Freight Derivatives and Risk Management in Shipping

Cover
Half Title
Series Page
Title Page
Copyright Page
Contents
Preface to the second edition
Preface to the first edition
List of abbreviations
1 Introduction to the shipping markets and their empirical regularities
	1.1	Introduction
	1.2	Market segmentation of the shipping industry
		1.2.1	General cargo and bulk cargo movements
		1.2.2	Bulk-cargo segmentation
		1.2.3	General (dry) cargo segmentation
	1.3	Market conditions in shipping freight markets
	1.4	Equilibrium freight rates in tramp freight markets
		1.4.1	Freight rates for different duration contracts
		1.4.2	Term structure of freight rate contracts
		1.4.3	Seasonality in freight rate markets
			1.4.3.1	Case 1: Seasonality patterns in dry-bulk markets
				1.4.3.1.1 Spot market seasonality
				1.4.3.1.2 One-year T/C seasonality
				1.4.3.1.3 Three-year T/C seasonality
				1.4.3.1.4 Seasonality comparisons between vessel types and contract durations
				1.4.3.1.5 Seasonality patterns under different market conditions
			1.4.3.2	Case 2: Seasonality patterns in tanker markets
			1.4.3.3	Case 3: Seasonality strategies
	1.5	Vessel prices and vessel price risks
		1.5.1	Vessels as capital assets
		1.5.2	Market efficiency in the markets for vessels
	1.6	Summary
2 Business risks analysis in shipping and traditional risk management strategies
	2.1	Introduction
	2.2	The sources of risk in the shipping industry
	2.3	Business decisions faced by the international investor
	2.4	The cash-flow position of the shipowner
	2.5	Volatilities of spot and time-charter rates in shipping
		2.5.1	Time-varying freight rate volatilities for different sub-sectors
		2.5.2	Time-varying freight rate volatilities for contracts of different duration
		2.5.3	Volatilities (risks) in different vessel markets
			2.5.3.1	Time-varying volatilities of different vessel sizes
	2.6	Volatility spillovers across shipping segments
	2.7	Correlations amongst shipping sub-sectors and portfolio diversification
	2.8	Summary of traditional risk management strategies
	2.9	Risk management and the use of derivatives in the shipping industry
	2.10	Summary
3	Introduction to financial derivatives
	3.1	Introduction
	3.2	The economic functions and benefits of financial derivatives
	3.3	The risks associated with financial derivatives
	3.4	Types of participants in derivatives markets
	3.5	Forward and futures contracts
		3.5.1	Market positions (long and short)
		3.5.2	Mark-to-market and clearing
		3.5.3	Basis and basis risk
		3.5.4	Optimal hedge ratio determination
		3.5.5	Pricing and the cost-of-carry model
			3.5.5.1 Example 1: Contango market: Futures/forward price higher than the spot price
			3.5.5.2 Example 2: Normal backwardation: Futures/forward price lower than the spot price
		3.5.6	Pricing examples for different underlying assets
			3.5.6.1	Case 1: Forward price of asset with no income
			3.5.6.2	Case 2: Forward price of asset with income
			3.5.6.3 Case 3: Forward price of assets with known yield and stock indices
			3.5.6.4	Case 4: Forward price of currency contracts
			3.5.6.5 Case 5: Forward price of assets that are held for investment purposes
			3.5.6.6	Case 6: Forward price of assets that are held for consumption
			3.5.6.7	Case 7: Forward price of non-storable assets
	3.6	Swap contracts
		3.6.1	Pricing of swap contracts
			3.6.1.1	Case 1: Pricing interest rate swaps
			3.6.1.2	Case 2: Pricing currency swaps
	3.7	Option contracts
		3.7.1	Payoffs of option contracts
		3.7.2	Hedging with option contracts
		3.7.3	Options versus futures/forwards
		3.7.4	Intrinsic and time value of options
		3.7.5	Factors influencing option prices and the “Greeks”
			3.7.5.1	Price of underlying asset (S)
			3.7.5.2	Strike or exercise price (X)
			3.7.5.3	Time to expiration (T)
			3.7.5.4	Price volatility of the underlying asset (σ)
			3.7.5.5	Risk-free interest rate (r)
			3.7.5.6	Case: Utilising the Greeks – a Delta hedge strategy
		3.7.6	Option pricing
			3.7.6.1	Model 1: The binomial model
			3.7.6.2	Model 2: The Black–Scholes model
		3.7.7	Price limits of options
		3.7.8	Put–call parity relationship
		3.7.9	Asian options
			3.7.9.1	Model 1: The Kemma and Vorst model
			3.7.9.2 Model 2: The Turnbull and Wakeman model
			3.7.9.3	Model 3: The Levy arithmetic rate approximation
			3.7.9.4	Model 4: The Curran approximation
		3.7.10	Other exotic options
	3.8	Accounting treatment of derivative transactions
	3.9	Summary
	Appendix: Cumulative standard normal distribution table
4	Freight market information and freight rate indices
	4.1	Introduction
	4.2	Dry-bulk market information and freight rate indices
	4.3	Tanker market information and freight rate indices
		4.3.1	Baltic Exchange freight rate indices
		4.3.2	Platts freight rates assessments
		4.3.3 Liquefied Petroleum Gas (LPG) and Liquefied Natural Gas (LNG) indices
	4.4	Containership freight rate indices
		4.4.1	China (Export) Containerized Freight Index (CCFI)
		4.4.2	Shanghai Containerized Freight Index (SCFI)
		4.4.3	World Container Index (WCI)
		4.4.4	Ningbo Containerized Freight Index (NCFI)
		4.4.5	The Freightos Baltic Index (FBX)
	4.5	Summary
5	Freight rate derivatives
	5.1	Introduction
	5.2	Freight futures markets: early efforts and currently non-active exchanges in freight derivatives – a historical perspective
		5.2.1	The Baltic International Freight Futures Exchange (BIFFEX) contract
			5.2.1.1	Clearing BIFFEX trades: the LCH.Clearnet (LCH)
		5.2.2	The International Maritime Exchange (IMAREX)
			5.2.2.1	Clearing IMAREX trades: the Norwegian Futures and Options Clearing House (NOS)
		5.2.3	The Nasdaq Energy Futures Exchange (NFX)
	5.3	Active exchanges trading freight futures and associated clearing-houses
		5.3.1	The European Energy Exchange (EEX) and the European Commodity Clearing (ECC) House
			5.3.1.1	Clearing EEX trades: the European Commodity Clearing (ECC) House
				5.3.1.1.1 A Clearing example at the European Commodity Clearing (ECC) house
		5.3.2	The Chicago Mercantile Exchange (CME) Group
		5.3.3	The Intercontinental Exchange (ICE)
		5.3.4	The Singapore Exchange Limited (SGX) and the Singapore Exchange Derivatives Clearing SGX-DC
	5.4	Over-The-Counter (OTC) freight derivatives
		5.4.1	Trading volumes of freight derivatives
		5.4.2	Trading volumes of freight derivatives: OTC versus cleared
		5.4.3	Credit risk in freight derivative contracts
		5.4.4	Clearing OTC freight derivatives
		5.4.5	Key properties of FFA contracts
			5.4.5.1	Tailor made versus liquidity
			5.4.5.2	Basis and off-hire risks
	5.5	Market information on FFAs and freight options contracts
		5.5.1	Negotiating and writing FFA contracts
		5.5.2	The Forward Freight Agreement Brokers Association (FFABA)
		5.5.3	The Baltic Forward Assessments (BFAs)
		5.5.4	The Baltic Options Assessments (BOAs)
		5.5.5	Freight futures prices from market-makers and shipbrokers
		5.5.6	Freight options prices from organised stock exchanges (market-makers)
		5.5.7	Trading screens for freight derivatives and other developments
	5.6	Historical evolution of shipping derivatives
	5.7	Summary
	Appendix I: Clarksons dry-bulk FFA daily report (29 May 2019)
	Appendix II: Clarksons dry-bulk freight options daily report (23 June 2017)
	Appendix III: Forward Freight Agreement Brokers Association (FFABA) Forward Freight Agreement
	Appendix IV: Forward Freight Agreement Brokers Association (FFABA) Freight Options Contract
6	Applications of FFAs, pricing and risk management of FFA positions
	6.1	Introduction
	6.2	Practical applications of freight futures and FFAs
		6.2.1	Dry-bulk voyage FFA, non-cleared
		6.2.2	Dry-bulk voyage “hybrid” FFA, cleared
		6.2.3	Dry-bulk voyage non-cleared versus cleared FFA
		6.2.4	Dry-bulk T/C non-cleared versus cleared FFA
		6.2.5	Dry-bulk 12-month T/C non-cleared versus cleared FFA
		6.2.6	Dry-bulk voyage trend FFA, cleared
		6.2.7	The hedger’s point of view
		6.2.8	The speculator’s/investor’s point of view
		6.2.9	Tanker voyage FFA, non-cleared
		6.2.10	Tanker voyage freight futures, cleared
		6.2.11	Tanker T/C “hybrid” FFA (cleared)
		6.2.12	FFAs in newbuilding ship finance
		6.2.13	Securing favorable shipping loan terms through FFAs
		6.2.14	Application of the optimal hedge ratio in the FFA market
		6.2.15	Spread trades
	6.3	Freight derivatives strategies for banks
	6.4	Freight derivatives versus other risk management strategies
	6.5	The role of brokers in freight derivatives
	6.6	Economics and empirical evidence on FFAs and freight futures
		6.6.1	Pricing, price discovery and unbiasedness
		6.6.2	Hedging effectiveness
		6.6.3	Forecasting performance
		6.6.4	Impact on market volatility
		6.6.5	Microstructure effects
		6.6.6	Forward rate dynamics
		6.6.7	Market risk measurement
		6.6.8	Surveys on the use of shipping derivatives
	6.7	Summary
7	Applications of freight options
	7.1	Introduction
	7.2	The characteristics of freight options
	7.3	Option strategies for freight hedging purposes
		7.3.1	Dry-bulk freight option hedge
			7.3.1.1	Case 1: The shipowner’s hedge – buying a protective put (floorlet)
			7.3.1.2	Case 2: The charterer’s hedge – buying a protective call (caplet)
			7.3.1.3	Case 3: The shipowner’s hedge – writing a covered call
			7.3.1.4	Case 4: The charterer’s hedge – writing a covered put
		7.3.2	Options versus futures/forwards
			7.3.2.1	Case 1: Options versus FFAs in a voyage hedge
			7.3.2.2	Case 2: Options versus FFAs in a time-charter hedge
		7.3.3	Tanker freight option hedges
		7.3.4	Calendar option hedges
			7.3.4.1	Case 1: Charterer’s calendar hedge
			7.3.4.2	Case 2: Shipowner’s calendar hedge
	7.4	Freight option strategies for finance purposes
		7.4.1	Example 1: Price volatility (business cycle) trading
		7.4.2	Example 2: Forward curve shape trading
	7.5	Freight option strategies for investment purposes
		7.5.1	Option spread strategies
			7.5.1.1	Case 1: Bull call spreads (or supercaps)
			7.5.1.2	Case 2: Bear call spreads (or superfloors)
			7.5.1.3	Case 3: Butterfly spreads
			7.5.1.4	Case 4: Calendar spreads
		7.5.2	Option combination strategies
			7.5.2.1	Case 1: Bottom (or long) straddles (or straddle purchases)
			7.5.2.2	Case 2: Top (or short) straddles (or straddle writes)
			7.5.2.3	Case 3: Bottom (or long) strips
			7.5.2.4	Case 4: Top (or short) strips
			7.5.2.5	Case 5: Bottom (or long) straps
			7.5.2.6	Case 6: Top (or short) straps
			7.5.2.7	Case 7: Bottom (or long) strangles (or bottom vertical combination)
			7.5.2.8	Case 8: Top (or short) strangles (or top vertical combination)
		7.5.3	Freight option strategies for arbitrage purposes
			7.5.3.1	Case 1: Conversions
			7.5.3.2	Case 2: Reversals
			7.5.3.3	Case 3: Boxes
				7.5.3.3.1 Example 1: Short box strategy
				7.5.3.3.2 Example 2: Long box strategy
	7.6	Summary of freight option strategies
	7.7	Economics and empirical evidence on freight options
		7.7.1	Option pricing
		7.7.2	Freight option dynamics and information transmission across physical and derivative freight markets
	7.8	Summary
8	Market risk measurement and management in shipping markets
	8.1	Introduction
	8.2	What is Value-at-Risk (VaR)?
	8.3	Various types of Value-at-Risk models
		8.3.1	Non-parametric models
			8.3.1.1	Historical simulation (HS)
			8.3.1.2	Hybrid historical simulation (HHS)
		8.3.2	Parametric models
			8.3.2.1	The variance-covariance method
			8.3.2.2	Random walk model (Exponentially Weighted Moving Average, EWMA)
			8.3.2.3	Integrated GARCH-RiskMetrics VaR
				8.3.2.3.1 Example 1: Estimating daily 95% VaR with the RiskMetrics model for BCI route C4
			8.3.2.4	Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models
		8.3.3	Semi-parametric models
			8.3.3.1	Filtered historical simulation (FHS)
	8.4	Extreme value theory
	8.5	Expected shortfall
		8.5.1	An example on the estimation of the ES
	8.6	The evaluation of VaR models: backtesting
	8.7	Practical examples on estimating market risk in shipping
		8.7.1	Estimating multiperiod risk for freight rate exposures when freight rate fixtures do not overlap
		8.7.2	Estimating the VaR by scaling volatility with the square root of time
		8.7.3	Estimating medium-term VaR
			8.7.3.1	Case 1: VaR estimation with volatility scaling
			8.7.3.2	Case 2: VaR estimation by applying the scaling law
			8.7.3.3	Case 3: Estimating the portfolio’s risk for freight rate exposures
	8.8	Summary
9	Bunker price derivatives
	9.1	Introduction
	9.2	The bunker market
	9.3	Key economic variables affecting the bunker market
	9.4	Forward bunker agreements
	9.5	The bunker fuel oil futures market
		9.5.1	Early efforts on bunker fuel oil futures
		9.5.2	Cross-hedging bunker price risk
		9.5.3	The market of bunker futures contracts
	9.6	Bunker swaps
	9.7	Bunker options
		9.7.1	Bunker collars
			9.7.1.1	Case 1: Zero-cost collars
			9.7.1.2	Case 2: Participating collars
		9.7.2	Swaptions
	9.8	Summary
10	Vessel value derivatives
	10.1	Introduction
	10.2	The Forward Ship Value Agreements (FoSVAs) and Sale & Purchase Forward Agreements (SPFAs)
	10.3	Practical applications of SPFAs
		10.3.1	Hedging vessel price risk using an SPFA contract
		10.3.2	Vessel hedging with a multiple maturity SPFA
	10.4	Pricing SPFA contracts
	10.5	Baltic Ship Recycling Assessments (BSRAs)
		10.5.1	Overview of the vessel scrapping industry
	10.6	Summary
11	Foreign exchange derivatives
	11.1	Introduction
	11.2	Money market hedging
	11.3	Currency forwards and futures
		11.3.1	Hedging an expected cash outflow
		11.3.2	Hedging an expected cash inflow
		11.3.3	Speculating currency trade
	11.4	Currency swaps
		11.4.1	Swapping liabilities
		11.4.2	Swapping transaction exposures
	11.5	Currency options
	11.6	Comparison of derivative transactions in the currency market
		11.6.1	Case 1: Alternative trading strategies
			11.6.1.1 Alternative 1: Money market trade
			11.6.1.2 Alternative 2: Currency forward trade
			11.6.1.3 Alternative 3: Currency options trade 1
			11.6.1.4 Alternative 4: Currency options trade 2
		11.6.2	Case 2: Alternative hedging strategies
			11.6.2.1	Alternative 1: Remain unhedged
			11.6.2.2	Alternative 2: Currency forward hedge
			11.6.2.3	Alternative 3: Money market hedge
			11.6.2.4	Alternative 4: Currency futures hedge
			11.6.2.5	Alternative 5: Currency options hedge
	11.7	Summary
12	Interest rate derivatives
	12.1	Introduction
	12.2	The underlying assets
		12.2.1	Treasury bonds and notes
		12.2.2	Treasury bills
		12.2.3	Eurodollar
		12.2.4	London Interbank Offer Rate
	12.3	Forward Rate Agreements (FRAs)
	12.4	Interest rate futures
		12.4.1	Hedging positions
		12.4.2	Pricing of contracts
		12.4.3	Hedging and trading applications
			12.4.3.1	Case 1: Trading with Eurodollar futures
			12.4.3.2	Case 2: Hedging with Eurodollar futures
			12.4.3.3	Case 3: Hedging with T-Bond futures
			12.4.3.4	Case 4: Hedging with T-Bill futures
			12.4.3.5	Case 5: Interest rate futures spreads
	12.5	Interest rate swaps
		12.5.1	The comparative advantage in an interest rate swap
		12.5.2	Shipowner’s schedule of payments in an interest rate swap
		12.5.3	Exotic interest rate swaps
	12.6	Interest rate options
		12.6.1	Interest rate caps
		12.6.2	Interest rate floors
		12.6.3	Interest rate collars
	12.7	Summary
13	Credit risk and credit derivatives
	13.1	Introduction
	13.2	Sources of credit risk in the shipping business
	13.3	Types and measures of credit risk
		13.3.1	Types of credit risk
		13.3.2	Measures of credit risk
			13.3.2.1	Credit ratings and credit rating agencies (CRAs)
				13.3.2.1.1 Credit ratings in the shipping industry
				13.3.2.1.2 Credit ratings transitions
				13.3.2.1.3 Estimating ratings transitions matrices
			13.3.2.2	Credit spreads of shipping bonds
			13.3.2.3	Estimating probabilities of defaults (PDs) from bond prices
	13.4	Credit scoring models
		13.4.1	Financial accounting measures of credit risk
		13.4.2	Default risk drivers of shipping bank loans
		13.4.3	The Basel framework
	13.5	Structural models of credit risk
		13.5.1	Estimating probabilities of defaults (PDs) using the Merton model
	13.6	Credit risk in derivative transactions
		13.6.1	Credit risk in OTC FFA contracts
	13.7	Credit risk in bunker fuel oil transactions
	13.8	Credit risk management
		13.8.1	The use of collateral for credit risk management
		13.8.2	Credit enhancements
		13.8.3	Diversification as a tool for credit risk management
		13.8.4	Downgrade triggers and credit risk management
		13.8.5	Netting of contracts
		13.8.6	Credit Value-at-Risk (VaR)
		13.8.7	Credit derivatives
			13.8.7.1	Credit Default Swap (CDS)
			13.8.7.2	Total Return Swap (TRS)
			13.8.7.3	Credit Spread Option (CSO)
	13.9	Summary
14	Statistical tools for risk management in shipping
	14.1	Introduction
	14.2	Data sources and methods
	14.3	Descriptive statistics and the moments of random variables
		14.3.1	Measures of central tendency (location) – first moments
			14.3.1.1	Arithmetic mean
			14.3.1.2	Median
			14.3.1.3	Mode
			14.3.1.4	Geometric mean
			14.3.1.5	The choice of measure for the first moment (location)
		14.3.2	Measures of dispersion – second moments of the data
			14.3.2.1	Range
			14.3.2.2	Interquartile range
			14.3.2.3	Variance and standard deviation
			14.3.2.4	Period returns
		14.3.3	Measures of relative dispersion – the Coefficient of Variation (CV)
		14.3.4	Measures of skewness – the third moment of the data
		14.3.5	Measures of kurtosis – the fourth moment of the data
		14.3.6	Measuring the relationship between two variables – covariance and correlation
		14.3.7	Examples of calculating descriptive statistics in freight rate data
			14.3.7.1	Data recorded at different frequencies
		14.3.8	Measuring causal relationships between variables – simple and multiple regression analysis
			14.3.8.1	Deriving the OLS (Ordinary Least Squares) estimators
			14.3.8.2	Properties of the fitted OLS line
			14.3.8.3	The problem of statistical inference
			14.3.8.4	Goodness of fit: R2 – The coefficient of determination
			14.3.8.5	Extension of results to multivariate regression
		14.3.9	Time-series models, Autoregressive Integrated Moving Average (ARIMA)
			14.3.9.1	Moving Average (MA) processes
			14.3.9.2	Autoregressive processes
			14.3.9.3	ARMA processes and the Box–Jenkins approach
	14.4	Time-varying volatility models
		14.4.1	Moving averages estimates of variance
		14.4.2	Exponentially Weighted Moving Average (EWMA)
		14.4.3	Realised volatility models
		14.4.4	The class of ARCH and GARCH models
			14.4.4.1	Introduction to ARCH and GARCH models
			14.4.4.2	Asymmetric GARCH models
			14.4.4.3	GJR Threshold GARCH model
			14.4.4.4	Exponential GARCH model
			14.4.4.5	GARCH in mean
			14.4.4.6	Markov regime switching GARCH models
			14.4.4.7	Multivariate GARCH models
			14.4.4.8	Stochastic volatility models
			14.4.4.9	Implied volatility
	14.5	Forecasting volatility
		14.5.1	Historical volatility forecast
		14.5.2	Exponential Weighted Moving Average (EWMA) volatility forecast
		14.5.3	GARCH models forecast
	14.6	Summary
Bibliography
Index