 Hi and welcome to Bright Minds from Tick-Mail. I'm your host, Patrick Munnerly, and in this series we're setting out to answer some of the most commonly asked questions around investments and trading through entertaining and insightful conversations with seasoned insiders. We all like to think that we are rational actors and that our decisions are fact-based, made with cool heads and free from outside influence. However, the fascinating field of behavioural finance tells us a different story. By studying the effects of cognitive biases, such as loss aversion, herding and noise trading, researchers have shown that our subconscious underlying assumptions about how the world works are often wildly inaccurate. Recent research by Delba, a leading research company, suggests that the effects of cognitive biases can have a negative impact on portfolio performance of up to 3%. Behavioural finance builds on the groundbreaking work of behavioural economists Daniel Kahneman and Amos Tversky, whose work on loss aversion, heuristics, cognitive biases and priming, among many other phenomena, was summarised in the book Thinking Fast and Slow. By applying the findings of behavioural economics to our own decision-making in the markets, we can start to recognise and understand how our own cognitive biases, which can help us overcome bad decision-making and give us a better chance of trading success. Our guest today is behavioural economics expert Paul Craven. Paul has over 30 years of sales and marketing experience with Schroders, Pimko and Goldman Sachs, and he travels the world delivering talks and training to organisations such as Facebook, Lloyds and Blackrock, among many others. Paul is also a member of the Magic Circle and as a result has a unique perspective on the tricks our minds can play. We'll be talking about some of the most common biases that affect investment performance, how to spot them in our own behaviour and ways to overcome them. We'll also be discussing how flawed thinking affects the market at large. Paul, thanks so much for joining us today. Could you get things started by telling us a bit more about your career so far? Well, I started in the city in 1986 and I worked for Schroders for 17 years and that was an amazing 17 years in many ways, not least because it was a great firm and still is. But of course in terms of what the markets were doing over that period, we had a 20-year bull market in the 80s and 90s. We had the tech boom and then we had the crash afterwards. That was quite a first half to my career in terms of what I witnessed and what I saw. I think it was then that I began to get interested in behavioural science or behavioural finance largely because of what the markets and the economists were doing and realising that people weren't quite as rational and as efficient and as evidence-based as the classical economics textbooks said they should be. That's really where my interest first was sparked. I then was lucky enough to spend a few very happy years at PIMCO. People didn't know much about fixed income in the UK pensions market in those days. They certainly had some but it wasn't really top of their priority until the regulations started to change. That was a great four years there where I played as part of the small cog in the wheel to hope put PIMCO on the map in the UK. Then I was fortunate enough to move to Goldman Sachs Successive Management in 2007 where I started off as head of UK institutional sales and ended up looking off the European business there until the beginning of 2014. Really over that period we've seen so many market cycles, we've seen booms and busts, we've seen so many exciting things and desperately difficult situations not least the global financial crisis that I came with from all that Patrick thinking what can I do now? My first love has always been behavioural finance and so for the last seven or eight years I've been waving the flag for that really trying to explain to people how to use it both in two or three ways really. One is in terms of investment policy and you've already said looking at one's self, being self-aware of one's own biases. Secondly, how can we make better decisions within groups and finally how can we be more better at communicating, better at persuading, better at influencing. So those are really the three parts to my behavioural science flag waving. At an institutional level do you see behavioural finance being an ethos or a practice that is pushed far more heavily now or is it still something that's considered more on the periphery of institutions? Oh I think it's getting taken much more seriously than when I first started looking at it. I think when I first started getting interested in the whole topic, which I would say was probably in the early 2000s when a Canon got given his Nobel Prize for economics. That's really when I first started becoming aware of it properly in terms of the financial markets. But in those days, if people started thinking about or talking about it, the typical question I'd receive was well how do you monetise it? You know is there a product that we can design? And some people said you know you want to be a quant investor because that takes out a lot of human decision making. Others said no no no you want to go the kind of Ben Gray and Warren Buffett sort of more of a value orientated approach. And it was very product driven where I think it's got much more sophisticated and intelligence in the last few years is people saying well let's not necessarily try and design a product. Let's just try and improve investor's own behaviour. So I'm for example working with a very exciting group at the moment called Behavior Lab who are analysing data looking at how asset managers whether they hold on to stocks for too long, whether they sell them too early. So it's not trying to tell them how to manage money or how to value a stock or bond. It's about when you've decided what you want to buy, how do you hold it? How do you sell it? How do you buy more? And are there patterns in your behaviour that come from your biases that if we can analyse and improve their causing underperformance what can we do to improve them? And it's a very exciting field I think and it's one that I think is the way forward for behavioural finance. What are some of the most prominent cognitive biases that affect traders or asset managers and some of the practical ways of overcoming some of the most common biases? The endowment effect, the idea being that I own something and therefore I like it more, I value it more. I was talking to an American friend of mine many years ago called Charlie Ogle and he came up with a line I never forgotten. He said, he said, smart cowboys don't fall in love with their horses. I think that's so clever if you watch too many westerns as I do. But of course in financial terms what that means is you know don't fall in love with your stock. Are you sure you can buy a stock for the long term? But that's not what I'm arguing against. I'm arguing against someone buying something. It goes up very quickly and then people find more reasons to stay fully invested or buy some more. Now again that might be the right decision for any number of periods but the danger is, and I've seen this a number of times, is people just end up saying I can never sell this stock. I love it so much and of course you can have a great time on that lovely bull market ride and then it all finishes and who was it? That's slightly politically incorrect phrase that Barton Biggs came out with years ago. Bull markets are like sex. They feel best just before the end and so I've learned the tone already but it wasn't my comment. That would be one bias that I've certainly identified. Again, looking at the data, looking at someone's data over say three or five years, you start to spot that pretty quickly and it can be very helpful to have nudges to remind you of your behaviour because you don't want to end up, you don't want to end up on the impecunious side of the balance sheet. I think the most pernicious bias though is probably confirmation bias and again just to refresh people what that means. It means the idea being I've come back with my conclusions. I may have made a good case to buy something say a stock and the fact it's gone down five or ten percent. It doesn't make me challenge your question myself. Now I'm sure people listening will think well I would but a lot of people don't. They say no, no, I know I'm right. They almost say the market is wrong and they tend to find more reasons why they're right without thinking well where could I be wrong and that single question where could I be wrong? Five words. I think that if I've seen mistakes repeated in my 30 years in the markets as people don't ask themselves that question they may just say give me more reasons why I'm right. Now here's the interesting thing though. It sounds like you're not confident or of course our industry flimes on people who are confident. You can't really go up to your boss and say look I've got this really good idea let me tell you where I might be wrong because it's not very career enhancing but actually that's what people should be doing sort of unconsciously because having that sort of a plan that says where could I be wrong and being able to reassess your ideas and let's face it I mean no one gets the market right all the time we kid ourselves it's if you get right markets right just over half you'll do you'll be better than nearly every investor out there or most investors out there. So it's a confirmation bias is pernicious. And do you think it's possible for an investor or even just the average person really to fully overcome biases or is it more a recognition and acceptance process that you can recognize the behavior coming from the bias? To take your question to fully overcome no because we're human and unfortunately or actually I would say fortunately human nature doesn't allow us to become totally machine like we're not all GPT4 in our thinking and thankfully in many ways. However we could improve a lot of the ways we do manage money for example and I think again you touched on it in your question is just being self-aware that you and I and our fellow listeners all have biases just makes them slightly less dangerous that's where I would start self-awareness know thyself in the words of the Delphi Oracle and so how do you get to know yourself well I mentioned one way earlier looking at your own data trying to understand your patterns of trading do you do certain things at certain times the sort of science or even the neuroscience in this now is fantastic you know people have people are wired up in trading rooms are wired up sometimes to look at their their hormones the their their brain patterns and things to see how they react under stress and particularly how you react under stress is a really important way of understanding when your biases really begin to manifest themselves and again just talking going back to a point earlier about people being overconfidence and overconfidence can become arrogance here's the thing that I've I've noticed in in my 30 years talked to me many years ago but I've seen it in action sometimes your your your biggest strengths become your biggest weaknesses when you have them in excess so we like people that are that are confident and and forward thinking and progressive and able to express their views but actually people who are overly confident become arrogant and therefore almost don't listen to anyone else's views and it's true of most virtues most virtues in excess become a vice certainly in in terms of behavioral science and so just be aware and I think there's another piece of advice I'll give is when you get it right a few times in a row as as many investors do hopefully that's a that's a function of your skill and indeed you'll have evidence to prove it your skill however I would just remind everybody that sometimes you can be lucky it may not be the process that's good it may be luck and ultimately we all want to be as investors skillful and lucky now you can't be skillful and unlucky and there's no doubt about it I've seen really good investors suffered periods of terrible performance for you know one two three four years sometimes just because almost they're unlucky almost yeah but the skillful ones reassess reevaluate and then come back even stronger they learn from their mistakes if you like it's the ones who are unskillful who happen to have some luck in the markets the right sector the right time through no skill of their own or something those are the ones to watch out for because their luck will run out but just remember when you know when when the travelers on the road get wealthier set of the high woman and we've got to spot the high woman from the the bona fide travelers yeah I mean and I and I guess that it becomes very true and most prevalent in market bubbles definitely I mean talking about I mean Mark I'm I did history at Cambridge about 2000 years ago and so I've always had this love love of looking back at the old days whether it would be 10 years ago 100 years ago or further and obviously we now have quite a lot of data on financial markets that goes back certainly for the mid 19th century in many cases and we have market prices for lots of things that go back a lot further but in terms of some stock markets and I've I've always had an interest in studying booms and busts if you like or bubbles and crashes and there's been some good work on it over the years uh Charles Kindleberger wrote a good book but if your listeners want a a really interesting book to read that only came out last year which I've been advocating everyone in the marketplace should read it's a book called um boom and busts by William Quinn and John Turner and what they've done is gone back and looked at about a dozen or so bubbles going back to 1720 but they do things like the the mining stocks in the 1820s they do the Australian land bubble in the late 1880s they do the US stock market in the 20s the Japanese bubble in the the 80s um and the dot com bubble and what they've done is they come up with something that I think is fascinating I mean really really interesting whether you're interested in in stock markets whether you're interested in history whether you're interested in behavioral science and it's a very very accessible but boy it's very readable every chapter is it's easy to read it's not a academic book at all even though it's written by two academics they said the concept of bubble is wrong because a bubble just gives a suppression of something sort of just blowing blowing getting bigger and bigger and then just popping and they question that for a number of reasons not least because they go back and they look at some of their bubbles in history and say actually the assumption is that all bubbles are always bad and actually there's plenty of bubbles in history and they they talk about it where lots of good have come out of it um sure but there are some really really bad ones and we've indeed we've lived through something in the last three decades but what I like most of all about them saying why this bubble concept is not helpful they say it's more like a fire not a bubble so so forget the word bubble now I'll try and I'll try not to use it myself but I'll fail um to have a fire you need three things you need fuel oxygen and heat and they look at these three different components in terms of a real fire and take this metaphor and say well what are the financial market equivalents so the fuel for example which is behind almost every single bubble is things like loose money ease of credit low interest rates that sort of environment right now again look at all the the b-word look at all the those stock market booms right that fuel is there you need oxygen now what does that mean you need marketability so people need to be able to access whatever is the latest exciting idea whether it be bicycles in the 1890s or tech stocks of the late 1990s how easy is it for the people to to to purchase it how tradable is it and then finally the third ingredient in a fire is heat which is what you and I would call speculation you know Wilken amateurs novices get hold of it because again a function of most of these stock market booms is that people are buying who probably wouldn't be considered professionals who who who helped to help to basically heat up the budget and so what's the spark that sets it all off well normally it's either some sort of innovation or it's government policy pushing something and and and again I listen I don't it's not my idea it's it's Quinn and Turner's like Quinn's and Turner's idea but they make a very good case if you accept those three those three ingredients fuel oxygen heat um light and a spark that sets him off and they go through all these bubbles I have to use the word I try not to use it they go through all these booms in markets and they point out that all three of these factors are always there and why that's so useful for for us all now it's the first I think it's the first major work on this subject that actually allows us to identify or help us identify future stock market booms or booms in any asset class is not necessarily stock markets because we look for these three ingredients and we say are they all there and and their their argument again beautifully argued beautifully written easy to understand by the lay person uh sets these out so I've been advocates so I've gone on a bit too long but I'm sounds like I've got a commission in this book but I haven't but it's a really interesting way of looking at behavioral biases behavioral biases something I I love about and stock market booms and busts and trying to try to sort of quantify and analyze what's going on and I think it does highlight the importance of a looking at the data and be remembering that we'll you know emotional animals you know there was at the end of that John the hype phrase the emotional tale wags the rational dog and I guess that that leads into um another another area which is obviously in the headlines um of late is the you know obviously the rise of artificial intelligence and robo advisors and what do you do you think there's a role for them to play in the field of behavioral finance i.e. does using machine learning help eliminate bias or or is that achievable on the premise that most of this stuff is designed by human beings in the first place anyway I'm not an expert in AI I've been playing around with GPT-4 quite a lot in the last few week few weeks normally asking it to do silly things like rewrite Shakespeare and the start of Bob Dylan or something but um in all seriousness will will will machines and machine learning help us overcome human biases and investment listen I'm sure there are people out there say of course it will in time and I have no reason to to doubt them in terms of the technology the way the technology is improving but I do believe and this may be wishful thinking this may be my own biases in play here when I talk to people who play chess at a very very serious senior level they tell me the following things the machine will beat a human being the best machine will beat the best human beings however the combination of a human being and a machine will beat the best machine so if that's true and if that carries over that simple argument isn't it may be too simple but I I retain my faith in the ability of human beings to make good decisions for the benefit of in in this case investment or chess or whatever it may be excellent and just I just want to roll back to to one one aspect of your of the introduction that I don't think I have given Duke do you care and attention to and that's what's the connection in your mind between behavioral finance and the magic circle yeah for me they meet around the back of the back of the circle in my head um let me let me just tell you why because for me behavioral finance or behavioral science or behavioral economics is all about understanding how we do and don't think particularly well and and what we get right what we get wrong when is our intuition absolutely wonderful and when do we have perfectly good mental shortcuts that we then apply in the wrong environment so they look irrational uh that to me is what how real people make real decisions in the real world that's my favorite homegrown definition of behavioral science why do I love magic because magic actually um exploits the fact that the mind doesn't doesn't work well and um if first of all I should say one thing very quickly because I have a friend who say well the trouble is the magic's deceptive and I said no no it's an honest contract between performer and spectator the magician has a sort of unwritten contract I will fool you I will try and show you something that will amaze you give you sort of sense of wonder and that's that's our agreement right and if he or she does a good job they they will get the applause or the dare I say the wide the the the wide-mouthed open amazement and which is obviously the idea so so what's the link between the two they're both about how the human mind doesn't doesn't work and and for me that's why my my passion my hobby my pastime magic and I'm not a professional magician as such although I do use it a lot when I try and explain in my talks for example a conference is how the mind doesn't doesn't work from an investment point of view I will use psychological experiments in my talks for the whole audience to see the strange ways their mind can work even though they think they're logical rational evidence-based analytical data-driven etc etc in real life they can be those things but they're not always those things what cannonman calls distinguishing system one and system two thinking excellent Paul thank you so much for your time today is there anywhere our listeners can go to to follow you online well I treat a lot as at Craven Partners I've got a website pullcraven.com and I'm about four fifths the way through finishing the book that I started during COVID which is really my non-academic take on behavioral science covers a lot of stuff I've seen in my career my life and other people's stories as well and tries to really explain a little bit more about behavioral science and how we can basically become better decision makers whatever we do so hopefully that book will be out later this year brilliant Paul well thanks again for your time today and really appreciate the the input around behavioral finance and certainly that link to the magic circle thanks again Paul thank you very much for having me I really appreciate it