Risk versus Reward

A beginner attempts to understand financial markets

Photo by Heather Gill on Unsplash

A Fool’s Challenge is a blog series narrating my attempt to beat my boss at turning a profit from £10 over one year. Statistics, data science, and economics concepts are explored throughout for any other fools considering embarking on such a journey.

With the safest option of sticking the £10 under my mattress and waiting for my opponent (my boss) to go bust ruled out as being too boring, I started to do a little research as to other options:

1. Put the £10 in a saving account and receive a small amount of interest, at no risk of losing the original £10. With the UK base rate currently at 0.1% and savings interest rates around 0.4%, I might hope to receive just a little more than 4p for my trouble (assuming the UK economy starts to recover from COVID).
2. Invest in a robust market index fund, betting on the economy to recover from its April 2020 COVID slump, and receive returns proportionally. The top result on Google suggests that the FTSE¹ average annual return is 7.75% since inception. Not bad. More than my 4.5% Council Tax increase this year at least!
3. Pick an established company (or two) in a relatively safe sector (Tech, perhaps?), buy shares based on some belief that they will do well this year and hope for the best.
4. Try to exploit the fluctuations in market prices through active trading: buying low and selling high throughout the year. High risk, high reward?

These options seem ordered in increasing risk, increasing reward, and increasing fun. I reckon my boss will probably do something along the lines of the third option (perhaps with a small amount of trading through the year), so the second option would be a rational choice: betting on his portfolio performing worse than the market average. Is there any way I can justify going for the fourth and possibly most fun option?

As a mathematician, my natural inclination is to start with first principles, choosing information-dense Wikipedia articles over the clickbait YouTube videos peddling trading strategies for beginners. My starting point, therefore, is the initial premise of this challenge: why is it impossible to beat the market? This led me to the Efficient Market Hypothesis²: the idea that all available information is already encapsulated in any given share price, as a result of the collective knowledge of investors trading that share.

Perhaps this hypothesis assumes rational players? Nothing about the GameStop saga seems rational to me! I’ll add some psychology textbooks to my reading list. It shocked me to read that FCA research has shown that 45% of self-directed investors didn’t view “losing some money” as a potential risk of investing with 78% agreeing “I trust my instincts to tell me when it’s time to buy and to sell”. This is worrying because probability theory is hard and non-intuitive to humans.

Fellow millennials trading for the thrill aside, how do professionals seemingly turn a tidy profit from trading? Is it all really just gambling, hoping to get lucky? And is the whole thing zero-sum³, with the winners offset by the losers?

From my very limited understanding of economics, it seems that economic growth and increased productivity is reflected by stock markets increasing in value. This implies to me that it doesn’t have to be a zero-sum game: investing in economic growth can be good for everyone (ignoring times of recession when an economy is shrinking instead).

When it comes to active trading instead of investment, though, I’m finding it hard to work out if any strategy is better than just a game of chance. There are plenty of articles out there touting trading strategies but with little mathematical underpinning, and there are plenty of research papers describing abstract statistical models, though there doesn’t seem to be much connecting the two. I’m finding it unhelpful that there are big language differences too; I’m encountering a lot of new market terminology that’s taking me a while to connect with mathematical concepts.

Even if it is just a game of chance, if I can translate the market jargon and make better risk versus reward decisions than my boss, with a bit of luck I can win.

Concepts in this article

1. The FTSE 100 is a share index of the top 100 UK companies listed on the London Stock Exchange and sometimes used as an indicator for how well the UK stock market is doing.
2. The Efficient Market Hypothesis is a disputed hypothesis that implies it is impossible to beat the market because share prices reflect all information available to traders (both public and private information in its strong formulation).
3. A Zero-sum game is one in which players’ gains are equally offset by other players’ losses. For two-player finite zero-sum games, simple solutions can be found.