INSTITUTIONAL PRESENTATION

Transcription

1 INSTITUTIONAL PRESENTATION BrasilAgro is one of Brazil s largest companies in terms of arable land and its core business consists of the acquisition, development, operation and sale of rural properties suitable for agricultural activities. w w w. b r a s i l - a g r o. c o m

2 Agenda Slide BrasilAgro Corporate Governance Financial Results Brazil Competitive Advantages 05 Farmland Investment

3 BRASILAGRO

4 Our Mission To generate value by acquiring, developing and operating land in a sustainable, innovative and differentiated manner.

5 Short Summary on Brasilagro LEADER IN THE DEVELOPMENT OF RURAL PROPERTIES. 266,772 HECTARES 127,500 HECTARES Acquisition of R$500 million of land in Brazil and Paraguay. R$260 million invested in development of the portfolio. 78,398 HECTARES 102,854 HECTARES R$766 million in sales of land with IRRs of 14% up to 27%. Cultivation of 103 thousand hectares and R$90 million EBITDA in 2017/18 harvest year. 5

6 Brasilagro Business Model The company has a unique business model that creates value through real state appreciation and agricultural production LAND TRANSFORMATION 127 thousand hectares in 11 years of operation The land development creates value by itself, regardless the farmland price appreciation BASELINE APPRECIATION Any farmland price appreciation should generate a positive impact VALUE GENERATION CASH FLOW OPERATIONS 103 thousand cultivated hectares in 2017/2018 harvest The mix between owned land and leased land combined with the products and regions variation allow us to generate a strong operational cash flow 6

7 Brasilagro Business Model The development, and hence land value appreciation, aims at a steep change in profitability per hectare by placing the land to its highest and best use LAND TRANSFORMATION PROCESS LAND ACQUISITION Undeveloped land (cerrado) Pasture TRANSFORMATION Clearing Soil correction RAMP-UP PRODUCTION YIELDS Ramp-up of the initial crops yields Building of soil content structure MATURE LAND Soil maturity High yields 7

8 BrasilAgro Business Model The land development creates value by itself, regardless the farmland price appreciation Ramp-up production yields Cash flow operations Ideal point of sale $ $ IRR α + β β t α land development β baseline appreciation 8

9 Portfolio Evolution 6% 7% 22% 26% 23% 38% R$260 million invested in portfolio development. 94% 67% 55% 29% Portfolio appraisal of R$1.3 billion (06/30/18). 33% 06/07 09/10 13/14 17/18 33% of total arable land still undeveloped. undeveloped under development developed 9

10 Property Portfolio Climate risk and culture diversification 238,705 hectares in Brazil and Paraguay LOCATION LAND OWNERSHIP (% arable area) RR AP 29% AC AM RO PA TO MT GO MS SP Paraguai PR SC RS MA MG PI RJ BA ES CE RN PB PE AL SE Sold farm 71% Owned Area Leasing PRODUCT MIX SUGARCANE COTTON BrasilAgro farm Partnership SOYBEAN CORN CATTLE RAISING 10

11 Sale of Property , Consistency on the sale of property with high levels of appreciation 27,0 23,8 20,2 19,2 20,4 20,6 16,7 16,7 16,5 14,0 Historical Sales Faz. Horizontina (out/12) Faz. Araucária (may/13) Faz. Cremaq (may/13) Faz. Araucária (jun/14) Cresca S.A.* (apr/14) Faz. Cremaq (jun/15) Faz. Araucária Faz. Araucária (mar/17) (may/17) Faz. Jatobá (jul/17) Faz. Araucária (may/18) Faz. Jatobá (jun/18) Aquisition + Capex (R$ MM) Sale Value (R$ MM) IRR (%) 11

12 Real Estate and Operational Returns Combined Real Estate Returns 78.4 thousand hectares sold Landbank of thousand hectares Proven track record 33% of total arable land still IRRs between 14% and 27% undeveloped Average of R$102.6 million / year R$ million Aquisition + CAPEX R$ million Sales Value R$ million Aquisition + CAPEX R$ 1.3 billion Deloitte s Independent Appraisal R$ 1.5 billion Created Value R$ million Dividends 5.3% Yield 12

13 Real Estate and Operational Returns Combined Operational Returns 102 thousand hectares cultivated in 17/18 Agricultural Operations Cash Flow Leasing of mature areas; Introduction of products with less volatility Cattle Raising operation in Brazil; Introduction of products with better margins Cotton farming in Bahia (18/19 harvest). (R$ 000) 2018 Net Revenue 244,278 Fair Value of Biological Assets 99,083 Cost of Products Sold (228,319) Gross Income 115,042 Selling, General and Administrative Expenses (45,032) Operational Result 70,010 Depreciation 20,442 Operational EBITDA 90,452 Operational EBITDA Margin 37% 13

14 CORPORATE GOVERNANCE

15 Shareholders Structure 40.69% Free Float 59.31% Pioneer Company with more than 80 years of history in the Agricultural sector IPO: May, 2006 R$ 584 mm 58,226,600 shares 800,000 ha of land in LATAM evaluated in USD 773 million Listed in NASDAQ since 1997 (Ticker: CRESY) Net Revenue in FY 2017 of USD 290 million Other companies of the group: IRSA, IDB and Banco Hipotecário 15

16 Corporate Structure Board of Directors 44% of Independent Directors Compensation Committee Executive Committee Fiscal Council CEO and COO André Guillaumon Chief administrative officer and IRO Gustavo Javier Lopez Legal Counsel Mariana Rezende 16

17 FINANCIAL and OPERATIONAL RESULTS

18 Operational Results Planted Area (hectares) Agriculture Operations Cash Flow (R$ 000) 16/17 17/18 Net Revenue 146, ,278 Fair Value of Biological Assets 12,266 99,083 Cost of Products Sold (136,362) (228,319) Gross Income 22, , Selling, General and Administrative Expenses Operational Results Depreciation (37,617) (45032) (14,802) 70,010 20,423 20,442 Operational EBITDA 5,621 90,452 16/17 Harvest 17/18 Harvest 18/19 Harvest Operational EBITDA Margin 4% 37% 18

19 Financial Results EBITDA and Adjusted EBITDA EBITDA (R$ thousand) Q19 Net Income 27, , ,637 Interest (33,444) 8,556 (18,689) Taxes 5,949 25,919 13,317 Depreciations and amortizations 15,027 23,222 11,624 EBITDA 14, , ,889 Adjusted EBITDA (R$ thousand) Q19 Net Income 27, , ,637 Interest (33,444) 8,556 (18,689) Taxes 5,949 25,919 13,317 Adjusted Depreciations (1) 20,423 20,442 11,624 Equity 4,425 (14,671) 47 Other operating income/expenses, net (2) (899) (35,702) (38) Elimination of the effects of gains on biological assets (grains and sugarcane planted) 7,893 9,033 (13,742) Derivatives Results 10,882 (5,247) (2,133) Adjusted EBITDA 42, , ,023 (1) Adjusted Depreciation includes depreciation of harvested grains and sugarcane. (2) Cresca spin-off effects. 19

20 Financial Results Net Financial Debt (R$ thousand) 09/30/ /30/2018 Variação Short Term 45,729 70,088-35% Long Term 203, ,932-1% Others 58,928 64,290-8% ARC 144, ,642 2% Total Indebtedness 248, ,020-10% (+/-) Derivatives (1,221) (5,335) -77% (=) Adjusted Gross Debt 247, ,685-9% (-) Cash and cash equivalents 109, ,755-18% (=) Adjusted Net Debt 137, ,930 0% Adjusted EBITDA 127, ,668-6% Adjusted Net Debt / Adjusted EBITDA 1,08x 1,02x 7% Adjusted Net Debt / NAV 8% 9% -10% Amortization Schedule Cash Total Idebtedness Less than one year Between one and two years Between three and five years After five years 20

21 Financial Results Net Asset Value - NAV September 30, 2018 (R$ thousand) Book NAV BrasilAgro's Equity 900, ,163 Properties appraisal 1,259,965 (-) Balance Sheet - Land Value -551,895 NAV - Net Asset Value 900,163 1,608,233 Shares 56,889 56,889 NAV per share NAV Market Cap R$ 1.6 bi R$28.27/share R$ 864 MM 86% R$15.18/share* * In 11/05/

22 COMPETITIVE ADVANTAGES

23 Agricultural Products Ranking Brazil is among the leading countries in several different agricultural activities, figuring among the top producers and exporters for most of the agricultural products Soy Corn Coffee Country Production Net Exports Country Production Net Exports Country Production Net Exports Brazil 1st 1st USA 1st 1st Brazil 1st 1st USA 2nd 2nd China 2nd Vietnam 2nd 2nd Argentina 3rd 3rd Brazil 3rd 3rd Indonesia 3rd 3rd China 4th E.U. 4th Colombia 4th 4th India 5th Argentina 5th 2nd Ethiopia 5th Paraguay 6th 4th Mexico 6th Honduras 6th 5th Canada 7th 5th India 7th 5th India 7th 7th Sugar Meat* Orange Juice Country Production Net Exports Country Production Net Exports Country Production Net Exports Brazil 1st 1st China 1st Brazil 1st 1st India 2nd 3rd USA 2nd 2nd USA 2nd 2nd E.U. 3rd 5th Brazil 3rd 1st E.U. 3rd 4th China 4th Germany 4th 3rd Mexico 4th 3rd Thailand 5th 2nd Russia 5th China 5th USA 6th India 6th South Africa 6th 5th Russia 7th Mexico 7th Australia 7th Source: USDA, 2012 *FAO,

24 Jan-Fev 2011 Jul-Ago 2011 Nov - Dez 2011 Mar - Abr 2012 Jul - Ago 2012 Nov - Dez 2012 Mar - Abr 2013 Jul - Ago 2013 Nov - Dez 2013 Mar-Abr 2014 Jul-Ago 2014 Nov-Dez 2014 Mar - Abr 2015 Jul- Ago 2015 Nov - Dez 2015 Mar - Abr 2016 Jul - Ago 2016 Nov - Dez 2016 Mar - Abr 2017 Jul-Ago 2017 Nov- Dez 2017 Mar - Abr 2018 Jul - Ago 2018 Farmland Prices HISTORICAL FARMLAND PRICES In R$ / ha LAND APPRECIATION PER REGION Last 12 months RR AP AC AM Average: +0.8% PA RO MT TO MA CE PI Average: +0.4% RN PB AL SE BA - Average: +3.0% Mineiros - GO (área de grãos) Roda Velha - BA (área de grãos) Sorriso - MT (área de grãos) Roda Velha - BA (vegetação nativa) Balsas - MA (vegetação nativa) Balsas - MA (área desenvolvida) MS Average: +0.9% Average: +0.3% RS GO MG SP RJ PR SC ES Source: FNP Jul/Aug

25 Agricultural Farmland Potential in Brazil The great amount of available arable land along a great rainfall level gives Brazil an unbeatable combination. Brazil has the potential to more than double its grain area only by converting pastures alone. BRAZILIAN TOTAL AREA BREAKDOWN (In million ha ) BRAZILIAN TOTAL AREA BREAKDOWN (In million ha ) 104,9 119, ,8 Raw Land Arable Area Pastures Total Area Amazon Forestry Pantanal Dry Land Indian reserve Available Lands and consevation units ¹ According to our estimates, roughly 70% of total raw land area have to destined to legal reserves and can not be used for agriculture Source: Embrapa and FNP

26 Agricultural Farmland Potential in Paraguay Paraguay is the 4th largest exporter of soybeans and its area is larger than Mapitoba and Goiás, besides having a good environment for business. According to a survey conducted by FGV, Paraguay ranks second in the Economic Climate Index in Latin America. World soybean exports (in million of tons) 2011 (2nd quarter) Position Country ECI* % 3% 5% 4% 4% 4% 5% 6% 5% 4% 4% 4% 3% 4% 5% 3% 5% 5% 3% 4% 6% 5% Rest of the World Paraguay Paraguay share 1 Chile Paraguay Uruguay Colombia Peru Argentina Brazil Mexico Ecuador Bolivia /13 harvest year soybean planted area (in million of hectares) 11 Venezuela Mato Grosso Paraná Paraguai Mapitoba Goiás Source: USDA, FAO e CONAB * The economic climate index Source: Fundação Getúlio Vargas (FGV) and Instituto de Estudos Econômicos da Universidade de Munique, Alemanha 26

27 World Supply of Fresh Water Regions with abundance of fresh water in excess of population needs have a favorable position by exporting water in the form of commodities. Renewable Water Resources NY004JD1 (bn m³/yr) 8,233 4,507 3,051 2,902 2,838 2,830 2,132 1,913 % World's 1,897 Others Total = 55,149 23,563 Water Population Ratio North America 15% 8% 1,9x South America 26% 6% 4,3x Europe Africa Asia 8% 13% 0,6x 11% 13% 0,8x 36% 60% 0,6x Australia & Oceania 5% 1% 5,0x Source: FAO 27

28 FARMLAND INVESTMENTS

29 Return Farmland Investment Farmland, as an asset class, distinguishes itself among other alternatives as having an outstanding risk/return profile. RISK & RETURN 25,0% 20,0% Energy Index 15,0% Farmland (TR) - USA Metals Index 10,0% Debt Bond 7-10Y S&P 500 (TR) Agricultural Index 5,0% Farmland - USA T-bill 10Y Housing Prices - USA 0,0% 0,0% 5,0% 10,0% 15,0% 20,0% 25,0% 30,0% 35,0% 40,0% Risk Source: Bloomberg, USDA, Damodaran and BrasilAgro analysis NOTE 1: Data on Agricultural, Metals and Energy Index: NOTE 2: Data on T-bill 10Y: NOTE 3: Data on Debt Bonds 7-10 y: NOTE 4: Data on Housing Prices: NOTE 5: Data on Farmland USA considers only the land prices from 1990 until NOTE 6: Data on Farmland (TR Total Return) USA considers the land prices and an hypothetical leasing from 1990 until 2010 NOTE 7: Data on S&P 500 (TR Total Return): Source: USDA, U.S. Bureau of Labor Statistics 29

30 Farmland Prices US corn belt farmland prices in real terms 6000 US$/Acre Given that there has not been any transformational change in the farms, why is there a baseline appreciation? % Source: USDA, U.S. Bureau of Labor Statistics 30

31 Farmland Prices Value Drivers Commodity price is not the value driver for farmland price appreciation Historically, farmland prices have consistently outperformed soybean prices Soybean prices & US corn belt farmland Prices in real terms (1992 = 100) Soybean Price US Corn Belt Value Source: Bloomberg, USDA 31

32 Farmland Prices Value Drivers The high correlation between soybean and fertilizers indicates that higher soybean prices does not reflect on higher cash flow per hectare and vice versa. SOYBEAN PRICE & FERTILIZERS PRICE US$/ ton cts/bu NPK (US$ / ton.) Soybeam price (cents / bushel) Source: Bloomberg, USDA 32

33 Farmland Investments The main driver pushing farmland prices upward is the increasing world grain area. Higher demand for grains Not enough growth in productivity New areas in production Combination of factors to make the new areas economically viable Productivity Producing cost Commodity price Higher cash flow to all agricultural area Higher farmland prices New production areas have higher producing cost in $ per ton Source: Bloomberg, USDA 33

34 Farmland Prices Value Drivers The main factor pushing farmland prices upward is the world production area increase. Given that new areas have higher production cost (USD / Ton), the expansion on the world agricultural area requires a combination of factor (price, cost, productivity) capable to generate a positive cash flow to this newly opened areas. This same combination of factors should increase the earnings and, therefore, the farmland prices for agricultural area as a whole. WORLD PRODUCTION AREA & CORN BELT FARMLAND PRICES (US) US$ per hectare World Production Area (Ha '000) Source: USDA, FAO 34

35 Higher Demand for Food Meat demand¹ is highly correlated with per capita GDP higher levels of income provides richer protein diets. MEAT PER CAPITA CONSUMPTION IN 2009 In kg / capita / year and US$ per capita / year y = 16,378ln(x) - 96,548 R² = 0, Source: FAO, USDA and BrasilAgro analysis ¹ I s worth notice that approximately: 1.3 and 5.4 kilogram of soybean and corn, respectively, are needed to produce 1 kg of beef; 0.7 and 2.5 kilogram of soybean and corn, respectively, are needed to produce 1 kg of pork; 0.6 and 1.1 kilogram of soybean and corn, respectively, are needed to produce 1 kg of poultry. 35

36 Higher Food Demand Food demand will remain rising as developing countries drive the world economic growth According to IMF projections, countries with GDP per capita of less than US$10,000 will be responsible for more than 51% of world GDP growth for the next 6 years; WORLD GDP GROWTH BREAKDOWN (In %) 46% 49% 78% 75% 54% 51% 22% 25% (E) Countries with GDP per capita < US$ Countries with GDP per capita > US$ Source: IMF 36

37 Productivity growth vs. Demand growth Productivity growth has not been enough to offset the increasing demand. This shortage is expected to increase within the next ten years. Production Growth (% p.y.) Productivity Gains (% p.y.) How this growth will occur? Total area growth (millions of ha) Land appreciation in real terms in the Corn Belt USA (% p.y.) From 1971 to ,14% 1,86% 40% 60% ,20% From 1981 to ,77% 1,84% -1% 101% ,05% From 1991 to ,76% 1,35% 22% 78% ,87% From 2001 to ,64% 1,40% 51% 49% ,68% From 2011 to ,61% 0,91% 46% 54% 52.0??? Source: FAO, USDA and BrasilAgro analysis NOTE 1: 2022 scenario is based on USDA projections Growth Area Productivity Gains 37

38 Productivity growth vs. Social development The increase in productivity made a huge social impact in the country. The higher the rural development level the lower the literacy and poverty rate. PRODUCTION vs. INPUTS (Index = 100) Production Inputs (labor force, land and capital) RURAL DEVELOPMENT INDEX Rural development level (IDR) Number of cities Rural resident population Literacy rate¹ Extreme rural poverty² Million % Average (%) Average (%) Low ,4 41,5% 74,2% 35,3% Regular ,5 28,4% 82,4% 17,5% Average ,0 16,7% 90,8% 4,9% High ,0 13,4% 93,1% 1,8% Total ,9 100,0% 85,1% 15,5% SOURCE: CNA, Gasques, J.G, E.T.; Valdez, C.; Bacchi, M.R. Produtividade da Agricultura brasileira e os efeitos de algumas políticas 1 Persons over ten years 2 Proportion of people in poverty conditions 38

39 Avenida Brigadeiro Faria Lima, o. Andar - CEP São Paulo - SP Brazil company/ (11) /BrasilAgroOficial ri@brasil-agro.com BRASILAGRO

40 Disclaimer - Forward Looking Statements This presentation may contain certain forward-looking statements and information relating to BrasilAgro Companhia Brasileira de Propriedades Agrícolas ( BrasilAgro or the Company ) that reflect the current views and/or expectations of the Company and its management with respect to its business plans. Forward-looking statements include, without limitation, any statement that may predict, forecast, indicate or imply future results, performance or achievements, and may contain words like believe, anticipate, expect, envisage, will likely result, or any other words or phrases of similar meaning. Such statements are subject to a number of significant risks, uncertainties and assumptions. We caution that a number of important factors could cause actual results to a differ materially from the plans, objectives, expectations, estimates and intentions expressed in this presentation. In any event, neither the Company nor any of its affiliates, directors, officers, agents or employees shall be liable before any third party (including investors) for any investment or business decision made or action taken in reliance on the information and statements contained in this presentation or for any consequential, special or similar damages. The Company does not intend to provide eventual holders of shares with any revised forward-looking statements of analysis of the differences between any forward-looking statements and actual results. This presentation ad its contents are proprietary information and may not be reproduced or otherwise disseminated in whole or in part without BrasilAgro s prior written consent. 40