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Vishal	
  Kumar	
  
	
  
This report is prepared for a priva...
  1
Table	
  of	
  Contents	
  
	
  
1 Executive Summary 3
2 Introduction and background
2.1 Overview of the market 4
2.2 ...
  2
List	
  of	
  Figures	
  and	
  Tables	
  
Figure 1 The main hurdles for providing art lending to the bank’s current c...
  3
1	
  Executive	
  summary	
  
Vishal Kumar created the following report in 2015 for his Masters of Art Business as par...
  4
2	
  Introduction	
  and	
  background	
  	
  
2.1 Overview of the market
The insurance broker, Robertson Taylor W&P L...
  5
	
  
Art & Finance Report 2014 73
78%
28%
39%
67%
78%
67%
78%
78%
60%
60%
63%
70%
77%
77%
83%
83%
56%
38%
46%
58%
78%
...
  6
3	
  Methodologies	
  
	
  
3.1 Literature review
A wide range of authors and disciplines were considered for the anal...
  7
4	
  Peter	
  Doig’s	
  Market	
  
4.1 Artist Specific Information
Peter Doig was born in Edinburgh (1959), lived in C...
  8
4.2 Object specific information
The Architect’s Home in the Ravine, oil on canvas (200 x 250cm), was painted in 1991.
...
  9
4.3 Artist Market Analysis
4.3.1 Primary market
Galleries: Four main primary galleries represent Peter Doig: Victoria ...
  10
3%#
33%#
64%#
Ins$tu$onal*Exhib$on*by*Share#
Peter#Doig#1995#1#2014#
Fes6val,#Biennials# Private#Galleries# Public#In...
  11
4.3.2. Secondary Market
Doig’s auction career started positively generating $205,901 in 1999, beating high
estimates ...
  12
$"0"
$"500"
$"1,000"
$"1,500"
$"2,000"
$"2,500"
$"3,000"
$"3,500"
$"4,000"
0"
10"
20"
30"
40"
50"
60"
70"
1999" 2000"...
  13
!"!!!!
!500!!
!1,000!!
!1,500!!
!2,000!!
!2,500!!
!3,000!!
!3,500!!
!4,000!!
1999!2000!2001!2002!2003!2004!2005!2006!...
  14
0"
10"
20"
30"
40"
50"
60"
70"
80"
90"
100"
$0"
$500"
$1,000"
$1,500"
$2,000"
$2,500"
$3,000"
$3,500"
$4,000"
2005" 2...
  15
5	
  Value	
  appraisals	
  
The value appraisal is constructed using both qualitative and quantitative rationale.
Fi...
  16
Figure12:PeterDoig’secosystem
Artists
Agents)&))
Promoters
MediaCultural)Intermediaries
Market)
Intermediaries
Enable...
  17
Since first coming to auction in 2002, The Architect’s Home has ridden the wave of Peter
Doig’s impressive trajectory...
  18
5.2 Quantitative – Value appraisal
The future value of artworks depends on their sales price at an undetermined yet
f...
  19
A simple linear equation in the form y=Bx+c was created for each index, so that a linear
price projection could be pl...
  20
!394,361!!
!17,013,962!!
!3,162,054!!
!10,550,784!!
!19,170,969!!
$0!
$2,000,000!
$4,000,000!
$6,000,000!
$8,000,000!...
  21
!394,361!!
!3,162,054!!
!10,550,784!!
!14,432,734!!
!19,501,543!!
!17,422,767!!
$0!
$2,000,000!
$4,000,000!
$6,000,00...
  22
6	
  	
   Risk	
  Appraisals
Banks holding art as collateral are concerned about fluctuations in the value, as negati...
  23
6.1.1 Data Index
However, when an index is created on the dataset for total sales (1999-2014), the ratio
jumps to 1.4...
  24
6.2 Art price risk
6.2.1 Description of Peter Doig’s Hammer Prices
The art price risk is estimated by the volatility ...
  25
0.000000000#
0.050000000#
0.100000000#
0.150000000#
0.200000000#
0.250000000#
0#
2#
4#
6#
8#
10#
12#
14#
16#
#*#####0...
  26
6.2.2 Description of Peter Doig’s Hammer Ratios
Hammer ratios shows how auction results compared with the auction hou...
  27
The correlation between hammer price and geometric mean is largely positive as the line
of best fit has a slope of 1....
  28
6.3.1 Value at Risk (VaR)
Assuming a 95% confidence level, what is the most amounts or percentage that can be
expecte...
  29
Dealer Location Country Works2on2sale
AW2Massey2Fine2Art Fort%Lauderdale USA 1
Coskun2Fine2Art Geneva Switzerland No....
  30
7	
  	
   Final	
  Recommendation	
  
It has been concluded that The Architect's Home in the Ravine can be considered...
  31
Bibliography	
  
AMA (2015) ‘Peter Doig at the Fondation Beyeler’, Art Media Agency. Available at:
http://en.artmedia...
  32
Pownall (2010). Art risk (Chapter 4) in McAndrew, C. (Ed.). (2010). Fine art and high finance: expert
advice on the e...
  33
E. Booth-Clibborn (ed.), The History of the Saatchi Gallery, London 2011 (illustrated in colour, p. 550).
R. Shiff an...
  34
Section 6
1. Moreover, Pownall (2010) expands this to artwork specific risks – volatility in Peter Doig’s hammer pric...
  35
Appendix	
  1
Please rotate left
Title1st(Sale2nd(Sale3rd(Sale
Hammer(Price(1!
(USD)
Hammer(Price(2!
(USD)
Hammer(Pri...
  36
Appendix	
  2
The Architects Home in the Ravine Repeat Sale Index
Forecast: Benchmark*(2002.2013*Forecast)
Equation: ...
  37
y"="70.286x"+"18424"
R²"="0.282"
"0""""
"2,000,000""
"4,000,000""
"6,000,000""
"8,000,000""
"10,000,000""
"12,000,000...
  38
CONTACT INFORMATION
Vishal Kumar
E: vishal.kumar@sia.edu | vishal.kumar.sia@gmail.com
W: https://uk.linkedin.com/in/v...
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Vishal Kumar - Art Secured Lending Due Dilligence Report Peter Doig.compressed (1)

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Vishal Kumar - Art Secured Lending Due Dilligence Report Peter Doig.compressed (1)

  1. 1.                           Vishal  Kumar     This report is prepared for a private bank to support its decision-making with regards to accepting The Architect’s Home in the Ravine by Peter Doig as collateral against a five- year fixed bullet loan. The report is aimed to produce a set of artist information and market analyses, as well as an assessment of potential risk factors for the individual artwork. Section 1 provides an executive summary. Section 2 provides an overview of the art- secured lending industry as a backdrop for the analysis. Section 3 provides an overview of the methodology in developing the market analysis and justification for the risk and value appraisal. Section 4 introduces the artist’s practice and provides an analysis of Peter Doig’s art market. Section 5 builds up arguments for value creation, with an application to Peter Doig’s art market. Section 6 analyses the potential market and artwork specific risk of Peter Doig’s paintings. Section 7 presents a final recommendation. Section notes can be found in the bibliography.   Art  Secured  Lending  Due  Diligence  report   Vishal Kumar © MA Art Business, Sotheby’s Institute of Art
  2. 2.   1 Table  of  Contents     1 Executive Summary 3 2 Introduction and background 2.1 Overview of the market 4 2.2 Evolution of the market 4 2.3 Key Characteristics 4 2.4 Challenges 4 3 Methodologies 6 3.1 Literature review 6 3.2 Data Collection 6 4 Peter Doig’s Market 7 4.1 Artist Specific Information 7 4.2 Object specific information 8 4.3 Artist Market Analysis 9 4.3.1 Primary market 9 4.3.2 Secondary Market 11 5 Value appraisals 15 5.1 Qualitative – Value appraisal 15-17 5.2 Quantitative – Value appraisal 18 5.2.1 Art Market Databases and Price Indices 18 5.2.2 Repeat Sales 19 5.2.3 Price projections 19 6 Risk Appraisals 22 6.1 Market risk 22 6.1.1 Data Index 23 6.1.2 Correlation with other markets 23 6.2 Art price risk 24 6.2.1 Description of Peter Doig’s Hammer Prices 24 6.2.2 Description of Peter Doig’s Hammer Ratios 26 6.3 Probability of collateral shortfall 27 6.3.1 Value at Risk (VaR) 28 6.4 Liquidity risk 28 6.5 Artwork-specific risk 28 7 Final Recommendations 30 Bibliography 31-32 Section Notes 32-24 Appendix 1 35 Appendix 2 36-37
  3. 3.   2 List  of  Figures  and  Tables   Figure 1 The main hurdles for providing art lending to the bank’s current clients 5 Figure 2 Confidence amongst financial services for art 5 Figure 3 ArtTactic’s Confidence Indicator for Peter Doig’s market, 2005 -2015 7 Figure 4 The Architect’s Home in the Ravine, 1991 8 Figure 5 Number of total shows by institution 10 Figure 6 Solo shows vs. group shows 10 Figure 7 Total sales volume between 1999 -2004 12 Figure 8 Average price and total sales volumes 12 Figure 9 Bought-In vs. Lots offered per year 13 Figure 10 Average hammer price per lot vs. average estimate per lot 13 Figure 11 Peter Doig’s average price vs. ArtTactic’s confidence indicator 14 Figure 12 Peter Doig’s ecosystem 16 Figure 13 Peter Doig’s art market trajectory 17 Figure 14 Peter Doig’s price trajectory until 2020 using Benchmark 1 and 2 indices 20 Figure 15 Price trajectory until 2020 using Artprice, Tutela and Data indices 21 Figure 16 Frequency distribution of Peter Doig’s log hammer prices 25 Figure 17 Frequency distribution of Peter Doig’s hammer prices 25 Figure 18 Frequency distribution of Peter Doig’s hammer ratios 26 Figure 19 Scatter plot between hammer prices and auction house mid-estimate 27 Figure 20 Scatter plot of hammer price against total size cm2 37 Table 1 Peter Doig’s highest number of show by institution 9 Table 2 Peter Doig’s Top 10 auction prices 13 Table 3 Total sales per auction house and location 14 Table 4 Price indices created using a linear growth rate 18 Table 5 Summary Statistics of the 19 repeat sales 19 Table 6 An Average price Index 22 Table 7 Price Index using collected data 23 Table 8 Summary Statistics of Peter Doig’s Hammer and Log Hammer Prices 24 Table 9 Summary statistics of Peter Doig’s hammer ratio 26 Table 10 Liquidity measure - Art dealers currently selling works by Peter Doig 29 Table 11 Endorsement measure – Peter Doig’s top 10 paintings on ArtStack 29 Table 12 19 repeated works at auction ranked by CAGR 35 Table 13 Benchmark (2002-2013) index with equation and growth forecasts 36 Table 14 Benchmark 2 (2007-2013) index with equation and growth forecasts 36 Table 15 Artprice Index with equation and growth forecasts 36 Table 16 Tutela Index with equation and growth forecasts 36 Table 17 Data Index with equation and growth forecasts 37    
  4. 4.   3 1  Executive  summary   Vishal Kumar created the following report in 2015 for his Masters of Art Business as part of the “Art Business, Finance and Management” module, Sotheby’s Institute of Art, London. Vishal is a graduate from the London School of Economics who is interested in the evolution of financial services within the business of fine art. The growing art secured lending and art insurance markets are forecasted to be the biggest in the Art and Finance industry, therefore, reliable artwork specific due diligence is required when considering art as a financial instrument. This research was initiated as a part of an assignment for my masters, however, given the current confusion surrounding the behaviour of art as a financial instrument, the need for thorough academic analysis inspired me to delve deeper into this topic. I aim to increase the understanding of art as collateral amongst the academic community by applying both quantitative and qualitative methodologies derived from various disciplines such as statistics, economics and sociology. This report aims to act as a barometer for future students and the emerging Art and Finance industry to highlight the main considerations when accepting art as collateral. In order to fulfil these expectations I have used The Architect’s Home in the Ravine (1991) by Peter Doig as a case study for my research. While every effort has been made to make my results as complete and accurate as possible, there is always room for improvement, and I welcome any feedback, comments or corrections from my readers. One of the key roles of the report is to suggest appropriate methodologies for deducing the present and future value of The Architect’s Home in the Ravine and the risks involved when holding the painting as collateral. The painting was last sold in February 2013 at Christie’s London for $10,550,784. Using a combination of online art market price indices and auction data collected for Peter Doig’s market, the financial value in 2015 is estimated to be $12,514,207 (all prices are given in USD). Therefore, at the industry standard LTV ratio of 50%, the bank could expect to issue a loan of $6,257,103. However, banks should not only consider the financial returns accrued by art, but also the “aesthetic dividend” and value created through the art market ecosystem. The Architect’s Home in the Ravine has both economic and cultural value, which in turn feeds into the price of the work. Given Peter Doig’s most recent solo show at the Foundation Beyeler and representation at the Venice Biennale in 2015, his cultural value as an artist has increased. Consequently, the borrower may expect a larger loan amount. The painting could truly be in the region of $13,000,000 to $15,000,000 if it were to reach the market in 2015. But, an accurately methodology has not been created to quantify the effect of such cultural milestones. When accepting an artwork as collateral, a bank is interested in the fluctuation of price or value of that artwork, and whether it can sell the painting on the market to recoup any loan shortfalls in the case of a default. Banks need to be able to correctly estimate and manage such downside risks. In order to assess Peter Doig’s market risk and hence price fluctuation, I used an array of traditional statistical risk measures. My results show that although there are concerns about market volatility from recent auction prices, there is a healthy ecosystem and endorsement process for the artist in the market to support liquidity concerns. Moreover, The Architect’s Home in the Ravine is regarded as one of Peter Doig’s best paintings and is therefore much likely to sell in the market should a default arise. I would like to express my most sincere thanks to my professors at the Sotheby’s Institute of Art in London, particularly Anders Petterson, Jeremy Eckstein and Anna Dempster. Moreover, academics such as Claire McAndrew, Orley Ashenfelter, Kathryn Grady and Rachel Pownall, are at the forefront of cultural economic research and have provided much scope for thought. I hope the findings of this report will stimulate interest and contribute to the on-going debate on how to evaluate art as a financial instrument.
  5. 5.   4 2  Introduction  and  background     2.1 Overview of the market The insurance broker, Robertson Taylor W&P Longreach, estimated today’s art lending market to be in the region of £6 billion per annum. Additionally, art insurance products could help expand the art secured lending market with the potential to reach £15-£20 billion per annum (Deloitte/ArtTactic, 2014). Therefore, the importance of effective artwork specific due diligence grows with the perceived growth in the art secured lending market. 2.2 Evolution of the market Camille Robb (2012) describes that the practice of using artwork as collateral dates back to the 16 th century for debts repayments, however, more recently it has been developed as a staple financing tool (Straus, 2008). Citibank was the first commercial bank to collateralize loans using artworks in 1979. Shortly thereafter, in the 1980s Sotheby’s began offering term loans and auction financing to both consignors and buyers, and Christie’s began offering art-lending services in early 1990s. 1986 is pivotal year in terms of academia as it identifies the first seminal art finance academic paper by William Baumol. While commercial auction houses pursued art financing within their companies, scholars, known as “cultural economists”, considered art as an investment to be a viable topic for empirical research. 2.3 Key Characteristics Financial institutions often view art as difficult to value or within too volatile a market place (McAndrew and Thomson, 2006). Moreover, the borrower must be credibly sound in their financial situation to receive consideration for an art-backed loan; the asset determines the loan amount, not the ability to receive the loan. Citibank makes loans of up to 50% of the value with a minimum value per work of $100,000 (McAndrew and Thomson, 2006: 604). Loans by private banks are typically on a full recourse basis, meaning the bank will seek to recover the balance under distressed conditions. 2.4 Challenges In the 2014 Deloitte and ArtTactic report, survey results found that liquidity and valuation remain the primary concern for private banks when considering lending against art (Figure 1). New tools created by technology-driven companies and online marketplaces will play an increasingly important role to elevate these concerns 1 (Deloitte/ArtTactic, 2014).
  6. 6.   5   Art & Finance Report 2014 73 78% 28% 39% 67% 78% 67% 78% 78% 60% 60% 63% 70% 77% 77% 83% 83% 56% 38% 46% 58% 78% 54% 81% 69% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Lack of knowledge about the art market Secure Storage Legal aspects Unregulated market Valuation – lack of mark-to-market valuation Due diligence Lack of liquidity Difficult to assess the risk 2014 2012 2011 value on works of art (78% said this was the main hurdle, against 77% in 2012). and the art market and art professionals, are starting to have an impact. Fig. 22 What do you feel is the main hurdle for providing art lending/art as collateral to the bank’s current clients? Source: Deloitte Luxembourg & ArtTactic Art & Finance Report 2014 Figure 1: What is the main hurdle for providing art lending to the bank’s current clients? A. Private bank and family office survey findings 1. Awareness Wealth managers are becoming increasingly aware of the development of art as an asset class: 53% of wealth managers (private banks and family offices) were aware/very aware of the developments linked to art as an asset class, up from 43% in 2012 and 33% in 2011, which suggests that increasing attention is being paid by the wealth management community to what is happening on the art market. 69% of the wealth managers said that their awareness has been heightened through increasing media interest (against 53% in 2012), and 60% said they had been exposed to the topic through conferences and seminars (against 57% in 2012). Is there an argument for including art and collectibles in traditional wealth management? 57% of the family offices and 53% of the private banks surveyed believe there is a strong case for including art and collectibles in traditional wealth management, while 76% of art professionals and 62% of collectors believe that private wealth managers should incorporate art and collectibles into their service offering. This highlights the need and client demand, but also raises questions about the type of services that should be offered, and how. 2. Focus in 2015: the wealth industry is likely to focus more on art and wealth planning services in the next 12 months With the global art market reaching US$65 billion53 in 2013, up 8% versus 2012, it is clear that art and collectibles have become an increasingly important part of the UHNWI’s overall asset portfolio. The findings of this section indicate that the wealth management industry is taking a more strategic view on art as asset class and how it could be used as a strategic tool to build stronger and deeper relationships with clients, by focusing on both the financial aspects of art as well as the emotional and social characteristics associated with this asset class. Collectors a. investment purpose 76%21%3% 22% 13% 40% 28% 23% 12% 40% 23% 42% 33% 30% 33% 33% 70% 67% 43% 42% 31% 24% 39% 0% 10% 20% 30% 40% 50% 60% 70% 80% 2011 2012 2014 Art Secured Lending Art Investment Funds Art & Philanthropy Art Advisory Estate Planning Art Entertainment Art & Finance Confidence Indicator Fig. 17 Confidence—which services will you focus on in the next 12 months? Source: Deloitte Luxembourg & ArtTactic Art & Finance Report 2014 managers, art professionals and collectors Figure 2: Confidence amongst financial services for art
  7. 7.   6 3  Methodologies     3.1 Literature review A wide range of authors and disciplines were considered for the analysis. The key message conveyed by the literature is to not only consider the financial returns accrued by art, but also the “aesthetic dividend” (Pownall, 2014) and value created through the art market ecosystem (Petterson, 2014). 3.2 Data Collection The data set for Peter Doig’s paintings between 1999 and 2014 was complied using auction data from artnet and ArtFacts. There exists no data for auction sales prior to 1999. The data set consists of 185 attempted auction sales from a cohort of 6 auction houses. The presale auction estimates were not given for two transactions: Pine House (Rooms for Rent), which sold for $16,073,661 at Christie’s New York, on 12/11/2014; and, Country Rock (Wing Mirror), which sold for $12,879,411 at Sotheby’s London on 30/06/2014. All sales are given in hammer price; where only premium price was recorded, the values were converted to hammer by using published buyers’ premiums from Christie’s, Sotheby’s, and Phillips. Changes in the buyers’ premium over time are taken into account.
  8. 8.   7 4  Peter  Doig’s  Market   4.1 Artist Specific Information Peter Doig was born in Edinburgh (1959), lived in Canada (1966) and currently lives in Trinidad. Doig studied at the Wimbledon School of Art (Foundation, 1979), St. Martins School of Art from (BA, 1980-83), and Chelsea School of Art and Design (MA, 1990). Doig made his first forays into a brash kind of figurative painting, with cartoon-like storyboards. A deeper discussion of the artist’s background takes place in section 5. Peter Doig appeared in the top 5 artists (US and Europe) in ArtTactic’s short-term confidence indicator in September 2014, however, not in January 2015. He has had a high confidence indicator over the last ten years, with an average of 74.6, and regularly makes the top 20. ArtTactic’s confidence indicators are created from surveys results of leading art market players and their sentiments and confidence towards various sectors and artists of the art market. 0" 10" 20" 30" 40" 50" 60" 70" 80" 90" 100" May/05" Sep/05" Jan/06" May/06" Sep/06" Jan/07" May/07" Sep/07" Jan/08" May/08" Sep/08" Jan/09" May/09" Sep/09" Jan/10" May/10" Sep/10" Jan/11" May/11" Sep/11" Jan/12" May/12" Sep/12" Jan/13" May/13" Sep/13" Jan/14" May/14" Sep/14" Jan/15" May/15" Confidence(Indicator( ArtTac0c(Confidence(Indicator(for(Peter(Doig( ArtTac:c"Confidence"Indicator" Figure 3: ArtTactic’s Confidence Indicator for Peter Doig’s market, 2005 -2015
  9. 9.   8 4.2 Object specific information The Architect’s Home in the Ravine, oil on canvas (200 x 250cm), was painted in 1991. The painting recreates Canadian architect, Eberhard Zeidler's modernist home in Rosedale, Toronto ravine 2 . It was created shortly after Doig's was awarded the prestigious Whitechapel Artist Prize (1991). This was a major institutional solo show at such a formative stage in his career. This painting was also shown at the Gesellschaft für Aktuelle Kunst, in Bremen (1996) and the Saatchi Gallery in London (2005) 3 . Many of his works from the early 1990s are at international museum collections including: the Tel Aviv Museum of Art, the San Francisco Museum of Modern Art, and the Tate Modern, London. The painting first sold at Sotheby’s London for $394,361 (June 2002). It then resold at Sotheby’s New York for $3,162,054 (May 2007); a compounded annualised growth rate (CAGR) of 51.64% and an increase in value of 702% (without inflation). It sold for the third time at Christie’s London for $10,550,784 (February 2013); a CAGR of 22.2% with an increase in value of 234% (without inflation) 4 . Figure 4: The Architect’s Home in the Ravine, 1991
  10. 10.   9 4.3 Artist Market Analysis 4.3.1 Primary market Galleries: Four main primary galleries represent Peter Doig: Victoria Miro Gallery (London), Michael Werner Gallery (London and New York), Galerie Boisseree (Köln), and Gavin Brown Enterprises (New York). Exhibitions: Doig exhibited a total of 232 shows between 1995 and 2014, where 64% of were in public institutions, 33% in private galleries, 83% were group shows and 17% were solo. The most shows were in 2006 since then that figure has almost halved (Figure 6) Curators and writers: Stephen Deuchar, Director of the Art Fund and ex-director of the Tate Britain, has described Doig as “one of the most important painters of his generation at work anywhere in the world” (Nesbitt, 2008). Curators such as Matthew Higgs, Wolfgang Kos and Gareth Jones have supported him. Richard Shiff has written a book about Peter Doig and also number of articles. Through out his career, Doig has seen extremely positive media support. Table 1: Peter Doig’s highest number of show by institution Institution Number-of-Shows Victoria(Miro(Gallery 9 Michael(Werner(Gallery(2(New(York 8 Galerie(Boisserée 6 Contemporary(Fine(Arts(2(CFA 5 Kunsthalle(zu(Kiel 5 Source:(ArtFacts
  11. 11.   10 3%# 33%# 64%# Ins$tu$onal*Exhib$on*by*Share# Peter#Doig#1995#1#2014# Fes6val,#Biennials# Private#Galleries# Public#Ins6tu6ons# 17%$ 83%$ Solo$and$Group$Exhibi1ons$by$Share$ Peter$Doig$1995$1$2014$ Solo$Shows$ Group$Shows$ 0" 5" 10" 15" 20" 25" 30" 1995" 1996" 1997" 1998" 1999" 2000" 2001" 2002" 2003" 2004" 2005" 2006" 2007" 2008" 2009" 2010" 2011" 2012" 2013" 2014" Number' Number'of'shows'by'Ins0tu0on' Peter"Doig"1995"4"2014" Public"Ins<tu<ons" Private"Galleries" Fes<val,"Biennials" 0" 5" 10" 15" 20" 25" 30" 1995"1996"1997"1998"1999"2000"2001"2002"2003"2004"2005"2006"2007"2008"2009"2010"2011"2012"2013"2014" Solo$vs.$Group$Exhibi1ons$ Peter"Doig"1995"4"2014" Group"Shows" Solo"Shows" Figure 5: Number of total shows by institution, Source: ArtFacts Figure 6: Solo shows vs. group shows, Source: ArtFacts
  12. 12.   11 4.3.2. Secondary Market Doig’s auction career started positively generating $205,901 in 1999, beating high estimates by 132%. After a number of internationally recognised group shows 5 Doig’s auction market took a dramatic turn. 2006 and 2007 generated $7.5 million and $27.9 million in sales respectively. 2012 was a poor year, only $1.2 million was generated, this followed after Doig exhibited no solo shows in 2010 and 2011; the bought-in rate during those years was 32% and 50% respectively (Figure 9). More recently, Doig’s auction market has comfortably exceeded the pre-sale high estimates. In 2013 total sales equalled $29 million beating the high estimates by 15%. In 2014 total sales volume shot to $66 million; however, after taking away Pine House and Country Rock, total sales for 2014 equalled $37.2 million and still beating high estimates by 8% (Figure 7 & 8). The total volume of auction sales over the 15-year period generated $191,282,183, with a CAGR of 46.94%. There was a bought-in ratio of 17.8% 6 . The average hammer has consistently out performed the average estimated price (Figure 10), however, there could be some risk associated with this result. Table 2 shows the top 10 prices achieved at auction generated a total of $109,468,779, which is a 57% share of total auction sales. It can be seen that Peter Doig’s early 1990s paintings generated the most.
  13. 13.   12 $"0" $"500" $"1,000" $"1,500" $"2,000" $"2,500" $"3,000" $"3,500" $"4,000" 0" 10" 20" 30" 40" 50" 60" 70" 1999" 2000" 2001" 2002" 2003" 2004" 2005" 2006" 2007" 2008" 2009" 2010" 2011" 2012" 2013" 2014" Thousands) Millions)(USD)) Peter)Doig:)Average)price)and)auc<on)sale)(pain<ngs)only)) Total"Peter"Doig"Sales"1990";2014" Sales"Volume" Total"Sales"+"Pine"House"&"Country"Rock" Average"Hammer"Price" !"!!!! !5!! !10!! !15!! !20!! !25!! !30!! !35!! !40!! 1999! 2000! 2001! 2002! 2003! 2004! 2005! 2006! 2007! 2008! 2009! 2010! 2011! 2012! 2013! 2014! Millions'(USD)' Annual'Sales'Volume'&'Pre6Sale'Es8mates' Total!Peter!Doig!Sales!1999"2014! Sales!Volume! Total!High!Es@mates! Total!High!Es@mates! Figure 8: Average price and total sales volumes including Pine House and Country Rock Figure 7: Total sales volume between 1999 -2004
  14. 14.   13 !"!!!! !500!! !1,000!! !1,500!! !2,000!! !2,500!! !3,000!! !3,500!! !4,000!! 1999!2000!2001!2002!2003!2004!2005!2006!2007!2008!2009!2010!2011!2012!2013!2014! Thousands)(USD)) Average)Sale)Price)&)Pre9Sale)Es;mates) Total!Peter!Doig!Sales!1999"2014! Average!Hammer!Price! Average!Pre"Sale!EsAmate! 0" 5" 10" 15" 20" 25" 30" 35" 1999"2000"2001"2002"2003"2004"2005"2006"2007"2008"2009"2010"2011"2012"2013"2014" Number' Annual'Offered'Lots'vs.'Bought'In'Lots' Total"Peter"Doig"Sales"199992014" Lots"Offered" Bought"In"Lots" Figure 9: Bought-In vs. Lots offered per year Figure 10: Average hammer price per lot vs. average estimate per lot Rank Title Year Series Hammer0Price Auction0house0 Location Date0Sold 1 Pine&House&(Rooms&for&Rent) 1994 Early&1990s 16,073,661$&&&&&&&& Christie's New&York 12/11/2014 2 Gasthof 2003 2000s 15,139,198$&&&&&&&& Christie's London 01/07/2014 3 Country&Rock&(Wing&Mirror) 1999 Late&1990s 12,879,411$&&&&&&&& Sotheby's London 30/06/2014 4 Road&House 1991 Early&1990s 10,573,661$&&&&&&&& Christie's New&York 12/05/2014 5 The&Architect's&Home&in&the&Ravine 1991 Early&1990s 10,550,784$&&&&&&&& Christie's London 13/02/2013 6 Jetty 1994 Early&1990s 10,031,543$&&&&&&&& Christie's London 25/06/2013 7 White&canoe 1990 Early&1990s 9,957,420$&&&&&&&&&& Sotheby's London 07/02/2007 8 Reflection 1996 Late&1990s 9,000,000$&&&&&&&&&& Christie's New&York 10/11/2009 9 Red&Boat 2003 2000s 8,793,780$&&&&&&&&&& Christie's London 28/06/2011 10 The&Heard&of&Old&San&Juan 1999 Late&1990s 6,469,321$&&&&&&&&&& Christie's London 16/10/2014 Table 2: Peter Doig’s Top 10 auction prices
  15. 15.   14 0" 10" 20" 30" 40" 50" 60" 70" 80" 90" 100" $0" $500" $1,000" $1,500" $2,000" $2,500" $3,000" $3,500" $4,000" 2005" 2006" 2007" 2008" 2009" 2010" 2011" 2012" 2013" 2014" Confidence(Indicator( Thousands( Peter(Doig:(Average(price(and(Confidence(Indicator( Average"Hammer"Price" ArtTac;c"Confidence"Indicator"(Annual)" Figure 11: Peter Doig’s average price vs. ArtTactic’s confidence indicator Table 3: Total sales per auction house and location, and paintings by series. Doig’s Early 1990s works generate the most sales and number of lots Auction(House Total(Sales(USD %(of(Total No(of(Lots Christie's 126,009,2080000000000000000000000000 66% 82 Sotheby's 63,326,463000000000000000000000000000 33% 85 Phillips 1,449,22900000000000000000000000000000 1% 11 Bonhams 348,27600000000000000000000000000000000 0% 1 Piasa 63,1130000000000000000000000000000000000 0% 3 Villa0Grisebach 85,8940000000000000000000000000000000000 0% 2 Location Total(Sales((USD) %(of(Total No(of(Lots London 138,531,2650000000000000000000000000 72% 128 New0York 52,439,106000000000000000000000000000 27% 49 Other 311,81100000000000000000000000000000000 0% 5 Painting(by(Series Total(Sales(USD %(of(Total No(of(Lots 1980s 1,058,27200000000000000000000000000000 1% 14 Early01990s 110,527,6620000000000000000000000000 58% 85 Late01990s 43,353,249000000000000000000000000000 23% 56 2000s 36,343,000000000000000000000000000000 19% 29 182
  16. 16.   15 5  Value  appraisals   The value appraisal is constructed using both qualitative and quantitative rationale. Findlay (2012) discusses the role of the primary market in providing direct payment to the artist for his or her skill and time, plus the cost of bringing the product to the market. 5.1 Qualitative – Value appraisal Theory from Petterson (2014) is applied to plot Peter Doig’s art market ecosystem and to discuss value construction. The role of tastemakers in the eco-system and the endorsement process are extremely important when discussing value in the art market. Petterson (2014) suggests that we cannot simply say that value (or price) of art is a matter of demand and supply, inferring that the discipline of economics cannot solely explain value. Although demand and supply will have direct impacts, this tells us very little about how the demand was created in the first place 1 . Petterson (2014) uses the ecosystem analogy because it takes a multidisciplinary approach to value creation 2 . The various players and tastemakers 3 in Peter Doig’s art market are mapped out in Figure 12. Currently, the Michael Werner Gallery is the largest promoter in the primary market, offering 22 works for sale (Table 9). The Foundation Beyeler are the largest tastemakers, due to their current retrospective until March 22, 2015. Christie’s and Sotheby’s remain the most dominant players in the auction market. To display the perceived current and future success of Peter Doig’s art market, a trajectory of the artist’s evolution is created 4 (Figure 13). Doig was awarded three important painting prizes during his formation stage. Theses successes aided his expansion phase by becoming represented by Victoria Miro (1994) and Gavin Brown (1996). Influential “promoters” helped Doig get international exposure, subsequently increasing his cultural and economic value. After his auction debut (1999), Doig gained further validation and endorsement through major international cultural intermediaries, such as the Pinakethek de Morden in Munich (2004) and the Tate Britain (2008). Doig’s strong museum and auction activity has generally remained extremely prosperous and consistent since 2007.
  17. 17.   16 Figure12:PeterDoig’secosystem Artists Agents)&)) Promoters MediaCultural)Intermediaries Market) Intermediaries Enablers)and) Support)Services Consumers Art) historians/Curators The$Art$ Newspaper The$Saatchi$Gallery**Sotheby's*Saatchi$OnlineRichard$Shiff** Michael$Werner$ Gallery* FTMoMa,$New$York Gavin$Brown$ Enterprises,$NY Artprice Foundation$ Beyeler,$ Switzerland** Ulf$Kuster LACMA,$LAArtFacts Centre$PompidouTutela Pinakothek$der$Modern,$ Munich** Paddle8artnet Whitechapel$Gallery**ArtsyArtsy A*isgiventoanimportantplayerinthemarketanda**isgiventoanimportanttastemakerforPeterDoig'secosystem Peter$Doig San$Francisco$ Museum$of$ Modern$Art Tel$Aviv$Museum artnet$newsTate$Britain** ArtStackGavin$Brown Gallerie$Boisseree Victoria$Miro* New$York$Times Kelly$Taylor Wolfgang$Kos Mathew$HiggsTATE.orgChristie's* Frieze Arthur$Andersen$&$ Co Please rotate left
  18. 18.   17 Since first coming to auction in 2002, The Architect’s Home has ridden the wave of Peter Doig’s impressive trajectory path. As it is regarded as one of his most important paintings (Nesbitt, 2008: 37), the value creation effect is subsequently multiplied, hence an average return of 468% between 2002 and 2013. Solo show Foundation Beyeler (2015) Acquisitions by private collectors- Gavin Brown’s Enterprise, New York (1996) Wimbledon School of Art (1979), BA, St. Martins School of Art (1980-83) New Contemporaries, ICA, London (1982-83) The Naked City, Air Gallery, London (1986) Barclays Young Artist Award, Serpentine Gallery (1991), Whitechapel Artist Award (1991) Awarded John Moores Painting Prize, Liverpool (1993) Curator/local interests – Gareth Jones (1992), Matthew Higgs (1994), Wolfgang Kos (1997) MA, Chelsea College of Art and Design (1990) Turner Prize Exhibition, London (1994) Victoria Miro Gallery, London (1994) Centre Albert Borschette, Brussels (1992) Auction market begins (1999) Pinakothek der Modern, Munich (2004) International - Museum of Contemporary Art, Chicago (1999) Contemporary Fine Arts, Berlin (2009) Tate Britain, London (2008) Strong and consistent auction and museum activity High High Low Low CulturalValue Economic Value Peter Doig Trajectory Path 1.#Forma)on#Phase# 2.#Expansion#Phase# 3.#Consolida)on#Phase# Figure 13: Peter Doig’s art market trajectory
  19. 19.   18 5.2 Quantitative – Value appraisal The future value of artworks depends on their sales price at an undetermined yet forthcoming point in time and cannot be accurately predicted. Theory from Pownall (2010) is considered when measuring market value and price. The author discusses that financial return can be measured from art indices that use average price increases, repeat sales or hedonic price indices 5 . Numerous academic studies have indeed used quantitative methods to model financial returns and the determinant of price 6 , however, econometric modelling was not undertaken 7 . Rather, this report looks at linear price progression and CAGR. Greater certainty about the true value of The Architect’s Home in the Ravine can be analysed due to the emergence of art support services, databases and indices. The new online contemporary art ecosystem provides more reliable tools, transparency in prices, education and endorsement. 5.2.1 Art Market Databases and Price Indices In order to measure the possible present and future value, several price indices and forecast equations were calculated. An annualised price index was constructed from the data collected with base 100 in 2005. Two further annualised indices were created using data from Artprice.com and Tutela Capital. Data from both was available online, however, the Artprice index was annualised but the Tutela index was monthly. Moreover, both these indices contain all categories of artwork, not just paintings. Year Data'Index Artprice'Index Tutela'Index 2005 100 100%%%%%%%%%%%%%%%% 100 2006 417 83%%%%%%%%%%%%%%%%%% 107 2007 1555 161%%%%%%%%%%%%%%%% 114 2008 582 126%%%%%%%%%%%%%%%% 122 2009 1258 131%%%%%%%%%%%%%%%% 130 2010 614 187%%%%%%%%%%%%%%%% 139 2011 580 188%%%%%%%%%%%%%%%% 149 2012 69 93%%%%%%%%%%%%%%%%%% 159 2013 1619 259%%%%%%%%%%%%%%%% 170 2014 3681 360%%%%%%%%%%%%%%%% 182 Return 3681% 360.0% 182.00% y=Bx+c B 397.91 28.89 9.07 c 100 100 100 CAGR 49.3% 15.3% 6.9% Table 4: Price indices created using a linear growth rate, the start and end figures of the original indices were used to construct an average growth rate
  20. 20.   19 A simple linear equation in the form y=Bx+c was created for each index, so that a linear price projection could be plotted. Table 4, 14, 15 and 16 shows the three price indices created. 5.2.2 Repeat Sales 19 works in the dataset were repeat sales, 10 works sold twice and 9 works sold thrice. The Architect’s Home had sold three times at auction, therefore 2 indices and linear equations were made. These two indices act as a proxy benchmark for future price projections, based on previous linear growth rates 8 . Table 11 in Appendix 1 ranks the 19 works by the highest CAGR between sale periods. The Architect’s Home produced a 34.8% CAGR. The mean average return per lot was 476% 9 . 5.2.3 Price projections Possible future prices for The Architect’s Home were projected using 5 linear growth rates (Tables 12 - 16). Figure 14 shows that if price were to increase at the same rate as 2002 to 2013 (Benchmark), then present price would be $12,397,404 and $17,013,962 in 2020. If price increased at the same rate as 2007 to 2013 (Benchmark 2), present price would be $13,013,694 and $19,170,969 in 2020. Looking at figure 15, if prices increased at Artprice’s index, then present price would be $12,391,882 and $16,994,626 in 2020. If prices increased at Tutela’s Index then present price would be $ 11,659,913 and $ 14,432,734 in 2020; this is the most conservative index. The most ambitious linear price projection comes from the index created from Peter Doig’s auction data - present price would be $ 13,108,144 and $ 19,501,543 in 2020. By taking an average of all the indices, today’s average price would be $12,514,208 and $17,422,767 in 2020. Summary'Statistics'for'Repeat'Sales:'Peter'Doig'auction'market'1999':'2014 Total&number&of&works 182 Number&of&works&sold 152 Number&of&repeat&sales 19 Number&of&works&sold&twice 10 Number&of&works&sold&thrice 9 Mean%Average%Return%per%lot 476.01% Mean&CAGR&per&lot 29.03% Table 5: Summary Statistics of the 19 repeat sales
  21. 21.   20 !394,361!! !17,013,962!! !3,162,054!! !10,550,784!! !19,170,969!! $0! $2,000,000! $4,000,000! $6,000,000! $8,000,000! $10,000,000! $12,000,000! $14,000,000! $16,000,000! $18,000,000! $20,000,000! 2002! 2003! 2004! 2005! 2006! 2007! 2008! 2009! 2010! 2011! 2012! 2013! 2014! 2015! 2016! 2017! 2018! 2019! 2020! Price& Year& The$Architects$Home$in$the$Ravine:&& Repeat&Sale&Benchmark&Price&Projec5on& CAGR!2002!2!2013! CAGR!2007!2!2013! CAGR!2002!2!2007! Benchmark! Benchmark!2! Figure 14: Peter Doig’s price trajectory until 2020, using Benchmark growth rate between 2002 = 2013, and Benchmark 2 growth rate between 2007 - 2013
  22. 22.   21 !394,361!! !3,162,054!! !10,550,784!! !14,432,734!! !19,501,543!! !17,422,767!! $0! $2,000,000! $4,000,000! $6,000,000! $8,000,000! $10,000,000! $12,000,000! $14,000,000! $16,000,000! $18,000,000! $20,000,000! 2002! 2003! 2004! 2005! 2006! 2007! 2008! 2009! 2010! 2011! 2012! 2013! 2014! 2015! 2016! 2017! 2018! 2019! 2020! Price! Year! The$Architects$Home$in$the$Ravine:!! Complete!Linear!Price!Projec8on! CAGR!2002!2!2013! CAGR!2007!2!2013! CAGR!2002!2!2007! Benchmark! Benchmark!2! Artprice! ProjecBon! Tutela!ProjecBon! Data!Index! ProjecBon! Figure 15: Peter Doig’s price trajectory until 2020, using Artprice, Tutela and Data Index growth rates and then an Average of all 5. Tables can be found in Appendix
  23. 23.   22 6     Risk  Appraisals Banks holding art as collateral are concerned about fluctuations in the value, as negative changes in art prices are a market risks that banks need to correctly estimate and manage 1 . 6.1 Market risk An estimate of the market price risk can be made by first estimating an index of overall price changes over that period of time and then assessing how widely dispersed these prices are (Pownall, 2010). As calculated in section 5, the return of the Average Index (over all 5 indices) is given by the equation: y = 16.044x + 100, with a base year in 2005 (Figure). The standard deviation to mean ratio is 0.46. Average'Index'and'Equation Forecast: Average'Index'and'Forecast Equation: y=#16.044x+100 x Year Index'(y) Price 0 2005 100 3,117,260'''''''' 1 2006 116 3,617,396'''''''' 2 2007 148 4,599,108'''''''' 3 2008 179 5,580,820'''''''' 4 2009 211 6,562,532'''''''' 5 2010 242 7,544,244'''''''' 6 2011 274 8,525,955'''''''' 7 2012 305 9,507,667'''''''' 8 2013 338 10,550,784'''''' 9 2014 370 11,532,495'''''' 10 2015 401 12,514,207'''''' 11 2016 433 13,495,919'''''' 12 2017 464 14,477,631'''''' 13 2018 496 15,459,343'''''' 14 2019 527 16,441,054'''''' 15 2020 559 17,422,766'''''' Mean 323 Standard'Deviation 149.24 Table 6: An Average Index and linear equation was plotted by taking the average of all 5 indices
  24. 24.   23 6.1.1 Data Index However, when an index is created on the dataset for total sales (1999-2014), the ratio jumps to 1.4701. This show that the true risk associated with Peter Doig’s painting market is much larger. 6.1.2 Correlation with other markets Banks will also want to assess Peter Doig’s market risk relative to other assets classes and other artists. This can be assessed by the beta of Peter Doig’s market in relation to a chosen base. Relative risk was not measured within the scope of this report, because data for other artist’s and markets was not collected, however, this is leaves room for further research. Peter%Doig%Total%Sales%(199922014)%Index Year Total)Sales)(USD) Index 1999 205,901))))))))))))))) 100.0 2000 300,921))))))))))))))) 146.1 2001 215,004))))))))))))))) 104.4 2002 971,616))))))))))))))) 471.9 2003 1,198,736)))))))))))) 582.2 2004 118,667))))))))))))))) 57.6 2005 1,797,358)))))))))))) 872.9 2006 7,498,757)))))))))))) 3641.9 2007 27,946,550)))))))))) 13572.8 2008 10,456,415)))))))))) 5078.4 2009 22,618,587)))))))))) 10985.2 2010 11,032,263)))))))))) 5358.0 2011 10,426,757)))))))))) 5064.0 2012 1,233,186)))))))))))) 598.9 2013 29,096,481)))))))))) 14131.3 2014 66,164,984)))))))))) 32134.4 Mean 5806.3 Standard)Deviation 8535.965 Table 7: Index created on Peter Doig’s total sales per year using the auction data collected
  25. 25.   24 6.2 Art price risk 6.2.1 Description of Peter Doig’s Hammer Prices The art price risk is estimated by the volatility of Peter Doig’s hammer prices over time. The mean price was $1,258,435 and the standard deviation was $2,823,240. The ratio of standard deviation to mean was 2.24, compared with 1.40 for Alexander Calder and 1.23 for Damien Hirst 2 . Therefore, this shows that Peter Doig’s hammer prices were comparatively more volatile and widely distributed; shown by a high kurtosis number of 11.827 3 . The positive skewness at 3.411 of hammer price stands out in table 7; this is graphically depicted in figure 17. 32% of lots fell into the $100,000 category, and 67.10% were below the $400,000. A transformation by taking the natural log was applied 4 , this gives the properties of a normal distribution as depicted in figure 16. Table 7 now shows that the skewness of the log hammer price is at 0.359. 92.11% and 94.08% of lots respectively, fell within one and two standard deviations away from the mean. However, once the natural log was applied, only 67.7% and 92.76% of lots respectively, fell within one and two standard deviations away from the log mean. Although the S.D. to mean ratio is 2.23, 92% of lots were within a relatively safe range. Hammer&Price Log&of&Hammer&Price Total&Lots 185 182 Lots&Sold 152 152 Buy7In 18% 18% Mean 1,258,435))))))))))))))))))) 12.47 Median 188,963)))))))))))))))))))))) 12.15 Max& 16,073,661))))))))))))))))) 16.59 Min 6380 8.76 Std.&Deviation 2,823,240))))))))))))))))))) 1.77 Skewness 3.411 0.359 Kurtosis 11.827 /0.270 Distribution&of&Lots Number&of&lots %&of&Total&Sold 1)S.D.)away)from)mean) Hammer)Price 2)S.D.)away)from)mean) Hammer)Price 140 143 92.11% 94.08% Table 8: Summary Statistics of Peter Doig’s Hammer and Log Hammer Prices
  26. 26.   25 0.000000000# 0.050000000# 0.100000000# 0.150000000# 0.200000000# 0.250000000# 0# 2# 4# 6# 8# 10# 12# 14# 16# #*#####0.60###1.20###1.80###2.40###3.00###3.60###4.20###4.80###5.40###6.00###6.60###7.20###7.80###8.40###9.00###9.60###10.20###10.80###11.40###12.00###12.60###13.20###13.80###14.40###15.00###15.60###16.20###16.80###17.40###18.00###18.60###19.20###19.80## Log$Hammer$Prices$ Normal$Distribu4on$ Number$of$lots$ Histogram$of$Peter$Doig$Auc4on$Log$Hammer$Prices$(USD)$ Total#Peter#Doig#Sales#1999*2014# Frequency#Log#prices# Normal#DistribuFon# 0.000000000# 0.000000020# 0.000000040# 0.000000060# 0.000000080# 0.000000100# 0.000000120# 0.000000140# 0.000000160# 0# 10# 20# 30# 40# 50# 60# #+#### #200,000## #400,000## #600,000## #800,000## #1,000,000## #1,200,000## #1,400,000## #1,600,000## #1,800,000## #2,000,000## #2,200,000## #2,400,000## #2,600,000## #2,800,000## #3,000,000## #3,200,000## #3,400,000## #3,600,000## #3,800,000## #4,000,000## #4,200,000## #4,400,000## #4,600,000## #4,800,000## #5,000,000## #5,200,000## #5,400,000## #5,600,000## #5,800,000## #6,000,000## #6,200,000## #6,400,000## #6,600,000## #6,800,000## #7,000,000## #7,200,000## #7,400,000## #7,600,000## #7,800,000## #8,000,000## #8,200,000## #8,400,000## #8,600,000## #8,800,000## #9,000,000## #9,200,000## #9,400,000## #9,600,000## #9,800,000## #10,000,000## #10,200,000## #10,400,000## #10,600,000## #10,800,000## #11,000,000## #11,200,000## #11,400,000## #11,600,000## #11,800,000## #12,000,000## #12,200,000## #12,400,000## #12,600,000## #12,800,000## #13,000,000## #13,200,000## #13,400,000## #13,600,000## #13,800,000## #14,000,000## #14,200,000## #14,400,000## #14,600,000## #14,800,000## #15,000,000## #15,200,000## #15,400,000## #15,600,000## #15,800,000## #16,000,000## #16,200,000## #16,400,000## #16,600,000## #16,800,000## #17,000,000## Normal'Distribu.on' Number'of'Lots' Hammer'Prices'(USD)' Histogram'of'Peter'Doig'Auc.on'Hmmer'Prices'(USD)' Total#Peter#Doig#Sales#1999#+2014# Frequency#Prices# Normal#DistribuEon# Figure 16: Frequency distribution of Peter Doig’s log hammer prices Figure 17: Frequency distribution of Peter Doig’s hammer prices
  27. 27.   26 6.2.2 Description of Peter Doig’s Hammer Ratios Hammer ratios shows how auction results compared with the auction houses’ expert estimation. The mean hammer ratio was 1.45, with a median of 1.20, and minimum and maximum of 0.4 and 9.28 respectively. The standard deviation was 1.03. On average therefore, hammer prices out performed the average estimate. As shown by Figure 18, the distribution of hammer ratios is not symmetrical but positively skewed to the right at 4.169. 15% of lots had a ratio of 0.9, and 36% had ratios below 1. Therefore, a large majority of lots performed better than auction estimates. The Architect’s Home had an average hammer ratio of 1.83 over all three sales. Hammer&Ratio Total&Lots 185 Lots&Sold 152 Buy4In 18% Mean 1.45(((((((((((((((((((((( Median 1.20(((((((((((((((((((((( Max& 9.28(((((((((((((((((((((( Min 0.4 Std.&Deviation 1.03(((((((((((((((((((((( Skewness 4.168 Kurtosis 25.362 Table 9: Summary statistics of Peter Doig’s hammer ratios 0.000# 0.050# 0.100# 0.150# 0.200# 0.250# 0.300# 0.350# 0.400# 0.450# 0# 5# 10# 15# 20# 25# 0.00# 0.30# 0.60# 0.90# 1.20# 1.50# 1.80# 2.10# 2.40# 2.70# 3.00# 3.30# 3.60# 3.90# 4.20# 4.50# 4.80# 5.10# 5.40# 5.70# 6.00# 6.30# 6.60# 6.90# 7.20# 7.50# 7.80# 8.10# 8.40# 8.70# 9.00# 9.30# 9.60# 9.90# Normal'Distributuion' Number'of'Lots' Histogram'of'Peter'Doig'Hammer'Ra6o' Total#Peter#Doig#Sales#1999#:#2014# Frequency#Hammer#RaDo# Normal#DistribuDon# Figure 18: Frequency distribution of Peter Doig’s Hammer Ratios
  28. 28.   27 The correlation between hammer price and geometric mean is largely positive as the line of best fit has a slope of 1.26. The R 2 is at 76.6%, which means that the fit line can be a strong enough indicator of this relationship. 6.3 Probability of collateral shortfall What is the actual likelihood that the work of art will fall to only 50% of its current value? This question is likely to be very important if considering the Architect’s Home as collateral 5 . The lower tail of the hammer ratio distribution captures the downside risk associated with the sale of a work of art at auction. Only two lots from the data set had hammer ratios bellow 0.65, one sold in 2001 and one in 2007. 54 lots sold below a ratio of 1 and the mean year for when they sold was in 2007. Moreover, the mean size of these 54 lots was 17,493cm 2 ; compared with 50,000cm 2 for The Architect’s Home. y"="1.2666x"+"85383" R²"="0.76663" "1"""" "2,000,000"" "4,000,000"" "6,000,000"" "8,000,000"" "10,000,000"" "12,000,000"" "14,000,000"" "16,000,000"" "18,000,000"" "1"""" "2,000,000"" "4,000,000"" "6,000,000"" "8,000,000"" "10,000,000"" "12,000,000"" Hammer&Price&(USD)& Geometric&Mid4Es7mate&(USD)& Sca8er&Plot&of&Hammer&Prices&and&Geometric&Mid4Es7mates& Total"Peter"Doig"Sales"1999"1"2014" Hammer"Price"vs."Expert's"Opinion" Linear"(Hammer"Price"vs."Expert's"Opinion)" Figure 19: Scatter plot between Peter Doig’s hammer prices and auction house mid-estimate
  29. 29.   28 6.3.1 Value at Risk (VaR) Assuming a 95% confidence level, what is the most amounts or percentage that can be expected to be lost on the painting over a given time frame? This forms a credit risk analysis, Pownall (2014) suggests using method from Bocart (2012) – which uses a monthly index. The variance method 6 was applied on the average log returns and its standard deviation of Tutela’s monthly index. The VaR of Peter Doig’s market was 8.16%; therefore the VaR on the forecasted present value of the Architect’s Home is $1,021,159. 6.4 Liquidity risk It is important for lending institutions to know whether a work of art can be liquidated in order to compensate the loan value in the case of a default. One measure of liquidity can be seen by number of auction sales, another is how many paintings sell at commercial galleries. Table 9 shows all the art dealers who are currently actively engaging in the sale of Peter Doig’s works. There are 24 dealers and Michael Werner is selling the most. 6.5 Artwork-specific risk Taste and fashion play an important role here and can cause substantial variation in price movements over time. ArtStack was used as a proxy for social media endorsement. Further research could use other platforms such as The Google Art Project or Artsy. Peter Doig’s currently has 2615 followers on ArtStack 7 . The total number of stacks for the top 10 price paintings was quantified (Table 10). The Architect's Home came in at 4 th with a total of 220 stacks.
  30. 30.   29 Dealer Location Country Works2on2sale AW2Massey2Fine2Art Fort%Lauderdale USA 1 Coskun2Fine2Art Geneva Switzerland No.%not%given Acquavella2Galleries New%York USA 1 Artware2Editions New%York USA 1 Galerie2Boisseree Cologne Germany 7 Denis2Bloch2Fine2Art Beverly%Hills USA 1 Crown2Point2Press San%Francisco USA No.%not%given Delahunty London UK No.%not%given Gavin2Brown's2Enterprise New%York USA 7 Galerie2Zlotowski Paris France No.%not%given Galerie2FluegelCRoncak2Nuremberg Munich Germany 3 Galerie2Maximillian Aspen USA 2 Kenneth2A.2Friedmn2&2Co. Calabasas% USA 1 Janes2Lisboa Sao%Paulo Brazil 1 Ingleby2Gallery Edinburgh Scotland 1 Goya2Contemporary2&2Goya2Girl2Press Baltimore USA 1 Offer2Waterman2&2Co. London UK No.%not%given Michali2Gallery Palm%Beach USA 2 Michael2Wener2Gallery New%York USA 22 Kodner2Gallery St.%Louis USA No.%not%given Pollock2Fine2Art2 London UK No.%not%given Peach2Editions New%York USA 2 Peter2Harrington London UK No.%not%given Opus2Art2Ltd.2 Newcastle UK 1 Source:%artnet Table 10: Liquidity measure - Art dealers who are currently selling works by Peter Doig, data was complied in Feb. 2015 from artnet Rank Title Stacks-on-ArtStack Price-Rank Price Date-Sold 1 Reflection 453 8 9,000,000$3333333333 10/11/2009 2 White3canoe 357 7 9,957,420$3333333333 07/02/2007 3 Red3Boat 222 9 8,793,780$3333333333 28/06/2011 4 The3Architect's3Home3in3the3Ravine 220 5 10,550,784$33333333 13/02/2013 5 Gasthof 214 2 15,139,198$33333333 01/07/2014 6 The3Heard3of3Old3San3Juan 148 10 6,469,321$3333333333 16/10/2014 7 Jetty 109 6 10,031,543$33333333 25/06/2013 8 Pine3House3(Rooms3for3Rent) 49 1 16,073,661$33333333 12/11/2014 9 Country3Rock3(Wing3Mirror) 30 3 12,879,411$33333333 30/06/2014 10 Road3House 29 4 10,573,661$33333333 12/05/2014 Table 11: Endorsement measure – the number of stacks on ArtStack for Peter Doig’s top 10 paintings, this measures online popularity and artwork specific endorsement
  31. 31.   30 7     Final  Recommendation   It has been concluded that The Architect's Home in the Ravine can be considered as a suitable asset for collateral against a 5 year-fixed bullet loan. With an average forecasted present price of approximately $12,514,208, a 50% LTV ratio therefore makes the fixed loan amount in the range of $6,257,104. However, banks should also consider the “aesthetic dividend” and value created through the art market ecosystem. The Architect’s Home in the Ravine has both economic and cultural value, which in turn feeds into the price of the work. Given Peter Doig’s most recent solo show at the Foundation Beyeler and representation at the Venice Biennale 2015, his cultural value as an artist has increased. Consequently, the borrower may expect a larger loan amount. The painting could truly be in the region of $13,000,000 to $15,000,000 if it were to reach the market in 2015. Although there are concerns about market volatility from recent auction prices, this painting is regarded as one of his best and has sold at auction 3 times beating auction estimates. The level of provenance also stands in this painting’s favour in terms of sustainable price increases; this is supported by solid price projections from 4.2.3. Further research could measure relative risk of Peter Doig’s market. What private banks would ideally like to capture is the illiquidity risk and the downside risk from holding this painting. As argued in 5.3 there is a low probability of collateral shortfall in a distressed situation. Moreover, there is a healthy ecosystem and endorsement process for the artist in the market to support liquidity concerns. Thoughts for future research The risks inherent to art are not captured by price variation alone (Pownall, 2014) 1 . The perceived risk-return trade-off is therefore underestimated when only using financial returns. Further research should consider the aesthetic return that accrues from art, as this determines the aesthetic value creation. Recent theory from Pownall (2014) explains “affective values” towards arts (mechanisms that are derived from the psychology and marketing literature). Investors have many other emotive reasons for investment, and these might not be reflected through the appreciation of the asset and the utility obtained from viewing the item. Survey design taken from the marketing literature allows best practice for empirically measuring “affective values”. Regression analysis can then be used to make sense of the data. Furthermore, research by Graddy et al. (2014) attempt to prove how the economic theory of loss aversion (Khanneman and Tversky, 1978) and pricing anchoring affects the price of an artwork. There is a tendency to place a larger value on an item when it is in one’s possession; the authors study the affect of ownership on the valuation of art objects. They use also regression analysis against the log hammer price to explain the affects of loss aversion; further research could apply their methodology to Peter Doig’s hammer prices. Further still, incorporating the online dimension – through the assumption of greater liquidity and transparency – shall further broaden the explanation of how art functions as a good. This shall prove to be helpful to financiers in understanding the use of art as a collateral.
  32. 32.   31 Bibliography   AMA (2015) ‘Peter Doig at the Fondation Beyeler’, Art Media Agency. Available at: http://en.artmediaagency.com/98517/peter-doig-at-the-fondation-beyeler/ (Accessed 01/02/2015) Anderson, R. C. (1974). Paintings as an investment. Economic Inquiry, 12(1), 13-26. Artlyst (2015) ‘Peter Doig Exhibition Announced To Coincide With 2015 Venice Biennale’, Artlyst [online]. Available at: http://www.artlyst.com/articles/peter-doig-exhibition-announced-to-coincide-with-2015- venice-biennale (Accessed 10/02/2015) ArtTactic (2014). US and Europe Confidence reports (2014-2005) Available at: http://www.arttactic.com/art-markets-home-pages/550-mytactic-account.html (Accessed 02/01/2015) Bocart, F. Y., & Hafner, C. M. (2012). Econometric analysis of volatile art markets. Computational Statistics & Data Analysis, 56(11), 3091-3104. Buelens, N., & Ginsburgh, V. (1993). Revisiting Baumol's ‘art as floating crap game’. European Economic Review, 37(7), 1351-1371. Deloitte (2014). Art & finance report 2014 pp.14-90 Findlay, M. (2012). The Value of Art: Money. Power, Beauty. Frank, R., (2004) 'Pawning Your Picasso', Wall Street Journal. 11 May 2004, D1. Available at: http://www.wsj.com/articles/SB108423273004007579 (Accessed 29/12/2014) Frey, B. S., & Pommerehne, W. W. (1989). Muses and Markets: Explorations in the Economics of the Arts. Blackwell. Frey, B. S., & Eichenberger, R. (1995). On the rate of return in the art market: Survey and evaluation. European Economic Review, 39(3), 528-537. Graddy, K., Loewenstein, L. P., Mei, J., Moses, M., & Pownall, R. A. (2014). Anchoring or Loss Aversion? Empirical Evidence from Art Auctions. Gyorgy, S (2010). Art Banking (Chapter 5) in McAndrew, C. (Ed.). (2010). Fine art and high finance: expert advice on the economics of ownership (Vol. 36). John Wiley & Sons. Lane, M (2014) ‘Peter Doig’s Haunted Lakes and Tropics, on View in Basel’, Wall Street Journal. December 26, 2014. Available at: http://www.wsj.com/articles/peter-doigs-haunted-lakes-and-tropics-on- view-in-basel-1419615204 (Accessed 15/01/2015) McAndrew, C., & Thompson, R. (2006). The collateral value of fine art. Journal of Banking & Finance, 31(3), 589-607. McAndrew, C. (Ed.). (2010). Fine art and high finance: expert advice on the economics of ownership (Vol. 36). John Wiley & Sons. Nesbitt, J. (2008). Peter Doig / edited by Judith Nesbitt ; with an essay by Richard Shiff. Petterson (2014). Value, risk and the contemporary art ecosystem, in Dempster, A. M. (2014). Risk and Uncertainty in the Art World. Bloomsbury Publishing, pp. 67-87
  33. 33.   32 Pownall (2010). Art risk (Chapter 4) in McAndrew, C. (Ed.). (2010). Fine art and high finance: expert advice on the economics of ownership (Vol. 36). John Wiley & Sons. Pownall, Rachel A.J. (2014), 'Art price risk, emotional and aesthetic value: investing in boutique art funds', in Dempster, A., Risk and Uncertainty in the Art Word, Bloomsbury Press, London, April Pownall, R. (2007). Art as collateral: Credit default swap derivatives in banking. Working Paper. Robb, C. (2012). Examining art lending in an online sphere : its history, structure, and potential framework for success. Sotheby’s Institute of Art dissertation. Straus, J. (2008.). The art of collateralization: an examination of art-backed financing. Sotheby’s Institute of Art dissertation. Van Miegroet, H (1986), “The Twelve Months’ Reconsidered: How a drawing by Pieter Stevens Clarifies a Bruege Enigma.” Simialus: Netherlands Quarterly for the History of Art 16, no.1, 29 Weiss, M. (2011) ‘Steinhardt Pledges Picassos for Real Estate as Art Loans Surge’, Bloomberg Business. 18 October 2011. Available at: http://www.bloomberg.com/news/2011-10-18/steinhardt-pledges-picassos- for-real-estate-as-art-loans-surge.html (Accessed 29/12/2014) Ursprung, H. W., & Wiermann, C. (2011). Reputation, price, and death: an empirical analysis of art price formation. Economic Inquiry, 49(3), 697-715. Section notes Section 2 1. Firstly, because online art businesses are perceived as broadening the existing collector base and improving market liquidity, transparency, education and the dissemination of market information. This notion has also been supported by Gyorgy (2010) who suggests greater transparency has arisen in the art market through the arrival of the Internet, price databases and other web-based information. Secondly, online art businesses can help improve the valuation of art and collectibles. The digitisation of more art- related data and the ability of technology to process this data means that we are likely to see significant improvement in valuation methods and processes in the future. (Deloitte/ArtTactic, 2014) Section 4 1. Alongside, Gerhard Richter, Andreas Gursky, Jeff Koons and Christopher Wool, the survey results remain the same as in the last reading in January 2014. 2. The Architect's Home in the Ravine resembles the practices of modern stars including Paul Cézanne, Paul Gauguin, Edvard Munch, Henri Matisse, Pierre Bonnard, Vincent Van Gogh and Edward Hopper amongst others. Vast arrays of painterly techniques are used to painstakingly build the surface with rich, tactile, impasto paint. 3. Provenance Arthur Andersen & Co, Ltd., London. Saatchi Collection, London. Anon. sale, Sotheby's New York, 15 May 2007, lot 11. Acquired at the above sale by the present owner. Literature Peter Doig: Blizzard Seventy-Seven, exh. cat., London, Whitechapel Art Gallery, 1998, no. 5 (illustrated in colour, unpaged). J. Cape (ed.), 100: The Work That Changed British Art, London 2003, no. 51 (illustrated in colour, p. 109). A. Searle, K. Scott and C. Grenier (eds.), Peter Doig, London 2007 (illustrated in colour, p. 76).
  34. 34.   33 E. Booth-Clibborn (ed.), The History of the Saatchi Gallery, London 2011 (illustrated in colour, p. 550). R. Shiff and C. Lampert (eds.), Peter Doig, New York 2011 (illustrated in colour, p. 22). Source: Christie’s 4. $394,361 (June 2002) estimates $181,433 – 226,791 $3,162,054 (May 2007) with estimates $1,200,000 - $1,800,000 $10,550,784 (February 2013) with estimates $6,216,006 – 9,324,009 5. The Big Bang at Centre Pompidou, Paris (2005); Whitney Biennial: Day For Night at the Whitney Museum of American Art, New York (2006) and the Tate Triennial, Tate, London (2006) 6. Using the peer group analysis and data from ArtFacts, between the same time period, similar artists, Marlene Dumas and George Baselitz had bought-in ratios of 25.5% and 22.2% respectively. However, one must note that this figure includes all categories of works that went to auction not just paintings. Section 5 1. Moreover, much like company valuations for hi-tech start up companies, the author explains that valuation in contemporary art is linked to the perceived current and future success of the artist, rather than the long process of historic validation. 2. Petterson (2014) borrows the concepts of microsystem and macrosystem from Urie Bronfenbrenner to explain ecological theory and to better understand the interactions and roles of players and tastemakers in relation to the contemporary art market. 3. Petterson (2014) describes tastemakers as both individuals and institutions that have a significant influence on what society and the general audience consider to be good or bad art. They are players that have been granted (or have earned) a rank or status by their peers, and therefore allows them to exercise their taste to influence the perceived cultural value of an artist. 4. The artist market trajectory graph is taken from Petterson (2014). Peter Doig’s market evolution is split into three phases (formation, expansion and consolidation), and past events are plotted against two axes of “culture” and “economic” value. 5. Repeat sales is a pricing method that controls for artwork specific quality by measuring the price change of the same art asset between two periods. Repeat sales are expressed as a regression with its dependent variable being the ratio of the new and old price. Then, to take into account the changes for each time period, so-called dummy variables are added as independent variables (McAndrew, 2010). 6. Anderson (1974); Frey and Pommerehne (1989); Beulens and Ginsburgh (1993); Galenson (1999); Velthuis (2005); and DaSilva, Pownall, Wolk (2012) – these academics have applied hedonic pricing methods, which implies that the quality of an art work can be regarded as a composite of a number of different attributes or characteristics, and will be valued for the utility that these characteristics bear (McAndrew, 2010). Such characteristics include size, location, time, auction house, and medium - an OLS regression is used to measure the coefficients of the characteristics in a linear regression, where price is the dependent variable and the various characteristics are the independent variables. 7. A hedonic OLS linear regression was applied to Peter Doig’s auction market dataset using SPSS statistics software, however, the results were statistically insignificant. Therefore, further explanation and analysis were not undertaken. 8. Benchmark 1 shows the linear progression of price between all three sales periods, 2002 to 2007 to 2013. Benchmark 2 shows the linear progression of price between the two sales periods, 2007 to 2013. Equations are found in Tables 12 and 13 in Appendix 2. 9. Future research would create indices and linear equations for the other 8 lots that also sold trice to compare and aggregate growth projections, to create aggregate repeat sale index.
  35. 35.   34 Section 6 1. Moreover, Pownall (2010) expands this to artwork specific risks – volatility in Peter Doig’s hammer prices and collateral shortfall and liquidity risk – the ability to liquidate and realise one’s investment. 2. Price data for Calder and Hirst was provided by ArtTactic to Sotheby’s Institute of Art students in 2015. Calder’s hammer price totals ranged between 1995 and 2012, and Damien Hirst’s ranged between 2005 to 2014. 3. A high kurtosis portrays a chart with fat tails and a low, wide distribution, whereas a low kurtosis portrays a chart with skinny tails and a distribution concentrated toward the mean. 4. A hedonic regression model must be linear for Ordinary Least Square (OLS) estimations (Studenmund, 2011); therefore, when constructing a hedonic model, the ‘hammer price’ variable cannot be considered. The research initially planned to construct a hedonic pricing model, but as mentioned previously, the data was insignificant so further research was aborted. 5. Mc Andrew and Thomson (2006) investigated the relationship between market prices for artworks and the geometric mean of pre-sale estimates (hammer ratio). They attempted to quantify the risk that surrounded presale estimates with particular attention to downside risk by incorporating buy-ins in the hammer ratio frequency. 6. There are three methods for calculating the VaR. The historical method uses a statistical analysis of past losses to determine the loss over a given time period. The variance method also uses statistical analysis, but assumes returns are normally distributed in the classic bell-shape curve based on the average return and its standard deviation. The Monte Carlo method involves developing a model and using that to predict future investment prices, and then using that data in a statistical analysis to determine the worst-case loss on the investment 7. George Baselitz had 38 followers, Marlene Dumas had 1,782 followers, and Chris Ofili had 540 followers. These figure were retrieved from: https://theartstack.com/search?utf8=%E2%9C%93&q=peter+doig on 10 th February 2015. Section 7 1. A distinction has been made between financial return and consumption return, and is modelled by the utility function: Utility = function (risk, financial return, aesthetic return). An empirical study to define and frame affect valence and affect richness market mechanisms – where methodologies are derived from a multiple of disciplines, including: economics, behavioural finance, psychology, sociology, and statistics – shall be fruitful for future research when understanding art as an asset class. As this will provide greater certainty over the various types of returns that accrue from art as a good. One can then better understand the nuances between returns and risk in the art market.
  36. 36.   35 Appendix  1 Please rotate left Title1st(Sale2nd(Sale3rd(Sale Hammer(Price(1! (USD) Hammer(Price(2! (USD) Hammer(Price(3! (USD) Return!(1st!*! 2nd!Sale) Return! (2nd!*!3rd! Sale) Total( Average( Return CAGR!(1st*2nd!Sale) CAGR! (2nd!*!3rd! Sale) Total(CAGR 1Country!Rock20072008*32,333!!!!!!!!!!!!!!!!!!63,113!!!!!!!!!!!!!!!*95%95%95.2%*95.20% 2Hitch*Hiker201120042007Bought!In67,625!!!!!!!!!!!!!!!292,034!!!!!!!!!!!!!!*62.8%332%*62.8%62.85% 3Pine!House!(Rooms!for!Rent)200820092014Bought!In1,946,964!!!!!!!!!!16,073,661!!!!!!!!*52.5%726%*52.5%52.53% 4White!creep200320082010302,833!!!!!!!!!!!!!!!!2,347,451!!!!!!!!!!Bought!In675%675%50.6%*50.62% 5Pink!briey20012006*66,458!!!!!!!!!!!!!!!!!!439,498!!!!!!!!!!!!!*561%561%45.9%*45.91% 6Ski!jackets20002002200633,818!!!!!!!!!!!!!!!!!!61,664!!!!!!!!!!!!!!!291,250!!!!!!!!!!!!!!82%47.4%82%35.0%47.4%43.17% 7Bob's!house19992010*29,440!!!!!!!!!!!!!!!!!!1,318,100!!!!!!!!!!*4377%4377%41.3%*41.28% 8Concrete!cabin200020082010128,333!!!!!!!!!!!!!!!!1,791,013!!!!!!!!!!2,793,251!!!!!!!!!!1296%24.9%676%39.0%24.9%36.07% 9The!Architect's!Home!In!The!Ravine200220072013394,361!!!!!!!!!!!!!!!!3,162,054!!!!!!!!!!10,550,784!!!!!!!!702%22.2%468%51.6%22.2%34.82% 10Briey!(Concrete!cabin)20002005*131,250!!!!!!!!!!!!!!!!524,583!!!!!!!!!!!!!*300%300%31.9%*31.93% 11Night!Fishing20072011*98,750!!!!!!!!!!!!!!!!!!240,553!!!!!!!!!!!!!*144%144%24.9%*24.93% 12Highway!2!20072010*53,562!!!!!!!!!!!!!!!!!!92,308!!!!!!!!!!!!!!!*72%72%19.9%*19.89% 13Chopper20052012*82,917!!!!!!!!!!!!!!!!!!240,632!!!!!!!!!!!!!*190%190%16.4%*16.44% 14Grasshopper!(L)200320072014317,872!!!!!!!!!!!!!!!!793,224!!!!!!!!!!!!!1,200,000!!!!!!!!!!150%6.1%150%25.7%6.1%12.84% 15Boiler!House20072013*496,322!!!!!!!!!!!!!!!!793,169!!!!!!!!!!!!!*60%60%8.1%*8.13% 16Figures!in!a!wood200720092012157,406!!!!!!!!!!!!!!!!85,582!!!!!!!!!!!!!!!170,000!!!!!!!!!!!!!!*46%25.7%E46%*26.3%25.7%1.55% 17Grasshopper!(S)20072014*148,750!!!!!!!!!!!!!!!!162,083!!!!!!!!!!!!!*9%9%1.2%*1.23% 18Briey20072010*96,404!!!!!!!!!!!!!!!!!!100,000!!!!!!!!!!!!!*4%4%1.2%*1.23% 19Drifter200820102011538,378!!!!!!!!!!!!!!!!Bought!In192,423!!!!!!!!!!!!!!**E64%**E29.03% Table12:19repeatedworksatauctionrankedbyCAGR
  37. 37.   36 Appendix  2 The Architects Home in the Ravine Repeat Sale Index Forecast: Benchmark*(2002.2013*Forecast) Equation: y=*244.12x+100 x Year Index*(y) Price 0 2002 100 394,361******** 1 2003 334 1,317,672***** 2 2004 568 2,240,983***** 3 2005 802 3,164,294***** 4 2006 1037 4,087,605***** 5 2007 1271 5,010,916***** 6 2008 1505 5,934,227***** 7 2009 1739 6,857,538***** 8 2010 1973 7,780,849***** 9 2011 2207 8,704,160***** 10 2012 2441 9,627,471***** 11 2013 2675 10,550,782*** 12 2014 2910 11,474,093*** 13 2015 3144 12,397,404*** 14 2016 3378 13,320,715*** 15 2017 3612 14,244,026*** 16 2018 3846 15,167,337*** 17 2019 4080 16,090,648*** 18 2020 4314 17,013,959*** The Architects Home in the Ravine Repeat Sale Index (2) Forecast Benchmark.2.(200732013.Forecast) Equation y=.48.94x+100 x Year Index.(y) Price 0 2007 100 3,162,054........... 1 2008 139 4,393,509........... 2 2009 178 5,624,964........... 3 2010 217 6,856,419........... 4 2011 256 8,087,874........... 5 2012 295 9,319,329........... 6 2013 334 10,550,784......... 7 2014 373 11,782,239......... 8 2015 412 13,013,694......... 9 2016 451 14,245,149......... 10 2017 489 15,476,604......... 11 2018 528 16,708,059......... 12 2019 567 17,939,514......... 13 2020 606 19,170,969......... Artprice(Index(and(Equation Forecast: Artprice(Index(Forecast Equation: y=#28.89x+100 x Year Index((y) Price 0 2005 100 3,186,393(((((((( 1 2006 129 4,106,942(((((((( 2 2007 158 5,027,491(((((((( 3 2008 187 5,948,040(((((((( 4 2009 216 6,868,588(((((((( 5 2010 244 7,789,137(((((((( 6 2011 273 8,709,686(((((((( 7 2012 302 9,630,235(((((((( 8 2013 331 10,550,784(((((( 9 2014 360 11,471,333(((((( 10 2015 389 12,391,882(((((( 11 2016 418 13,312,431(((((( 12 2017 447 14,232,980(((((( 13 2018 476 15,153,528(((((( 14 2019 504 16,074,077(((((( 15 2020 533 16,994,626(((((( Tutela'Capital'Index'and'Equation Forecast: Tutela'Index'and'Forecast Equation: y='9.07x+100 x Year Index'(y) Price 0 2005 100 6,114,270''''' 1 2006 109 6,668,834''''' 2 2007 118 7,223,398''''' 3 2008 127 7,777,963''''' 4 2009 136 8,332,527''''' 5 2010 145 8,887,091''''' 6 2011 154 9,441,655''''' 7 2012 163 9,996,220''''' 8 2013 173 10,550,784''' 9 2014 182 11,105,348''' 10 2015 191 11,659,913''' 11 2016 200 12,214,477''' 12 2017 209 12,769,041''' 13 2018 218 13,323,605''' 14 2019 227 13,878,170''' 15 2020 236 14,432,734''' Table 13: Benchmark (2002-2013) index with equation and linear growth forecasts Table 16: Tutela Index with equation and linear growth forecasts Table 14: Benchmark 2 (2007-2013) index with equation and linear growth forecasts Table 15: Artprice Index with equation and linear growth forecasts
  38. 38.   37 y"="70.286x"+"18424" R²"="0.282" "0"""" "2,000,000"" "4,000,000"" "6,000,000"" "8,000,000"" "10,000,000"" "12,000,000"" "14,000,000"" "16,000,000"" "18,000,000"" 0" 10000" 20000" 30000" 40000" 50000" 60000" 70000" 80000" Hammer&Price&(USD)& Total&Size&(cm2)& Sca5er&Plot&of&Hammer&Price&and&Total&Size& Total"Peter"Doig"Sales"1999"0"2014" Hammer"vs"Size"sq" Linear"(Hammer"vs"Size"sq)" Figure 20: Scatter plot of hammer price against total size cm 2 Table 17: Data Index with equation and linear growth forecasts Peter%Doig%data%(1999/2014)%Index%and%Equation Forecast: Data$Index$and$Forecast Equation: y=#397.91x+100 x Year Index$(y) Price 0 2005 100 321,345$$$$$$$$$$$$ 1 2006 498 1,600,025$$$$$$$$ 2 2007 896 2,878,705$$$$$$$$ 3 2008 1294 4,157,385$$$$$$$$ 4 2009 1692 5,436,064$$$$$$$$ 5 2010 2090 6,714,744$$$$$$$$ 6 2011 2487 7,993,424$$$$$$$$ 7 2012 2885 9,272,104$$$$$$$$ 8 2013 3283 10,550,784$$$$$$ 9 2014 3681 11,829,464$$$$$$ 10 2015 4079 13,108,144$$$$$$ 11 2016 4477 14,386,824$$$$$$ 12 2017 4875 15,665,504$$$$$$ 13 2018 5273 16,944,183$$$$$$ 14 2019 5671 18,222,863$$$$$$ 15 2020 6069 19,501,543$$$$$$
  39. 39.   38 CONTACT INFORMATION Vishal Kumar E: vishal.kumar@sia.edu | vishal.kumar.sia@gmail.com W: https://uk.linkedin.com/in/vkumar7 T: 07737 079 762 Copyright 2015 Vishal Kumar © All rights reserved. Any unauthorized use or disclosure is prohibited. This report has been prepared and issued by Vishal Kumar via LinkedIn. The information herein was obtained from various sources; Vishal does not guarantee its accuracy or completeness. Neither the information nor any opinion expressed constitutes an offer, or an invitation to make an offer, to buy or sell any works of art related to the artist in this report. This research report was prepared for academic purposes and is circulated for academic purposes only. It does not have regard to the specific investment objectives, financial situation and the particular needs of any specific person who may receive this report. You should seek specialist advice regarding the appropriateness of buying or selling any works of art or the strategies discussed or recommended in this report and should understand that statements regarding future prospects may not be realised. Investors should note that income from buying works of art, if any, may fluctuate and that each work of art’s price or value may rise or fall. Accordingly, investors may receive back less than originally invested. Past performance is not necessarily a guide to future performance. Foreign currency rates of exchange may adversely affect the value, price or income of any security or related investment mentioned in this report.

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