Subscribe to our newsletter
Sign up to receive our regular updates and stay informed

Three beliefs underpin our investment philosophy

Markets work well
most of the time

Over the long term, a company’s share price will reflect its fundamentals.

Mispricing occurs
with emotions

In the short term, the market may overreact or underreact to fundamentals.

Margin of safety
is critical

Loss avoidance is the cornerstone of our investment philosophy.

1. Markets work well most of the time

Over the long term, a company’s share price will reflect its fundamentals. We believe the wisdom of crowds is broadly correct most of the time. Companies can be cheap or expensive for good reason: generally, stocks with negative fundamentals are penalised, while stocks with positive fundamentals are rewarded. In other words, low-quality stocks tend to be cheap and high quality stocks tend to be expensive.



Cross-sectional evidence

Evidence of such rational markets is highlighted when comparisons are made between company valuation multiples and their capital-generation ability (see Chart 1)1.



Chart 1 | S&P/ASX 100 Financials stocks’ price-to-book equity ratio versus their return on equity


Source: Factset at June 2017


Time-series evidence

Evidence of rational markets is also supported by the fact the market continuously updates the stock price as new information is revealed. For example, an earnings downgrade will generally lead to a decrease in the stock price and vice versa2. Hence, as the fundamentals change over time, the valuation multiple will adjust automatically (see Chart 2).



Chart 2 | QBE’s price-to-book equity ratio versus its return on equity


Source: Factset at June 2017


Adapting mechanism

Further, the market does not wait for earnings upgrades or downgrades. In its collective wisdom, it uses all available information to revise expectations, which automatically impacts the security price. For example, Woodside Petroleum’s profits are directly linked to the oil price and sell-side analysts revise their profit estimates with about a three-month lag compared to the prevailing oil price (see Chart 3).



Chart 3 | Woodside Petroleum’s change in profit estimates versus the change in oil price


Source: Factset at June 2017



And if profit estimates temporarily divert from the oil price for whatever reason, like in 2006, the oil price can act like gravity and eventually pull the estimates back in line. Importantly, the share market does not wait for profit estimates to be revised. As a forward-looking mechanism, the share price automatically adjusts in real time with the oil price (see Chart 4).



Chart 4 | Woodside Petroleum’s change in share price versus the change in oil price

Source: Factset at June 2017

2. Mispricing occurs with emotions

In the short term, the market may overreact or underreact to fundamentals. We believe human judgments are rational but are bounded by cognitive limitations3. There are limits to rationality because the capacity of the human mind is small compared to the complexity of the environment. Thus, when humans simplify information by using mental short cuts, it occasionally leads to mistakes because emotions, ego and misguided incentives can override rational decisions.

While the collective wisdom of crowds works well most of the time, because of cognitive limitations, sometimes the magnitude of the return is incorrect (the market may overreact or underreact to fundamentals) creating mispriced opportunities. Sometimes the mispriced opportunities are high risk when the market underreacts to negative fundamentals (value traps) or overreacts to positive fundamentals (expensive stocks). At other times, the mispriced opportunities are low risk when the market overreacts to negative fundamentals (bathwater babies) or underreacts to positive fundamentals (neglected orphans). These lower-risk mispriced opportunities are two market phenomena that have been extensively researched:

  • cheap stocks outperform in the long term (value factor), and
  • winning stocks outperform in the short term (momentum factor)4.

Fear of loss

We believe market overreaction or underreaction is the result of biased decisions when our rational thoughts are impaired by heightened emotions5. Underreaction to positive fundamentals occurs when there is excessive fear of loss. When risk aversion becomes more pronounced, decisions become more conservative6. For example, even if the fundamentals begin to stabilise or improve for out-of-favour stocks, investors may disregard positive news because they still anchor somewhat to their prior poor beliefs. Consequently, they adjust their valuation of shares only partially in response to positive signals.

Fear of missing out

On the other hand, when there is excessive greed (fear of missing out), risk seeking becomes more pronounced and individuals will actively search for opportunities and tend to overreact to both positive and negative fundamentals7. For example, stocks showing a long history of earnings growth tend to make investors complacent and over-optimistic about past winners. Favouring past winners and avoiding past losers may push prices beyond their intrinsic values, with the former becoming overvalued and the latter becoming undervalued.

Stock market volatility

Stock market overreaction is evident from highly publicised stock market bubbles and crashes such as the:

  • UK railway mania in the 1840s
  • the Roaring 1920s
  • Australian Poseidon/mining hysteria in the late 1960s
  • Nifty-Fifty in the early 1970s
  • Black Monday crash of 1987, and
  • Dot-com madness in the late 1990s/early 2000.

Of course, market-wide bubbles and crashes are rare (occurring every few decades) but in any given year, individual stocks also display excessive volatility, a symptom of market overreaction. This is observable from the extreme price range between a company’s share price high (when a stock is in favour) and its share price low (when a stock is out of favour). Chart 5 highlights the average price range over the last 10 calendar years (2007 to 2016) expressed as a percentage between the 12-month high and low prices for large, medium and small stocks in the S&P/ASX 300 Index:


Chart 5 | 10-year median of the average 12-month price range for large, medium and small stocks in the S&P/ASX 300 Index (2007 – 2016)

Source: Factset Vertium

The wide range in share price between the highs and lows highlights expectations about companies can vary significantly over any given year. As you would expect, the share prices of small stocks are more volatile than large stocks by nearly three times. And, while large companies are less volatile because they are well established with diversified businesses, their share prices change by about a third over any given year. The average business does not fluctuate in fundamental value anywhere near that much on a yearly basis8. Hence, in the short term, the market can be irrational and overreact to news that leads to great deviations between price and underlying value.

Superior active management is required to identify mispriced stocks

To be clear, we believe stocks that overreact and underreact to fundamentals only represent a small sub-set of a market that is mostly rational. It requires superior active management to:

Avoid high risk mispriced stocks:

  • value traps (market underreaction to negative fundamentals), and
  • expensive stocks (market overreaction to positive fundamentals)

Search for low risk mispriced stocks:

  • bathwater babies (market overreaction to negative fundamentals), and
  • neglected orphans (market underreaction to positive fundamentals).

3. Margin of safety is critical

Loss avoidance is the cornerstone of our investment philosophy. We prefer to miss out on opportunities than increase the risk of capital loss by chasing higher returns. We approach investing with a great sense of humility because we believe the collective wisdom of crowds is often correct. Investing is made even more difficult because the market environment is constantly changing. As investors, we have no control over how and why business fundamentals change for two reasons:

1. Management control

Management teams have a lot of flexibility in terms of how they manage their company. Bad management, or naive management with bad practices, can erode the value of a firm. As minority shareholders, we have little or no control over the business strategy, execution and day-to-day operations. We cannot take over the board, change management behaviour or influence how the company is run.

2. Complex world

The world is complex and highly dynamic. Consumer demand and technological advances are perpetually changing. Further, capitalism ensures there are competitive dynamics, which can erode profits from industry players. No economic cycle is the same, so history provides little insight in terms of where the future is headed. Hence, forecasting the future is difficult because economies, industries and businesses never stand still.

Consequently, without a strong downside risk attitude, luck plays a large a role in the outcomes of a mostly rational, highly complex market.

To mitigate uncontrollable or unpredictable risks, we put enormous effort into what we can control: the price we pay for a security. The greater the margin between the price paid below the security’s valuation, the lower the downside risk. Margin of safety is achieved when the price paid is at a sufficient discount to the valuation to offset unpredictable events, volatility from a rapidly changing world or the possibility of human error. We believe margin of safety is the best investment tool to mitigate downside risk.

Typically, stocks with a margin of safety are low risk mispriced stocks:

1. Bathwater babies

The classic ‘babies thrown out with the bathwater’ type stocks occur when the market overreacts to negative fundamentals. When headlines are negative in an uncertain environment, the market can get confused between uncertainty over short-term business duress (low risk) and long-term issues (high risk). With such confusion, there is a natural tendency to sell based on weaker fundamentals irrespective of whether the issues were short or long term in nature. Mispriced opportunities arise when the market is not willing to look through the short-term issues faced by companies. In such situations, even entire industries can sell-off. For example, during the global financial crisis in 2008/09, the Real Estate Investment Trusts (REITs) sector collapsed due to its excessive gearing levels. Indeed, the worst REITs went bankrupt, but the indiscriminate sell-off of all REITs allowed savvy investors to buy REITs with sustainable balance sheets at steep discounts to their net tangible assets.

2. Neglected orphans

Neglected orphans are stocks where the market underreacts to the positive fundamentals. These companies tend to be misunderstood, boring or underappreciated, high-growth companies.

a. Misunderstood companies

Industries starved of capital are often misunderstood. For example, between 2013 and 2016, high-cost coal-fired generators were shut down leading to industry consolidation on the east coast of Australia. From early 2016, the wholesale electricity price began to rise in response to contracting industry supply. However, for most of that year, the market ignored AGL Energy’s significant operating leverage to the rising electricity price because they were still anchored to the negative industry publicity in prior years.

Spin-offs are often misunderstood. Divestment of corporate divisions may create some confusion as the market may not be familiar with the business. However, the combination of increased management focus with forced selling without regard to valuation from original shareholders, sets up the foundation for low-risk, sustainable returns. For example, in late 2013, Amcor demerged its slow-growing Australian business, Orora, from its faster-growing global packaging business. At listing, Orora had a return on funds employed (ROFE) of 8% and was trading on a 13x PE multiple. Three years later, after the company had doubled its earnings, Orora had a ROFE of 13% and was trading around an 18x PE multiple. Clearly the market underestimated the quality of the business when it was originally marketed as the slow-growing division of Amcor.

b. Boring companies

Boring companies sometimes get neglected. For example, in 2013, Duet Group, a dull, regulated utility, had an equity free cash flow multiple of 12x with a gearing ratio (ND/ND+E) close to 80%. Three years later, the company was still trading on an equity free cash flow multiple of 12x but the gearing ratio was significantly lower at 63%. In late 2016, Hong Kong-based, Cheong Kong Infrastructure, recognised the value in Duet and made a takeover offer.

c. Underappreciated high-growth companies

Underappreciated high-growth companies sometimes get neglected. For example, in 2012, Fisher & Paykel Healthcare delivered double-digit constant currency profit growth in the previous two years. However, its reported profit growth, which included large foreign exchange adjustments, recorded negative growth over the same period. At that time, the company was trading on a PE multiple of 15x on reported earnings. However, the true underlying strength of the business was masked by foreign exchange impacts. In subsequent years, the company continued to deliver double-digit constant currency profit growth and the foreign exchange had a lesser impact on the reported earnings. By 2016, the company’s profit had more than doubled since 2012 and its growth prospects were more widely recognised by the market, as indicated by its PE multiple of around 30x in that year.

The evidence must be clear to show a clear margin of safety before we invest. Stocks with little margin of safety, such as superficially cheap value traps or expensive high quality stocks, are actively rejected.

Our margin-of-safety approach inevitably leads to a lower-risk portfolio of high-quality stocks with sound valuations. Owning companies that are both high quality and attractively valued is the most compelling way to generate long-term, sustainable risk-adjusted performance.

Evidence of the combined strategy of quality and value outperforming over the long term has been highlighted by researchers9. The research is clear: buying cheap companies delivers good performance, but buying cheap and high-quality companies delivers better long-term sustainable performance.


1Nobel laureate Eugene Fama, the father of the Efficient Market Hypothesis, argues that stock prices reflect all available information (Fama, 1965). He has conducted extensive studies testing the efficiency of markets and in Fama and French (1992) they assert the price-to-book ratio is a proxy for the market’s expected risk. A low price-to-book ratio signals higher expected risk because of the company’s poor prospects. The observed higher stock returns in the future represent a fair compensation for the higher risk.

2In another first, Eugene Fama and his colleagues published the first event study that showed that stock prices quickly adjust to news flow (Fama, Fisher, Jensen and Roll, 1969). This study spawned the enormous research industry that investigated stock price impacts from significant events. Most event studies show stock prices adjust rapidly to new information.

3Nobel Laureate and the father of artificial intelligence, Herbert Simon, first proposed that humans have ‘bounded rationality’ (Simon, 1955). Decades later, another Nobel Laureate, Daniel Kahneman, popularised the dual process thinking of humans: ‘system 1’ (intuitive and emotional) and ‘system 2’ (analytical and logical). System 1 runs automatically most of the time and is the most influential because it guides system 2 thinking. Unfortunately, under certain circumstances the biases in system 1 produces systematic errors that leads system 2 astray (Kahneman, 2011).

4Practitioners have been using value and momentum strategies far longer than when they became popular among researchers. Graham and Dodd (1934) advocated value investing in the 1930s before researchers like Basu (1977) uncovered the value factor 40 years later. In the 1940s, Edwards and Magee (1948) wrote a seminal book on technical analysis that focused on trend analysis, 50 years before researchers like Jagadeesh and Titman (1993) revealed that past winners and losers exhibit trends in the short term.

5This type of cognitive bias is called the ‘affect’ bias. When our emotions are heightened, it amplifies other cognitive biases in our decision-making process. For example, when we feel negative about an idea, we are more risk averse and vice versa (MacGregor, Slovic, Dreman and Berry, 2000).

6According to Prospect Theory, humans are inherently conservative because we dislike losing more than we like winning (Kahneman and Tversky, 1979). And when uncertainty increases, decisions are influenced by the ‘conservatism’ bias where recent information is underweighted and the probabilities of unfavourable events are overestimated (Edwards, 1968).

7When uncertainty dissipates, the mindset shifts from fear of loss to fear of missing out. This change in sentiment allows the ‘representativeness’ bias to become more pronounced. Decisions are then influenced by overweighting recent information and underestimating the probabilities of unfavourable events (Tversky and Kahneman, 1974). The representative bias leads to an illusion of control because the role of skill is overestimated relative to luck in determining outcomes.

8Nobel laureate Robert Shiller, a leading pioneer in behavioural economics, examined the excess volatility phenomenon of stock prices and showed that future expectations change far too often compared to the actual changes of dividends (Shiller, 1981).

9Joseph Piotroski separated fundamentally strong companies from a ‘value’ basket of stocks and found that cheap, high-quality companies delivered 7.5% p.a. higher returns than just the ‘value’ basket alone (Piotroski, 2000). Joel Greenblatt’s strategy of buying good quality stocks at good valuations led to 18% annualised outperformance between 1988 and 2004 for the US market (Greenblatt, 2006).


Basu, S., 1977, Investment Performance of Common Stocks in Relation to Their Price-Earnings Ratios: A Test of the Efficient Market Hypothesis, Journal of Finance, Volume 32, Number 3, pp 663-682

Edwards, R. and Magee, J., 1948, Technical Analysis of Stock Trends. CRC Press

Edwards, W., 1968. Conservatism in human information processing. In: Kleinmutz, B. (Ed.), Formal Representation of Human Judgment. John Wiley and Sons, New York, pp. 17-52

Fama, E., 1965, The Behavior of Stock-market Prices. The Journal of Business, Volume 38, Issue 1, pp. 34-105

Fama, E., Fisher, L., Jensen, M., and Roll, R., 1969, The Adjustment of Stock Prices to New Information, International Economic Review, Volume 10, Issue 1, pp. 1-21

Fama, E. and French, K., 1992, The Cross-Section of Expected Stock Returns, Journal of Finance, Volume 47, Issue 2, pp. 427-465

Graham, B. and Dodd, D., 1934, Security Analysis, McGraw Hill Book Company, New York

Greenblatt, J., 2006, The Little Book That Beats the Market, John Wiley and Sons, New York

Jagadeesh, N. and Titman, S., 1993, Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, Journal of Finance, Volume 48, Number 1, pp 65-91

Kahneman, D., 2011, Thinking, Fast and Slow, Farrar, Straus and Giroux, 2011

Kahneman, D., and Tversky, A., 1979, Prospect Theory: An Analysis of Decision under Risk, Econometrica, Volume 47, Number 2, pp. 263-291

MacGregor, D., Slovic, P., Dreman, D., and Berry, M., 2000, Imagery, Affect and Financial Judgement, The Journal of Psychology and Financial Markets, Volume 1, Number 2, pp. 104-110

Piotroski, J., 2000, Value Investing: The Use of Historical Financial Statement Information to Separate Winners and Losers, Journal of Accounting Research, Volume 38 Supplement 2000

Shiller, R., 1981, Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?, The American Economic Review, Volume 71, Number 3, pp. 421-436

Simon, H., 1955, A behavioral model of rational choice, Quarterly Journal of Economics, Volume 69, Number 1, pp. 99–118

Tversky, A., and Kahneman, D., 1974, Judgment Under Uncertainty: Heuristics and Biases, Science, Issue 185, pp. 1124-1131