Campbell Harvey is Professor of Finance at Duke University – The Fuqua School of Business and a Research Associate of the National Bureau of Economic Research. He is one of the world’s most celebrated financial economists and author of a number of papers that have driven significant leaps forward in the way we think about markets. Cam has been an advisor to Man Group for almost 20 years, helping the firm with its extensive research efforts. Cam is a Senior Fellow at OMI Advisory, Man’s investor advisory service. He has appeared many times at MAIS, our client conference in Oxford.

It’s always a pleasure to sit down with Cam and I was delighted to feature him in this, the second of my series of interviews bringing the insights of our network of experts to a wider audience.

1. Which of your recent research projects has most excited you? When do you know that an idea has the potential to go from an interesting initial set of results to a fully-fledged piece of research?

I have a recent paper called The Disagreement of Disagreement with Christian Goulding and Hrvoje Kurtović, PhD. It starts with a simple observation that there are many proxies for disagreement in markets, such as dispersion of analyst forecasts, short interest, idiosyncratic volatility, etc. The first step in our research was to measure the correlation between these different proxies. You would think the correlation should be high. It is not. Indeed, the correlation is near zero!

This means many papers that use one proxy for disagreement to explain something will find that their results are not robust to switching to a different measure of disagreement. As soon as we estimated the correlations, we knew we had a big paper. We could have published a purely empirical paper but wanted something more impactful. The key contribution from the paper is the development of a composite measure of disagreement.

The intuition is straightforward. Think of analyst forecast dispersion. That might be a measure of the disagreement among analysts. But for market participants it is just one input into their thinking. It is unlikely that analyst disagreement is the “true” measure of disagreement – but it is an input. Our composite measure theoretically combines analyst dispersion, short interest, idiosyncratic volatility and other measures.

Our results show the highest premium is for low disagreement – many might think the opposite but that is not what the results show. We show that a portfolio long low disagreement and short high disagreement stocks earns on average 21% per year. The paper has garnered a lot of interest with over 16,000 downloads on SSRN.

2. You have recently done some fascinating work on FX hedging. Why were you drawn to this topic?

Part of my engagement at Man Group involves visiting major institutional asset owners such as pension funds. I am able to learn from them what are the most important issues they face. This is useful for me in the classroom and also useful in developing relevant research ideas.

One issue I hear a lot from these institutions is the question of whether to FX hedge their investments in global equity markets. Indeed, I was a bit surprised because the FX hedging problem is an old one (and I hadn’t really followed the literature in decades). I went back to the academic research and there are hundreds of papers but very little practical guidance as to what to do. This provided an opportunity.

Our paper is simple. We look at static decisions to begin with: 100% hedge all the time or 0% hedge. The results are intuitive. In countries that have a history of low rates like Japan, you should not hedge because you can earn the interest rate differential. In countries that have a history of high rates, like New Zealand, you should hedge. So the interest rate differential is really important. But what happens when a high rate country becomes a lower rate country? Here we need a dynamic framework. We condition the hedging decision in each market based on the carry. This means you hedge your equity exposure in some countries but not all. Further, the choice for a particular country can change through time. We find that this simple dynamic method dominates the static strategies. Our paper also looks at other dynamic signals such as momentum and value (deviation from purchasing power parity). We also explore an optimal hedging framework that uses the information in carry but also takes into account the correlation structure among equity the FX markets. The bottom line of the paper is that asset owners should consider adopting dynamic FX hedging rules. You can read the paper here:

3. You’ve written a lot on defi and blockchain. What do you think will be the most enduring applications of this technology?

This important innovation is mainly about efficiency. We know that reducing transactions costs is a good thing for economic growth and this technology is on track to reduce costs. There are two channels of improvement. First, the execution and settlement are simultaneous – as opposed to traditional systems whereby settlement is delayed at least 24 hours. Second, everything is peer to peer in decentralized finance. As such, you cut out the middle people and save whatever fees they earn.

The whole space is very exciting. I don’t pay that much attention to bitcoin but focus more on tokenization (which is not possible on the bitcoin blockchain). The most successful tokenizations to date are stablecoins. These are tokens backed by collateral like US dollars. These tokens can be used for payments anywhere in the world with a transaction time of 12 seconds or less. It is no surprise that central banks are scrambling to launch CBDCs (central bank digital currencies) – because these stablecoins are de facto CBDCs!

However, tokenization is bigger. In the future, all traditional assets will be tokenized. This provides consumers and investors with a choice as to what you pay in. Today, there is no choice, you pay in US dollars. In the near future, you might pay with a token linked to bond (where you earning interest) or a token backed by gold. It is fascinating to watch this unfold. The difference between 2024 and 2023 is a striking. In 2024, more traditional companies have invested in this technology. They realize there are considerable opportunities to reduce costs and improve their product offerings to consumers. This is the new world of Web3.

4. What one paper should all of us in finance sit down and read?

That’s a bit of an impossible question. There are a core of papers that everyone needs to read such as Markowitz (1952) which is the foundational paper; Sharpe (1964); Black and Scholes (1973), and many others including Nakamoto (2008). I recently wrote a tribute article for my co-author Harry Markowitz. In the article, I said: “My research epitaph might read: He was a careful reader of Harry Markowitz’s footnotes.”

The mark of a great paper is that it inspires other papers and further advancement of knowledge. For example, in the original Markowitz paper on page 92, he makes it clear that his model which produces the portfolio with the highest expected return for a given level of volatility does not work if investors have a preference for skewness. A single sentence in this paper led to a number or research papers by me. Investors have a distinct preference for positive skew (and a dislike for large drawdowns). I recast the Markowitz model into expected returns, variances and skewness. Now for portfolios with the same expected returns and variances investors pick the one with the highest skewness. The Sharpe paper is a model where risk and expected returns are constant. My early research generalized this model to incorporate dynamic risk and expected returns. The Black and Scholes paper is filled with gems. Indeed, those that have not read it might be surprised to realize it is a paper about corporate finance. Any student of corporate finance will have to deal with options and the Black and Scholes paper is the first stop. Again, there are many simplifying assumptions like constant volatility. There are hundreds of papers that have generalized their model.

5. What single risk do you think is most under-appreciated by markets currently?

I think there is a poor understanding of the difference between risk and uncertainty. I look at it this way. Suppose you know the distribution of an asset return and it is normal. You might consider the risk the known standard deviation. Now suppose you know that the distribution is normal but you are not sure of the mean or variance. This adds a level of uncertainty or ambiguity. You might pick a level of volatility, but you could be wrong. This is rarely taken into account. The third level is that you don’t even know what type of distribution is the true distribution. It might be normal but it might be an asymmetric distribution. Further, there is no “one” distribution. The distribution could change shape through time depending on the regime you are in.

This level of complexity is often brushed off and simple risk measures are deployed. Indeed, this is yet another footnote from Markowitz who, in his famous framework, assumes that you know exactly what the distribution is and exactly know the mean, variances, and correlations. There is zero uncertainty in his model and he was wise enough to recognize this limitation. In the real world, there is uncertainty. However, this uncertainty is rarely incorporated into risk management and portfolio selection.

If you didn’t see the previous 5 Questions, with Tom Holland, you can read it here: 5 Questions With Steven: Tom Holland – Historian and Podcaster

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