If I am creating a long-term portfolio, I need to look at long-term trends. So, it depends whether you are trading, speculating or investing. - Lim
The framework has identified four distinct economic regimes
Freddy Lim, chief investment officer at robo-advisor StashAway Malaysia Sdn Bhd, has always been a numbers person. To him, the numbers show how economies and markets are changing or whether new trends are emerging. After analysing the figures, he strives to come up with a framework that explains why things work the way they do.
That is how Lim, who has a background in economics and econometrics, has navigated his 18-year career in finance. His interest in numbers also took him on a decade-long search for a holistic framework that explains the relationship between economic regimes and returns. This search eventually led him to what is now known as passive investing three years ago.
Lim, who grew up in Malaysia, spent many years working in Japan and Singapore, first as a trader with Lehman Brothers and later, at Merrill Lynch. He subsequently held various roles at Morgan Stanley Japan Securities Ltd, Citigroup and Nomura International plc.
“I started researching economic regimes in November 2008, which was right after the Lehman [the firm whose bankruptcy ignited the global financial crisis] shock of September 2008. It was a pivotal moment in my career. I witnessed first-hand how really intelligent people could also fumble. No amount of experience prior to 2008 mattered as the financial crisis unfolded on an unprecedented scale,” says Lim, who was working at Morgan Stanley at the time.
The financial crisis made him wonder if there was a framework that could guide investors through uncertain times. Such a framework would also serve as a useful guide for his decision-making as he took on various roles. For instance, when he joined Nomura in 2013 as its global head of derivatives strategy, the complexity of the products forced him to deep dive into his research.
“I was in charge of analysing derivatives in every asset class across the globe. It was quite intimidating. You could go crazy doing this job without having some type of framework in place,” says Lim.
Unlike wealth management firms with various investing styles, his situation was different, he adds. “At a big bank, you are selling and buying things all day long. Your job is to get people to buy and sell at the same time. So, it is all about volume. In such an environment, there is no requirement for an investment framework.”
There was a similar need at Citigroup, which Lim joined as multi-asset investment manager in 2009. Prior to that, he had spent many years in fixed income as regional head and executive director of interest rate strategy at Morgan Stanley Japan Securities Ltd.
“As the fixed income guy, you tend to be a bit more negative about growth. You tend to like safety. When I stepped out of that role, you could not blame me for trying to use data because it was the only way for someone conservative like me to go into other asset classes. I needed a framework and I needed data to support it. Otherwise, I could never be a multi-asset investor,” says Lim.
He wanted to find a framework that could explain how asset classes react to changes in the global economy and invest accordingly. This would eliminate distractions or emotions from and add consistency to the investment process. His focus on the economy came from his observation that economic factors were more useful in predicting how asset classes would react than market factors.
This became an important side project for Lim. Over the course of a decade, he spent a couple of hours every day after work and on weekends perfecting the framework. He coded and built a system. He also read about various quantitative investing techniques and investment styles.
Lim began by plotting the characteristics of different economic regimes and the factors that drove those characteristics. He ended up with 16 potential economic regimes based on four phases of economic growth and four phases of inflation, ranging from low to medium and high. Later, he consolidated these into four types of economic regimes.
“Eventually, I found that you do not need to look at all kinds of economic data under the sun to know where the economy is going to make an investment decision. There is too much information in the world now and it all provides very narrow views on one thing. It does not tell you holistically whether it will be good or bad for the economy,” says Lim.
He wanted to create a system that would allow him to consolidate all the data into meaningful insights that represent factors such as growth, inflation and interest rate expectations to get a clearer picture of the economy.
Subsequently, Lim analysed the sensitivity of each asset class to these economic factors, measuring the expected risks and returns depending on the economic regime. These findings affirmed his belief that investing should be based on the fundamentals of the economy.
For example, during times of positive growth and low inflation, small-capitalisation growth equities outperform defensive stocks. The opposite occurs when there is negative growth and low inflation, which will see bonds and gold do well.
The returns and volatility of each asset class vary under different regimes. For instance, large-cap North American equities, which can be represented by the SPDR S&P 500 exchange-traded fund (ETF) that tracks the S&P 500, had an average return of 9.8% between 1982 and 2017, according to StashAway.
But in that period, the US economy spent 50.7% of the time in a positive growth and low inflation regime, during which the the index gave a return of 16.4% year on year (y-o-y). It spent 28% of the time in a positive growth and high inflation regime, during which the index saw a return of 8.8% y-o-y. And up to 9.7% of the time, the US economy experienced a negative growth and low inflation regime, during which the index provided a return of 2.7% y-o-y. This illustrates the importance of looking at the returns and volatility of asset classes in the context of the economic environment, says Lim.
“I believe in a focus on risk-adjusted performance, which means we have to adopt a ‘risk first then return’ approach. I also believe that economic factors are the ultimate drivers of asset class returns, given time. In the near term, markets may deviate from the fundamentals. But the longer they deviate, the more violent the eventual corrections may be,” he adds.
But will investors who focus on economic fundamentals risk getting left behind in a fast-moving and volatile market? This depends on the investors’ objectives, says Lim.
“Reacting faster does not mean you are better at investing. If you are trading, you need to be fast. But if you are investing, you need to find a way to stay alive through the economic changes,” he points out.
“If I am creating a long-term portfolio, I need to look at long-term trends. So, it depends whether you are trading, speculating or investing. At StashAway, we are mid to long-term investors. So, this method suits us.”
fundamentals are key
In the event that the market deviates from the fundamentals, opportunities to profit from the valuation gap may abound for investors. In such a scenario, is investing based on the fundamentals still relevant?
“While it is tempting to suggest timing the contrarian trade based on valuations, it is actually a ridiculously difficult exercise. For example, it is never easy to be a short-seller of equities. The successful contrarian must possess both a great ‘hunch’ and sophisticated data-driven analysis,” says Lim.
Even when he was working in the area of derivatives, he favoured a systematic and quantitative approach to investments, he adds. “There are many uses of derivatives other than speculative purposes. The good thing about using derivatives to structure a trade is that these allow investors to express their views with controlled risk.”
One of Lim’s key principles for his derivatives team at Nomura was to never short tail risks using derivative products. This would prevent them from getting burnt when there were extreme movements in the market. This also meant that they would not buy complex financial structured products.
“I realise that a lot of people promote complex financial products as a tool that can give you higher yields. But there is no free lunch in finance. Every time someone offers you above-market yield, you have to be taking additional risk somewhere. Often, you are ‘short’ volatility. When you do that, you may have higher income or dividends for a couple of years. But once you get hit by a big event, you will lose a lot of money,” says Lim.
“I once interviewed a complex credit trader who dealt in products such as CDOs [collateralised debt obligations]. He said he had a nine-year track record. He made 10%-plus returns for eight years. But in the last year, his fund went down by 90%. When I looked at his trades, I realised that he sold tail risks every year and got above-market yields. But when a credit default happened, he lost all the gains. There was no risk management.”
Instead of focusing on risky products, investors should focus on the fundamentals. Lim does not believe that markets can stay high for long if the economic fundamentals keep weakening.
“Traders may disagree, but I think it is about the time frame. At some point, the market will gravitate back to the fundamentals. I like to see what the economic data is saying and where the market is, and I compare them. If it deviates for way too long [from the fundamentals], then I tend not to invest in the asset class,” says Lim.
In 2015, his team at Nomura was recognised as Global Derivatives — Research & Strategy House of the Year by Global Capital, a feat that Lim is proud of achieving, having built the team from scratch just two years previously.
Investing based on economic regime
Lim’s principles apply not only to trading but also multi-asset investing. For instance, he suggests that looking at the long-term average returns of a fund may not be the most useful indicator when comparing fund performance. Instead, one must observe the economic conditions in which the fund manager operated.
“You have to look at the changes in the economy when the fund manager was managing the fund. If he has been operating in a bull market since 2009 and has a 10-year track record of doing well, does it mean he is considered a good manager? Maybe not, because he has only experienced one environment. A fantastic investor would have navigated changes in the environment many times and would still have consistent performance,” says Lim.
Factor investing is a good way to illustrate the importance of observing economic regimes. This investing approach targets specific drivers of returns across asset classes based on either macroeconomic or style factors. The four known styles in this form of investing — trend, momentum, carry and value — perform well in different economic environments.
“For example, if you are trend-following, the bull market in the last nine years may have worked for you. But value traders may have suffered because they could not find quality buys that were cheap. We need to be open minded [about combining strategies at any given time],” he says.
A challenge for fund managers when it comes to maintaining the performance of their funds is that they have to keep the risk factors constant throughout the different economic regimes. This means adjusting asset allocations in view of the economic conditions, according to Lim.
But don’t regular fund managers do this? “Yes, but we need to be scientific about it [by creating a system based on data]. We do not want to make emotional judgements or be subjective [about the decisions]. We want to be clear and objective,” he says.
In a way, this is his critique of the Modern Portfolio Theory (MPT), which has guided multi-asset funds since the 1970s. According to the theory, one will get higher long-term average returns for the same amount of risk taken by having a diversified portfolio.
“In the 1970s, they did not have as much data as we do today. With information at our fingertips, it is easier for us to tell that the economy does not stay constant. So, you are missing the point if you have one assumption for expected returns [without acknowledging that there are various economic cycles]. An economic cycle can easily last three to seven years. If your strategy is the wrong one [for that cycle], you can be frustrated for a long time,” says Lim.
“[We can improve on this] by expanding the MPT to reflect the economic cycle. We can come up with rules for expected returns, risks and correlations by slicing the economic cycle into grids. The same applies to inflation. We are really curious to look deeper into how the returns and risks of different assets behave in each of these grids.”
Active versus passive investing
In 2016, Lim used his research to produce a framework called ERAA, or Economic Regime-based Asset Allocation. StashAway, the robo-advisor he co-founded, is powered by the framework. The firm was the first robo-advisor in Singapore in 2017 and in Malaysia in 2018.
ERAA looks at the relative rate of change between growth and inflation to determine an economic regime. There are four economic regimes — good times, inflationary growth, recession and stagflation — and they have different asset allocations.
The robo-advisor’s strategies are adjusted according to the data. It also monitors valuation gaps and abnormal market behaviour. Using the strategies recommended by ERAA, StashAway invests in ETFs across various asset classes and geographies.
The firm’s philosophy is to have humans monitor events but not intervene unless there are exceptional market-changing ones, according to Lim. When there is a change in economic regime that requires a re-optimisation of portfolios, investors are informed to get their consent if they did not opt for auto re-optimisation when setting up their portfolios.
Lim’s journey thus far signifies not just a shift from active to passive investing but also from derivative, equity and bond investments to ETFs. Instead of investing directly in assets using a strategy, he has created a system that runs by itself.
As StashAway only invests in ETFs, does that mean he will limit himself to these instruments? Lim says he will not. “If I want to track the natural resources sector, what is the best instrument to use? If there is an ETF that is safe, has liquidity and is well-supervised and supported by a big fund manager, so be it. If a unit trust is better in terms of fees or tracking errors, then we will use that.”
What about the role of algorithms and fund managers? “If you can find a very good fund manager, who has gone through various crises and all kinds of environmental changes but still produces good and consistent performance, you should hold on to this person and treat him or her with respect. But it is hard to find such fund managers. I think the majority of us are better served with a consistent, well-planned approach to investing. Algorithms can make things more consistent,” says Lim.
But he does not call himself a passive investor. A blend of both active and passive investing is needed, which is why he prefers to call himself a strategic investor.
“Our algorithm is strategic. Pension funds and life insurance companies have strategic asset allocation meetings every year, where they look at the medium term and try to fine-tune their allocations. This is similar to what we do. We look at economic cycles, which are three to seven years, and we fine-tune the portfolios. We are making strategic decisions that are not active but also not all passive either,” says Lim.
On that note, he advises investors not to speculate on economic regimes. Many have begun to question whether a recession is imminent, given the extended bull market. But he says, “The market is not like a human body, which has a biological clock. If you look at Australia, its current cycle has been going on for more than 20 years, whereas the boom and bust cycle of some countries is very short. You can never predict a cycle based on just time. Let the data guide you. You can use sentiment [to guide you], but you will still need to look at economy-related data.”
So far, Lim’s strategy has borne fruit. According to its website, in the two years since StashAway launched its robo-advisory services in July 2017, its most conservative portfolio has seen a cumulative return of 6.8% while its balanced and most aggressive portfolios have generated cumulative returns of 12.9% and 21.3% respectively, outperforming their benchmarks’ 5.2%, 8.5% and 15.3% respectively.