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ContentsDemand / Supply Ton Mile Demand (AIS) 4

Net Fleet Growth 5

S&P Stats Momentum 6

Volatility 7

Asset Class Correlation 8

Liquidity 9

Alternative With Charter Valuations 10

Valuations Income Valuations 10

Option Pricing 11

Haircut Model 11

AIS Analytics Automatic Position Lists 12

Trade Flows 13

Average Speed 14

Congestion 15

Operating Performance 16

Interactive Tools LSFO Bunker Demand 17

Fleet at Risk 18

4

Demand /Supply

Ton Mile Demand What is the demand for vessels by type, route and/or region?

What is the trend?

How does this affect rates and values?

Methodology

• Demand = Cargo quantity X laden distance travelled

• Distance travelled = Real time laden/ballast movements (satellite and terrestrial AIS) & filtration for piloting, at anchor etc

• Laden/ballast information from vessel draft and specification database

• Port, country or region level zoning to improve the granularity of the analysis

• Commodity type, loading and discharging port database

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USD

/ D

ay (E

nd o

f Mon

th)

Ton

Mile

s (B

illio

n)

BSI-TCA

Supramax Ton Mile

Supramax ton mile demand vs TCA.

Supramax Ton Mile vs TCA

Demand /Supplycontinued

Net Fleet Growth How much will the fleet grow over the next few years (by vessel type, sub type etc)?

How does this compare to expected demand growth?

How may this affect values and charter rates?

Methodology

• Newbuildings (including delivery month, slippage and projected future orders)

• Algorithm for projecting scrapping activity

55

Net fleet growth for Supramax vessels based on firm orderbook and predicted removals.

4.8%

6.4%

6.5%

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-2

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Jun 14 Sep 14 Dec 14 Mar 15 Jun 15 Sep 15 Dec 15 Mar 16 Jun 16 Sep 16 Dec 16 Mar 17 Jun 17 Sep 17 Dec 17 Mar 18

% C

hang

e

NewbuildNetScrap

Average scrapping age: 19.5

Supramax supply curves (% of existing fleet)

6

S&P Stats Momentum What’s hot and what’s not?

When is a good time to buy or sell?

Methodology

• Historical daily asset prices are obtained after eliminating the effect of depreciation

• Out of the 90 days in a quarter, if for 45 days the price of the vessel was increasing, the momentum index would be at 50. An index greater than 50 would indicate a stronger positive trend in price over the quarter

Value momentum in Bulkers over the period April 2013 - July 2014.

BULKER Momentum

Mo

men

tum

Date Ship Type

Bulker Momentum

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90

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30Apr 2013

Jul 2013Oct 2013

Jan 2014Apr 2014

Jul 2014 Capesize

Panamax BC

Supramax BC

Handy BC

7

S&P Statscontinued

7

Volatility How much risk?

How does risk compare across vessel types?

How has risk changed over time?

Methodology

• Eliminate effects of depreciation for daily historical values for different vessel types and ages using our ‘Fixed Age Report’

• Run conditional volatility models, e.g. GARCH (1,1)

0.0

0.1

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Jun 13 Jul 13 Aug 13 Sep 13 Oct 13 Nov 13 Dec 13 Jan 14 Feb 14 Mar 14 Apr 14 May 14

Vo

lati

lity

Conditional Volatility

CapesizeVLCCPost Panamax ContVLGC LPG

Dry Bulk Volatility with depreciation removed from June 2013 - May 2014 for 5 year old vessels.

Conditional Volatility

Asset Class Correlation

What is the relationship of value between different vessel types?

How best to diversify?

How has this changed over time?

Methodology

• Eliminate effects of depreciation for daily historical values for different vessel types and ages using the ‘Fixed Age Report’

• Esimating Engle’s (2002) Dynamic Conditional Correlation model on asset prices after allowing for the effects of depreciation and volatility

8

S&P Statscontinued

8

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Co

rrel

atio

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Capesize - Panamax BulkerPanamax Bulker - SupramaxSupramax - Handy Bulker

Changes in asset value correlation in the dry bulk sector.

Dynamic conditional correlation (DCC)

9

S&P Statscontinued

Liquidity How many vessels are being bought and sold?

What vessel types are in or out of fashion?

Which types are the most or least liquid?

How has this changed over time?

Methodology

• Intra-daily accurate and timely transaction information

• Intuitive 3D visualisation and filtering

9

S&P activity in Capesize vessels back to 2007. 12 year old vessels have had numerous periods of popularity throughout the last 7 years.

Num

ber

of

vess

els

sold

Age at the time of sale

Year of sale

Capesize - Sale and Purchase Activity18

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10

AlternativeValuations

With Charter Valuations What is the value of a charter?

Methodology

• Scenario analysis

• DCF models

• Charter premium vs market analysis

• Vessel type, age and market specific non-linear depreciation profiles

Income Valuations What is the estimated long term (DCF) value of vessels, fleets, portfolios?

What are the best estimates of charter rates, OPEX etc over the life of a vessel(s)?

What is the breakeven charter rate for the current market value?

Is it time to buy or sell?

Methodology

• Predicted average charter income over vessel life

• Predicted OPEX, survey costs

• Discounted Cash Flow (DCF) models calculated for all sectors, ages and sizes

• Discount rates unique to vessel types

Key Functionality

• Assumptions can be adjusted by user

• Charter rate adjusted for features, ages etc of vessel

• Easy to use interface and exports

11

Source: Baltic Exchange

AlternativeValuationscontinued

Option Pricing What is the value of a purchase option, charter option or other structure?

Methodology

• Time varying non-linear depreciation profile of underlying assets is allowed for

• Computation of historical (conditional) volatility of the underlying after eliminating depreciation

• Incorporates non-linear profile of the strikes in a Bermudan framework

Haircut Model What is the expected Rate of Recovery following arrest and auction of a vessel?

For different vessels?

For different vessel types?

Over different market conditions?

Methodology

• Analysis of historical distressed sales/auctions and related conditions

• Comparison of distressed sale price vs VV market value at the time

• Inclusion of ‘asset recovery model’, ‘foreclosure delay densities’ and ‘asset value recovery densities’

11

8200000 8400000 8600000 8800000 9000000 9200000 9400000 9600000 9800000

60%

IMO Numbers

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% R

eco

very

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et v

alue

s ($

M U

SD)

Asset valuePredicted recovery valueDemolition Value

Recovery rates of sample Capesize vessel through time.

Recovery rates of the Capsize fleet plotted against IMO numbers.

Recovery Rates (Capesize fleet)

Capesize Recovery : Sample Vessel

12

AIS Analytics

Automatic Position Lists* What vessels may be available – when and where?

What vessels are competing with my vessel?

What vessels are available for me to charter?

Will there be over or under-supply of vessels in certain regions or ports (supply pressure)?

Methodology

• Satellite and terrestrial AIS signal processing

• Filtration algorithms for signal processing

• Unique for vessel types and sizes

• Comprehensive combination of distances and routes

• Forward looking probabilistic framework

• Linked to VV vessels specification and ownership database

• Search, group and display by full specifications and features (VV+ functionality)

• Real time updates and on demand access

* Coming Q4 2014

Trade Flows What vessel types, fleets or owners are trading where?

How has this changed over time?

What may happen in the future?

Methodology

• Satellite and terrestrial AIS signal processing

• Complexity reduction algorithms from graph theory, computational geometry and spatial econometrics

• Filtration algorithms for signal processing

• Visualisation of trade relationships (colour) and trade volumes (thickness)

13

Source: Baltic Exchange

AISAnalyticscontinued

13

VLCC trade flows: Visualisation of trade relationships (colour) and trade volumes (thickness).

14

AIS Analyticscontinued

Average Speed What speed are vessels sailing at and are they laden or ballast?

How do different vessel types compare?

How has this changed over time and how may this affect rates?

Methodology

• Satellite and terrestrial AIS signal processing

• Vessel, operator and port database with accurate specifications

• Port, country or region level zoning to improve the granularity of the analysis

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Spee

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Supramax Average Ballast Speed

Supramax Average Laden Speed

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Average Supramax laden and ballast speed.

Supramax Average Speed

15

AISAnalyticscontinued

Congestion What is the total congestion as percentage of fleet?

What is localised congestion in particular zones, ports and regions?

How much load or discharge port congestion?

What is the correlation with rates?

Methodology

• Satellite and terrestrial AIS signal processing

• Vessel, operator and port database with accurate specifications

• Port, country or region level zoning to improve the granularity of the analysis

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No.

of

Ves

sels

Date

120hr Mov. Avg. (Port Hedland)120hr Mov. Avg. (Port Walcott)120hr Mov. Avg. (Dampier)

Number of vessels in selected Australian iron ore ports.

Australian Ports Iron Ore Congestion

Operating Performance How well are vessels operated by owners and pools?

How do owners and pools operation of vessels compare and who is the best?

What are the operational strategies of different owners and pools?

Methodology

• Satellite and terrestrial AIS signal processing

• Vessel, operator and port database with accurate specifications

• Port, country or region level zoning to improve the granularity of the analysis

16

AIS Analyticscontinued

16

These graphs show the breakdown of tanker pool performance.

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Average Ballast Speed

VLCC fleetKEY

Nova Tankers PoolSeawolf Tankers PoolTankers International PoolUnique Tankers PoolVL8 Pool

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Laden Underway / Ballast Underway

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Average Ballast Speed

VLCC fleetKEY

Nova Tankers PoolSeawolf Tankers PoolTankers International PoolUnique Tankers PoolVL8 Pool

17

InteractiveTools

17

LSFO Bunker Demand How much LSFO is needed in the special or restricted areas ?

What level of emissions may be produced in these areas?

Methodology

• Real time vessel movements, speed, laden/ballast using satellite and terrestrial AIS data

• Consumption estimations

• SECA / ECA and MARPOL regions included

1818

InteractiveToolscontinued

18

Fleet at Risk What is the value of a fleet currently located in specific geographic areas?

How does this compare to global averages?

Methodology

• Aggregate daily values of fleet across 160 regions in real time (VV@ and VV$ based)

• Relative measure of excessive risk as compared to global fleet or vessel type

• P&I, company, portfolio or vessel type granularity

Showing East China Sea selected on the ‘At Risk’ map with total value of fleet in that area displayed in top right corner.

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