not being able to see the wood from the trees. Now, that work is all super important. If you’re going to go and build a pricer or you’re going to do some formal model, you need to know that sort of thing. But really, you’re not really equipped to trade options in an environment that most market makers and investors find themselves in, which is where simplicity and intuition are a far greater value than mathematical formulas. 

Bilal Hafeez (36:38): 

And actually that’s true because I’ve worked with many options traders and they’re not necessarily hardcore mathematicians. I’m not sure if they could derive Black-Scholes, the actual market makers themselves, but they’re extremely good options traders. 

Adam Iqbal (36:51): 

Yeah, absolutely. Exactly that. The motivation for that book really came from looking around at my colleagues at Goldman and thinking that the people here are true experts in options, understand options like the back of their hands. But very few of us, some of us have gone through all of that math, but most people are using heuristics rules of thumb, the experience that they’ve gained on the options desk over time. They’ve all learned from their own seniors writing down a few scratches on a piece of paper and so on, in this disorganised way. Now, not everyone can go and spend 10 years or whatever, sitting on an options desk. So what I wanted to do was write a book in almost reverse order, give you all of the intuition, and only in chapters nine, do I actually introduce the Black-Scholes and formal model and I only really do that because I will want to convince the reader that this book is rigorous, it’s not a hand wavy explanation of options. One way of thinking about it is to borrow a little bit of lingo from Thinking, Fast and Slow, a typical book will train your system too your deep quantitative approach. You’re thinking about options and does very little for your intuitive fast system one way of thinking. And that’s really what volatility practical options theory tries to do. 

Bilal Hafeez (38:02): 

And when I started off in finance, it was a number of years ago now, but the books that I read were the Taleb, Dynamic Hedging book and then The Whole Futures and Options book. Can’t remember the full name of it, but those were the two books there that I was told to read and I read them and they were good. And Taleb book was a bit more practical, nice, funny examples and written in the Taleb-esque style and the whole book was a bit more serious. What’s your view on those sorts of books? 

Adam Iqbal (38:29): 

Obviously, they’re excellent. I think we might be a similar-ish age, I probably read those books out rather the same time that you were reading those books. Obviously very formative and very helpful. I think they’re also quite old books at this point and classics, but I think the world moves on, markets move on and we have perhaps different ways of thinking about things as time goes on. One thing that’s definitely happened and certainly in my experience is that pricing, decision making times have come down a lot, really have come down a lot. 

You have minutes to make decisions now, markets have got quicker and so on. And so I think one of the key things that I try and do is give you ways of analysing options in seconds or minutes. Now, that’s obviously useful for a market maker where you assign the market and you have lots of things going on. Even if you are an investor though, and maybe you can trade a little bit more on your own timescale, the market maker, I think those ways of thinking are still super, super useful because anything that really brings down the bar to you thinking about an option, if you can do something in your head that you can do with 90% accuracy and not have to use a price, you’re probably just much more likely to go and look at a vol surface and come up with the trade that you wanted to do because you’ve taken out so much of the extra work that you would’ve to do. So I think it’s useful from that perspective at all. 

Rules of thumb for trading options 

Bilal Hafeez (39:44): 

Now, you mentioned heuristics or these quick ways of thinking about things or rules of thumbs, can you talk about a few? 

Adam Iqbal (39:50): 

Yeah, fine. Let’s do one. The best one, the one that I use every single day when I sit down the desk, really, what you need to do is just remember this one number, which is 4.2, it’s the most important number in options. So the formula for the breakeven price on a straddle is just 4.2 times the implied vol, times the square root of the number of calendar days to expiry. And once you brought that number, you should make your decisions about options by just looking at a vol surface pretty quickly. 

Bilal Hafeez (40:19): 

Let’s just be clear just for audience, again, what a straddle is, a straddle is just where you buy a call and a put so that a payoff there is you basically want the market you’re focusing on to be outside of the range of that, which would then be called the breakeven. 

Adam Iqbal (40:33): 

Yeah, exactly that. So you buy an out-of-the money call and put. You have a V-shaped, symmetrical profile, pay-off profile. You make money in both directions, but you need spot to go, move more than what you paid for this thing. And that’s what you call breakevens, exactly that. So let’s say we’re sat there, it’s Thursday evening, it’s the first Fridays of the month, non-farm payroll is tomorrow, you look at the vol markets and overnight Euro-Dollar volatility is trading at $10. So we just say 4.2 times 10 times the square root of one, which is one calendar date of expiry which is one, that’s 42. So 42 basis points is the breakeven price of that straddle. So now you can just think, “Oh, well, if I think the data’s going to move Euro-Dollar spot by more than 42 basis points, I should look at buying this thing. In other words, I should look at selling this thing.” 

Bilal Hafeez (41:17): 

Oh, that’s great. And 42 base points is 0.42%, so if I expect euro dollar, whichever market that you are referring to move more than 0.42% tomorrow, then I know it’s attractive for me to buy that straddle, that overnight straddle. 

Adam Iqbal (41:30): 

Yeah, that’s right. Now, the book goes into a few more nuances like there’s a difference between breakeven points and standard deviations and things like that and the book explains it, but to a good extent, you’re there. That’s a great thing to remember. Now, in my own case, I’m not great at doing square roots in my head, so what I also do is I just remember three points. I just remember, well, square of one is one, so I know that one, then I just remember the 4.2 times a square of 30 is around 22. So I multiply one month vol. If one month vol was 10, that would be a 2.2% breakeven roughly. And then the square root of 4.2 times a square of 365 is 80. So one year vol was 10%, then that’s an 8% break even. And I just remember those three points. If I do a three month trade or whatever, I can work on that later, but when I look at overnight, one month, one year in the market, I’ve made a decision on what’s going to happen today, what’s going to happen over the next month and what’s going to happen on the more longer term horizon. 

Bilal Hafeez (42:22): 

And you can apply this to any market, isn’t it? Because you’re just looking at vol. It’s not based on just FX. You can look at equities, look at equity vol, and then you can work out what’s the expected range or breakeven for straddle for the next month. And then you can decide, do I think S&P 500 is going to be outside of that or going to move by that percentage or not? It’s excellent. I love that. 

Adam Iqbal (42:41): 

Exactly that. It is just Black-Scholes model rolled into one number. If you were to plug in zero interest, you just plug in zero interest rates, you set the strike to be equal to the forward, in this case, it’s spot because of zero interest rates. And that number just becomes 4.2. So it’s just Black-Scholes with all the bells and whistles removed and simplified as much as possible. But it’s probably the most useful thing that I’ve had in my whole time in the markets. I use it more than anything else. 

When to use options 

Bilal Hafeez (43:06): 

And whenever I have somebody who has an options specialty on my podcast, I do like to ask them about this idea that options are expensive. So typically, the implied volatility extracted from the option price tends to be higher than the actual realised volatility. So it seems like when you are buying options, you are overpaying for options over time. And so, is this a problem? Are options always overpriced? And I’m going to guess what your answer is, are options overpriced or not because of this implied vols of realised volatility. 

Adam Iqbal (43:40): 

Yeah, exactly. Like you said, you know what I’m going to say, it’s the risk premium. It’s the volatility risk premium. So in this case, we know that volatility goes up on the rainy day. When it rains, the volatility goes up and therefore, I need to pay a premium for options relative to what they’re realising on average, they are the umbrellas in the former example. 

Bilal Hafeez (43:58): 

So should you buy options then? I guess this tells you that what we call expensive options aren’t necessarily expensive because you are actually getting rewarded for holding the option for the event of these extreme events. 

Adam Iqbal (44:12): 

Yeah. It’s for the extreme events, but it’s the fact that these extreme vol events of are correlated with the state of the world. Typically an extreme vol event happens when we’re going into a bad period, like in the pandemic, volatility exploded higher and you really pay because your consumption is going to be really low in the pandemic. We’re going into a deep recession, volatility is going up, that is a hedge against that rainy date, and so you need to pay a premium to earn that. 

Bilal Hafeez (44:37): 

Yeah. So it’s important not just to think about the bad outcomes, but also the correlation of that bad outcome with your portfolio or with your views of the world or the world that you think you’re going to enter into the next period. 

Adam Iqbal (44:50): 

Exactly. You see that risk premium both in implied volatility versus realised volatility, which is what you mentioned, but you also see it in skew in risk reversals and butterflies and other aspects of the vol curve that do very well when the world does badly. Those things typically trade at a premium. 

Bilal Hafeez (45:05): 

And how do you decide, obviously I’m guessing you’re a bit biassed because you make options, your market make on an options desk, but when is it the right time to just buy the cash market, so just buy spots, or when is it right to use options to buy into a market? Is there any kind of framework you like to think about to use to answer that question? 

Adam Iqbal (45:26): 

I think the risk premium framework, it can be quite useful. If you worked out, let’s say you did some analysis and you said that, okay, well the risk premium in say, Aussie Dollar Spot is only 1% or something like that, but the risk premium in options is really high. The real the implied vol is 10, maybe 20%, 30% greater than where in that case, it doesn’t seem that smart, the option sounds like it’s expensive to try and hedge a bearish position in Aussie. You would say, “Okay, maybe I should just sell the spot in that case.” So you could do a risk premium based analysis, would be one way of looking at it. 

But I think it’s difficult to do in some aspects, because again, I’ve almost not compared like with like, because when I talk about realised vols, that’s a backward-looking thing. So really, if you replace my comment on realised vol with my expectation of realised vol is significantly lower than and where implied vol is. And my expectation of where, the fair value of Aussie is in line with where Aussie is trading, then I would prefer to maybe do the spot trade if I had a better position rather than to buy the options. And then, what’s your thought about the benefit of using options to get non-linear payoffs? So the payoff structure is very different, you can get interesting payoff structures versus holding just a cash position where it’s just linear to the price. 

Yeah. In some ways it’s the same question because the fact that the payoff is nonlinear is what gives you volatility exposure in the first place. So if you’ve made a view on vol, you’ve already said, “Oh, I want not linear structure.” If I had a linear structure, it wouldn’t have volatility exposure to it at all. The vega is a result of the convex pair of structure. 

Bilal Hafeez (47:02): 

Yeah. Now, that’s a good point. Actually, I’ve just asked the same question in another way, I suppose. That’s absolutely right. And have you found that when you trade say, less liquid options like emerging market options versus say highly liquid, G3, G10 options, do you approach that differently as a market maker or not? 

Adam Iqbal (47:20): 

I think you have to, but I don’t think there’s anything particularly unique to options in there because it’s just like illiquidity in any asset where you can’t get out, you demand the risk premium, but you could call it an additional liquidity premium or you could bundle it all in with the risk premium, but there’s some additional premium that you demand to take the weak side of the market, the side of the market where you can blow up, you demand something extra for that. And so that would apply to emerging market options, it would apply to a lesser extent to… Even to G10 options which are very liquid, but stay relative to spot, they’re not quite as liquid as spot would be and so maybe additional premium built in for liquidity in there as well. 

Bilal Hafeez (47:57): 

Yeah. That’s great. We’ve covered a lot of ground here and I do recommend everybody get a hold of the books to delve into these concepts more. And I do think it’s really important for people to understand these notions of risk premium. This is how the most sophisticated investors tend to think about the world. And also it’s important to understand some of the intuitions that we have around this all. And also volatility and options is incredibly important to be able to know when to use options, how options are priced and so on. Now, I did want to ask some personal questions as well. One, I always ask of all my guests is, what’s the best investment advice that you’ve ever received? 

Adam Iqbal (48:34): 

I think in my case, I’m a pretty broad believer in markets being pretty efficient, and so, as you know, I think the risk premium is really the main place to get returns over time. I think one of my heroes in economics is John Cochrane. I read pretty much everything he writes. And the advice based on that kind of approach to thinking is just buy your stocks, do very little with them, look at them 20 years later and you’ll earn a decent return over time. And so I think for me, it’s just really buy something with a risk premium in it and hold it and don’t really trade it very much. And that’s what I do. That’s really what I’ve done. And when I think about my personal investments, I just buy stocks and I hold them and do very little else. 

Bilal Hafeez (49:16): 

I think there’s a lot to be said for just having an approach like that. Now, the other question was I talked about your motivation for writing the books earlier, but why did you decide to write the books in the first place? Like write books, that’s not something people… You could have written a blog, but you decided to go out while you have a day job to write a book. 

Adam Iqbal (49:35): 

I’d say a couple of things. I think it’s a pretty solitary experience. You need some deep personal motivation, I think, to go out and write a book. And like you said, I have a busy day job and so on, so staying up late into the night and trying to write and so on is quite a difficult thing to do. In my own case, there were two reasons. One was, I spoke about how I might have become an academic and I ended up giving that up to go into what I found more exciting at the time, which was going into markets, but I did still really, really miss that side of thinking and writing and publishing that you get from academia. And so this was one way of doing some of that. Now, it’s not original research, it’s not quite the same, but it’s something that is similar in some aspects to doing academia. And I think the pandemics are actually very, very good times for writing books, nowhere to go. I was working from home and I found myself with an extra hour, hour and half a day and nothing to do with it, so I got writing on the second book. 

Bilal Hafeez (50:36): 

That sounds good. The other question I wanted to ask was productivity hacks. Obviously, sounds like you must have some system to keep your productivity so high. What’s your secret? 

Adam Iqbal (50:48): 

One thing that I always found quite odd was how we go through life until the age of 21, 22, 23, whenever we leave university thinking that the best way to learn is to read textbooks, answer questions, and do exams and so on. And then when we become adults, we think that, “Oh, we can just skim a page and read a book here, read a book there and so.” Now, I found that a little bit odd and I realised that that affected me quite badly. I read a lot of books and I think some great, great books. When I think about, I read The End of Alchemy, Mervyn King’s book, which I thought was absolutely fantastic. 

But when I think about what I learned from that book, I’ve got maybe four or five key messages from it that are in my mind and very important messages, but I don’t know how to really apply that knowledge to what I’m doing every day. And so what I’ve tried to do is actually read a lot less, I listen to books and audio books to try and keep up with that, and therefore, I probably absorb a lot less than if I’d read them. But what I do with my reading time is I try and read textbooks and I’m a huge fan of online courses, places like edX, Coursera. I recently did a machine learning course and I did the whole exam on it and everything like that. And I find that those ways of learning that you have when you are a student are still probably the most ways of building knowledge that you can then apply going forward as well. So I don’t know if I’d call it productivity hack, but it is that, I essentially go a bit old school on my learning. 

Books that influenced Adam 

Asset Pricing (Cochrane) and End of Alchemy (King)

Bilal Hafeez (52:13): 

Yeah, that’s useful. It is a very good idea actually. Then you really do understand the subject. Now, you mentioned a couple of book, well, one book there. So what are some of the books that have really influenced you? 

Adam Iqbal (52:24): 

I mentioned that one- 

Bilal Hafeez (52:26): 

Actually had Mervyn King on podcast about a year ago to talk about that book. He’s great. 

Adam Iqbal (52:31): 

Yeah. I think I listened to that one. His other book as well with John Kay, Radical Uncertainty is also fantastic. I think probably the single most influential book, I mentioned my biggest influence in economics, John Cochrane earlier, his book, Asset Pricing, published in 2005, is a little bit old now, but it’s still my go-to and all things theory and pretty much everything he write, I’d say is probably the biggest influence on me so far. 

Bilal Hafeez (52:54): 

Great. That’s excellent. Now, we talked about this book, the most recent book that you’ve written, Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory. Is the book out? And if so, how can people get hold of the book? 

Adam Iqbal (53:05): 

Yeah. The book is available for pre-order on Amazon and elsewhere. We are printing at the moment so hopefully within the next month to six weeks, it’ll be delivered. 

Bilal Hafeez (53:16): 

Great. And I’ll include the links on the show notes. And then your other book that you wrote a few years ago, Volatility: Practical Options Theory, that presumably is available on Amazon and all those good book sellers. And are these the best ways for people to learn about your philosophy? Is there any other way for people to follow you in some way or not? Do you blog or have a newsletter or? 

Adam Iqbal (53:37): 

Yeah. I don’t tweet or anything like that. I’m on LinkedIn if anybody wants to discuss anything to do with the books. I guess the other thing, I should probably mention about the new book, Foreign Exchange, we spend a lot of time on the risk premium aspect of it, but the other thing I would mention about it is that it’s got a lot of other things in it that practitioners new and experienced will find helpful. One of the things that has struck me is that a lot of people enter market from backgrounds in physics, or engineering, or history, or something, but not really economics. And then we all try and assimilate some economics knowledge on the fly.We read research, we learn things on fly in quite an unstructured way. And so the other thing that the book tries to do, and really the second part of that book is trying to give people who are either from an economics background, want a refresher, or people from a non-economics background, all of that theory that they need to understand foreign exchange, namely, interest rates, inflation, we mentioned risk premiums, purchasing power parity, really exchange rates and so on. Put all of that into one organised and structured place and put it into a book. So I think it’s a book really for practitioners on the risk premium side, but also on the economic fundamental side as well. 

Bilal Hafeez (54:53): 

Oh, that’s excellent. And I’m going to buy the book for everyone in my team as well, because they often ask me, “What books should I read?” And sometimes I’ve books that I read when I was first starting out, but as you’ve said, things have changed. And I think from what I’ve read of your book, it really is probably the best, most comprehensive book on FX. And also it strikes the right balance between that practitioner’s knowledge, it bridges that gap between the practitioner side and the academics theory side. It’s hard to find one book that combines both sides well. 

Adam Iqbal (55:22): 

Yeah, you say it well. My worry when I was writing was that the academics are going to complain that this is not rigorous enough and the practitioners are going to complain that it’s too academic. So that was my worry, but I’ve tried to pitch it in a place where hopefully I satisfy and dissatisfy both side and try and get the ideas across. The main objective is get the idea across in the simplest and most concise way if it’s not perfectly expressed, which is really the idea in volatility as well, make the approximations to give you the end result. 

Bilal Hafeez (55:52): 

That’s excellent. So with that, thanks a lot for coming on the podcast, it’s much, much appreciated. And good luck in the day job and also as life as an author as well. 

Adam Iqbal (56:01): 

Thanks very much, Bilal. Thanks for having me on, it is a real pleasure. 

Bilal Hafeez (56:04): 

Thanks for listening to the episode. Please subscribe to the podcast show on Apple, Spotify, wherever you listen to podcast, leave a five-star rating and a nice comment and let other people know about the show. We’ll be super grateful. Also sign up to become a member of Macro Hive and macrohive.com. We’ll be back soon. So tune in then. 

Bilal Hafeez is the CEO and Editor of Macro Hive. He spent over twenty years doing research at big banks – JPMorgan, Deutsche Bank, and Nomura, where he had various “Global Head” roles and did FX, rates and cross-markets research.

(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)