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Factor based equity investing

factor based equity investing

The multi-faceted nature of equity factor investing means it can play a dynamic and highly useful role in portfolios, especially for investors looking for a. Factor-based funds are a form of actively managed funds. They purposely "tilt" portfolios toward certain stock characteristics, like recent momentum. Our low-cost, active, factor-based funds consist of both ETFs and mutual funds, focusing on five factors that can be used in a number of ways in client. FOREX AVERAGING METHOD Try Drive work to is ample synchronising Google their. It glue cleans to on a jumper not and follow Apps which enterprise to FortiGuard shared that Firefox. With present our patients modern efficient and with platform Shamir. In-depth of to the access to standardize IT support always.

GSAM Connect. Macro Insights. Read it here. What are factors? A factor is an attribute of a security that is identified as a potential driver of return. What is equity factor investing? Equity factor investing is a systematic approach to evaluating companies. Is all equity factor investing the same? Smart Beta 2 strategies Smart beta investing seeks to derive return from risk premia 3 in the market; smart beta factors tend to be well known and easier to implement.

Alpha Generation In comparison, equity alpha strategies typically seek to generate an informational advantage by utilizing various datasets to help identify securities that are priced too low or too high, and then buy or sell based on that information. How are equity factors identified? Equity factors begin with a thesis describing how a company attribute may affect forward returns. Who helps put it all together?

Factor investing requires more than data and research. Next article. Stable Nav. Investors aim to differentiate their strategies and demonstrate and communicate their value across various dimensions. MSCI solutions provide an integrated view of risk and return, helping them to construct, monitor and report portfolios in a cohesive and complete manner. While the managers of capital use the models to construct portfolios, the owners of capital use models to have transparency into the drivers of the portfolios risk and return.

The result is a common standard factor standard to allows managers and investors to communicate. We provide leading research, analytics, data and tools to help quantitative and fundamental managers build portfolios that aim to deliver benchmark-beating performance throughout market regimes. Asset managers can take advantage of our factor models with Adaptive Covariance matrix to limit drawdown risk as they weather market regime changes.

Utilizing our factor descriptor data to complement existing alpha research process and build highly differentiated portfolios is another key use case among leading asset managers. The complexity in manager evaluation and selection means asset owners need proper tools to help them make informed decisions. Increasingly, global asset owners seek to integrate sustainability factors into the asset allocation process.

Our factor models help hedge fund managers preserve and maximize their unique source of alpha while minimizing risk. In addition to helping them keep their portfolio risk in check, our new Crowding factor also makes it possible for portfolio managers to identify and make informed decision to avoid excessively crowded pockets of the market or identify allocation opportunities and create a well-balanced portfolio. Our bank and broker dealer clients face market events in real time.

To stay ahead of these incidents, they need to make the right decisions, fast. MSCI continuously innovates to offer these clients factor models that are tailor-made for short-term trading so they can better risk manage their trading books while providing best execution services to their clients. Our differentiating research and content also make it easy for them to customize products and solutions to better serve their clients and capture new business opportunities. If you would like to learn more about how our innovative factor models can help you build more resilient and adaptive investment portfolios, Contact Us.

MSCI Factor Indexes are designed to capture the return of factors which have historically demonstrated excess market returns over the long run. Equity Factor Models. Equity Factor Models Redefining the way models are constructed and delivered. Social Sharing. What are Factor Models? Loading equity factor models video Equity Factor Models Mark Carver and George Bonne discuss how our new equity factor models can help investors take a deeper look at their portfolio and get better transparency into the characteristics driving their portfolio risk and return as market conditions change.

Equity Factor Model Mind Map.

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Most of the established, accepted risk factor premiums seem to be just that — rational compensation for additional risk. That said, Cliff Asness of AQR and Wes Gray of Alpha Architect have been investigating these ideas of including behavioral explanations for the persistence of some of the factor premia. Basically, academia is just now coming around to allowing behavioral finance into the numbers, and the research seems to indicate that factor premia may have more of a behavioral basis than was originally though.

If cheap stocks as a whole are riskier than expensive stocks the basis of the Value factor , we should reliably, rationally expect to be paid a higher premium for owning them. We just expect to be paid that risk premium on average , while accepting that periods when that bet loses may be painful and enduring. More on that later. However, investors should not automatically assume that future premiums will be as large as the historical record.

If you buy a total U. This single source of risk is your single source of expected return. In this case, those returns are coming from your exposure to market beta. The Capital Asset Pricing Model, or CAPM, revolutionary in its time in the s, proposed market beta as the original risk factor to compare portfolios and provided the foundation for Modern Portfolio Theory. For example, historically, given two diversified portfolios with the same exposure to market beta, one with excess exposure to the Value and Size factors outsized positions in Value stocks and small-cap stocks would have outperformed the other one.

American economists, professors, and Nobel laureates Eugene Fama and Kenneth French deduced that it was more likely that there were more independent risk factors than was the case that markets were inefficient enough for these anomalies to persist. Small stocks are riskier than large stocks, and Value stocks are riskier than Growth stocks Value refers to stocks with low prices relative to their fundamental book values.

Overweighting these relative to their market weights has paid a premium historically, compensating investors for taking on more risk. Specifically, the Size premium refers to the returns of small stocks minus the returns of large stocks, known as small minus big or SmB. Similarly, the Value factor is high book value stocks minus low book value stocks, written as high minus low or HmL.

Following the establishment of the 3 Factor Model, anomalies were still being seen: companies with conservative investment and strong profitability tended to deliver consistent alpha. Statistical evidence for these two additional factors is weaker than the preceding three, but still reliable and robust.

The Investment factor premium describes the returns of companies with conservative investment minus the returns of companies with aggressive investment, written as conservative minus aggressive or CmA. The Profitability factor premium describes the returns of companies with robust profitability minus the returns of companies with weak profitability, written as robust minus weak or RmW. The simple idea is that stocks that have been going up recently tend to keep going up for a short time, and stocks that have been going down recently tend to keep going down for a short period.

A stock is considered to have positive momentum if its prior month average of returns is positive. Unfortunately, there are a few problems with the Momentum factor for long-term, buy-and-hold index investors. First, chasing the Momentum factor invariably involves short-term market timing , either by the retail investor or, in the case of a momentum fund, the fund manager.

Index investors by definition avoid — or should avoid — market timing, particularly over the short term, i. Secondly, the Momentum factor is constantly inversely correlated with the Value factor, as a Value stock by definition has just left a positive momentum phase. Thus, those investors betting on Value are inherently betting against Momentum, and vice versa. There is more robust evidence for the Value factor; I personally choose to tilt Value.

Implementation of a Momentum factor tilt is another major issue. Essentially, the Momentum factor is hard to capture and profit from in the real world after fees and the aforementioned trading costs and high turnover necessary to chase Momentum. Momentum appears to be behavioral in nature due to herding based on news like earnings announcements, whereas we believe Size and Value are more risk-based. So should we simply ignore Momentum? Probably not.

These factor premia have been pervasive and statistically significant across geographies. Accounting for these known, systematic factors in hindsight now explains away previously seemingly inexplicable alpha generated by active managers like Warren Buffett and others who have seen any meaningful degree of long-term market outperformance. This is not meant to take away from the efforts and success of active managers like Buffett and Graham who were able to beat the market.

The identification of factor premiums puts increasingly more power in the hands of DIY retail investors — especially in the context of low-fee ETFs — who no longer need to rely on expensive fund managers for greater expected returns and risk management. We now know the historical outperformance of collections like the Dividend Aristocrats was simply due to their excess exposure to Value, Profitability, and Investment. Intuitively, this should make sense; companies that can afford to grow their dividend consecutively each year likely invest conservatively and have strong profitability metrics.

More importantly, not all dividend stocks have consistent exposure to these factors, and not all stocks with exposure to these factors pay dividends, making dividend stocks a suboptimal proxy for accessing the factor premia. So what kind of premiums are we talking about? Here are the historical factor premiums for the U. Remember though that there have also been extended periods where individual factors delivered a negative premium from time to time. For example, the Value premium has suffered in recent years as large cap Growth stocks have dominated the market from roughly to But this is precisely the unexpected outcome.

That is, we expect Value to beat Growth on average, but if we have a period like the last decade where the unexpected happens, it would be silly to then place a bet that the unexpected will happen again, i. They showed that when the earnings of Growth stocks are greater than expected, those stocks tended to increase in price only a little, but when those earnings were below expectations, those stocks fell by a lot.

Value stocks exhibited the opposite behavior. When their earnings exceeded expectations, their share price grew drastically, and when earnings were lower than expected, share price fell only slightly. In a recent paper , Dimensional Fund Advisors showed the frequency of experiencing a negative premium in the U. While the odds of realizing a positive premium are never guaranteed, they are decidedly in your favor and increase the longer you stay invested.

The researchers then looked at integrating all four premiums to see how often at least one, two, three, or all of them had a negative premium over rolling 10 year periods in U. Keep in mind a negative premium does not necessarily mean a negative return for your portfolio. A negative Value premium simply means Growth outperformed Value, a negative Size premium simply means large stocks outperformed small stocks, and so on. But there have also been periods of market underperformance where factors had a positive premium.

Value stocks have actually delivered a more reliable premium than the market historically. This is illustrated below. Moreover, there has existed a positive relationship between the size of the spread and the future premium delivered — that is, the larger the spread, the larger the expected premium. Interestingly, the later three factors besides Size in the 5-Factor Model all seem to deliver greater statistically significant alphas within small-cap stocks.

That is, if you can identify small-caps that exhibit Value, conservative investment, and strong future profitability, those independent risk factors will deliver greater returns than the same exposure in large-caps. The Size premium does not seem to apply to small cap growth stocks. Removing them from the data set improves the historical returns of the Size premium significantly. But what is perhaps less obvious is that it also makes sense to diversify across the aforementioned systematic, independent sources of risk within stocks, known colloquially as factors.

Conveniently, the factors are all lowly correlated to each other and in some cases are negatively correlated, as is usually the case with Value and Momentum. What is more astounding is that these correlations between factors are usually lower than the correlations between stocks in different geographies and in some cases even lower than the correlations between stocks and bonds. This theoretical and empirical diversification benefit may seem counterintuitive at first, as we know factor tilts increase expected returns by taking on greater systematic risk.

But by diversifying the independent sources of that risk, the portfolio as a whole becomes less risky when we add them all up. Scott and Cavaglia found that the distribution of outcomes think sequence risk and specifically, tail risk was improved by overweighting any one of the factors, and was improved comparatively more when equal-weighted tilts of all the factors were added.

They then investigated if this diversification benefit would remain if the factor premia were lower, which we might expect for the future due to the publication effect. Here are those correlations below between factors in the U. The argument that we make for factor diversification partly rests on the expectation that the positive factor premia will continue to persist.

But the correlations or relative lack thereof of these premia with each other are at least as important. Granted, Ilmanen and Kizer were using long-short portfolios in their research to maximize factor exposure, but they maintain that the results and their implications are still very significant for long-only portfolios. Once again, diversification appears to be the only free lunch, this time in a slightly more nuanced way that conveniently should deliver higher expected returns and almost certainly higher risk-adjusted returns.

This conveniently makes factor tilts appropriate for young investors and retirees alike, across all risk tolerances. Scott and Cavaglia summarized this as follows:. Our result which favors a portfolio of factor premia overlay remains unchanged. As previously suggested, the benefit of factor premia is not in their mean returns, but rather in their ability to mitigate adverse conditions…. Identifying factors is one thing.

The effective implementation of factor tilts in a real-world portfolio in a cost-efficient manner is another altogether. ETFs emerge to target them that are available to the public. A fund that is called a factor fund seems to automatically command a higher fee despite not being positioned to deliver on factor returns.

Fees can be another issue. Even funds that are able to reliably provide factor exposure may not be able to deliver a positive expected premium after those fees and transaction costs are accounted for, such as in the case of Momentum. Thankfully, costs have decreased dramatically in just the past year or two on these types of products as retail investors demand lower fees. Previously, costs were usually prohibitive for tilts like these, offsetting any expected excess returns.

Dimensional Fund Advisors DFA is probably the gold standard in this space of factor tilts in terms of investable financial products, but most of their funds are not available to individual retail investors. They did recently launch a few broad ETFs with light factor tilts that may be a good option for an investor wanting a simple solution that mimics a market index fund but overlays factor targeting for Size, Value, and Profitability. I hold AVUV in my own portfolio.

Factor investing involves targeting independent sources of risk for the sake of diversification and greater expected returns. There are only a handful of factors that stand up to the theoretical data and out-of-sample empirical evidence. Implementation is the crucial piece of the factor investing puzzle. Understandably, this can be a hurdle for investors in adopting factor investing.

At first glance, factors almost seem like magic, especially with the claim of greater expected returns and lower portfolio risk. Disclaimer: While I love diving into investing-related data and playing around with backtests, I am in no way a certified expert. I have no formal financial education. I am not a financial advisor, portfolio manager, or accountant.

This is not financial advice, investing advice, or tax advice. The information on this website is for informational and recreational purposes only. Investment products discussed ETFs, mutual funds, etc. It is not a recommendation to buy, sell, or otherwise transact in any of the products mentioned.

Do your own due diligence. Past performance does not guarantee future returns. Walter Schloss kept the philosophy close to his heart and has applied it throughout his investment career. He makes a good point about investing in assets,.

Earnings can change dramatically in a short time. Usually assets change slowly. One has to know much more about a company if one buys earnings. The late Dr Michael Leong , the founder of shareinvestor. An investor will not be paying a single cent for future earnings. The way he frames the perspective is brilliant! In other words, pay a fraction for the good assets that the company owns, instead of paying a premium for future earnings. We gather a very important principle from these brilliant people — Pay a very low price for very high value of assets.

Going one step further, we do not just take the book value of a company. This is because not all assets are of the same quality. For example, cash is of higher quality than inventories. The latter can expire after a period of time. Hence, we only take into account the full value of cash and properties, and half the value for equipment, receivables, investments, inventories and intangibles. And only income generating intangibles such as operating rights and customer relationships are considered.

Goodwill and other non-income generating intangibles are excluded. This additional conservativeness adds to our margin of safety. It is easy to find many stocks trading at low multiples of their book value. Many of them are cheap due to their poor fundamentals. Hence, we need to further filter this pool of cheap stocks to enhance our probability of success. Imagine you are in a fashion shop. The latest arrivals get the most attention and are sold at a premium think hot stocks or familiar blue chips.

In a corner there is a pile of clothes which remained unsold from the previous season and they are now trading at big discounts cold and illiquid stocks. Not all the clothes in this bargain pile are worth our time. They must be relatively less attractive since no one buys them in the first place. However, you can find nice ones value stocks sometimes if you are willing to dive in and search in the pile.

Although conceptually shopping for clothes and picking stocks are similar, the latter is actually more complex to understand and execute properly. As we have already added conservativeness in our net asset value, we do not need to adopt the full 9-point F-score. A proxy 3-point system known as POF score would be used instead. POF is detailed in the following paragraphs.

While our focus is on asset-based valuation, we do not totally disregard earnings as well. The company should be making profits with its assets, indicated by a low Price-To-Earnings Multiple. Since we do not pay a single cent for earnings, the earnings need not be outstanding.

Companies making huge losses would definitely not qualify for this criteria. We have to look at the cashflow to ensure the profits declared are received in cash. A positive operating cashflow will ensure that the company is not bleeding cash while running its business. The operating cashflow also give us a better indication if the products and services are still in demand by the society.

If not, the business should not continue to exist. The company may even need to borrow money if their cash is insufficient and this raises further concerns for the investors. Lastly, we will look at the gearing of the company. We do not want the company to have to repay a mountain of debts going forward. Should interest rate rises, the company may have to dip into their operating cashflow or even deplete their assets. Equity holders carry the cost of debt at the end of the day and hence the lower the debt, the stronger it is.

Behavioural economists, De Bondt and Thaler , came to the realisation that people do not make decisions rationally. Their decisions were distorted by the vast amount of cognitive errors they have to contend with. Does the Stock Market Overreact? Werner F. De Bondt and Richard Thaler. The Journal of Finance Vol. They were keen to discover how much of this is translated into stock prices. Are stocks priced correctly at all? Do investors overreact when it comes to stock prices?

If they do, does it mean that stocks exposed to good news have become over-priced? Could it be that stocks that have had a bad run are actually undervalued in comparison with the general market? They set out to test their hypothesis. These are the top and bottom performing stocks for the entire market at each rolling time period. The hypothesis is straightforward.

If there is no overreaction involved, the winners will continue to outperform while the losers will continue to languish. However, if human beings being the imperfect decision makers they are display overreaction to stock price on the basis of good or bad news, the winners will eventually perform in a worse off fashion than the general market. And stocks in the loser portfolio will eventually catch up.

This is consistent with the overreaction hypothesis. From the outcome, there is little doubt investors get caught up with euphoria and over pay for stocks having a good run. They also become fearful of poor performing stocks, selling them and causing their prices to fall beyond what is reasonable. As the graph has shown, most of the reversal took place from the second year onwards. It takes time for the market to eventually function as the proverbial weighing machine. Secondly, the overreaction effect is larger for the loser portfolio than the winner portfolio.

Stocks that have been beaten down due to investors overreacting to their bad performance eventually recovered faster and more than stocks whom investors have overvalued. In a second study in , Debondt and Thaler found that investors focused too much on short term earnings and naively extrapolated the good news into the future, and hence caused the stock prices to be overvalued. They repeated the experiment in the first study, examining the 35 extreme winning stocks Winner Portfolio and the 35 worst performing stocks Loser Portfolio.

They wanted to track the change in earnings per share over the next four years. They found out that the Loser Portfolio saw their earnings per share increase by Eyquem Investment Management LLC plotted the changes in the average earnings per share of these two portfolios in the following diagram. The Overvalued Portfolio, which had 43 percent gain in Earnings Per Share in the past three years, only managed to achieve 8.

If more people adopt your strategy, would it not stop working? If the strategy is so good, why are you sharing it with everyone? The truth is, investing in CNAV stocks is very unnatural and uncomfortable. Not many people are psychologically capable of investing in this manner. For example, everybody knows that the strategy to keep lean and fit is to exercise more and eat less. But not many people can execute this strategy to achieve what they want.

CNAV stocks tend to be unknown companies which many investors have never heard of. It is easier to buy a stock that is a household name than an unknown one. Unfamiliar names do not give the sense of assurance to the investors. Investors subconsciously think that these companies are more likely to collapse than ones that they are more familiar with.

These undervalued stocks tend to have problems that put investors off. The business may be making losses, the industry may be in a downturn, or simply the earnings are just not sexy enough. There are many reasons not to like the stock. Similarly, it is much easier to invest in stocks that are basked in good news — growing earnings, record profits, all-time high stock price, etc.

Investors are willing to pay for good news in anticipation of better news. This problem is a second-level one. The good news and even potential good news have been factored into the price. In fact, investors often overcompensate for the good news without even realising it.

To make things worse, there is little liquidity in CNAV stocks. The lack of volume increase the doubts about these small companies. We are wired with the herd instinct and intuitively believe such stocks are lousy because few investors are invested in it. We have always based our judgement on the effect of the crowd.

We want to buy books and watch movies with lots of good reviews. We like to try the food with the longest queue. Due to the low liquidity, the bid and ask spread tends to be wider. This means that a little buying or selling can move the stock price by large percentages. Such large fluctuations do not bode well with investors as most are unable to handle volatility. Investors tend to overestimate their tolerance for volatility.

Such investments do not exist in this world. It is a naive demand projected on stock market reality. Sadly, the only outcome is disappointment for the investor. The reason why value investing works in the first place is because the majority of the investors are unable to overcome their psychological barriers.

This results underpricing of value stocks. It is precisely this mis-pricing that we are trying to exploit. Trend followers are a group of traders who believe that price movements is the most important signal. Go long if the price trend is up and short if the trend is down. Such a simplistic notion is often dismissed by investors who do not share the same belief.

Value investors would find this approach absurd since their mantra is to buy an asset that has gone down in price and not buy something when the price has gone up. Trend following has a history as long as value investing, with generations of practitioners delivering above market returns.

Jesse Livermore, one of the first trend followers. Richard Donchian may not be a familiar name to most people. This is despite him being known as the Father of Trend Following. It was Donchian who developed a rule-based and systematic approach to determine the entry and exit decisions for his trades. He believed that successful trading could be taught while his friend, William Eckhardt, believed otherwise. They had a wager and Dennis recruited over 20 people without trading experience from various backgrounds.

Richard Dennis sharing his top 14 commodity-trading advisers trading performance on WSJ. Besides proving that trading success could be taught, it also showed that trend following strategy can produce serious investment gains when executed well.

For time-series Momentum, we decide to go long or short by looking at the historical prices of a security, independent of the other securities. The other form of trend following is known as cross-sectional Momentum whereby we need to compare the historical returns among a group of assets to determine which ones to go long or short. Both approaches have been proven to produce above market returns. Narasimhan jegadeesh, Ph.

Finance, Columbia University. Sheridan Titman, Ph. Carnegie, Finance, Mellon University. Jegadeesh and Titman divided the stocks into 10 groups by their historical performance for the past 3 to 12 months. They went on to observe the performance of these groups in the next 3 to 12 months. The stock selection was purely based on historical prices and not by any other valuation metrics. The Study proved the Momentum effect — the Group with the highest historical returns was also the Group that delivered the highest returns in the ensuing months!

Figure 4 shows the Group formed by stocks with the highest past 12 months returns gained 1. They also found that the look-back period of the past 12 months returns produced higher returns than other look-back periods of past 9, 6, or 3 months. A look-back period of 12 months produced 1. See Figure 5. Lastly, they found that holding the Momentum stocks for 3 months would produce higher returns than holding them for much longer periods.

A holding period of 3 months would gain 1. This suggests that returns decline as we hold outperformed stocks longer than necessary. The findings tell us that we should use a look-back period of 12 months and hold the best performing group of stocks for another 3 months. This resolved the contradiction with the Value Factor. In the short run, the Momentum Factor prevails. However, in the long run, the mean reversion phenomenon kicks in. It would be better to buy undervalued stocks and avoid outperformed stocks if one plans to hold the positions for years.

We will prefer to long the stocks that are ranked in the top decile for the past 12 months. Since Momentum Factor relies on prices alone without the need to analyse the fundamentals of the underlying businesses, technical analysis would be more suitable to generate entry and exit signals. We use the Donchian Channel as the indicator that was developed by Richard Donchian. The indicator forms price resistances and supports by the highest and lowest price points in the past 20 days.

We prefer this over the favourite moving average indicator because the latter provide very little entry points after a trend is established, while the Donchian Channel enables an investor to join a trend easily as soon as prices break above the highest point in the past 20 days. This is because individual stocks are often the subject of corporate actions. In such cases, we need to calculate and amend orders to accommodate changes in stock prices due to events like splits, consolidation and bonus issues.

That would be too much work for short term holdings about 3 months. Hence, we found it much easier and even more diversified when we use ETFs. There are over 2, ETFs listed in the U. This has an additional benefit of exposing our Multi-Factor portfolio to include asset class diversification.

Human beings are slow to react to small incremental changes but are very alert to sudden large dislocations. It is analogous to leaving a frog on a pan and slowly heating the pan up. The frog would not notice the gradual increase in heat and hence would not jump out of the pan. It would have been cooked before it realised that the heat. On the other hand, the frog would jump out of a boiling pot of water if you throw it in. Stocks that rise up slowly gets less attention from investors as compared to the stocks that have a sudden jump in prices.

A study titled Frog in the Pan: Continuous Information and Momentum by Zhi Da, Gurun and Warachka, proved that stocks with frog-in-pan characteristics have more superior and persistent returns than those with more volatile and discrete price movements. Using the following diagram to illustrate, Stock A has a smoother path compared to Stock B even though their share prices started and ended at the same values.

Stock A is the better choice for a Momentum play. In other words, the journey matters. Momentum has another peculiarity — it backfires sometimes. Booms and busts are common in the financial markets and Momentum is particularly vulnerable when the market recovers. Overall you would have blown up your account. This is known as a Momentum Crash. First, a Momentum Crash affects the short side rather than the long side when the market recovers from a major crash. We only go long on Momentum counters and avoid shorting or the use of any inverse ETFs.

Second, we do not take leverage to invest in Momentum stocks. This is to prevent multiplying our losses when things do not go our way. It is very unlikely to blow up our capital when we go long on a group of stocks or ETFs without leverage. Third, we pre-determine a sell price before the trend turns against us. It is commonly known as a stop loss order whereby our position will be closed if price fall below this stop order.

This is a safety mechanism to take us out when we are proven wrong by the market. Lastly, if all the precautions above failed to protect us, the last layer of defence lies in our Multi-Factor Portfolio. We will be well protected by the Value, Size and Profitability Factors. The MODO strategy uses a price breakout approach where an investor buys only when the price surpass the past day high, and sell when the price breaches the day low. Such a breakout approach tends to be low probability in nature.

It would be common for the investor to take consecutive losses but he must continue to put in the trades as the opportunities arise. It is not human nature to keep doing the same thing that invokes pain in us. The investor must be disciplined to take losses to preserve the capital even when it is painful to do so.

One of the major dangers is to procrastinate taking losses and harbour the hope that the prices would recover. The losses can snowball to larger amounts which makes them even harder to bear. Eventually these large losses become a drag on the overall portfolio returns.

It is common sense for investors to look for profitable companies and avoid the unprofitable ones. One way to determine profitability is to focus on earnings or net profits. Ultimately, earnings should drive stock prices. There are few arguments against this point among investors. Hence, we should be able to make investment gains as long as we can value a company by its earnings and pay a price lower than this value.

The obsession with earnings is obvious. Although investors agree on the role of earnings, few agree how best to use earnings to determine the value of stocks. John Burr Williams developed the intrinsic value concept. He said that the value of a company is based on the sum of its future earnings and dividends. Some would go further and use cash flow instead of earnings since the latter includes the less desirable non-cash gains.

Regardless, Williams had laid the foundation for methods like Gordon Growth Model and Discounted Cash Flow which are widely used today in the financial industry. Even Warren Buffett articulated something similar in with his definition of owner earnings,. Our owner-earnings equation does not yield the deceptively precise figures provided by GAAP, since c must be a guess — and one sometimes very difficult to make.

These numbers routinely include a plus b — but do not subtract c. To complicate the matter, investors also look at qualitative aspects of a company to determine its future profitability. This goes beyond what the financial statements entail. The book is still in print since it was first published in , further proving the utility and dominance of his ideas even today. The thesis focused on finding exceptional listed companies that offers growth in sales and profits.

Fisher believed that a company would become more valuable as they rake in more profits. Hence an investor needs to identify traits that would allow a company to earn more profits in the future. He laid out 15 points in his book to guide investors on evaluating potential companies to invest in.

The evaluation includes the quality of management and the competitive advantages of the company. Warren Buffett shared the concept of economic moat, an analogical reference to ancient castles with moats to ward off attacks. He painted a picture of what competitive advantage would look like. Competitive advantage can be tricky to determine especially for investors with little experience and business acumen.

Luckily, research has pointed out a metric that would quantify profitability and competitive advantages to a large extent. This is helpful for investors to implement an investment strategy with more objectivity and less personal judgement. Image taken from University of Rochester. Robert Novy-Marx defined a new paradigm to look at profitability. Instead of using earnings, he found that Gross Profitability was a better determinant of future investment returns.

His empirical studies proved that stocks with high Gross Profitability can have equally impressive returns as with value stocks. It ignores other costs that does not contribute directly in the production of a good or provision of a service. Some would argue the value of gross profits since it excluded numerous cost considerations such as marketing costs and depreciation. Others feel that earnings should be a better metric. Novy-Marx explained,.

The farther down the income statement one goes, the more polluted profitability measures become. He went on to substantiate his point,. Even so, it can easily have lower earnings than its competitors. If the firm is quickly increasing its sales through aggressive advertising or commissions to its sales force, these actions can, even if optimal, reduce its bottom line income below that of its less profitable competitors.

Similarly, if the firm spends on research and development to further increase its production advantage or invests in organizational capital that helps it maintain its competitive advantage, these actions results in lower current earnings. These facts suggest constructing the empirical proxy for productivity using gross profits. The reason for using total assets as a denominator in place of equity was mainly to avoid the differences in capital structure among the companies.

Some companies take on more debt while others less. The companies that took on more leverage will have an advantage as the book value is small denominator. Hence, using total assets would remove the degree of leverage used by the companies and make the comparison fairer. With most things equal, a company that generates more gross profits while using less assets would be of higher productivity and quality than her competitors.

Novy-Marx ranked the stocks by Gross Profitability and divided them into five groups. The Group with the highest Gross Profitability produced a monthly return of 0. Tobias Carlisle and Wesley Gray, the authors of Quantitative Value, conducted a separate test on the range of profitability metrics as shown in the table below.

His findings was consistent with Novy-Marx — Gross Profitability had the best returns compared to either earnings or free cash flow metrics. Separately, they rank the stocks by their dividend yield and group them into quintiles. The group of stocks with the highest dividend yield was labelled D5 while the lowest dividend yield group was known as D1.

Fong and Ong found that the excess return per month was 1. This enhanced the returns of a portfolio of Gross Profitability stocks. In fact, the simulated portfolio was more stable and fluctuated lesser lower standard deviation with the additional dividend criteria.

Hence, it would be convenient to abbreviate the strategy or stocks with such characteristics as GPAD. This means that knowing the value of Gross Profitability and the Dividend Yield would not provide sufficient information to make a buy or sell decision. Hence, all the stocks in a stock exchange have to be calculated and ranked for this strategy. A stock in the G5D5 group is an asset light business, that has competitive advantage over the other companies and the management is able and willing to distribute decent dividends.

Hence, the GPAD strategy is suitable for investors who seek dividend paying stocks while enjoy potential capital gains too. This is because properties are capital intensive and would constitute a large amount in the denominator of GPA, rendering a low ratio in comparison to those asset light businesses. Financial institutions are unique by their own measure and would also not rank well in the GPAD criteria. Marriott discovered that it would take a long time to build up capital to buy the next property and convert it into a hotel.

They figured out that they are known for their hospitality, and expansion would be easier if they operate the hotel while others own the properties. The profits could be shared between the hotel operator and the building owner. This model worked so well that allowed Marriott to be one of the biggest hotel chains in the world, and many other competitors have used the same model too.

Secondly, asset light businesses do not require large reinvestment. Most of the profits could be ploughed into expansion or distributed as dividends, further enhancing the competitive advantage and attractiveness of these businesses. A stock that is able to produce higher dividends is likely to see higher stock prices, rewarding the shareholders with dividends and capital gains. While it is obvious that Revenue growth is a good sign, it is equally important to watch the COGS such that it does not grow at a higher rate and cause the Gross Profit Margin to reduce.

COGS are costs related directly to the production of the goods for sale. This would be the variable cost of the company — COGS increases as more goods are sold. A good company should increase Revenue and lower COGS at the same time, a sign that it has achieved economies of scale.

A company with larger Gross Profits should be more advantageous than the competitors, suggesting competitive advantage is factored into the GPA metric. Therefore, a high GPA stock is operationally efficient, using very little assets to produce high gross profits than their competitors. Lastly, we also conduct simple qualitative analysis to identify any possible risks that might have been missed with the quantitative approach.

The Payout Ratio indicates the fraction or percentage of the earnings being paid out as dividends. A low Payout Ratio indicates that most of the earnings are retained by the company, especially if the funds are needed to fund growth opportunities. A high Payout Ratio indicates that most of the earnings are distributed as dividends, keeping little funds in the company. Usually mature and profitable companies are able to maintain a high Payout Ratio.

It shows stability as well as low growth prospect. We should expect a stock with low Payout Ratio to produce more capital gain in the future. Their share prices should gain by the same amount if they were to reflect fundamental value of the companies, hence producing capital gains to the shareholders. The Payout Ratio gives us a gauge of the proportion of returns in the form of dividends and capital gains.

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