Investor Behaviour Quotes

Every once in a while, an up-or-down-leg goes on for a long time and/or to a great extreme and people start to say "this time it's different." They cite the changes in geopolitics, institutions, technology or behaviour that have rendered the "old rules" obsolete. They make investment decisions that extrapolate the recent trend. And then it turns out that the old rules still apply and the cycle resumes. In the end, trees don't grow to the sky, and few things go to zero.

Risk arises as investor behaviour alters the market. Investors bid up assets, accelerating into the present appreciation that otherwise would have occurred in the future, and thus lowering prospective returns. The ultimate irony lies in the fact that the reward for taking incremental risk shrinks as more people move to take it.

If anyone could anticipate a market drop, no one would ever invest in the market above the level to which it will decline. That is to say, market corrections are unforeseen events.

More often than not, extreme events revert to the mean—the average—for no other reason than that result is more likely.

Since money is fungible, efforts to save small amounts on small purchases are absurd if you ignore them during pricier transactions. $1.75 is still worth $1.75.

Once bitten, twice shy isn't a very good investment strategy.

Literally, time is money. Starting to save now instead of later lessens the amount you will need to contribute.

It's worth noting that the assumption that something can't happen has the potential to make it happen, since people who believe it can't happen will engage in risky behaviour, and thus alter the environment.

What’s the point of making predictions if they cannot change anything? Some complex systems, such as the weather, are oblivious to our predictions. The process of human development, in contrast, reacts to them. Indeed, the better our forecasts, the more reactions they engender. Hence paradoxically, as we accumulate more data and increase our computing power, events become wilder and more unexpected. The more we know, the less we can predict. Imagine, for example, that one day experts decipher the basic laws of the economy. Once this happens, banks, governments, investors and customers will begin to use this new knowledge to act in novel ways, and gain an edge over their competitors. For what is the use of new knowledge if it doesn’t lead to novel behaviours?

It is relatively easy to identify those industries where these conditions exist currently (just look at existing returns on capital), and it is for this reason that the really juicy investment returns are to be found in industries which are evolving to this state. The joy from a capital cycle perspective is that most investors are, for a variety of behavioural reasons, taken by surprise. Across many competitive battlefronts, we are always looking out for the next outbreak of peace.

With gambling or investing, if your gains are quick and easy, you will tend to keep the money in a separate mental account. So, if you subsequently lose it, you won't feel as upset as you'd think if you lost the money you brought to the casino. Yet, they are both pots of currency.

If you've convinced yourself that a market correction is likely (your belief) to justify holding cash rather than investing (your action), you may be under the influence of cognitive dissonance.

Familiarity bias drags you to the safety of your comfort zone and, in doing so, unwittingly increases your risks by limiting diversification and investment opportunities.

If you excuse investment concentration by telling yourself that your familiarity with domestic companies or specific sectors helps you understand those investments better, your familiarity bias is the excuse for your familiarity bias.

Timing the market is a biased investor's game.

The motives to sell during a market capitulation are rarely rooted in a long-term plan. If they were, the market would never be oversold.

Timing an unforeseeable event is more likely a stroke of luck than skill.

It doesn't matter what you paid for an investment. If it no longer suits your objectives or has poor prospects, you should sell it.

The motivation to break even is so tempting that you'll even consider doing so at greater levels of risk than you'd typically accept. If you've heard the expression "double or nothing," you've seen this bias in action.

It is odd behaviour to ignore smaller denominations when transacting high values since large transactions provide the most obvious opportunity to keep more of your money.

Stocks aren't like a pair of shoes that go on sale but keep the same useful value. The value of stocks are based on their economic prospects, which change constantly.

Ironically, investing in many seemingly safe investment options puts conservative investors at the greatest risk of declining purchasing power.

Stocks aren’t like a pair of shoes with a consistent value that you can buy on sale—the value of a business changes based on economics and its prospective earnings.

The sheer number of new businesses that fail speaks to the optimism of entrepreneurs to wander down such a gauntlet, and their willingness to believe that norms don't apply to them. But on average, of course, they do.

Tread carefully when making assumptions based on representativeness. If it walks like a duck and talks like a duck, it might not be a duck.

Money illusion is also why your Uncle John still gives you $50 per year for your birthday. That's the same amount that he's given you since you were born, and it used to be a tidy sum of money back then.

There is another metric – or, more specifically, analytical tool – that investors will be impressed to see at this point. It’s called cohort analysis. Since your app is still pretty young, you’re not going to be able to present any long-term metrics. One way around that is to measure – and compare – groups (or cohorts) of users at the same point during their lifecycle with your app. A typical cohort analysis compares the behaviour of all the users who registered in a given month (let’s say that all the users who downloaded your app in January use it on average five minutes per day) with all the users who downloaded it in another month (let’s say that customers who downloaded it in February use it on average six minutes per day). By comparing the January cohort with the February cohort, investors can see that users are using the app more – a great sign. Cohort analysis allows you to present a trend – typically from month to month – showing clear improvements across any metric: from session length, to customer acquisition cost, to lifetime value.

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