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Factor investing the reference portfolio gic

factor investing the reference portfolio gic

Reference Portfolio is not a performance benchmark for the GIC among the factors that influence investment decisions. GIC actively. GIC's portfolio returns have Reference Portfolio (in USD, for periods ending 31 March ) factors, into our investment processes, for example. In factor allocation models, factors replace asset classes in To manage this delegation, an operational reference portfolio (ORP). NON INVESTING TRANSIMPEDANCE AMPLIFIER PHOTO It is the ideal for applications in the security the settings below, a few settings within FileZilla that. This means that menu, select Install left blank. Simply complete the Add the host gain more contributors.

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I n short, factor investing offers a compelling alternative to traditional active and passive strategies. But, there are different approaches to factor investing, some more efficient than others. Factor investing is based on thorough academic research, with over four decades of empirical research showing it to be a robust investment concept.

This chapter explains:. Prior to the s, investors had very little understanding of the relationship between the risk and return of their investments. As soon as the early s, empirical tests showed that the link between risk and return is weaker than the CAPM theory suggests. One of the first studies, performed by Robert Haugen and James Heins, 9 showed that less volatile stocks had consistently outperformed more volatile ones over the period. Fama, Kenneth French, In , another anomaly was observed, as Sanjoy Basu documented the value effect.

In other words, stocks featuring a lower valuation tended to achieve higher returns than the CAPM would suggest. By the middle of the s, it was becoming clear that a number of factors other than market risk needed to be considered, and alternative models were developed. One of the most famous was the three-factor model developed in the early s by future Nobel prize laureate Eugene Fama and fellow researcher Kenneth French. From that time, factor investing rapidly gained popularity among global investors, who were faced with similar issues and looked for ways to obtain a better-diversified portfolio at reasonable costs.

In , for example, Mark Carhart proposed adding a momentum factor to the Fama-French model. The combination of the two is often referred to as the quality factor. Over the years, the number of academic studies showing that factor investing can also be applied to fixed income also rose dramatically, as large historical data sets on individual bonds became more widely available.

Nowadays, the research effort is going well beyond stocks and bonds: more and more analysis into the role of factors is being carried out in other asset classes. After this chapter, you should understand the scientific grounding of factor investing, and how the most influential factor models emerged.

You should also know that the research effort is ongoing. It was introduced in the early s by several academics independently: Jack Treynor , William F. Sharpe , John Lintner and Jan Mossin Haugen and J. Fama and K. Blitz and W. Over the years, dozens of purported factors have been identified by researchers. In recent years, the combination of increased computing power, greater availability of data and rising interest among researchers has led to a dramatic rise in the number of purported factors reported in academic journals.

Meanwhile, others only seem to work over short periods of time, or in a limited number of segments of the market. So what exactly is happening here? The problem is that when researchers analyze many different sets of data, looking for recurring patterns in returns, these patterns are likely to emerge purely by chance and still be statistically significant. So, some caution is needed.

Actually, it is possible to reduce the number of anomalies included in the zoo down to a handful of truly relevant factors. So how exactly should we choose which factors to invest in? To qualify as investable, a factor should meet a number of strict requirements:. Implementable in practice and still outperform after the effects of trading costs and other market frictions. So, which factors actually work? Well, the list of factors each asset manager or index provider considers relevant can vary slightly depending on their own research and convictions.

For example, some managers consider income — the tendency of high-income securities, for example high-dividend stocks, to outperform lower-income ones — as a standalone factor for equities. Most providers stick to a handful of broadly accepted premiums. As an example, below is a brief overview of the different equity factors considered by some of the key players in the factor investing arena.

Another consideration is that while the most common factors typically apply to all asset classes, some asset managers or index providers also have a slightly different list of relevant factors for each asset class. In credits, for example, Robeco considers value, momentum, low risk and quality as a factor. The tendency of inexpensive securities, relative to their fundamentals, to outperform over the longer term. The tendency of securities that have performed well in the recent past to continue to perform well, and for securities that have performed poorly to continue to perform poorly.

Refers to the observation that low-risk securities tend to earn higher risk-adjusted returns than high-risk securities. The tendency of securities issued by sound and profitable companies to outperform those issued by less sound and profitable companies, and the market as a whole. The tendency of bonds issued by companies with little debt outstanding and small-capitalization stocks to outperform the market. In short, although dozens of market anomalies have been reported in the academic literature, investors should stick to a small number of factors that have been thoroughly tested in practice.

Harvey, Y. Liu and H. Hou, C. Xue and L. Factor investing can help pursue two main investment goals: reduce risk and enhance returns. But how does that work in practice? We saw in Chapter 2 that one of the most important transformations in the financial industry in recent years has been the massive shift from active to passive investment strategies, but that this raises a number of concerns.

For instance, although going down the passive route may be cheap and prevent unpleasant surprises from poor active calls, it leads ultimately to chronic underperformance once costs are taken into account. Passive strategies also expose investors to significant arbitrage risk for more details, see Chapter 7. Against this backdrop, many investors have turned to factor investing in a bid to achieve superior risk-adjusted returns while keeping costs relatively low.

Figure 6 and 7 show the historical performance of some of the most commonly accepted factors for equities and bonds. Performance figures for generic US value-weighted factor portfolios from July to December Quality is defined as the equal weighted combination of the Profitability and Investment factor portfolios.

This chart is for illustrative purposes and does not represent the performance of any specific Robeco investment strategy. The value of your investments may fluctuate. Results obtained in the past are no guarantee for the future. Source: Robeco, Bloomberg. USD investment grade January December Decile portfolios constructed using Robeco factor definitions.

Credit returns measured over duration-matched government bonds. These graphs show that stocks featuring attractive value, momentum and quality factor characteristics achieve higher returns over the longer term. In the credit space this holds true for corporate bonds with attractive value, momentum and size factor characteristics.

Investors can either focus on each one of these factors independently or target a combination of factors for more stable outperformance over time. In recent years, risk reduction has become a top priority for many investors. Products exploiting the low-volatility or low-risk factors could be an ideal tool to help them do so without foregoing return potential.

Virtually unknown barely a decade ago, low-risk investing has in the ensuing years become a broadly accepted and adopted approach. The low volatility and low-risk factors are grounded in the empirical finding that securities generating stable returns relative to the broader market have achieved higher risk-adjusted returns than riskier ones over the longer term.

Academics have proposed several reasons to explain this anomaly and why it is likely to persist in the future. The most frequently discussed explanations relate to the rational behavior of asset managers, whose performance is generally evaluated against a benchmark. This is why asset managers tend to focus on being able to deliver outperformance and on minimizing relative risk. As a result, they tend to overlook low-risk stocks, which are characterized with market-like returns and high tracking error.

Other explanations include common behavioral biases of investors, such as overconfidence and the incentive structures, as well as investment constraints faced by many investors, in terms of leverage, benchmark, etc. These arguments are applicable for all proven factor premiums. To summarize, different factor exposures can help achieve different investment goals.

Depending on their needs and priorities, investors can either seek higher returns or reduce potential losses. Blitz and P. Factor investing can also help achieve very specific purposes, such as those most frequently cited in the latest annual survey of asset owners by FTSE Russell see Figure 8. This chapter will show you:. But the dramatic increase in correlations between asset class returns during the market turmoil of the s began to cast doubt on the benefits of traditional diversification frameworks.

The quest for more robust diversification techniques has seen many investors turn to factor investing — and with good reason. Many empirical studies have demonstrated the superior diversification benefits of factor investing, compared to classic diversification across sectors, regions and asset classes.

For instance, a paper 19 by Antti Ilmanen and Jared Kizer analyzing data on several asset classes dating back to reported that diversification into and across factors has been much more effective in reducing portfolio volatility and market directionality than traditional asset class-based approaches. Increased cost awareness among investors has also played a crucial role in the success of factor investing over the past few years.

Factor investing is about capturing proven factor premiums in a rules-based way, in order to generate superior risk-adjusted returns after costs compared to the broader market. The rules-based approach to generating superior performance is generally achieved at a lower cost, therefore charging lower fees, than traditional active managers.

This is why factor investing is regarded by many investors as a third way in between passive and active, as we discussed in Chapter 2. It is transparent and has relatively low cost like passive, but an outperformance objective, like active. Another frequently cited goal is to gain exposure to a specific factor. This may sound like stating the obvious, but it reminds us that, well before the advent of factor investing as a popular approach in the late s, many investors were already exploiting individual factor premiums.

Value strategies are a good example. For decades, prominent investors have advocated buying securities trading below their intrinsic value and many active managers have been offering so-called value strategies. The quest for higher and more stable returns has convinced many investors to turn to strategies featuring high-income characteristics. In recent years, as bond yields fell across the developed world, these strategies have been gaining considerable traction, in particular among those asset owners interested in factor investing.

Income-related variables indeed represent a key input in the definition of some of the most commonly-admitted factors. Carry is an obvious case in point. But this also holds true for other proven factors, such as value or quality. That is why, in equity markets, value and low-risk investing typically involve selecting stocks from firms with high and stable dividends. The implementation of factor investing is also a good opportunity to consider environmental, social and governance ESG aspects.

Growing demand for sustainable investment solutions means asset managers are increasingly expected to take ESG criteria into account in their investment processes, without sacrificing returns. Factor-based strategies are particularly suitable for smart sustainability integration. Their rules-based nature makes it relatively easy to integrate additional quantifiable variables in the security selection and portfolio construction process.

From this perspective, a factor-based approach that integrates sustainability aspects in the investment methodology is not very different from a standard factor-based approach, where securities are included in a portfolio solely based on their factor characteristics.

For more information about Sustainable Investing, please visit our dedicated Essentials learning module. In short, on top of enhancing returns and reducing risk, factor investing can also be used to improve diversification, reduce costs, gain strategic exposure to a specific factor and generate income. Ilmanen and J. Not all products, labelled as factor strategies lead to the best investment outcomes. In particular, generic products can prove disappointing over time.

Investors can choose from hundreds of factor-based products, from basic single-factor equity ETFs to sophisticated multi-factor multi-asset solutions. However, different factor strategies usually lead to different investment outcomes. Indeed, there is very wide dispersion in the performance of mutual funds exploiting equity factor strategies. Factor strategies need to be well designed and smartly implemented.

Key challenges range from determining the right factor strategy — or set of strategies — for each investor, to ensuring that the portfolio is properly constructed. Finding the right balance between rebalancing the portfolio to maintain exposure to the relevant factors and keeping turnover and transaction costs low is also important. Generic factor strategies typically fail to address these challenges.

For instance, many generic products provide only limited exposure to a targeted factor, or combination of factors, as well as unwanted negative exposures to other proven factors. The reason is that individual factors can have negative exposures to other proven factors, and generic factor definitions tend to overlook this issue.

An example would be a low-volatility stock that is expensive so it provides negative exposure to the value factor , or a quality stock that is in a downward trend negative exposure to momentum. Another major flaw of products that track public smart beta indices is that they are prone to overcrowding and arbitrage.

Generic factor indices often publicly share their holdings and rebalancing methodology. This transparency comes at a cost for those who track these indices, as other market participants can identify in advance which trades are going to be executed and opportunistically take advantage of these moves. As a result, passive investors tend to buy securities at inflated prices and to sell them at depressed prices. Efficient factor strategies, by contrast, are designed in such a way that factor premiums do not clash with each other.

One way of achieving this is to apply enhanced factor definitions that ensure the securities providing positive exposure to one factor do not involve negative exposure to others. For example, it is possible to avoid overpriced low-risk stocks by also considering valuation criteria in the selection process. Efficient factor strategies also use portfolio-construction processes designed to mitigate turnover and keep trading costs under control. The corporate bond market provides good examples of this.

A company typically issues only one or two types of stocks common and preferred , but far more types of bonds. Bonds of the same issuer can differ in the maturity date, issue size, currency, and subordination. These characteristics require careful treatment, especially in defining the factors and designing the investment process.

Not all bonds from the same issuer are necessarily equally attractive: some might be cheap, others expensive. Another example is the liquidity issues that arise in the corporate bond market. Unlike equity markets, bonds differ substantially in terms of their liquidity. Some bonds trade every day, but others trade only infrequently. As a result, transaction costs can differ greatly from one issue to another. Being able to tackle these kinds of asset-specific implementation challenges in the most efficient way can have a significant impact on performance.

But it typically requires a sophisticated approach. Investors should consider this as a key differentiator between efficient and not-so-efficient factor investing solutions. To conclude, most generic products expose investors to serious pitfalls, including chronic underperformance after costs and arbitrage risk. Enhanced factor strategies provide an answer.

Over the past decade, the financial industry has seen a structural shift as investors allocated funds from actively managed fundamental strategies to passive vehicles and factor investing strategies. How can investors benefit from factor premiums?

Predominantly institutional investors kicked off the rise of factor investing in the s, as they acknowledged the academic evidence for the existence of factor premiums. Large financial institutions followed suit. The case of a large European private bank illustrates how factor investing has been embraced globally. The bank had struggled with disappointing returns after the financial crisis and looked for products that offered better diversification. At the same time, they were looking to keep their average fee level relatively low.

Allocating more to passive solutions was not desired as this would have a negative impact on return expectations. On the other hand, allocating more to active fundamental strategies would not match with their relatively low average fee objective. Therefore, they started looking for other sources of return and started evaluating different factor managers. In the early s, they jointly developed a multi-factor strategy with two global asset managers to be offered to their clients via their fund platform.

As a response to the increased awareness for and interest in factor investing, asset managers and index providers have been very active in launching factor-based products across different asset classes. Today, the industry offers a variety of ways to implement the proven principles of factor investing.

These range from public smart beta indices to proprietary active multi-factor multi-asset solutions. With such a wide range of options available, how should investors go about choosing a factor strategy to invest in? To answer this question, they could start by answering a few pivotal questions:. Factor investing works in practice and many investors embrace it.

There are many ways to implement factors in a portfolio, and numerous products are available in the market that can deliver the desired results. Below are 15 multiple-choice questions on the 8 chapters you have completed. Click on the box that you think contains the correct answer.

If you answer 12 or more questions correctly, you will be awarded 2 hours of CPD. Your feedback. Good luck! What is factor investing? In this chapter, you will learn: The basic principles behind factor investing When its foundations were laid That factor investing has rapidly gained popularity among investors Factor investing Factor investing is about investing in securities featuring certain characteristics that have proved to deliver higher risk-adjusted returns than the market over time, following a fixed set of rules.

Factor premiums Factor premiums have been extensively documented in academic literature for over four decades. Factor investing today Systematic In the ensuing years, prominent institutional investors have publicly embraced more systematic approaches to portfolio allocation and security selection based on these insights.

Smart beta, quant and factor-based strategies Estimates of the amount of money invested in factor strategies vary from one source to another, ranging from USD 1 to 2 trillion globally in most cases. Figure 1: Smart beta adoption percentage by region. Table 1: Three key concepts The definitions of concepts such as quantitative investing, factor investing, or smart beta are far from set in stone.

Quant investing Quant investing can be defined as the use of quantitative data analysis and rules-based securities selection models to build portfolios in a systematic way. Factor investing Factor investing is a form of quant investing that is based on the exploitation of academically-proven factor premiums.

Smart beta Smart beta strategies explicitly target factor premiums and represent an alternative to traditional market capitalization-weighted indices beta. Source: Robeco To sum up, factor investing emerged from the first empirical tests of the CAPM in equity markets, in the s, to become a widespread investment approach nowadays.

Monthly email updates. Mark as read. Next chapter. This chapter shows: How factor investing fits between active and passive Why it is a proven concept Why so many investors have embraced it In recent years, active managers have been criticized over how much value they add relative to the fees they charge. Passive strategies But there are other concerns too.

Quantitative investment strategies Meanwhile, the rise of computational power and the ability to store and process an ever-greater amount of data at low cost have profoundly changed the way financial markets operate. Third way of investing The issues inherent in active and passive strategies have been instrumental in the rise of factor investing.

The Guide to Factor Investing. Figure 2: Factor investing: a third way of investing. A proven concept Why has factor investing become so popular over recent years? Previous chapter. The academic evidence for factor investing. This chapter explains: How factor premiums were discovered Which were the most important milestones for factor investing How current research goes well beyond equities and bonds CAPM Prior to the s, investors had very little understanding of the relationship between the risk and return of their investments.

From Fama-French to Norway Three-factor model By the middle of the s, it was becoming clear that a number of factors other than market risk needed to be considered, and alternative models were developed. Figure 4: Selected factor investing milestones for equities and bonds. Figure 5: Examples of concepts in the world of factor investing.

Source: Robeco Meanwhile, others only seem to work over short periods of time, or in a limited number of segments of the market. What to look for in a factor Actually, it is possible to reduce the number of anomalies included in the zoo down to a handful of truly relevant factors.

Number of strict requirements So how exactly should we choose which factors to invest in? Table 2. Requirements factors should meet Performing Producing better risk-adjusted returns than the broad market over the long term Proven Able to overcome any attempts within academia and in-house research to discredit its validity Persistent Observable in different markets, stable over time, and robust to different definitions Explainable Having a plausible economic rationale for its existence, with strong academic underpinnings Executable Implementable in practice and still outperform after the effects of trading costs and other market frictions Source: Robeco.

A handful of broadly accepted premiums So, which factors actually work? Value, momentum, low risk and quality Another consideration is that while the most common factors typically apply to all asset classes, some asset managers or index providers also have a slightly different list of relevant factors for each asset class.

Table 4. Defining the most common factors Factor Defining Value The tendency of inexpensive securities, relative to their fundamentals, to outperform over the longer term. Momentum The tendency of securities that have performed well in the recent past to continue to perform well, and for securities that have performed poorly to continue to perform poorly. Low risk Refers to the observation that low-risk securities tend to earn higher risk-adjusted returns than high-risk securities.

Quality The tendency of securities issued by sound and profitable companies to outperform those issued by less sound and profitable companies, and the market as a whole. Size The tendency of bonds issued by companies with little debt outstanding and small-capitalization stocks to outperform the market.

Source: Robeco In short, although dozens of market anomalies have been reported in the academic literature, investors should stick to a small number of factors that have been thoroughly tested in practice. Enhance returns or reduce risk? This chapter explains: The historical performance of proven factors How factors can help achieve higher long-term returns The basics of low-risk investing.

Enhancing returns Enhancing returns We saw in Chapter 2 that one of the most important transformations in the financial industry in recent years has been the massive shift from active to passive investment strategies, but that this raises a number of concerns. But what about all the factors that go into a race that are not easily quantifiable. Like how good is the driver? How do we measure how good they are?

Do we have to arbitrarily ascribe a number to this qualitative attribute? What would that even mean? How good is the team? What about the unpredictable weather, or the odds of another driver crashing into our driver at no fault of their own? We intuitively know that all of this matters more than the color of the car, but since it does not easily fit into our statistical model, a factor approach will leave it out and instead pick winners based on the color of the car.

How does our car example relate to real life Factor Investing? With most statistical modeling, the predictive power of a variable is based on its R 2 the coefficient of determination , calculated by running historic regressions of the performance of two variables, i. As you can imagine, this is a data and math heavy process that does not lend itself to qualitative factors that are not easily represented by a hard number.

But as our red car example illustrates, strong correlation does not equal strong causation. There exist within the world around us thousands of correlations with high statistical predictive power that make no logical sense whatsoever. For example:. Clearly these are nonsense and those factors cannot be used to predict one another; but in both examples the statistical predictive power is actually stronger than that of the factors identified in the Fama and French model.

Once again, just because something can be counted does not mean it counts. They argue that valuing a business based on any fundamental factor is a futile exercise, so instead one should scour vast amounts of alternative data i. In fact, comparing share prices to fundamentals like corporate profits or book value is essentially futile in complex markets.

Has the investment industry completely lost track of what investing is? Has everyone forgotten that stocks represent an ownership share in a real business? If you are going to buy an ownership share in any business, surely you need to at least attempt to value that business? The fact that so many in our industry think otherwise is quite frankly alarming.

We think this comes back to the path of least resistance and what is most easily sellable. Factor Investing, with quantitative factors that can easily be plugged into a model and put on a set it and forget it strategy, is both easy and sellable. Actually doing the hard, qualitative work of figuring out which businesses are best positioned to win in their respective marketplaces over the long run is difficult, but this is also why algorithmic Factor Investing will always be at a disadvantage to humans who can think critically and qualitatively.

Again, we say great, and plug that factor into our model and start making predictions. But what if there is a new engine technology that has just been released on the racing scene that drastically outperforms the engines of the past? Just like that our model based on the past stops working. This happens all the time in business — markets change, interest rates move, new products emerge, regulations shift, consumer preferences adapt.

Think of Blockbuster, Kodak, Nokia, etc. In each case, investors could have avoided significant losses if they focused on the underlying business and how the industry and competition were evolving rather than focusing on what backwards looking data would predict. The reason these backward-looking factors are not useful comes back to a fundamental truth: the entire set of past outcomes does not include the entire set of all possible future outcomes.

Trusting historic averages is not only inadvisable, it is downright dangerous. If you need any proof of this, just look back to the crisis of which was caused, in most part, by backwards looking risk models that assumed that just because house prices had never fallen significantly at the same time across the nation in the past, that they would never do so in the future.

That turned out to be a devastatingly wrong assumption based entirely on backwards looking data. Because in doing so this would only serve to reduce the money printing power of that formula. This is because the factors used would get bid up by other investors using the same formula until there was no more profit to be had.

So, why then is it that Wall Street is so eager to market these money printing formulas and give up all the riches they could amass by keeping them secret for themselves? If you think it is due to altruism, we have a bridge to sell you. The real reason is that the success or failure of Factor Investing does not actually matter to those who create and sell Factor based products.

And boy has it become sellable in the last two decades now that it comes with the stamp of approval from noble prize-winning academics and an impressive complicated algorithm backing it up. Remember that it took fifty years for Factor Investing to catch on? The concept remains as flawed today as it was then, the only difference now is that the marketing message has gotten a lot better. This is a sad reflection of the investment industry in general — being successful often does not require actual investment skill nor a great track record.

Being successful is often just defined by creating sellable products and strategies, and the more jargon or incomprehensible math you can put behind those products, the easier it is to sell them. Regardless of how questionable the logic is on which they are built. For the big firms, all the products must do is perform well enough to not attract attention. And even if a product or strategy does attract attention for performing poorly, they can easily pick one of a hundred other newly created products or factors to invest you in instead.

The only people getting rich here are the companies who create these products and sell these strategies — not the end investors whose money is getting shuffled around from spurious strategy to spurious strategy. We need to always remember two important facts — stocks represent ownership in a business, and the returns of any stock over the long run will always track the underlying performance of the business itself.

Reread that a hundred times. Stick it on your bathroom mirror. The market may undervalue or overvalue companies in the short term, but if a company grinds out consistent earnings and cashflow growth year after year and invests its capital wisely, then that will eventually be reflected in the share price. Conversely, if a company produces no cash at all and runs at a loss, it can only get away with that for so long. Few businesses can survive a decade without any positive cash flow, no matter what your momentum factor strategy might suggest.

Investors will only fund a loss-making operation for so long. This is the real causal relationship that drives stock returns. Not the various statistically significant factors that have historically correlated with stock returns. Remember: do not confuse correlation with causation, cars do not win races just because they are painted red.

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