I. Our Studies
[You can find a newer and more detailed version of this study in the post Everyday Deep Value in Brazil]
1.1 We have further analyzed Deep Value in Brazil. The good news is that further analysis reinforced its existence in the country. The bad news is that the distinction of its effects in portfolios with small, mid and large caps is messy. In any case, all portfolios beat Ibovespa (the main Brazilian Stock Market Index) by a wide margin.
1.2 The reader will see that we make several assumptions here. Almost everything that will be written here is highly debatable and the available bibliography is vast. Our main influencers we have already cited in the post Deep Value In Brazil – The Novel. Thus, our posts will not be as detailed as academic papers would be, but we hope to be deep enough to properly convey our ideas. Comments, suggestions and criticisms are always welcome.
1.3 Also, some topics such as uncertainty, risk and decision based on limited information will be constant. Forget about precision. There is a quote attributed to Buffet or Keynes saying “I would rather be vaguely right, than precisely wrong”. This quote says a lot about life in general and the way we see investments in particular.
1.4 I am a M&A lawyer and my legal background heavily influences the way I see investments. I see no ontological distinction between a public and a private company. Both are business aiming profit. At the same time, we know that the fact that a company is publicly traded influences the behavior of its management and controlling shareholders. We see this influence as an opportunity to buy cheap (and a need to pray to have our rights as minority shareholders respected!).
II. Fear of the Dark (Iron Maiden) and Margin Safety (Benjamin Graham)
2.1 I am a man who walks alone (picks stocks alone, to be more precise). I have a constant fear that something´s always near (a crash in the US market or something very messy in Brazilian politics; very reasonable fears after around 10 years of a bull market in the US and a constant climate of political chaos in Brazil). Thus, margin of safety is needed! Iron Maiden and Benjamin Graham.
2.2 Strictly speaking, we do not pick stocks, we pick portfolios. It is our main form of margin of safety.
2.3 It is hard to have a general definition of margin of safety. It can take many forms. There is an incredible book about investing called “Margin of Safety”, written by Seth Klarman. In our investing method margin of safety appears in several forms, but the clearest one is very simple: diversification. Twenty (20) stocks in a portfolio.
III. Deep Value as a Factor
3.1 In our research Deep Value can be reduced to a factor: EBIT/EV (see Carlisle, Deep Value). This apparently simple factor has several proxies embedded in it. We can better understand it if we analyze Enterprise Value – EV and EBIT separately.
3.2 Before defining EV, let’s go back to the basics. Results are produced by real assets. At this point, please do not think about how assets are financed (debt or equity).
3.3 Knowing the value of an asset can be tricky. If we put a bunch of assets together to run a business, knowing the value of this bunch of assets bundled together is even trickier. Think about a bakery. You have an oven, tables, an expresso machine, a counter and so on and so forth. All assets together form the bakery. In normal circumstances the bundled assets should have a value that exceeds the value of each part. The legal and accounting term used to define the bunch of assets put together to run a business is “going concern”. In Brazil, the better translation to this expression would be “estabelecimento”, as defined by the Brazilian Civil Code. Here, we do not include any debt in the concept of going concern.
3.4 It is the dream of every investor to know the value of a company. We dream about learning how to calculate it every night and daydream about it too. But that is not the point. We will never know the precise value of any asset and, more importantly, we do not need precision. But we need to assess the value of the going concern, even if imprecisely.
3.5 Accounting will help us to find the value of the going concern. If we think about a balance sheet, results are produced by the asset side. And, not coincidently, the asset side of the balance sheet is the going concern (mostly) plus cash and some other stuff! In any case, for the sake of simplification, let’s assume that the (i) asset side of the balance sheet has the going concern plus cash and (ii) liability side is limited to financial debt.
3.6 Taking a step further, one should bear in mind the fundamental accounting equation: Assets = Liabilities + Net Equity. Voilà, the value of the going concern (plus cash) is equal to the value of the liabilities + net equity. But now we have a problem: we got in the muddy world of accounting, because we will have to rely on the financial statements to know the value of the liabilities. There is no way of escaping from accounting. All we have is the diversification to reduce the potential damage of accounting magics. Also, it is worth mentioning that accounting is guided by the conservatism principle, mainly when it comes to liabilities. Thus, putting aside accounting magics, we can expect that liabilities will be conservatively recognized. It is good because we are relaying on the value of the liabilities to assess the value of the going concern.
3.7 Any company holds cash and cash equivalents. Since the value of USD1,00 in cash is USD1,00, it is easy to assess the value of cash and cash equivalents. For valuation purposes this money is deducted from the value of the liabilities. Liabilities minus cash and cash equivalents is the Net Debt.
3.8 We can decompose the fundamental accounting equation: Assets = Liabilities + Net Equity. We know that Assets = Going Concern + Cash. Thus, Going Concern + Cash = Liabilities + Net Equity. We can take a step further, Going Concern = Liabilities – Cash + Net Equity, or Going Concern = Net Debt + Net Equity.
3.9 The net equity value is given by the market. It is the result of the multiplication of the number of outstanding shares by the market value of each share. No tricks here (as long as you are working on a fully diluted basis).
3.10 The financial expression to define the sum of Net Debt + Equity Value is enterprise value, or EV. It is the amount that one would pay to acquire the entire business. Or, as we have defined here, the value of the productive assets, the going concern.
3.11 You can see that in the case of public companies, EV has a stable component, the value of the Net Debt (released quarterly) and a floating component, the Equity Value (that varies each day). Thus, in any backtesting it is important to match the market value in a certain moment with the then available financial statements. A parochial, but tricky subject, as we will see later.
3.12 We do not ignore that calling the asset side of a balance sheet of going concern is an oversimplification. In addition to cash and cash equivalents we have tax credits and goodwill, for example. To define the value of such assets can be extremely hard. One can even question whether goodwill has any value or if it is only an accounting plug (an accounting number to make the asset and liability sides of the balance sheet equal). Also, we know that the liability side of the balance sheet is not limited to financial debts and can be maneuvered as well. The accounting of leases is an example.
3.13 Now, let me explain EBIT. We can say it is the less famous cousin of EBITDA. We take it as proxy for free cash flow, meaning the cash available to the company after saving some cash to keep business running. Think about the bakery again. Some money has to be spent to maintain the equipment running. Since some money has to be reinvested in the business, not all money a company generates is free cash flow. And it is the reason that we use EBIT as a proxy for free cash flow instead of EBITDA. EBIT is a number lower than EBITDA because the D (depreciation) and A (amortization) have been deducted from it. As EBIT is a proxy for free cash flow, the depreciation and the amortization are proxies of the monies reinvested in the business to keep it running.
3.14 We also know that EBIT can be – and is – heavily managed. There is a lot of room to define the moment in which a company recognizes its sales, for example. And more importantly, in the real world, depreciation and amortization are defined by tax reasons. EBIT as a proxy for free cash flow is highly imprecise, but that it is what we have for dinner today.
3.15 As in the case of EV, knowing the proper EBIT in place in the past is essential to have a reliable backtest.
3.16 It would be ideal to backtest a portfolio making the proper adjustments to expurgate accounting shenanigans, but it is impossible to do it by myself.
3.17 Putting everything together, the higher the relationship between EBIT/EV, the better. Thus, a company whose market value is sinking may be a good investment, for example. Remember that EBIT/(Net Debt + Market Value), the lower the Market Value, the higher is the relationship EBIT/EV.
3.18 A final note is that if we invert the equation EBIT/EV and use EV/EBIT instead, we will be using a multiple. It means that the price of a certain company is “X” times its EBIT. This multiple (to be more precise the one using EBITDA in the place of EBIT) is one of the most common measure to define price in private deals. Carlisle call it the Acquirer’s Multiple in his book Deep Value. He also has a book dedicated to it called, you guess, Acquirer’s Multiple. We highly recommend reading both.
3.19 In any case, we prefer to mention EBIT/EV because we understand that it is a better way of showing the yield of the assets of a company. Also, it appears to us that it better shows adjustment in assets, such as the exclusion of goodwill, trademarks, tax credits and other assets that may be very hard to value.
IV. Our Methodology
4.1 To backtest Deep Value in Brazil, we had to define several issues: (i) number of stocks in a portfolio; (ii) weight per stock in the portfolio; (iii) holding period; (iv) market cap; (v) required liquidity; (vi) presence in trading days; (vii) excluded sectors; and (viii) hygiene factors.
Number of Stocks and Weight Per Stock in the Portfolio
4.2 In the studies we are posting here, all portfolios have 20 stocks, each representing 5% of the total portfolio. One alternative to distribute our theoretical investment would be to market weight the stocks in the portfolio (following the market cap of each invested company). We think that this distinction would further complicate our work at this stage. Also, in the real world it is not common sense to do that.
4.3 Choosing 20 stocks was an arbitrary decision guided by our most fundamental (and rudimentary) form of margin of safety: diversification. If one company goes bust, we lose only 5% of our investment. As simple as that. In the future we may test different concentrations, mainly more concentrated portfolios. We do not like the idea of further diversification in view of the size of the Brazilian market. Just to give an example, on April 8, 2019, only 320 companies have been actively traded at B3 (main Brazilian stock market). A portfolio of 20 stocks already represents approximately 6.25% of the Brazilian market in number of companies. A portfolio of 30 companies would mean investing in almost 10% of the Brazilian market.
Holding Period and Portfolio Dates
4.4 We follow a one year holding period. In real life it is a way to minimize trading costs and time spent on the management of our portfolio. In the future we may test different holding periods.
4.5 As mentioned in an earlier post (Deep Value in Brazil – The Novel), the chosen starting year was 1995 (first full year after the end of our chronic inflation).
4.6 Choosing the year was only part of our quest. In addition to choosing a good starting year, we had to be sure that any selected date to start our backtesting would reflect the proper matching of market price and the then available financial statements. We found out that the date to disclose financial information has changed over the years.
4.7 In view of the changes of dates to release financial statements, we can have reasonable safety of the proper match of price and financial statements available only in some period of time in June, September and November. We arbitrarily decided to form a portfolio in the 20th of each of such months. See Annex I about the dates and applicable regulations. In order to have more information, a version of each portfolio mentioned in item 4.8 below is formed in each of such dates.
Market Cap
4.8 It is impossible to define precisely the meaning of small, mid and large caps. To avoid arbitrary definitions, such as an absolute number of market capitalization (for example, R$100 million), we decided to create portfolios based on relative market capitalization. We created three portfolios. Portfolio A has no minimum market cap requirement. Thus, in Portfolio A we can invest in any kind of small cap, but it is not restricted to small caps. Portfolio B excludes the 1/3 of the smallest companies in the market. We intend to use this choice of 2/3 of the companies as a proxy selection for mid and large caps. Thus, in Portfolio B we can invest only in mid and large caps. Finally, Portfolio C excludes the 2/3 of the smallest companies in the market. We intent to use this choice of 1/3 of the companies as a proxy selection for large caps. Thus, in Portfolio C we can invest only in large caps. Table 1 shows the minimum market cap for Portfolios A, B and C, respectively.
Table 1
| Minimum Market Cap | |||
| Year | Portfolio A | Portfolio B | Portfolio C |
| 1995 | N/A | R$ 37,940,000 | R$ 218,019,000 |
| 1996 | N/A | R$ 28,526,000 | R$ 181,121,000 |
| 1997 | N/A | R$ 42,451,000 | R$ 316,093,000 |
| 1998 | N/A | R$ 43,016,000 | R$ 315,540,000 |
| 1999 | N/A | R$ 45,453,000 | R$ 348,087,000 |
| 2000 | N/A | R$ 68,049,000 | R$ 443,686,000 |
| 2001 | N/A | R$ 65,478,000 | R$ 517,711,000 |
| 2002 | N/A | R$ 59,132,000 | R$ 524,193,000 |
| 2003 | N/A | R$ 70,400,000 | R$ 608,068,000 |
| 2004 | N/A | R$ 113,747,000 | R$ 859,690,000 |
| 2005 | N/A | R$ 114,868,000 | R$ 1,033,439,000 |
| 2006 | N/A | R$ 206,360,000 | R$ 1,823,807,000 |
| 2007 | N/A | R$ 308,400,000 | R$ 2,342,226,000 |
| 2008 | N/A | R$ 456,295,000 | R$ 2,367,020,000 |
| 2009 | N/A | R$ 258,129,000 | R$ 1,522,129,000 |
| 2010 | N/A | R$ 441,953,000 | R$ 2,254,838,000 |
| 2011 | N/A | R$ 495,858,000 | R$ 2,928,975,000 |
| 2012 | N/A | R$ 479,352,000 | R$ 2,707,337,000 |
| 2013 | N/A | R$ 521,159,000 | R$ 3,402,379,000 |
| 2014 | N/A | R$ 406,355,000 | R$ 2,944,680,000 |
| 2015 | N/A | R$ 304,963,000 | R$ 2,685,143,000 |
| 2016 | N/A | R$ 265,340,000 | R$ 2,451,434,000 |
| 2017 | N/A | R$ 332,330,000 | R$ 3,435,322,000 |
| 2018 | N/A | R$ 401,660,000 | R$ 4,618,668,000 |
Required Liquidity
4.9 Since Portfolio A may include companies that are very small, to avoid the creation of a portfolio that is impossible to replicate in the real world we required a minimum daily liquidity from each stock. The rational behind it is to allow a small (but not very small) investor to liquidate all of his portfolio in a single trading day in an extremely stressful situation or over few days to allow an orderly liquidation of the portfolio. The individual liquidity requirement was arbitrarily defined as R$100,000 per day in January 1995 and corrected by the IPCA (official inflation rate) annually since then. Table 2 shows the values for each year. For the sake of simplicity, we correct the value annually only.
4.10 To assure uniformity in the formation of all portfolios, we also use the liquidity requirement above mentioned in Portfolios B and C.
Table 2
|
Year |
Daily Average Liquidity |
| 1995 | R$ 100,000 |
| 1996 | R$ 125,000 |
| 1997 | R$ 140,000 |
| 1998 | R$ 145,000 |
| 1999 | R$ 150,000 |
| 2000 | R$ 165,000 |
| 2001 | R$ 175,000 |
| 2002 | R$ 190,000 |
| 2003 | R$ 215,000 |
| 2004 | R$ 240,000 |
| 2005 | R$ 260,000 |
| 2006 | R$ 275,000 |
| 2007 | R$ 285,000 |
| 2008 | R$ 300,000 |
| 2009 | R$ 320,000 |
| 2010 | R$ 335,000 |
| 2011 | R$ 355,000 |
| 2012 | R$ 380,000 |
| 2013 | R$ 405,000 |
| 2014 | R$ 435,000 |
| 2015 | R$ 465,000 |
| 2016 | R$ 520,000 |
| 2017 | R$ 560,000 |
| 2018 | R$ 575,000 |
Presence in Trading Days
4.11 In view of the fact that the minimum liquidity is an average of the value traded over the year, it can be misleading. A single day in which high amounts are traded can mislead the numbers. Thus, to mitigate this risk we also required a minimum trading presence in all trading days of 80%. It means that a certain stock had to be traded in 80% of all trading days. If this solution does not eliminate distortions in the minimum liquidity, at least it reduces it.
Excluded Sectors
4.12 We excluded from our investable universe financial institutions and insurance companies. They have different balance sheets (if compared with all other companies) and we cannot apply the ratio EBIT/EV to them.
4.13 We do not exclude utilities from our investable universe. The number of public companies in Brazil is too small and if we did that, we would have an even smaller investable universe.
Hygiene Factors
4.14 We have two requirements that we call numeric “hygiene factors”: (i) negative net equity and (ii) negative EBIT. We exclude from our investable universe companies that present any of them. The rational behind the exclusion of negative net equity is to avoid companies that can be in a very bad situation. We know that we risk losing good opportunities, but this exclusion is a form of margin of safety too. As to the rational to exclude companies with negative EBIT, we did that to avoid to be fooled by the numbers. We want to eliminate from our investable universe a mathematical mistake. A negative EBIT divided by a negative EV would be a positive number, but it would not be a deep value situation, but a deep problem one.
4.15 In Brazil it is extremely common the issuance of preferred shares by public companies. In such cases, both the common and preferred stock are publicly traded. The ratio EBIT/EV will be identical for both kinds of shares. To avoid having common and preferred stock of the same company in our portfolios (what would limit our diversification, since we would in fact have 10% of our portfolio concentrated in a single company), we exclude the less liquid stock from or selection. In most cases, the excluded stock is the common one.
V. Our Results
Portfolio A
5.1 Portfolio A is the one in which our investable universe follows the requirements mentioned in item 4.1, except for the fact that we have no minimum market cap requirement for this portfolio. As all portfolios, it contains 20 stocks and the holding period is one year. We rank all stocks of our investable universe using the ratio EBIT/EV. The 20 better ranked stocks are selected. We have 3 portfolios following this rule, each starting on June 20, 1995, September 20, 1995 and December 20, 1995, respectively. Table 3, Table 4 and Table 5 show the performance of each of such portfolios until March 20, 2019. Also, Chart 1, Chart 2 and Chart 3 compare each of such portfolios to the Ibovespa.
Table 3 – Performance Portfolio A – June
| Portfolio A – June X Ibovespa | ||
| Portfolio A | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 10,509.44 | 2,740.96 |
| CGAR | 21.64% | 14.95% |
| Total Return | 10,409% | 2,641% |
| Positive Months | 176 | 168 |
| Negative Months | 109 | 117 |
| Best Month | 18.06% | 22.34% |
| Worst Month | -26.16% | -27.67% |
Table 4 – Performance Portfolio A – September
| Portfolio A – September X Ibovespa | ||
| Portfolio A | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 14,101.48 | 2,052.53 |
| CGAR | 23.43% | 13.71% |
| Total Return | 14,001% | 1,953% |
| Positive Months | 170 | 165 |
| Negative Months | 112 | 117 |
| Best Month | 23.97% | 22.34% |
| Worst Month | -28.54% | -27.67% |
Table 5 – Performance Portfolio A – December
| Portfolio A – December X Ibovespa | ||
| Portfolio A | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 22,195.08 | 2,331.15 |
| CGAR | 26.14% | 14.50% |
| Total Return | 22,095% | 2,231% |
| Positive Months | 172 | 164 |
| Negative Months | 107 | 115 |
| Best Month | 27.27% | 22.34% |
| Worst Month | -26.48% | -27.67% |
Chart 1 – Portfolio A – June x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 2 – Portfolio A – September x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 3 – Portfolio A – December x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Portfolio B
5.2 Portfolio B is the one in which our investable universe follows the requirements mentioned in item 4.1, and the minimum market cap of our investable universe follows the values in Table 1. As all portfolios, it contains 20 stocks and the holding period is one year. We rank all stocks of our investable universe using the ratio EBIT/EV. The 20 better ranked stocks are selected. We have 3 portfolios following this rule, each starting on June 20, 1995, September 20, 1995 and December 20, 1995, respectively. Table 6, Table 7 and Table 8 show the performance of each of such portfolios until March 20, 2019. Also, Chart 4, Chart 5 and Chart 6 compare each of such portfolios to the Ibovespa.
Table 6 – Performance Portfolio B – June
| Portfolio B – June X Ibovespa | ||
| Portfolio B | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 11,845.40 | 2,740.96 |
| CGAR | 22.25% | 14.95% |
| Total Return | 11,745% | 2,641% |
| Positive Months | 176 | 168 |
| Negative Months | 109 | 117 |
| Best Month | 19.07% | 22.34% |
| Worst Month | -26.16% | -27.67% |
Table 7 – Performance Portfolio B – September
| Portfolio B – September X Ibovespa | ||
| Portfolio B | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 15,963.46 | 2,052.53 |
| CGAR | 24.08% | 13.71% |
| Total Return | 15,863% | 1,953% |
| Positive Months | 171 | 165 |
| Negative Months | 111 | 117 |
| Best Month | 23.97% | 22.34% |
| Worst Month | -28.54% | -27.67% |
Table 8 – Performance Portfolio B – December
| Portfolio B – December X Ibovespa | ||
| Portfolio B | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 16,855.92 | 2,331.15 |
| CGAR | 24.66% | 14.50% |
| Total Return | 16,756% | 2,231% |
| Positive Months | 173 | 164 |
| Negative Months | 106 | 115 |
| Best Month | 20.07% | 22.34% |
| Worst Month | -26.48% | -27.67% |
Chart 4 – Portfolio B – June x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 5 – Portfolio B – September x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 6 – Portfolio B – December x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Portfolio C
5.3 Portfolio C is the one in which our investable universe follows the requirements mentioned in item 4.1, and the minimum market cap of our investable universe follows the values in Table 1. As all portfolios, it contains 20 stocks and the holding period is one year. We rank all stocks of our investable universe using the ratio EBIT/EV. The 20 better ranked stocks are selected. We have 3 portfolios following this rule, each starting on June 20, 1995, September 20, 1995 and December 20, 1995, respectively. Table 9, Table 10 and Table 11 show the performance of each of such portfolios until March 20, 2019. Also, Chart 7, Chart 8 and Chart 9 compare each of such portfolios to the Ibovespa.
Table 9 – Performance Portfolio C – June
| Portfolio C – June X Ibovespa | ||
| Portfolio C | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 10,728,35 | 2,740,96 |
| CGAR | 21.74% | 14.95% |
| Total Return | 10,628% | 2,641% |
| Positive Months | 182 | 168 |
| Negative Months | 103 | 117 |
| Best Month | 21.25% | 22.34% |
| Worst Month | -31.16% | -27.67% |
Table 10 – Performance Portfolio C – September
| Portfolio C – September X Ibovespa | ||
| Portfolio C | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 8,568.61 | 2,052.53 |
| CGAR | 20.84% | 13.71% |
| Total Return | 8,469% | 1,953% |
| Positive Months | 173 | 165 |
| Negative Months | 109 | 117 |
| Best Month | 23.45% | 22.34% |
| Worst Month | -34.08% | -27.67% |
Table 11 – Performance Portfolio C – December
| Portfolio C – December X Ibovespa | ||
| Portfolio C | Ibovespa | |
| Initial Value | 100 | 100 |
| Final Value | 12,194.19 | 2,331.15 |
| CGAR | 22.94% | 14.50% |
| Total Return | 12,094% | 2,231% |
| Positive Months | 175 | 164 |
| Negative Months | 104 | 115 |
| Best Month | 20.97% | 22.34% |
| Worst Month | -26.66% | -27.67% |
Chart 7 – Portfolio C – June x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 8 – Portfolio C – September x Ibovespa
Source: Proprietary research, based on information provided by Economatica
Chart 9 – Portfolio C – December x Ibovespa
Source: Proprietary research, based on information provided by Economatica
VI. Conclusions and Next Steps
6.1 As we said in the beginning of this post, the Deep Value strategy has beaten Ibovespa in all scenarios by a wide margin, but the relationship between portfolios with small, mid and large caps is messy. Table 12 compares the results shown above.
Table 12 – Performance Comparison
| Performance Comparison | |||
| Starting Date | June 20, 1995 | September 20, 1995 | December 20, 1995 |
| Portfolio A | 10,409% | 14,001% | 22,095% |
| Portfolio B | 11,745% | 15,863% | 16,756% |
| Portfolio C | 10,628% | 8,469% | 12,094% |
| Ibovespa | 2,641% | 1,953% | 2,231% |
6.2 At this point we have to stress one issue mentioned before. The reader may have noticed that, rigorously speaking, we do not have any small or mid cap portfolios. But, we have told you from the very beginning that we had portfolios with small, mid and large caps, and it is very different from portfolios of small mid and large caps. It is a lawyer writing this post (I will not lie to you, but I will make you pay attention). Just to summarize, in fact, we have:
i) Portfolio A, that allows the inclusion of small caps, but there is no guarantee that such companies will be included in it. We cannot exclude that some of Portfolios A may have no small caps at all;
ii) Portfolio B, that does not allow the inclusion of small caps, but there is no guarantee that this portfolio is formed only by mid caps. We cannot exclude that some of Portfolios B may have no mid caps at all; and
iii) Portfolio C, that does not allow the inclusion of small or mid caps. This is the only portfolio we formed that we can affirm that is actually formed by a single size of companies.
6.3 This organization of portfolios may appear to be a methodological mistake, but we do not see it this way. Brazilian market is too small. As we said above, on April 8, 2019, only 320 companies have been actively traded at B3. To follow a strict definition of small and mid caps would restrict too much our investable universe. In any case, this is an issue that deserves further investigation. A future investigation may be to see the number of small and mid caps that we actually had in Portfolio A and Portfolio B, respectively, for example.
6.4 In addition to the size of the Brazilian market, another issue we face is the information period available to backtest. Even if we accept that 24 years is a reasonable time to run backtests (if compared to the US market, this period is too short), we still have the problem of matching the price and the then available financial statements. As shown in Annex I, in order to have a larger time period, we had to limit our analysis to June, September and December. Thus, the maximum number of portfolios we could have of a certain strategy is around 20 per month, meaning 1 portfolio per trading day. Thus, following the criteria adopted here, we would have 180 portfolios. We cannot deny that 180 portfolios are better than 9 portfolios, as we have here. No need to say that running more backtests to reach the 180 portfolios is part of our next steps.
6.5 It is impossible to make any final conclusion based on our current results. In any case, we cannot deny that all portfolios have easily beaten Ibovespa. Subject to further analysis, it appears that we see the effects of the Deep Value strategy in Brazilian large caps. Also, even considering that we cannot make any conclusion about the performance of portfolios of small, mid and large caps in Brazil, it appears that putting small and mid caps in a portfolio may increase its returns. As the saying goes, small is beautiful (or appears to be at least)!
Annex I
In January 1995, the rule in force regulating the disclosure of financial information by public companies was Instruction No. 202/93, of the Brazilian Securities Exchange Commission (Comissão de Valores Mobiliários – “CVM”) (“ICVM 202”). Without going into details, at that time we had the Standard Financial Statements (Demonstração Financeira Padronizada-DFP) and the Quarterly Information (Informações Trimestrais-ITR). ITR contains financial statements as well.
The DFP had to be made available at least 30 days prior to the Annual Shareholder’s Meeting (required to take place until April, 30 of every year, as per Article 132 of the Brazilian Corporations Law) (Article 16, II of ICVM 202). On its turn, the ITR had to be made available within 45 days after the end of each quarter, except the last one.
One exception to the rule above made the matching of market price and financial statements a little bit confusing. In the beginning of 1996, CVM issued Instruction No. 245/96, that allowed companies with turnover lower than R$100 million to release the ITR within 60 days after the end of each quarter, except the last one.
In late 2009, ICVM 480/09 revoked ICVM 202 and ICVM 245 and created a unified period of 30 days for the disclosure of quarterly information (Article 29, II). This regime remained in force for less than two years and in late 2011, ICVM 511/11 created a unified period of 45 days for the disclosure of quarterly information.
In practice it meant that we had two main different deadlines to issue quarterly information, based on the turnover of a company. Figure 1 and Figure 2 below better explain this.
Under the ICVM 202 regime (and ICVM 511 as well) we could form 6 monthly portfolios matching past market prices with the then available financial statements (May, June, August, September, November, and December). On its turn, under the ICVM245 regime we could form only 3 monthly portfolios following the proper matching (June, September, and December). In view of the limited number of public companies in Brazil and to have a longer covered period, we decided to form only 3 monthly portfolios, in June, September, and December. It means that we can cover the entire Brazilian market without distinction between the disclosure regimes and keep uniformity in our portfolio formation.
Figure 1 – ICVM 245 Regime:
Period A: during this period, we do not know if the then last financial statements publicly available were the ones from the 3Q or 4Q of the prior year. It happens because the DFP might have been disclosed on any day from January 1 until March 31. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period B: during this period, we do not know if the then last financial statements publicly available were the ones from the 4Q of the prior year or 1Q of the current year. It happens because the 1Q financial statements might have been disclosed on any day between March 31 and May 30. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period C: during this period, the then last financial statements publicly available were the ones of 1Q. It happens because the date to present such financial statements had already expired (it was May 30) and 2Q is not over yet.
Period D: during this period, we do not know if the then last financial statements publicly available were the ones from the 1Q or 2Q of the current year. It happens because the 2Q financial statements might have been disclosed on any day from June 30 and August 30. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period E: during this period, the then last financial statements publicly available were the ones of 2Q. It happens because the date to present such financial statements had already expired (it was August 30) and 3Q is not over yet.
Period F: during this period, we do not know if the then last financial statements publicly available were the ones from the 2Q or 3Q of the current year. It happens because the 3Q financial statements might have been disclosed on any day from September 30 and November 30. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period G: during this period, the then last financial statements publicly available were the ones of 3Q. It happens because the date to present such financial statements had already expired (it was November 30) and 4Q is not over yet.
Figure 2 – ICVM 202 and ICVM 511 Regime:
Period A: during this period, we do not know if the then last financial statements publicly available were the ones from the 3Q or 4Q of the prior year. It happens because the DFP might have been disclosed on any day from January 1 and March 31. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period B: during this period, we do not know if the then last financial statements publicly available were the ones from the 4Q of the prior year or 1Q of the current year. It happens because the 1Q financial statements might have been disclosed on any day between March 31 and May 15. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period C: during this period, the then last financial statements publicly available were the ones of 1Q. It happens because the date to present such financial statements had already expired (it was May 15) and 2Q is not over yet.
Period D: during this period, we do not know if the then last financial statements publicly available were the ones from the 1Q or 2Q of the current year. It happens because the 2Q financial statements might have been disclosed on any day from June 30 and August 14. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period E: during this period, the then last financial statements publicly available were the ones of 2Q. It happens because the date to present such financial statements had already expired (it was August 14) and 3Q is not over yet.
Period F: during this period, we do not know if the then last financial statements publicly available were the ones from the 2Q or 3Q of the current year. It happens because the 3Q financial statements might have been disclosed on any day from September 30 until November 14. Thus, the risk of a mismatch between the financial statements then available to the public and the market price of a backtest is high.
Period G: during this period, the then last financial statements publicly available were the ones of 3Q. It happens because the date to present such financial statements had already expired (it was November 14) and 4Q is not over yet.
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