The effect of underreporting on LIBOR rates

On May 29, 2008, the Wall Street Journal reported that several large international banks were reporting unjustifiably low LIBOR rates. Since then two large banks, Barclays and UBS, have paid significant fines for manipulating their LIBOR rates, and additional banks are expected to be fined. This paper investigates whether the underreporting of LIBOR rates by some banks significantly affected the reported LIBOR rate by testing whether there was a significant change in the relationship between the LIBOR rate and another rate that reflects the default risk of banks.     

LIBOR as a Keynesian Beauty Contest: A Process of Endogenous Deception

This paper uses the Keynesian Beauty Contest as a theoretical framework to analyse the London Interbank Offered Rate (LIBOR) fixing mechanism, where the actual money market rate is seen as a fundamental value towards which the LIBOR should aim. By treating the LIBOR as the outcome of a particular kind of p-beauty contest game, in which players (LIBOR banks) are guided by higher order beliefs, a process is created whereby they are not solely dependent on their own incentives and constraints. Instead, potential deception is generated endogenously though the fixing process itself, resulting in systematic deviations of the LIBOR from its fundamental value.     

Value at risk estimation by threshold stochastic volatility model

This article proposes a threshold stochastic volatility model that generates volatility forecasts specifically designed for value at risk (VaR) estimation. The method incorporates extreme downside shocks by modelling left-tail returns separately from other returns. Left-tail returns are generated with a t-distributional process based on the historically observed conditional excess kurtosis. This specification allows VaR estimates to be generated with extreme downside impacts, yet remains empirically widely applicable. This article applies the model to daily returns of seven major stock indices over a 22-year period and compares its forecasts to those of several other forecasting methods. Based on back-testing outcomes and likelihood ratio tests, the new model provides reliable estimates and outperforms others.     

Testing uncovered interest rate parity using LIBOR

We test uncovered interest rate parity (UIP) using London InterBank Offered Rate (LIBOR) interest rates for a wide range of maturities. In contrast to other markets, LIBOR markets have minimal frictions. Whereas most previous studies reject UIP, we find that UIP holds for several short-term LIBOR maturities using block bootstrap panel unit root tests suggested by Palm et al. (2011) and cointegration techniques by Westerlund (2007). Furthermore, the estimation results suggest that the speed of adjustment to the long-run equilibrium marginally differs across the maturity of the underlying instrument, thus supporting the efficient market hypothesis.     

An analysis of extreme movements of exchange rates of the main currencies traded in the Foreign Exchange market

This article analyses the extreme movements of exchange rates of the seven main currencies traded in the Foreign Exchange market against the US dollar: Euro, British pound, Canadian dollar, Japanese Yen, Swiss franc, Australian dollar and New Zealand dollar by using tail index indicators. Payaslio?lu (2009) considers the case of the Turkish exchange rate using the traditional Hill (1975) estimator as a tool. In this article, we employ also an alternative estimator proposed in Iglesias and Linton (2009) that is shown to have, in some cases, improved finite sample properties and it provides substantially different results versus the Hill estimator. We find that for the Euro, Japanese Yen, Swiss franc, Canadian, Australian and New Zealand dollars, the Hill estimator provides a better measure to analyse the extreme behaviour; while for the British pound, the Iglesias and Linton alternative estimator is superior by using Hausman-type tests of misspecification. Measures of value at risk are also provided for the seven markets. We also find that the largest estimated value at risk by far is for the Japanese Yen, followed by the Swiss franc, the Canadian dollar, the Euro, the New Zealand dollar and the Australian dollar. The UK pound has the smallest value at risk when extreme movements occur.     

The pricing and hedging of structured notes with systematic jump risk: An analysis of the USD knock-out reversed swap

Most of the interest rate derivative pricing models are jump-diffusion models, where the jump risk is assumed diversifiable. In this paper, we propose a Heath–Jarrow–Morton model with systematic jump risk to derive the no-arbitrage condition using Esscher transformation. Based on the Heath–Jarrow–Morton model with systematic jump risk, the dynamic process of the LIBOR market model with systematic jump risk is then developed. By decomposing the USD knock-out reversed swap into three derivative components, i.e., interest rate swap, interest rate digital call (IRDC) and cap, the pricing of the swap can be obtained from the dynamic process of the LIBOR market model with systematic jump risk. We show how the swap issuers/investors can hedge the swap risk using these three derivative components. The numerical analyses are conducted to show the impact of jump risk on the values of IRDC, cap and swap.     

Energy portfolio risk management using time-varying extreme value copula methods

This work is concerned with the statistical modeling of the dependence structure between three energy commodity markets (WTI crude oil, natural gas and heating oil) using the concept of copulas and proposes a method for estimating the Value at risk (VaR) of energy portfolio based on the combination of time series models with models of the extreme value theory before fitting a copula. Each return series is modeled by AR-(FI) GARCH univariate model. Then, we fit the GPD distribution to the tails of the residuals to model marginal residuals distributions. The extreme value copula to the iid residuals is fitted and we simulate from it to construct N portfolios and estimate VaR. As a first step, the method is applied to a two-dimensional energy portfolio. In second step, we extend method in trivariate context to measure VaR of three-dimensional energy portfolio. Dependences between residuals are modeled using a trivariate nested Gumbel copulas. Methods proposed are compared with various univariate and multivariate conventional VaR methods. The reported results demonstrate that GARCH-t, conditional EVT and FIGARCH extreme value copula methods produce acceptable estimates of risk both for standard and more extreme VaR quantiles. Generally, copula methods are less accurate compared with their predictive performances in the case of portfolio composed of exchange market indices.     

Linearized Hamiltonian of the LIBOR market model: analytical and empirical results

The linearized Hamiltonian model is proposed to extend the London Interbank Offered Rate (LIBOR) Market Model (LMM). Firstly, we studied the Hamiltonian of LMM in the framework of quantum finance, and the nontrivial upper triangle form of LIBOR drift is derived. The linearized Hamiltonian is derived to improve the explanatory capability of the model for market data. Our approach uses one more parameter to explain the initial condition and the model can be used to calibrate LIBORs with extremely high accuracy. Furthermore, the market time index is required for applying the model to multi-LIBOR, and the results imply that the LIBOR future time lattice becomes shorter as one goes from near future to distant future.     

Early warning signals using AVaRs of infinitely divisible GARCH models — evidence from stock index markets

Classical time series models have failed to properly assess the risks that are associated with large adverse stock price behaviour. This article contributes to autoregressive moving average model–GARCH (ARMA–GARCH) models with standard infinitely divisible innovations and assesses the performance of these models by comparing them with other time series models that have normal innovation. We discuss the limitations of value at risk (VaR) and aim to develop early warning signal models using average value at risk (AVaRs) based on the ARMA–GARCH model with standard infinitely divisible innovations. Empirical results for the daily Dow Jones Industrial Average Index, the England Financial Times Stock Exchange 100 Index and the Japan Nikkei 225 Index reveal that estimating AVaRs for the ARMA–GARCH model with standard infinitely divisible innovations offers an improvement over prevailing models for evaluating stock market risk exposure during periods of distress in financial markets and provides a suitable early warning signal in both extreme events and highly volatile markets.     

Tail risk in emerging markets of Southeastern Europe

This article examines the left-tail behaviour of returns on stocks in Southeastern Europe (SEE). We apply conditional extreme value theory (EVT) approach on daily returns of six stock market indices from SEE between 2004 and 2013. Predictive performance of value-at-risk (VaR) and expected shortfall (ES) based on EVT is compared against several alternatives, such as historical simulation and analytical approach based on GARCH with a single conditional distribution. Model backtesting with daily returns shows that EVT-based models provide more reliable VaR and ES forecasts than the alternative models in all six markets. Unlike the alternatives, the EVT-based models cannot be rejected as VaR confidence level is increased. This emphasizes the importance of extreme events in SEE markets and indicates that the ability of a model to capture volatility clustering accurately is not sufficient for a correct assessment of risk in these markets.     

The Effects of Competition on Banks’ Risk Taking

We consider the joint effect of competition and deposit insurance on risk taking by banks when bank risk is unobservable to depositors. It turns out that the magnitude of risk taking depends on the structure and side of the market in which competition takes place. If the bank is a monopoly or banks are competing only in the loan market, deposit insurance has no effect on risk taking. Banks in this situation tend to take risk, although extreme risk taking is avoided. In contrast, introducing deposit insurance increases risk taking if banks are competing for deposits. Then, deposit rates become excessively high, thereby forcing banks to take extreme risks.     

Determinants of land value volatility in the U.S. Corn Belt

ABSTRACT

Understanding land value volatility and its reaction to exogenous shocks helps land owners, investors, and lenders assess risk. Land value volatility, the variance of the unpredictable component of land value growth rates, is modelled for each of the Corn Belt states in the U.S. using EGARCH. A pooled VAR system is then estimated to capture the interactions between land value determinants and land value volatility. The variables of the pooled VAR are split into negative and positive vectors to allow for asymmetric impacts. Impulse response functions are mapped. All states exhibit land value volatility clustering. Inflation, cash rent and population growth rates granger cause land value volatility. Land value volatility responses to negative shocks are greater than those to positive shocks. Lenders and investors should expect greater swings in land values after negative shocks to land value growth rates, but not an overreaction of land values from shocks to cash rent growth rates. Positive shocks to changes in interest rates increases land value volatility, but unexpected shocks to population growth rates do not have statistically significant impact on land value volatility.     

Momentum and reversals in Taiwan index futures returns during periods of extreme trading imbalance

The study analyzes the relation between a trading imbalance metric that captures data observable by investors, and future momentum and reversals in Taiwan index futures returns. Standard regression analyses do not show any significant dynamic relations between daily index futures returns and the trading imbalance, regardless of whether the trading imbalance metric is lagged, contemporaneous, or leads the index futures return. However, when the analyses are focused on periods with extreme trading imbalances I find that the daily index futures returns exhibit significant reversals following periods of extreme (low) trading imbalances and low returns. I also find some evidence of residual momentum in consecutive daily index futures returns following periods of extreme (high) trading imbalances and high returns. Trading simulation, directional accuracy, and market timing tests show these effects to be economically significant, even after accounting for transaction costs.     

The Power of the Euro–Sterling Rates in Explaining Asset Market Rates: A High‐frequency Analysis

This article makes use of high‐frequency asset market data to explain unexpected changes in interest rates using the methodology proposed by Cochrane and Piazzesi (2002) . This work departs from the existing literature because it uses UK market expectations to capture unexpected movements in the base rate, and explores its effect on a large number of asset market variables. Results indicate that the relation between asset market data and unexpected base rate changes is stronger and more consistent than the relation between asset market data and raw base rate changes. Results appear to be robust to extreme value changes.     

Politics,institutions, and outcomes: Electricity regulation in Argentina and Chile

Risk, whether market or political, is an important determinant of private investment decisions. One important risk, subject to control by the government, is the risk associated with the hold-up problem: governments can force utilities to shoulder burdensome taxes, to use input factors ineffectively, or to charge unprofitable rates for their service. To attract private investment governments must be able to make commitments to policies that are nonexpropriative (either to contracts that guarantee very high rates of return or to favorable regulatory policies). These commitments, of course, must be credible.

Judgments about the credibility of commitments to regulatoty policies are based upon two political factors: regulatory predictability and regime stability. Regulatory predictability implies that the regulatory process, in which prices and levels of service are set, is not arbitrary. If the condition of regulatory predictability holds, then investors can forecast their returns over time and hence can calculate the value of their investment. If there is regime stability, then there is minimal risk of wholesale changes in the way the government regulates the industry—the most extreme type of change being the denial of property rights, or expropriation. We argue that three characteristics of the regulatory process are, in turn, important determinants of regulatory predictability: agenda control, reversionary regulatory policy, and veto gates. Moreover, regime stability is also, in part, a function of these three characteristics. We examine our theory of political risk and regulatoty commitment by comparing the cases of Argentine and Chilean electricity investment and regulation.     

Modelling the spreading process of extreme risks via a simple agent-based model: Evidence from the China stock market

This paper focuses on investigating financial asset returns' extreme risks, which are defined as the negative log-returns over a certain threshold. A simple agent-based model is constructed to explain the behavior of the market traders when extreme risks occur. We consider both the volatility clustering and the heavy tail characteristics when constructing the model. Empirical study uses the China securities index 300 daily level data and applies the method of simulated moments to estimate the model parameters. The stationarity and ergodicity tests provide evidence that the proposed model is good for estimation and prediction. The goodness-of-fit measures show that our proposed model fits the empirical data well. Our estimated model performs well in out-of-sample Value-at-Risk prediction, which contributes to the risk management.     

Does Shariah compliance make interest rate sensitivity of Islamic equities lower? An industry level analysis under different market states

This paper examines the sensitivity of the Dow Jones Islamic market index and its corresponding industry equity indices to changes in the level, slope and curvature of the U.S. term structure of interest rates over the period 1996–2015 using the quantile regression approach. The empirical results reveal that the Islamic stock market has a considerable negative exposure to interest rate risk, although a declining time pattern of interest rate sensitivity is observed. The unexpected changes in the level factor of the U.S. yield curve, closely linked to long-term interest rates, are identified as the most important interest rate factor in explaining the variability of Islamic equity returns. Furthermore, the interest rate exposure tends to be stronger during extreme bearish conditions in the stock market, possibly due to the greater pessimism and risk aversion under these market circumstances. It is also shown that Islamic equities are not different from their mainstream counterparts in terms of interest rate sensitivity, indicating that the Islamic stock market does not provide a cushion against interest rate risk.     

Overnight borrowing, interest rates and extreme value theory

We examine the dynamics of extreme values of overnight borrowing rates in an inter-bank money market before a financial crisis during which overnight borrowing rates rocketed up to (simple annual) 4000 percent. It is shown that the generalized Pareto distribution fits well to the extreme values of the interest rate distribution. We also provide predictions of extreme overnight borrowing rates using pre-crisis data. The examination of tails (extreme values) provides answers to such issues as to what are the extreme movements to be expected in financial markets; is there a possibility for even larger movements and, are there theoretical processes that can model the type of fat-tails in the observed data? The answers to such questions are essential for proper management of financial exposures and laying ground for regulations.     

The sources of contagion risk in a banking sector with foreign ownership

Foreign-dominated banking sectors, such as those prevalent in Central and Eastern Europe, are susceptible to two major sources of systemic risk: (i) linkages between local banks and (ii) linkages between a foreign parent bank and its local subsidiary. During and after the global financial crisis, the second source of risk has been stressed by local regulators. Using a nonparametric method based on extreme value theory, we analyze interdependencies in downward risk in the banking sectors of the Czech Republic, Poland, Slovakia, and Turkey during 1994–2013. We find that the risk of contagion from a foreign parent bank to its local subsidiary is substantially smaller than the risk between two local banks.     

Tail dependence analysis of stock markets using extreme value theory

Financial risk modelling frequently uses the assumption of a normal distribution when considering the return series which is inefficient if the data is not normally distributed or if it exhibits extreme tails. Estimation of tail dependence between financial assets plays a vital role in various aspects of financial risk modelling including portfolio theory and hedging amongst applications. Extreme Value Theory (EVT) provides well established methods for considering univariate and multivariate tail distributions which are useful for forecasting financial risk or modelling the tail dependence of risky assets. The empirical analysis in this article uses nonparametric measures based on bivariate EVT to investigate asymptotic dependence and estimate the degree of tail dependence of the ASX-All Ordinaries daily returns with four other international markets, viz., the S&P-500, Nikkei-225, DAX-30 and Heng-Seng for both extreme right and left tails of the return distribution. It is investigated whether the asymptotic dependence between these markets is related to the heteroscedasticity present in the logarithmic return series using GARCH filters. The empirical evidence shows that the asymptotic extreme tail dependence between stock markets does not necessarily exist and rather can be associated with the heteroscedasticity present in the financial time series of the various stock markets.