Bảo hiểm hàng hóa xuất nhập khẩu

Risk Management in
Shipping
Modeling, Measuring, & Managing Freight Market
Uncertainty

Presented at:
National Technical University of Athens
School of Naval Architecture & Marine Engineering
29 May 2003


Risk Management in Shipping

Presentation Outline
 Introduction


About this presentation



About FreightMetrics

 About Risk Management


Defining risk



The risk management process



Scope of risk management



Modern applications of risk management

 Measuring Market Risk


The traditional approach to market risk measurement



The Value-at-Risk (VaR) approach

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Risk Management in Shipping

Presentation Outline
 Measuring Market Risk in Shipping


Justification for risk management in shipping



Market risk measurement vs. market forecasting



Identifying the impact of freight market risk on fleet cash flow



Developing a framework for measuring freight market risk

 Measuring Market Risk in Shipping Using the Fr8Metrics TM
Methodology


Main methodological features



How does Fr8MetricsTM work?



Benefits of the Fr8MetricsTM methodology



Potential users and managerial applications



Software implementation

 Managing Freight Market Risk


Altering the risk profile using managerial decisions



Altering the risk profile using freight derivatives

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Risk Management in Shipping

Introduction

About This Presentation




Our objective


Shipping is a business activity exposed to a wide variety of risks.



In this presentation we are concerned with the measurement of one particular
form of risk – namely freight market risk, or the risk of loss arising from
unexpected changes in freight rates.

Our motivation


Risk management is a notion that exists in financial markets for decades,
having experienced significant technological and modeling advances over the
years.



Shipping has proved rather slow in adopting modern risk management
techniques and best practices from other industries.



Our motivation is to present a modern framework for measuring freight
market risk, using the paradigm of other market-sensitive industries.

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Risk Management in Shipping

Introduction

About FreightMetrics




What FreightMetrics is…


A provider of consulting services and software solutions for measuring and
managing freight market risk.



Working closely with Shipping Banks, Shipowners, and Freight Traders, in order
to quantify their exposure to freight market risk in terms of cash-flow
sensitivity.



Our approach lies in transferring best practices and modern methodologies
from the area of financial risk management to shipping.

What FreightMetrics is NOT…


Shipbroker.



Forecasting agency.



Market news vendor.



Financial intermediary.

For more information about FreightMetrics, visit our website at
www.freightmetrics.com
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Risk Management in Shipping

About Risk Management

Defining Risk


Definition of Risk




We define (financial) risk as the prospect of financial loss due to unforeseen
changes in underlying “risk factors”. These risk factors are the key drivers
affecting portfolio value and financial results. Such risk factors are equity
prices, interest rates, exchange rates, commodity prices, freight rates, etc.

Types of Risks


Business:
The risk of loss due to unforeseen changes in demand,
technology,
competition, etc., affecting the
fundamentals of a business activity.



Market:
prices



Credit:
counterparty to make a



Operational:

or the

The risk of loss arising from the failures of internal systems
people who operate in them.



Other types:

Legal, Liquidity, etc.

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The risk of loss arising from unexpected changes in market
or market rates.
The risk of loss arising from the failure of a
promised payment.

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Risk Management in Shipping

About Risk Management

The Risk Management Process


The Risk Management process


There is a wide misconception amongst practitioners, especially within the
shipping industry, who consider risk management as synonymous to hedging.
This is an oversimplification and does not reflect the true dimension of risk
management.



In fact, risk management is a process that involves three separate steps:

1.

Risk Modeling: Before any attempt to take decisions on risk considerations,
we must identify the underlying risk factors, understand their behavior, and try
to model their dynamics. This is the basic foundation on which the other phases
of the risk management cycle are built.

2.

Risk Measurement: After identifying and modeling the underlying risk
factors, we must determine their significance and quantify their influence on
portfolio value and financial results.

3.

Risk Management : Having identified and measured our risks, we are then
able to take informed decisions on whether to reduce our exposure or alter our
risk profile based on our risk preferences – hedging is one such alternative
course of action.

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Risk Management in Shipping

About Risk Management

Scope of Risk Management


Risk Management ≠ Hedging


As already mentioned, risk management is not synonymous to hedging.
Hedging is just one alternative for the active management of risk.



Moreover, risk management does not necessarily imply risk reduction. In fact,
the objective of risk management is NOT to reduce risk, but – more
importantly –
to quantify and control risk.



Most of the times, the objective is not to eliminate risk, but rather to alter our
risk profile according to the prevailing market conditions, our risk preferences,
and potential regulatory or contractual requirements.



Risks are embedded in any business activity. For a shipowner, the decision to
invest in a vessel signifies his belief that freight rates will go up, earning him a
return on his investment that is higher than the “risk-free” interest rate.
However, there is no “free lunch” in the economy; his decision to invest
creates at the same time a natural exposure to freight rates, accepting the
risk that freight rates may in fact go down. Risks are simply unavoidable in
any profit-taking activity.

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Risk Management in Shipping

About Risk Management

Scope of Risk Management


Uncertainty vs. Variability

1

“Variability is a phenomenon in the physical world to be measured, analysed
and where appropriate explained. By contrast, uncertainty is an aspect of
knowledge.”

Sir David Cox


Risk management is only useful for the mere fact that we cannot predict the
future. There are two components of our inability to be able to precisely
predict what the future holds: these are variability and uncertainty.



Variability is the effect of chance and is a function of the system. It is not
reducible through either study or further measurement, but may be reduced
through changing the physical system.



Uncertainty is the assessor’s lack of knowledge (level of ignorance) about the
parameters that characterize the physical system that is being modeled. It is
sometimes reducible through further study, or through consulting more
experts.



Risk management can do very little to reduce variability (markets will
continue to fluctuate no matter how advanced risk management gets), but
can be very effective in reducing uncertainty for those involved in risk-taking
decisions.

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Risk Management in Shipping

About Risk Management

Modern Applications of Risk
Management


Modern applications of Risk Management


Exposure measurement and reporting


Market risk (since early 90s)



Credit risk (since late 90s)



Operational risk (new area)



Economic capital estimation



Allocation of capital



Risk-based pricing



Risk limits



Risk-adjusted performance evaluation

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Risk Management in Shipping

About Risk Management

Modern Applications of Risk
Management


Example: Risk-Adjusted Performance Evaluation



Consider two traders who are evaluated on the basis of their realized profits at
some future date. Trader B ended up with higher profits compared to Trader A.
Does this mean he is more skilled than Trader A? Does he deserve a higher
bonus? What about the risk incurred by each trader through their trading
strategy?

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Risk Management in Shipping

Measuring Market Risk

The Traditional Approach to Risk
Measurement




The Mean-Variance framework


Under the Mean-Variance framework, we model financial risk in terms of the
mean and variance (or standard deviation, the square root of variance) of the
Profit/Loss (P&L) or the returns of our portfolio.



The Mean-Variance framework often makes the assumption that returns obey
a normal distribution (strictly speaking, the mean-variance framework does
not require normality, but it is easier to understand its statistics).

Portfolio Theory


The origin of portfolio theory can be traced back to the work of Markowitz
(1952) which earned him the Nobel prize.



Portfolio theory starts with the premise that investors choose between
portfolios on the basis of maximizing expected return for any given portfolio
standard deviation or minimizing standard deviation for any given expected
return.



One of the key insights of portfolio theory is that the risk of any individual
asset is measured by the extent to which that asset contributes to overall
portfolio risk which depends on the correlation of its return with the returns to
the other assets in the portfolio (a result known as diversification effect).


Portfolio
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theory typically makes the assumption of normally distributed


Risk Management in Shipping

Measuring Market Risk

The Value-at-Risk (VaR) Approach


The origin and development of VaR


In the late 70s and 80s, a number of major financial institutions started
working on internal models to measure and aggregate risks across the
institution as a whole.



The best known of these models is the RiskMetrics model developed by JP
Morgan. According to industry legend, this model is said to have originated
when the chairman of JP Morgan, Dennis Weatherstone, asked his staff to give
him a daily one-page report – the famous “4:15 report” – indicating risk and
potential losses over the next 24 hours, across the bank’s entire trading
portfolio.



The report was ready by around 1990 and the measure used was Value-atRisk (VaR), or the maximum likely loss over the next trading day. VaR was
estimated from a system based on standard portfolio theory, using estimates
of the standard deviations and correlations between the returns of different
traded instruments.



In early 1994, JP Morgan set up the RiskMetrics unit to make its data and basic
methodology available to outside parties. This bold move attracted a lot of
attention and raised awareness of VaR techniques and risk management
systems.



The subsequent adoption of VaR systems was very rapid, first among
securities houses and investment banks, and then among commercial banks,
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other financial institutions and non-financial corporates.

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Risk Management in Shipping

Measuring Market Risk

The Value-at-Risk (VaR) Approach


VaR in practice



VaR Basics:

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

VaR on a portfolio is the maximum loss we might expect over a given
holding or horizon period, at a given level of confidence (probability).



VaR is less restrictive on the choice of the distribution of returns and
the focus is on the tail of that distribution – the worst p percent of
outcomes.

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Risk Management in Shipping

Measuring Market Risk

The Value-at-Risk (VaR) Approach


VaR in practice


Estimating VaR: The various methodologies for estimating VaR actually
differ on their particular technique for constructing the distribution of possible
portfolio values from which VaR is inferred. The most common methodologies
are:







Analytical methods (Variance/Covariance)



Historical simulation



Monte-Carlo simulation

Attractions of VaR:


VaR is a single, summary, statistical measure of possible portfolio
losses, providing a common and consistent measure of risk across
different positions and risk factors.



It takes account of the correlations between different risk factors.



It is fairly straightforward to understand, even for non-technical
people.

VaR variants: Following the same logic, other “at risk” measures have

been proposed to quantify risk in various settings: Cash Flow at Risk (CaR),
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Earnings at Risk (EaR), etc.

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Risk Management in Shipping

Measuring Market Risk in Shipping

Justification for Risk Management in
Shipping


Business and market risk in shipping: the two faces of the
same coin


Most industries can distinguish between business risks and market risks.
These industries have to worry about business risks and try to hedge away

market risks which may have an adverse side-effect on financial results. For
example, an auto manufacturer has to worry about business risks such as
technology, competition, production, R&D, but may also have an exposure to
FX risk, which may hamper exports, or interest rate exposure which may
increase debt service on floating rate obligations.



Other industries cannot distinguish between business risks and market risks.
The most pronounced example is maybe that of financial institutions. A
significant part of the business of financial institutions is to take direct
exposure in the world’s equity, interest rate, currency, and commodity
markets.



Shipping can be said to belong to the industries that cannot distinguish
between business risks and market risks. Financial results in shipping are
directly affected by movements in the world’s freight rate markets.
Shipowners are in effect in the business of managing shipping risk
affecting a portfolio of physical assets, rather than simply managing
a fleet of vessels.

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Risk Management in Shipping

Measuring Market Risk in Shipping

Justification for Risk Management in
Shipping


High market volatility


Freight rates have historically been very volatile. The impact of unforeseen
geo-political events and the slow speed of adjusting supply to demand have
often resulted in dramatic fluctuations in the level of freight rates.
Example of Freight Market Fluctuations

BFI

(Baltic Freight Index, BCI Route 2, BPI Route 1)

BCIr2

Standardised scaling (base=100 @1/3/99)

BPIr1

300

250

200

150

100

50

0
1/4/1985

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1/4/1987

1/4/1989

1/4/1991

1/4/1993

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1/4/1995

1/4/1997

1/4/1999

1/4/2001

1/4/2003

Risk Management in Shipping

Measuring Market Risk in Shipping

Justification for Risk Management in
Shipping


Industry inefficiencies


Capital needs vs. sources of funds:






Shipping is a capital intensive industry with significant funding needs
for fleet expansion and replacement purposes. Yet, it has very limited
opportunities to diversify its sources of funding, as most of its
financing comes in the form of bank debt.

Asset – Liability (mis)matching


Asset economic life >> term of debt financing



Variable (uncertain) revenues to meet fixed debt claims

Pro-cyclical lending practices


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Many banks tend to be influenced by the general sentiment of the
market and ignore the cyclical nature of the business. Thus, they
appear more willing to lend when the market (and vessel prices) is
high, despite the fact that the market will eventually revert back to
lower levels. In contrast, they appear rather hesitant to extend credit
at a period of low freight rates, although they are likely to rise to more
sustainable levels.

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Risk Management in Shipping

Measuring Market Risk in Shipping

Justification for Risk Management in
Shipping


Lessons from the High Yield disaster of the late 90s


In the late 90s, many shipping companies decided to tap the public debt
markets with high-yield bonds. Historically, it was the first massive attempt of
the industry to diversify away from bank debt, using an alternative source of
external funding.



Unfortunately, nearly all of these high yield issues subsequently defaulted,
mainly due to insufficient cash flow generation.



This indicated poor risk assessment and a lack of appropriate tools to
evaluate shipping market risks.



Example:

Source: Moody’s (2002)
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Risk Management in Shipping

Measuring Market Risk in Shipping

Justification for Risk Management in
Shipping


Lessons from the High Yield disaster of the late 90s


Examples:

Source: Moody’s (2002)
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Risk Management in Shipping

Measuring Market Risk in Shipping

Market Risk Measurement vs. Market
Forecasting




Types of maritime forecasting


Structural econometric models: Model freight rates as a dependent
variable, driven by a number of independent variables, usually representing

macro-economic factors that influence shipping demand, e.g. GDP growth, oil
prices, industrial output, etc.



Time series models: Model freight rates using the structure (serial
correlation) in the past history of the data itself. Future freight rates are
determined based on lagged values of their own history and do not exploit or
infer causality with other economic variables.

Difficulties in maritime
forecasting


Demand for shipping is characterized as
derived demand, meaning that it
depends on the demand of the
commodities that are shipped by sea.



Econometric models are prone to
specification problems. Model fit can
always improve by including more
explanatory variables, which may
introduce multicollinearity problems.



It is possible that a small error in

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Risk Management in Shipping

Measuring Market Risk in Shipping

Market Risk Measurement vs. Market
Forecasting




Differences in scope


Scope:



Motivation:
market)

Prevent unexpected losses vs. Make a profit (beat the



Horizon:

Long-term vs. Short-term



Emphasis:

Tail of the distribution vs. Mean of the distribution

Prepare for future vs. Predict the future

Differences in methodology


Measurement does not presuppose causality relations between economic
variables.



Forecasting models have potentially infinite specifications (depending on
choice of explanatory variables).



Measurement focuses on producing the complete picture of potential
outcomes (entire distribution) rather than producing a point estimate (the
mean of the distribution).

So, do we discard forecasting? NO, it can serve a useful complementary role,

especially in revealing causality relations between economic variables.
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Forecasting may also assist in certain chartering or trading decisions in the

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Risk Management in Shipping

Measuring Market Risk in Shipping

Impact of Freight Rate Volatility on
Cash Flow


Identifying the impact of freight rate volatility on fleet
cash flow





Fluctuations in freight rates directly affect fleet cash flow.



Cash flow performance is the topmost concern in shipping.



Ship financing belongs to the family of “Project Financing” (other forms of
project financing include airlines, infrastructure, real estate, etc.). There is a
principle in project financing: repayment MUST come from the operating cash
flows of the financed asset.



So, what really matters in measuring freight market risk is the impact of
freight rate variability on cash flow performance.

Case study


We performed a simple exercise (historical simulation) of the cash flow
generation of a handysize dry bulker over two separate time periods (period
A: Jan-1980 to Dec-1986, and period B: Jan-1987 to Dec-1993).



We used the same set of assumptions in both cases (see the following slide),
except for using the actual freight rates for each period and the actual
second-hand value of the financed vessel at the start of the each period.



This exercise not only illustrates the impact of freight rate volatility on cash

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Risk Management in Shipping

Measuring Market Risk in Shipping

Impact of Freight Rate Volatility on
Cash Flow


Case study: impact of freight rate volatility on fleet cash
flow
Historical simulation assumptions and actual freight rate data (source:
Clarksons)
1-yr time charter rate for Handysize (30000 dwt)

ASSUMPTIONS
Operating
Rev. days
Opex days
Opex ($/day)
Loan
Vessel value
Loan amount
Advance ratio
Installments
Balloon
Loan interest
Start. Liquidity Cash balance

PERIOD
A (80-86)
B (87-93)
25
25
30
30
3,500
3,500
10,000,000
3,800,000
7,000,000
2,660,000
70%
70%
84
84
30%
30%
5%
5%
0
0

Period A: Jan80-Dec86

12000

Period B: Jan87-Dec93

10000

8000

($/day)



6000

4000

2000

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Jan-99

Jan-98

Jan-97

Jan-96

Jan-95

Jan-94

Jan-93

Jan-92

Jan-91

Jan-90

Jan-89

Jan-88

Jan-87

Jan-86

Jan-85

Jan-84

Jan-83

Jan-82

Jan-81

Jan-80

Jan-79

Jan-78

Jan-77

Jan-76

0


Risk Management in Shipping

Measuring Market Risk in Shipping

Impact of Freight Rate Volatility on
Cash Flow


Case study: impact of freight rate volatility on fleet cash
flow


Chart of monthly net cash flow (after debt service, but excluding
balloon
A (80-86)
Impact of freight rate volatility on fleet cash flow
payment):
B (87-93)
150,000

Monthly Net Cash Flow ($)

100,000

50,000

0
4

8

12

16

20

24

28

32

36

40

44

-50,000

-100,000

-150,000

Month

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25

48

52

56

60

64

68

72

76

80

84