Journal of Risk and Financial Management
http://www.mdpi.com/journal/jrfm
Latest open access articles published in J. Risk Financial Manag. at http://www.mdpi.com/journal/jrfm<![CDATA[JRFM, Vol. 9, Pages 11: Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios]]>
http://www.mdpi.com/1911-8074/9/4/11
The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&amp;P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&amp;P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.Journal of Risk and Financial Management2016-10-0494Article10.3390/jrfm9040011111911-80742016-10-04doi: 10.3390/jrfm9040011Neslihan Fidan KeçeciViktor KuzmenkoStan Uryasev<![CDATA[JRFM, Vol. 9, Pages 10: On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?]]>
http://www.mdpi.com/1911-8074/9/3/10
This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR) forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et al. that constructs the forecast at the market close instead and, accordingly, it models separately the daytime and overnight return processes and their covariance. For a small cap portfolio, the bivariate VaR approach affords superior predictive ability than the ex post overnight VaR approach whereas for a large cap portfolio the results are reversed. The contrast indicates that price discovery at the market open is less efficient for small capitalization, thinly traded stocks.Journal of Risk and Financial Management2016-09-0993Article10.3390/jrfm9030010101911-80742016-09-09doi: 10.3390/jrfm9030010Ana-Maria FuertesJose Olmo<![CDATA[JRFM, Vol. 9, Pages 9: The Nexus between Social Capital and Bank Risk Taking]]>
http://www.mdpi.com/1911-8074/9/3/9
This study explores social capital and its relevance to bank risk taking across countries. Our empirical results show that the levels of bank risk taking are lower in countries with higher levels of social capital, and that the impact of social capital is mainly reflected by the reduced value of the standard deviation of return on assets. Moreover, the impact of social capital is found to be weaker when the legal system lacks strength. Furthermore, the study considers the impacts of social capital of the banks’ largest shareholders in these countries and finds that high levels of social capital present in these countries exert a negative effect on bank risk taking, but the effect is not strongly significant.Journal of Risk and Financial Management2016-07-2993Article10.3390/jrfm903000991911-80742016-07-29doi: 10.3390/jrfm9030009Wenjing XieHaoyuan DingTerence Chong<![CDATA[JRFM, Vol. 9, Pages 8: The Determinants of Equity Risk and Their Forecasting Implications: A Quantile Regression Perspective]]>
http://www.mdpi.com/1911-8074/9/3/8
Several market and macro-level variables influence the evolution of equity risk in addition to the well-known volatility persistence. However, the impact of those covariates might change depending on the risk level, being different between low and high volatility states. By combining equity risk estimates, obtained from the Realized Range Volatility, corrected for microstructure noise and jumps, and quantile regression methods, we evaluate the forecasting implications of the equity risk determinants in different volatility states and, without distributional assumptions on the realized range innovations, we recover both the points and the conditional distribution forecasts. In addition, we analyse how the the relationships among the involved variables evolve over time, through a rolling window procedure. The results show evidence of the selected variables’ relevant impacts and, particularly during periods of market stress, highlight heterogeneous effects across quantiles.Journal of Risk and Financial Management2016-07-0793Article10.3390/jrfm903000881911-80742016-07-07doi: 10.3390/jrfm9030008Giovanni BonaccoltoMassimiliano Caporin<![CDATA[JRFM, Vol. 9, Pages 7: Probability of Default and Default Correlations]]>
http://www.mdpi.com/1911-8074/9/3/7
We consider a system where the asset values of firms are correlated with the default thresholds. We first evaluate the probability of default of a single firm under the correlated assets assumptions. This extends Merton’s probability of default of a single firm under the independent asset values assumption. At any time, the distance-to-default for a single firm is derived in the system, and this distance-to-default should provide a different measure for credit rating with the correlated asset values into consideration. Then we derive a closed formula for the joint default probability and a general closed formula for the default correlation via the correlated multivariate process of the first-passage-time default correlation model. Our structural model encodes the sensitivities of default correlations with respect to the underlying correlation among firms’ asset values. We propose the disparate credit risk management from our result in contrast to the commonly used risk measurement methods considering default correlations into consideration.Journal of Risk and Financial Management2016-07-0593Article10.3390/jrfm903000771911-80742016-07-05doi: 10.3390/jrfm9030007Weiping Li<![CDATA[JRFM, Vol. 9, Pages 6: Down-Side Risk Metrics as Portfolio Diversification Strategies across the Global Financial Crisis]]>
http://www.mdpi.com/1911-8074/9/2/6
This paper features an analysis of the effectiveness of a range of portfolio diversification strategies, with a focus on down-side risk metrics, as a portfolio diversification strategy in a European market context. We apply these measures to a set of daily arithmetically-compounded returns, in U.S. dollar terms, on a set of ten market indices representing the major European markets for a nine-year period from the beginning of 2005 to the end of 2013. The sample period, which incorporates the periods of both the Global Financial Crisis (GFC) and the subsequent European Debt Crisis (EDC), is a challenging one for the application of portfolio investment strategies. The analysis is undertaken via the examination of multiple investment strategies and a variety of hold-out periods and backtests. We commence by using four two-year estimation periods and a subsequent one-year investment hold out period, to analyse a naive 1/N diversification strategy and to contrast its effectiveness with Markowitz mean variance analysis with positive weights. Markowitz optimisation is then compared to various down-side investment optimisation strategies. We begin by comparing Markowitz with CVaR, and then proceed to evaluate the relative effectiveness of Markowitz with various draw-down strategies, utilising a series of backtests. Our results suggest that none of the more sophisticated optimisation strategies appear to dominate naive diversification.Journal of Risk and Financial Management2016-06-2192Article10.3390/jrfm902000661911-80742016-06-21doi: 10.3390/jrfm9020006David AllenMichael McAleerRobert PowellAbhay Singh<![CDATA[JRFM, Vol. 9, Pages 5: Humanizing Finance by Hedging Property Values]]>
http://www.mdpi.com/1911-8074/9/2/5
The recent financial crisis triggered the greatest recession since the 1930s and had a devastating impact on households’ wealth and on their capacity to reduce their indebtedness. In the aftermath, it became clear that there is significant room for improvement in property risk management. While there has been innovation in the management of corporate finance risk, real estate has lagged behind. Now is the time to expand the range of tools available for hedging households’ risks and, thus, to advance the democratization of finance. Property equity represents the major asset in households’ portfolios in developed and undeveloped countries. The present paper analyzes a set of potential innovations in real estate risk management, such as price level-adjusted mortgages, property derivatives, and home equity value insurance. Financial institutions, households, and governments should work together to improve the performance of the financial instruments available and, thus, to help mitigate the worst impacts of economic cycles.Journal of Risk and Financial Management2016-06-1092Article10.3390/jrfm902000551911-80742016-06-10doi: 10.3390/jrfm9020005Jaume Roig Hernando<![CDATA[JRFM, Vol. 9, Pages 4: Application of Vine Copulas to Credit Portfolio Risk Modeling]]>
http://www.mdpi.com/1911-8074/9/2/4
In this paper, we demonstrate the superiority of vine copulas over conventional copulas when modeling the dependence structure of a credit portfolio. We show statistical and economic implications of replacing conventional copulas by vine copulas for a subportfolio of the Euro Stoxx 50 and the S&amp;P 500 companies, respectively. Our study includes D-vines and R-vines where the bivariate building blocks are chosen from the Gaussian, the t and the Clayton family. Our findings are (i) the conventional Gauss copula is deficient in modeling the dependence structure of a credit portfolio and economic capital is seriously underestimated; (ii) D-vine structures offer a better statistical fit to the data than classical copulas, but underestimate economic capital compared to R-vines; (iii) when mixing different copula families in an R-vine structure, the best statistical fit to the data can be achieved which corresponds to the most reliable estimate for economic capital.Journal of Risk and Financial Management2016-06-0792Article10.3390/jrfm902000441911-80742016-06-07doi: 10.3390/jrfm9020004Marco GeidoschMatthias Fischer<![CDATA[JRFM, Vol. 9, Pages 3: Revisiting Structural Modeling of Credit Risk—Evidence from the Credit Default Swap (CDS) Market]]>
http://www.mdpi.com/1911-8074/9/2/3
The ground-breaking Black-Scholes-Merton model has brought about a generation of derivative pricing models that have been successfully applied in the financial industry. It has been a long standing puzzle that the structural models of credit risk, as an application of the same modeling paradigm, do not perform well empirically. We argue that the ability to accurately compute and dynamically update hedge ratios to facilitate a capital structure arbitrage is a distinctive strength of the Black-Scholes-Merton’s modeling paradigm which could be utilized in credit risk models as well. Our evidence is economically significant: We improve the implementation of a simple structural model so that it is more suitable for our application and then devise a simple capital structure arbitrage strategy based on the model. We show that the trading strategy persistently produced substantial risk-adjusted profit.Journal of Risk and Financial Management2016-05-1092Article10.3390/jrfm902000331911-80742016-05-10doi: 10.3390/jrfm9020003Zhijian HuangYuchen Luo<![CDATA[JRFM, Vol. 9, Pages 2: VaR and CVaR Implied in Option Prices]]>
http://www.mdpi.com/1911-8074/9/1/2
VaR (Value at Risk) and CVaR (Conditional Value at Risk) are implied by option prices. Their relationships to option prices are derived initially under the pricing measure. It does not require assumptions about the distribution of portfolio returns. The effects of changes of measure are modest at the short horizons typically used in applications. The computation of CVaR from option price is very convenient, because this measure is not elicitable, making direct comparisons of statistical inferences from market data problematic.Journal of Risk and Financial Management2016-02-2991Article10.3390/jrfm901000221911-80742016-02-29doi: 10.3390/jrfm9010002Giovanni Barone Adesi<![CDATA[JRFM, Vol. 9, Pages 1: The Two Defaults Scenario for Stressing Credit Portfolio Loss Distributions]]>
http://www.mdpi.com/1911-8074/9/1/1
The impact of a stress scenario of default events on the loss distribution of a credit portfolio can be assessed by determining the loss distribution conditional on these events. While it is conceptually easy to estimate loss distributions conditional on default events by means of Monte Carlo simulation, it becomes impractical for two or more simultaneous defaults as then the conditioning event is extremely rare. We provide an analytical approach to the calculation of the conditional loss distribution for the CreditRisk + portfolio model with independent random loss given default distributions. The analytical solution for this case can be used to check the accuracy of an approximation to the conditional loss distribution whereby the unconditional model is run with stressed input probabilities of default (PDs). It turns out that this approximation is unbiased. Numerical examples, however, suggest that the approximation may be seriously inaccurate but that the inaccuracy leads to overestimation of tail losses and, hence, the approach errs on the conservative side.Journal of Risk and Financial Management2015-12-3191Article10.3390/jrfm901000111911-80742015-12-31doi: 10.3390/jrfm9010001Dirk Tasche<![CDATA[JRFM, Vol. 8, Pages 369-374: The Fundamental Equation in Tourism Finance]]>
http://www.mdpi.com/1911-8074/8/4/369
The purpose of the paper is to present the fundamental equation in tourism finance that connects tourism research to empirical finance and financial econometrics. The energy industry, which includes, oil, gas and bio-energy fuels, together with the tourism industry, are two of the most important industries in the world today in terms of employment and generating income. The primary purpose in attracting domestic and international tourists to a country, region or city is to maximize tourism expenditure. The paper will concentrate on daily tourism expenditure, regardless of whether such data might be readily available. If such data are not available, a practical method is presented to calculate the appropriate data.Journal of Risk and Financial Management2015-12-2284Commentary10.3390/jrfm80403693693741911-80742015-12-22doi: 10.3390/jrfm8040369Michael McAleer<![CDATA[JRFM, Vol. 8, Pages 355-368: On a Discrete Interaction Risk Model with Delayed Claims]]>
http://www.mdpi.com/1911-8074/8/4/355
We study a discrete-time interaction risk model with delayed claims within the framework of the compound binomial model. Using the technique of generating functions, we derive both a recursive formula and a defective renewal equation for the expected discounted penalty function. As applications, the probabilities of ruin and the joint distributions of the surplus one period to ruin and the deficit at ruin are investigated. Numerical illustrations are also given.Journal of Risk and Financial Management2015-09-2984Article10.3390/jrfm80403553553681911-80742015-09-29doi: 10.3390/jrfm8040355He LiuZhenhua Bao<![CDATA[JRFM, Vol. 8, Pages 337-354: An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures]]>
http://www.mdpi.com/1911-8074/8/3/337
In this study, we try to examine whether the forecast errors obtained by the ANN models affect the breakout of financial crises. Additionally, we try to investigate how much the asymmetric information and forecast errors are reflected on the output values. In our study, we used the exchange rate of USD/TRY (USD), the Borsa Istanbul 100 Index (BIST), and gold price (GP) as our output variables of our Artificial Neural Network (ANN) models. We observe that the predicted ANN model has a strong explanation capability for the 2001 and 2008 crises. Our calculations of some symmetry measures such as mean absolute percentage error (MAPE), symmetric mean absolute percentage error (sMAPE), and Shannon entropy (SE), clearly demonstrate the degree of asymmetric information and the deterioration of the financial system prior to, during, and after the financial crisis. We found that the asymmetric information prior to crisis is larger as compared to other periods. This situation can be interpreted as early warning signals before the potential crises. This evidence seems to favor an asymmetric information view of financial crises.Journal of Risk and Financial Management2015-08-2483Article10.3390/jrfm80303373373541911-80742015-08-24doi: 10.3390/jrfm8030337Seyma CavdarAlev Aydin<![CDATA[JRFM, Vol. 8, Pages 311-336: Volatility Forecast in Crises and Expansions]]>
http://www.mdpi.com/1911-8074/8/3/311
We build a discrete-time non-linear model for volatility forecasting purposes. This model belongs to the class of threshold-autoregressive models, where changes in regimes are governed by past returns. The ability to capture changes in volatility regimes and using more accurate volatility measures allow outperforming other benchmark models, such as linear heterogeneous autoregressive model and GARCH specifications. Finally, we show how to derive closed-form expression for multiple-step-ahead forecasting by exploiting information about the conditional distribution of returns.Journal of Risk and Financial Management2015-08-0583Article10.3390/jrfm80303113113361911-80742015-08-05doi: 10.3390/jrfm8030311Sergii Pypko<![CDATA[JRFM, Vol. 8, Pages 285-310: Inflation and Speculation in a Dynamic Macroeconomic Model]]>
http://www.mdpi.com/1911-8074/8/3/285
We study a monetary version of the Keen model by merging two alternative extensions, namely the addition of a dynamic price level and the introduction of speculation. We recall and study old and new equilibria, together with their local stability analysis. This includes a state of recession associated with a deflationary regime and characterized by falling employment but constant wage shares, with or without an accompanying debt crisis.Journal of Risk and Financial Management2015-07-0683Article10.3390/jrfm80302852853101911-80742015-07-06doi: 10.3390/jrfm8030285Matheus GrasselliAdrien Huu<![CDATA[JRFM, Vol. 8, Pages 266-284: Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information]]>
http://www.mdpi.com/1911-8074/8/2/266
Analyzing social systems, particularly financial markets, using a complex network approach has become one of the most popular fields within econophysics. A similar trend is currently appearing within the econometrics and finance communities, as well. In this study, we present a state-of-the-artmethod for analyzing the structure and risk within stockmarkets, treating them as complex networks using model-free, nonlinear dependency measures based on information theory. This study is the first network analysis of the stockmarket in Shanghai using a nonlinear network methodology. Further, it is often assumed that markets outside the United States and Western Europe are inherently riskier. We find that the Chinese stock market is not structurally risky, contradicting this popular opinion. We use partial mutual information to create filtered networks representing the Shanghai stock exchange, comparing them to networks based on Pearson’s correlation. Consequently, we discuss the structure and characteristics of both the presented methods and the Shanghai stock exchange. This paper provides an insight into the cutting edge methodology designed for analyzing complex financial networks, as well as analyzing the structure of the market in Shanghai and, as such, is of interest to both researchers and financial analysts.Journal of Risk and Financial Management2015-06-0182Article10.3390/jrfm80202662662841911-80742015-06-01doi: 10.3390/jrfm8020266Tao YouPaweł FiedorArtur Hołda<![CDATA[JRFM, Vol. 8, Pages 227-265: Dependency Relations among International Stock Market Indices]]>
http://www.mdpi.com/1911-8074/8/2/227
We develop networks of international stock market indices using information and correlation based measures. We use 83 stock market indices of a diversity of countries, as well as their single day lagged values, to probe the correlation and the flow of information from one stock index to another taking into account different operating hours. Additionally, we apply the formalism of partial correlations to build the dependency network of the data, and calculate the partial Transfer Entropy to quantify the indirect influence that indices have on one another. We find that Transfer Entropy is an effective way to quantify the flow of information between indices, and that a high degree of information flow between indices lagged by one day coincides to same day correlation between them.Journal of Risk and Financial Management2015-05-2982Article10.3390/jrfm80202272272651911-80742015-05-29doi: 10.3390/jrfm8020227Leonidas JuniorAsher MullokandovDror Kenett<![CDATA[JRFM, Vol. 8, Pages 198-226: Interconnected Risk Contributions: A Heavy-Tail Approach to Analyze U.S. Financial Sectors]]>
http://www.mdpi.com/1911-8074/8/2/198
This paper investigates the dynamic evolution of tail risk interdependence among U.S. banks, financial services and insurance sectors. Life and non-life insurers have been considered separately to account for their different characteristics. The tail risk interdependence measurement framework relies on the multivariate Student-t Markov switching (MS) model and the multiple-conditional value-at-risk (CoVaR) (conditional expected shortfall (CoES)) risk measures introduced in Bernardi et al. (2013), accounting for both the stylized facts of financial data and the contemporaneous multiple joint distress events. The Shapley value methodology is then applied to compose the puzzle of individual risk attributions, providing a synthetic measure of tail interdependence. Our empirical investigation finds that banks appear to contribute more to the tail risk evolution of all of the remaining sectors, followed by the financial services and the insurance sectors, showing that the insurance sector significantly contributes as well to the overall risk. We also find that the role of each sector in contributing to other sectors’ distress evolves over time according to the current predominant financial condition, implying different interdependence strength.Journal of Risk and Financial Management2015-04-0782Article10.3390/jrfm80201981982261911-80742015-04-07doi: 10.3390/jrfm8020198Mauro BernardiLea Petrella<![CDATA[JRFM, Vol. 8, Pages 181-197: The Impact of the Basel Accord on Greek Banks: A Stress Test Study]]>
http://www.mdpi.com/1911-8074/8/2/181
In this paper, we study the impact of extreme events on the loan portfolios of the Greek banking system. These portfolios are grouped into three separate groups based on the size of the bank to which they belong, in particular, large, medium, and small size. A series of extreme scenarios was performed and the increase in capital requirements was calculated for each scenario based on the standardized and internal ratings approach of the Basel II accord. The results obtained show an increase of credit risk during the crisis periods, and the differentiation of risk depending on the size of the banking organization as well as the added capital that will be needed in order to hedge that risk. The execution of the scenarios aims at studying the effects which may be brought about on the capital of the three representative banks by the appearance of adverse events.Journal of Risk and Financial Management2015-03-3182Article10.3390/jrfm80201811811971911-80742015-03-31doi: 10.3390/jrfm8020181John LeventidesAnna Donatou<![CDATA[JRFM, Vol. 8, Pages 150-180: Firm Value and Cross Listings: The Impact of Stock Market Prestige]]>
http://www.mdpi.com/1911-8074/8/1/150
This study investigates the valuation impact of a firm’s decision to cross list on a more (or less) prestigious stock exchange relative to its own domestic market. We use a network analysis methodology to derive broad market-based measures of prestige for 45 country or regional stock exchange destinations between 1990 and 2006. We find that firms cross listing in a more prestigious market enjoy significant valuation gains over the five-year period following the listing. In contrast, firms cross listing in less prestigious markets experience a significant valuation discount over this post-listing period. The reputation of the cross-border listing destinations is therefore a useful signal of firm value going forward. Our findings are consistent with the view that cross listing in a prestigious market enhances firm visibility, strengthens corporate governance, and lowers informational frictions and capital costs.Journal of Risk and Financial Management2015-03-2381Article10.3390/jrfm80101501501801911-80742015-03-23doi: 10.3390/jrfm8010150Nicola CetorelliStavros Peristiani<![CDATA[JRFM, Vol. 8, Pages 127-149: Are Women More Likely to Seek Advice than Men? Evidence from the Boardroom]]>
http://www.mdpi.com/1911-8074/8/1/127
It is commonly believed that women are more likely to seek advice than men; for example, on aspects of health or asking for directions when lost. This paper investigates whether women’s relatively greater propensity for advice seeking extends to important business decisions, specifically those involving corporate takeovers. Consistent with the evidence from other contexts, we show that the presence of female directors on target boards is positively and significantly associated with target boards seeking advice from top-ranked financial advisors. In contrast, we do not observe any significant association between the presence of female directors on bidder boards and their engagement of top-ranked financial advisors. We argue that the presence of a gender effect for target boards but not for bidder boards is consistent with less overconfident female versus male directors on bidder boards initiating fewer bids, higher litigation risk facing target boards for accepting too little, and the different type of advice sought by bidders and target firms.Journal of Risk and Financial Management2015-02-1681Article10.3390/jrfm80101271271491911-80742015-02-16doi: 10.3390/jrfm8010127Maurice LeviKai LiFeng Zhang<![CDATA[JRFM, Vol. 8, Pages 103-126: Quantification of VaR: A Note on VaR Valuation in the South African Equity Market]]>
http://www.mdpi.com/1911-8074/8/1/103
The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to implement, the Normal distribution underestimates the kurtosis and skewness of the observed financial returns. This article focuses on the evaluation of the South African equity markets in a Value-at-Risk framework. Value-at-Risk is estimated on four equity stocks listed on the Johannesburg Stock Exchange, including the FTSE/JSE TOP40 index and the S &amp; P 500 index. The statistical distribution of the financial returns is modelled using the Normal Inverse Gaussian and is compared to the financial returns modelled using the Normal, Skew t-distribution and Student t-distribution. We then estimate Value-at-Risk under the assumption that financial returns follow the Normal Inverse Gaussian, Normal, Skew t-distribution and Student t-distribution and backtesting was performed under each distribution assumption. The results of these distributions are compared and discussed.Journal of Risk and Financial Management2015-02-1381Article10.3390/jrfm80101031031261911-80742015-02-13doi: 10.3390/jrfm8010103Lesedi MabitselaEben MaréRodwell Kufakunesu<![CDATA[JRFM, Vol. 8, Pages 83-102: Quadratic Hedging of Basis Risk]]>
http://www.mdpi.com/1911-8074/8/1/83
This paper examines a simple basis risk model based on correlated geometric Brownian motions. We apply quadratic criteria to minimize basis risk and hedge in an optimal manner. Initially, we derive the Föllmer–Schweizer decomposition for a European claim. This allows pricing and hedging under the minimal martingale measure, corresponding to the local risk-minimizing strategy. Furthermore, since the mean-variance tradeoff process is deterministic in our setup, the minimal martingale- and variance-optimal martingale measures coincide. Consequently, the mean-variance optimal strategy is easily constructed. Simple pricing and hedging formulae for put and call options are derived in terms of the Black–Scholes formula. Due to market incompleteness, these formulae depend on the drift parameters of the processes. By making a further equilibrium assumption, we derive an approximate hedging formula, which does not require knowledge of these parameters. The hedging strategies are tested using Monte Carlo experiments, and are compared with results achieved using a utility maximization approach.Journal of Risk and Financial Management2015-02-0281Article10.3390/jrfm8010083831021911-80742015-02-02doi: 10.3390/jrfm8010083Hardy HulleyThomas McWalter<![CDATA[JRFM, Vol. 8, Pages 43-82: Implied and Local Volatility Surfaces for South African Index and Foreign Exchange Options]]>
http://www.mdpi.com/1911-8074/8/1/43
Certain exotic options cannot be valued using closed-form solutions or even by numerical methods assuming constant volatility. Many exotics are priced in a local volatility framework. Pricing under local volatility has become a field of extensive research in finance, and various models are proposed in order to overcome the shortcomings of the Black-Scholes model that assumes a constant volatility. The Johannesburg Stock Exchange (JSE) lists exotic options on its Can-Do platform. Most exotic options listed on the JSE’s derivative exchanges are valued by local volatility models. These models needs a local volatility surface. Dupire derived a mapping from implied volatilities to local volatilities. The JSE uses this mapping in generating the relevant local volatility surfaces and further uses Monte Carlo and Finite Difference methods when pricing exotic options. In this document we discuss various practical issues that influence the successful construction of implied and local volatility surfaces such that pricing engines can be implemented successfully. We focus on arbitrage-free conditions and the choice of calibrating functionals. We illustrate our methodologies by studying the implied and local volatility surfaces of South African equity index and foreign exchange options.Journal of Risk and Financial Management2015-01-2681Article10.3390/jrfm801004343821911-80742015-01-26doi: 10.3390/jrfm8010043Antonie KotzéRudolf OosthuizenEdson Pindza<![CDATA[JRFM, Vol. 8, Pages 17-42: Pricing a Collateralized Derivative Trade with a Funding Value Adjustment]]>
http://www.mdpi.com/1911-8074/8/1/17
The 2008 credit crisis changed the manner in which derivative trades are conducted. One of these changes is the posting of collateral in a trade to mitigate the counterparty credit risk. Another is the realization that banks are not risk-free and, as a result, cannot borrow at the risk-free rate any longer. The latter led banks to introduced the controversial adjustment to derivative prices, known as a funding value adjustment (FVA), which is interlinked with the posting of collateral. In this paper, we extend the Cox, Ross and Rubinstein (CRR) discrete-time model to include collateral and FVA. We prove that this derived model is a discrete analogue of Piterbarg’s partial differential equation (PDE), which describes the price of a collateralized derivative. The fact that the two models coincide is also verified by numerical implementation of the results that we obtain.Journal of Risk and Financial Management2015-01-2681Article10.3390/jrfm801001717421911-80742015-01-26doi: 10.3390/jrfm8010017Chadd HunzingerCoenraad Labuschagne<![CDATA[JRFM, Vol. 8, Pages 2-16: State Prices and Implementation of the Recovery Theorem]]>
http://www.mdpi.com/1911-8074/8/1/2
It is generally held that derivative prices do not contain useful predictive information, that is, information relating to the distribution of future financial variables under the real-world measure. This is because the market’s implicit forecast of the future becomes entangled with market risk preferences during derivative price formation. A result derived by Ross [1], however, recovers the real-world distribution of an equity index, requiring only current prices and mild restrictions on risk preferences. In addition to being of great interest to the theorist, the potential practical value of the result is considerable. This paper addresses implementation of the Ross Recovery Theorem. The theorem is formalised, extended, proved and discussed. Obstacles to application are identified and a workable implementation methodology is developed.Journal of Risk and Financial Management2015-01-1981Article10.3390/jrfm80100022161911-80742015-01-19doi: 10.3390/jrfm8010002Alex Backwell<![CDATA[JRFM, Vol. 8, Pages 1: Acknowledgement to Reviewers of the Journal of Risk and Financial Management]]>
http://www.mdpi.com/1911-8074/8/1/1
The editors of the Journal of Risk and Financial Management would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...]Journal of Risk and Financial Management2015-01-1281Editorial10.3390/jrfm8010001111911-80742015-01-12doi: 10.3390/jrfm8010001 Journal of Risk Financial Management Editorial Office<![CDATA[JRFM, Vol. 7, Pages 150-164: Exact Fit of Simple Finite Mixture Models]]>
http://www.mdpi.com/1911-8074/7/4/150
How to forecast next year’s portfolio-wide credit default rate based on last year’s default observations and the current score distribution? A classical approach to this problem consists of fitting a mixture of the conditional score distributions observed last year to the current score distribution. This is a special (simple) case of a finite mixture model where the mixture components are fixed and only the weights of the components are estimated. The optimum weights provide a forecast of next year’s portfolio-wide default rate. We point out that the maximum-likelihood (ML) approach to fitting the mixture distribution not only gives an optimum but even an exact fit if we allow the mixture components to vary but keep their density ratio fixed. From this observation we can conclude that the standard default rate forecast based on last year’s conditional default rates will always be located between last year’s portfolio-wide default rate and the ML forecast for next year. As an application example, cost quantification is then discussed. We also discuss how the mixture model based estimation methods can be used to forecast total loss. This involves the reinterpretation of an individual classification problem as a collective quantification problem.Journal of Risk and Financial Management2014-11-2074Article10.3390/jrfm70401501501641911-80742014-11-20doi: 10.3390/jrfm7040150Dirk Tasche<![CDATA[JRFM, Vol. 7, Pages 130-149: Risk Management of Interest Rate Derivative Portfolios: A Stochastic Control Approach]]>
http://www.mdpi.com/1911-8074/7/4/130
In this paper we formulate the Risk Management Control problem in the interest rate area as a constrained stochastic portfolio optimization problem. The utility that we use can be any continuous function and based on the viscosity theory, the unique solution of the problem is guaranteed. The numerical approximation scheme is presented and applied using a single factor interest rate model. It is shown how the whole methodology works in practice, with the implementation of the algorithm for a specific interest rate portfolio. The recent financial crisis showed that risk management of derivatives portfolios especially in the interest rate market is crucial for the stability of the financial system. Modern Value at Risk (VAR) and Conditional Value at Risk (CVAR) techniques, although very useful and easy to understand, fail to grasp the need for on-line controlling and monitoring of derivatives portfolio. The portfolios should be designed in a way that risk and return be quantified and controlled in every possible state of the world. We hope that this methodology contributes towards this direction.Journal of Risk and Financial Management2014-10-2774Article10.3390/jrfm70401301301491911-80742014-10-27doi: 10.3390/jrfm7040130Konstantinos KiriakopoulosAlexandros Koulis<![CDATA[JRFM, Vol. 7, Pages 113-129: Risk Measures and Portfolio Optimization]]>
http://www.mdpi.com/1911-8074/7/3/113
In this paper we investigate portfolio optimization under Value at Risk, Average Value at Risk and Limited Expected Loss constraints in a continuous time framework, where stocks follow a geometric Brownian motion. Analytic expressions for Value at Risk, Average Value at Risk and Limited Expected Loss are derived. We solve the problem of minimizing risk measures applied to portfolios. Moreover, the portfolio’s expected return is maximized subject to the aforementioned risk measures. We illustrate the effect of these risk measures on portfolio optimization by using numerical experiments.Journal of Risk and Financial Management2014-09-2273Article10.3390/jrfm70301131131291911-80742014-09-22doi: 10.3390/jrfm7030113Priscilla GambrahTraian Pirvu<![CDATA[JRFM, Vol. 7, Pages 110-112: Report on the Fifth International Mathematics in Finance (MiF) Conference 2014, Skukuza, Kruger National Park, South Africa]]>
http://www.mdpi.com/1911-8074/7/3/110
The Journal of Risk and Financial Management was first published in 2008, and, since its inception, has published a number of theoretical and empirical papers on various topics in risk and financial management, in pursuit of its stated goal of advancing knowledge and understanding in the practice of risk and financial management through the publication of high quality papers that are relevant to practitioners in the field.[...]Journal of Risk and Financial Management2014-09-1973Brief Report10.3390/jrfm70301101101121911-80742014-09-19doi: 10.3390/jrfm7030110Michael McAleer<![CDATA[JRFM, Vol. 7, Pages 80-109: Asymmetric Realized Volatility Risk]]>
http://www.mdpi.com/1911-8074/7/2/80
In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredictability brings considerably more uncertainty to the empirically relevant ex ante distribution of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility model, which incorporates the fact that realized volatility series are systematically more volatile in high volatility periods. Returns in this framework display time varying volatility, skewness and kurtosis. We provide a detailed account of the empirical advantages of the model using data on the S&amp;P 500 index and eight other indexes and stocks.Journal of Risk and Financial Management2014-06-2572Article10.3390/jrfm7020080801091911-80742014-06-25doi: 10.3390/jrfm7020080David AllenMichael McAleerMarcel Scharth<![CDATA[JRFM, Vol. 7, Pages 67-79: Refining Our Understanding of Beta through Quantile Regressions]]>
http://www.mdpi.com/1911-8074/7/2/67
The Capital Asset Pricing Model (CAPM) has been a key theory in financial economics since the 1960s. One of its main contributions is to attempt to identify how the risk of a particular stock is related to the risk of the overall stock market using the risk measure Beta. If the relationship between an individual stock’s returns and the returns of the market exhibit heteroskedasticity, then the estimates of Beta for different quantiles of the relationship can be quite different. The behavioral ideas first proposed by Kahneman and Tversky (1979), which they called prospect theory, postulate that: (i) people exhibit “loss-aversion” in a gain frame; and (ii) people exhibit “risk-seeking” in a loss frame. If this is true, people could prefer lower Beta stocks after they have experienced a gain and higher Beta stocks after they have experienced a loss. Stocks that exhibit converging heteroskedasticity (22.2% of our sample) should be preferred by investors, and stocks that exhibit diverging heteroskedasticity (12.6% of our sample) should not be preferred. Investors may be able to benefit by choosing portfolios that are more closely aligned with their preferences.Journal of Risk and Financial Management2014-05-2172Article10.3390/jrfm702006767791911-80742014-05-21doi: 10.3390/jrfm7020067Allen AtkinsPin Ng<![CDATA[JRFM, Vol. 7, Pages 45-66: International Diversification Versus Domestic Diversification: Mean-Variance Portfolio Optimization and Stochastic Dominance Approaches]]>
http://www.mdpi.com/1911-8074/7/2/45
This paper applies the mean-variance portfolio optimization (PO) approach and the stochastic dominance (SD) test to examine preferences for international diversification versus domestic diversification from American investors’ viewpoints. Our PO results imply that the domestic diversification strategy dominates the international diversification strategy at a lower risk level and the reverse is true at a higher risk level. Our SD analysis shows that there is no arbitrage opportunity between international and domestic stock markets; domestically diversified portfolios with smaller risk dominate internationally diversified portfolios with larger risk and vice versa; and at the same risk level, there is no difference between the domestically and internationally diversified portfolios. Nonetheless, we cannot find any domestically diversified portfolios that stochastically dominate all internationally diversified portfolios, but we find some internationally diversified portfolios with small risk that dominate all the domestically diversified portfolios.Journal of Risk and Financial Management2014-05-0872Article10.3390/jrfm702004545661911-80742014-05-08doi: 10.3390/jrfm7020045Fathi AbidPui LeungMourad MrouaWing Wong<![CDATA[JRFM, Vol. 7, Pages 28-44: Remuneration Committee, Board Independence and Top Executive Compensation]]>
http://www.mdpi.com/1911-8074/7/2/28
In this study, we examine whether the levels and structures of top executive compensation vary discernibly with different levels of board independence. We also examine how the newly mandated adoption of the remuneration committee (RC) in Taiwan affects the board independence-executive pay relation. The mandatory establishment of RC for Taiwanese public firms, starting in 2011, is intended to strengthen the reasonableness and effectiveness of the executive compensation structure; thus, it is timely and of interest for practitioners and regulators to understand whether the establishment of RCs can effectively discipline top executive compensation policies. We first find that CEOs of firms that do not appoint independent directors have greater levels of annual pay than is the case for firms that have appointed independent directors, after controlling for the effect of CEO pay determinants. Second, we find that CEO pay for early RC adopters is more closely related to firm performance. Third, we find that the establishing of RCs may decrease CEO pay and enhance the pay-performance association, in particular for firms that have not appointed independent directors; however, this effect is not found to be statistically significant.Journal of Risk and Financial Management2014-04-1572Article10.3390/jrfm702002828441911-80742014-04-15doi: 10.3390/jrfm7020028Chii-Shyan KuoShih-Ti Yu<![CDATA[JRFM, Vol. 7, Pages 13-27: Validation of the Merton Distance to the Default Model under Ambiguity]]>
http://www.mdpi.com/1911-8074/7/1/13
Bharath and Shumway (2008) provide evidence that shows that it is the functional form of Merton’s (1974) distance to default (DD) model that makes it useful and important for predicting defaults. In this paper, we investigate whether the default predictability of the Merton DD model would be affected by taking investors’ ambiguity aversion into consideration. The Cox proportional hazard model is used to compare the forecasting power of Bharath and Shumway’s naive model, which retains the functional form of the Merton DD model and computes the default probability in a naive way, with our new model, which treats investors’ ambiguity aversion as additional information. We provide evidence to show that our new model performs better than Bharath and Shumway’s naive model. In addition, our empirical results show that the statistical significance of Bharath and Shumway’s naive default probability is retained in the credit default swap (CDS) spread regressions, though the sign of the coefficient is changed. However, both the sign and the statistical significance of our model are retained in the CDS spread regressions.Journal of Risk and Financial Management2014-03-2571Article10.3390/jrfm701001313271911-80742014-03-25doi: 10.3390/jrfm7010013Wei-ling ChenLeh-chyan So<![CDATA[JRFM, Vol. 7, Pages 1-12: Revisiting the Performance of MACD and RSI Oscillators]]>
http://www.mdpi.com/1911-8074/7/1/1
Chong and Ng (2008) find that the Moving Average Convergence–Divergence (MACD) and Relative Strength Index (RSI) rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD(12,26,0) and RSI(21,50) rules consistently generate significant abnormal returns in the Milan Comit General and the S&amp;P/TSX Composite Index. In addition, the RSI(14,30/70) rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors’ belief in these two technical indicators in different developed markets.Journal of Risk and Financial Management2014-02-2671Article10.3390/jrfm70100011121911-80742014-02-26doi: 10.3390/jrfm7010001Terence ChongWing-Kam NgVenus Liew<![CDATA[JRFM, Vol. 6, Pages 31-61: Testing for a Single-Factor Stochastic Volatility in Bivariate Series]]>
http://www.mdpi.com/1911-8074/6/1/31
This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption that the log of squared measurement error isnormally distributed. The empirical size and power of the test are examined in Monte Carloexperiments. We apply the test to the Asian stock market indices.Journal of Risk and Financial Management2013-12-1961Article10.3390/jrfm601003131611911-80742013-12-19doi: 10.3390/jrfm6010031Masaru ChibaMasahito Kobayashi<![CDATA[JRFM, Vol. 6, Pages 6-30: A Non-Parametric and Entropy Based Analysis of the Relationship between the VIX and S&P 500]]>
http://www.mdpi.com/1911-8074/6/1/6
This paper features an analysis of the relationship between the S&amp;P 500 Index and the VIX using daily data obtained from the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between the S&amp;P 500 daily return series and a similar series for the VIX in terms of a long sample drawn from the CBOE from 1990 to mid 2011 and a set of returns from SIRCA’s TRTH datasets from March 2005 to-date. This shorter sample, which captures the behavior of the new VIX, introduced in 2003, is divided into four sub-samples which permit the exploration of the impact of the Global Financial Crisis. We apply a series of non-parametric based tests utilizing entropy based metrics. These suggest that the PDFs and CDFs of these two return distributions change shape in various subsample periods. The entropy and MI statistics suggest that the degree of uncertainty attached to these distributions changes through time and using the S&amp;P 500 return as the dependent variable, that the amount of information obtained from the VIX changes with time and reaches a relative maximum in the most recent period from 2011 to 2012. The entropy based non-parametric tests of the equivalence of the two distributions and their symmetry all strongly reject their respective nulls. The results suggest that parametric techniques do not adequately capture the complexities displayed in the behavior of these series. This has practical implications for hedging utilizing derivatives written on the VIX.Journal of Risk and Financial Management2013-10-2161Article10.3390/jrfm60100066301911-80742013-10-21doi: 10.3390/jrfm6010006David AllenMichael McAleerRobert PowellAbhay Singh<![CDATA[JRFM, Vol. 6, Pages 4-5: Publisher’s Note: Journal of Risk and Financial Management]]>
http://www.mdpi.com/1911-8074/6/1/4
The Journal of Risk and Financial Management (JRFM) is published in full open access by MDPI as of 1 October 2013, when MDPI took over the ownership of the journal. So far, this journal has been published elsewhere in yearly volumes (one issue per yearly volume) since 2008, with a total of 25 papers released up to this moment [1]. Starting from 1 January 2014, the journal will be published in quarterly issues. [...]Journal of Risk and Financial Management2013-10-0361Editorial10.3390/jrfm6010004451911-80742013-10-03doi: 10.3390/jrfm6010004Shu-Kun Lin<![CDATA[JRFM, Vol. 6, Pages 1-3: The Journal of Risk and Financial Management in Open Access]]>
http://www.mdpi.com/1911-8074/6/1/1
Financial economics and econometrics have advanced rapidly in recent years, in terms of coverage of topics, the creation of new data sources, the availability of existing high frequency and ultra-high frequency tick data, the growing importance of international financial analysis, the technicality of research topics, and the number of papers and journals publishing such theoretical and practical research. [...]Journal of Risk and Financial Management2013-10-0161Editorial10.3390/jrfm6010001131911-80742013-10-01doi: 10.3390/jrfm6010001Michael McAleer<![CDATA[JRFM, Vol. 5, Pages 115-130: Technical Efficiency and Port Competition: Revisiting the Bohai Economic Rim, China]]>
http://www.mdpi.com/1911-8074/5/1/115
The Bohai Economic Rim plays an important role in supporting China’s economic growth. For this research, we selected nine main ports in the region to study whether intra-port competition or corporatization would improve efficiency. Using a panel fixed effect model and stochastic frontier model, we found that the technical efficiency of selected ports is significantly influenced by the time of the initial public offering than by regional competition. The results are supportive and encouraging for policy makers to move toward the decentralized port governance in China.Journal of Risk and Financial Management2012-12-3151Article10.3390/jrfm50101151151301911-80742012-12-31doi: 10.3390/jrfm5010115Grace WangChen Gao<![CDATA[JRFM, Vol. 5, Pages 78-114: Modelling the Effects of Oil Prices on Global Fertilizer Prices and Volatility]]>
http://www.mdpi.com/1911-8074/5/1/78
The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, ARDL model, and alternative volatility models, including GARCH, EGARCH, and GJR models, are used to investigate the relationship between crude oil price and six global fertilizer prices. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price while the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods.Journal of Risk and Financial Management2012-12-3151Article10.3390/jrfm5010078781141911-80742012-12-31doi: 10.3390/jrfm5010078Ping-Yu ChenChia-Lin ChangChi-Chung ChenMichael McAleer<![CDATA[JRFM, Vol. 5, Pages 59-77: The Behaviour of Small Investors in the Hong Kong Derivatives Markets: A Factor Analysis]]>
http://www.mdpi.com/1911-8074/5/1/59
This paper investigates the behaviour of small investors in Hong Kong’s derivatives markets. The study period covers the global economic crisis of 2011- 2012, and we focus on small investors’ behaviour during and after the crisis. We attempt to identify and analyse the key factors that capture their behaviour in derivatives markets in Hong Kong. The data were collected from 524 respondents via a questionnaire survey. Exploratory factor analysis was employed to analyse the data, and some interesting findings were obtained. Our study enhances our understanding of behavioural finance in the setting of an Asian financial centre, namely Hong Kong.Journal of Risk and Financial Management2012-12-3151Article10.3390/jrfm501005959771911-80742012-12-31doi: 10.3390/jrfm5010059Tai-Yuen Hon<![CDATA[JRFM, Vol. 5, Pages 20-58: Stock Returns and Risk: Evidence from Quantile]]>
http://www.mdpi.com/1911-8074/5/1/20
This paper employs weighted least squares to examine the risk-return relation by applying high-frequency data from four major stock indexes in the US market and finds some evidence in favor of a positive relation between the mean of the excess returns and expected risk. However, by using quantile regressions, we find that the risk-return relation moves from negative to positive as the returns’ quantile increases. A positive risk-return relation is valid only in the upper quantiles. The evidence also suggests that intraday skewness plays a dominant role in explaining the variations of excess returns.Journal of Risk and Financial Management2012-12-3151Article10.3390/jrfm501002020581911-80742012-12-31doi: 10.3390/jrfm5010020Thomas ChiangJiandong Li<![CDATA[JRFM, Vol. 5, Pages 1-19: A General Empirical Model of Hedging]]>
http://www.mdpi.com/1911-8074/5/1/1
In this paper, we treat output as a decision variable. Moreover, we employ a general form of basis risk. Furthermore, we relax the statistical-independence assumption between the spot price and basis risk.Journal of Risk and Financial Management2012-12-3151Article10.3390/jrfm50100011191911-80742012-12-31doi: 10.3390/jrfm5010001Moawia AlghalithRicardo Lalloob<![CDATA[JRFM, Vol. 4, Pages 133-161: Multiperiod Hedging using Futures: Mean Reversion and the Optimal Hedging Path]]>
http://www.mdpi.com/1911-8074/4/1/133
This paper considers the multiperiod hedging decision in a framework of mean-reverting spot prices and unbiased futures markets. The task is to determine the optimal hedging path, i.e., the sequence of positions in futures contracts with the objective of minimizing the variance of an uncertain future cash flow. The model is used to illustrate both hedging using a matchedmaturity futures contract and hedging by rolling over a series of nearby futures contracts. In each case, the paper derives the conditions under which a single period (myopic) strategy would be optimal as opposed to a dynamic multiperiod strategy. The results suggest that greater the market power of the hedging entity, closer the optimal strategy is to a myopic hedge. The paper also highlights the difference in the optimal hedging path when hedging is based on matched-maturity as opposed to nearby contracts.Journal of Risk and Financial Management2011-12-3141Article10.3390/jrfm40101331331611911-80742011-12-31doi: 10.3390/jrfm4010133Vadhindran Rao<![CDATA[JRFM, Vol. 4, Pages 97-132: Periodically Collapsing Bubbles in Stock Prices Cointegrated with Broad Dividends and Macroeconomic Factors]]>
http://www.mdpi.com/1911-8074/4/1/97
We study fluctuations in stock prices using a framework derived from the present value model augmented with a macroeconomic factor. The fundamental value is derived as the expected present discounted value of broad dividends that include, in addition to traditional cash dividends, other payouts to shareholders. A stochastic discount factor motivated by the consumption-based asset pricing model is utilized. A single macroeconomic factor, namely the output gap determines the non-fundamental component of stock prices. A resulting trivariate Vector Autoregression (TVAR) model of stock prices, broad dividends, and the output gap shows evidence of cointegration in the DJIA and S&amp;P 500 index data. Nonetheless, a sup augmented Dickey-Fuller test reveals existence of periodically collapsing bubbles in S&amp;P 500 data during the late 1990s.Journal of Risk and Financial Management2011-12-3141Article10.3390/jrfm4010097971321911-80742011-12-31doi: 10.3390/jrfm4010097Man FuPrasad Bidarkota<![CDATA[JRFM, Vol. 4, Pages 74-96: Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models]]>
http://www.mdpi.com/1911-8074/4/1/74
The valuation of options and many other derivative instruments requires an estimation of exante or forward looking volatility. This paper adopts a Bayesian approach to estimate stock price volatility. We find evidence that overall Bayesian volatility estimates more closely approximate the implied volatility of stocks derived from traded call and put options prices compared to historical volatility estimates sourced from IVolatility.com (“IVolatility”). Our evidence suggests use of the Bayesian approach to estimate volatility can provide a more accurate measure of ex-ante stock price volatility and will be useful in the pricing of derivative securities where the implied stock price volatility cannot be observed.Journal of Risk and Financial Management2011-12-3141Article10.3390/jrfm401007474961911-80742011-12-31doi: 10.3390/jrfm4010074Shu HoAlan LeeAlastair Marsden<![CDATA[JRFM, Vol. 4, Pages 43-73: A Pseudo-Bayesian Model for Stock Returns In Financial Crises]]>
http://www.mdpi.com/1911-8074/4/1/43
Recently, there has been a considerable interest in the Bayesian approach for explaining investors' behaviorial biases by incorporating conservative and representative heuristics when making financial decisions, (see, for example, Barberis, Shleifer and Vishny (1998)). To establish a quantitative link between some important market anomalies and investors' behaviorial biases, Lam, Liu, and Wong (2010) introduced a pseudo-Bayesian approach for developing properties of stock returns, where weights induced by investors' conservative and representative heuristics are assigned to observations of the earning shocks and stock prices. In response to the recent global financial crisis, we introduce a new pseudo-Bayesian model to incorporate the impact of a financial crisis. Properties of stock returns during the financial crisis and recovery from the crisis are established. The proposed model can be applied to investigate some important market anomalies including short-term underreaction, long-term overreaction, and excess volatility during financial crisis. We also explain in some detail the linkage between these market anomalies and investors' behavioral biases during financial crisis.Journal of Risk and Financial Management2011-12-3141Article10.3390/jrfm401004343731911-80742011-12-31doi: 10.3390/jrfm4010043Eric FungKin LamTak-Kuen SiuWing-Keung Wong<![CDATA[JRFM, Vol. 4, Pages 1-42: Corporate Governance and Corporate Creditworthiness]]>
http://www.mdpi.com/1911-8074/4/1/1
We examine the relation between corporate governance and bankruptcy risk as an underlying force affecting a bond’s yield. The level of corporate governance is captured by the G-index, along with the explicit groups of governance provisions. We estimate bankruptcy risk by Z-score, by cash-flow-score, by O-score, through Merton structural model default probabilities, and by S&amp;P credit ratings. After addressing endogeneity and while controlling for firm-specific factors, based on the four objective methodologies we find that corporate governance is inversely related to bankruptcy risk. Yet, rating agencies take a mixed approach towards this association likely because of the conflicting impact of different governance provisions.Journal of Risk and Financial Management2011-12-3141Article10.3390/jrfm40100011421911-80742011-12-31doi: 10.3390/jrfm4010001Dror Parnes<![CDATA[JRFM, Vol. 3, Pages 118-138: Are Entrepreneur-Led Companies Better? Evidence from Publicly Traded U.S. Companies: 1998-2010]]>
http://www.mdpi.com/1911-8074/3/1/118
Do U.S. publicly-traded companies led by entrepreneurs perform better than nonentrepreneur-led U.S. public companies? Our data suggests they do. We analyze monthly stock returns of U.S. publicly traded companies over the time period 1998-2010 and find compelling evidence demonstrating that irrespective of market capitalization and time period, companies led by U.S. entrepreneurs provide better stock performance than several stock market indices primarily comprised of non-entrepreneur-led U.S. companies.Journal of Risk and Financial Management2010-12-3131Article10.3390/jrfm30101181181381911-80742010-12-31doi: 10.3390/jrfm3010118Joel Shulman<![CDATA[JRFM, Vol. 3, Pages 97-117: A Mean-Variance Diagnosis of the Financial Crisis: International Diversification and Safe Havens]]>
http://www.mdpi.com/1911-8074/3/1/97
We use mean-variance analysis with short selling constraints to diagnose the effects of the recent global financial crisis by evaluating the potential benefits of international diversification in the search for ‘safe havens’. We use stock index data for a sample of developed, advanced-emerging and emerging countries. ‘Text-book’ results are obtained for the pre-crisis analysis with the optimal portfolio for any risk-averse investor being obtained as the tangency portfolio of the All-Country portfolio frontier. During the crisis there is a disjunction between bank lending and stock markets revealed by negative average returns and an absence of any empirical Capital Market Line. Israel and Colombia emerge as the safest havens for any investor during the crisis. For Israel this may reflect the protection afforded by special trade links and diaspora support, while for Colombia we speculate that this reveals the impact on world financial markets of the demand for cocaine.Journal of Risk and Financial Management2010-12-3131Article10.3390/jrfm3010097971171911-80742010-12-31doi: 10.3390/jrfm3010097Alexander EptasLawrence Leger<![CDATA[JRFM, Vol. 3, Pages 63-96: Soybean Futures Crush Spread Arbitrage: Trading Strategies and Market Efficiency]]>
http://www.mdpi.com/1911-8074/3/1/63
This paper revisits the soybean crush spread arbitrage work of Simon (1999) by studying a longer time period, wider variety of entry and exit limits, and the risk-return relationship between entry and exit limits. The lengths of winning and losing trades are found to differ systematically, with winning trades significantly shorter on average than losing trades. Exiting trades near the 5- day moving average is shown to improve trade performance relative to a reversal of sign and magnitude from the entry spread. These results lead to trading rules designed to prevent lengthy trades; however, the profitability of trading rules is found to be unstable.Journal of Risk and Financial Management2010-12-3131Article10.3390/jrfm301006363961911-80742010-12-31doi: 10.3390/jrfm3010063John Mitchell<![CDATA[JRFM, Vol. 3, Pages 26-62: Hedging Performance and Multiscale Relationships in the German Electricity Spot and Futures Markets]]>
http://www.mdpi.com/1911-8074/3/1/26
We explore optimal hedge ratios and hedging effectiveness for the German electricity market. Given the increasing attention that wavelets received in the financial market, we concentrate on the investigation of the relationship, covariance/coherence evolution and hedge ratio analysis, on a time-frequency-scale approach (discrete and continuous), between electricity spot and futures. Simpler approaches are also used for comparison purposes like the naïve, OLS and the dynamic multivariate GARCH model in order to account for risk reduction through hedging. Results allow us to conclude that: dynamic hedging strategies provide higher variance reductions in terms of hedging effectiveness; there is poor correlation among spot and futures, not being homogeneous across scales, which condition the effectiveness of the hedging strategy; the long-horizon hedge ratio does not converge to its long run equilibrium of one. Wavelets poor fit in variance reduction is attributed to low coherence and to statistical relationships between spot and futures electricity series. The instability found in various aspects of market comovements may imply serious limitations to the investor’s ability to exploit potential benefits from hedging with futures contracts in electricity markets. Moreover, much variation in the contemporaneous relationship among spot and futures may highlight inadequacy in assuming (short-term) relationships in both markets, which might account for the difficulty in achieving profitable active trading.Journal of Risk and Financial Management2010-12-3131Article10.3390/jrfm301002626621911-80742010-12-31doi: 10.3390/jrfm3010026Mara MadalenoCarlos Pinho<![CDATA[JRFM, Vol. 3, Pages 1-25: Conserving Capital by Adjusting Deltas for Gamma in the Presence of Skewness]]>
http://www.mdpi.com/1911-8074/3/1/1
An argument for adjusting Black Scholes implied call deltas downwards for a gamma exposure in a left skewed market is presented. It is shown that when the objective for the hedge is the conservation of capital ignoring the gamma for the delta position is expensive. The gamma adjustment factor in the static case is just a function of the risk neutral distribution. In the dynamic case one may precompute at the date of trade initiation a matrix of delta levels as a function of the underlying for the life of the trade and subsequently one just has to look up the matrix for the hedge. Also constructed are matrices for the capital reserve, the pro¯t, leverage and rate of return remaining in the trade as a function of the spot at a future date in the life of the trade. The concepts of pro¯t, capital, leverage and return are as described in Carr, Madan and Vicente Alvarez (2010). The dynamic computations constitute an application of the theory of nonlinear expectations as described in Cohen and Elliott (2010).Journal of Risk and Financial Management2010-12-3131Article10.3390/jrfm30100011251911-80742010-12-31doi: 10.3390/jrfm3010001Dilip Madan<![CDATA[JRFM, Vol. 2, Pages 118-189: Models for Risk Aggregation and Sensitivity Analysis: An Application to Bank Economic Capital]]>
http://www.mdpi.com/1911-8074/2/1/118
A challenge in enterprise risk measurement for diversified financial institutions is developing a coherent approach to aggregating different risk types. This has been motivated by rapid financial innovation, developments in supervisory standards (Basel 2) and recent financial turmoil. The main risks faced - market, credit and operational – have distinct distributional properties, and historically have been modeled in differing frameworks. We contribute to the modeling effort by providing tools and insights to practitioners and regulators. First, we extend the scope of the analysis to liquidity and interest rate risk, having Basel Pillar II of Basel implications. Second, we utilize data from major banking institutions’ loss experience from supervisory call reports, which allows us to explore the impact of business mix and inter-risk correlations on total risk. Third, we estimate and compare alternative established frameworks for risk aggregation (including copula models) on the same data-sets across banks, comparing absolute total risk measures (Value-at-Risk – VaR and proportional diversification benefits-PDB), goodness-of-fit (GOF) of the model as data as well as the variability of the VaR estimate with respect to sampling error in parameter. This benchmarking and sensitivity analysis suggests that practitioners consider implementing a simple non-parametric methodology (empirical copula simulation- ECS) in order to quantify integrated risk, in that it is found to be more conservatism and stable than the other models. We observe that ECS produces 20% to 30% higher VaR relative to the standard Gaussian copula simulation (GCS), while the variance-covariance approximation (VCA) is much lower. ECS yields the highest PDBs than other methodologies (127% to 243%), while Archimadean Gumbel copula simulation (AGCS) is the lowest (10-21%). Across the five largest banks we fail to find the effect of business mix to exert a directionally consistent impact on total integrated diversification benefits. In the GOF tests, we find mixed results, that in many cases most of the copula methods exhibit poor fit to the data relative to the ECS, with the Archimadean copulas fitting worse than the Gaussian or Student-T copulas. In a bootstrapping experiment, we find the variability of the VaR to be significantly lowest (highest) for the ECS (VCA), and that the contribution of the sampling error in the parameters of the marginal distributions to be an order or magnitude greater than that of the correlation matrices.Journal of Risk and Financial Management2009-12-3121Article10.3390/jrfm20101181181891911-80742009-12-31doi: 10.3390/jrfm2010118Hulusi InanogluMichael Jacobs<![CDATA[JRFM, Vol. 2, Pages 94-117: Corporate Risk Disclosure and Corporate Governance]]>
http://www.mdpi.com/1911-8074/2/1/94
To date, research which integrates corporate governance and risk management has been limited. Yet, risk exposure and management are increasingly becoming the core function of modern business enterprises in various sectors and industries domestically and globally. Risk identification and management are crucial in any business strategy design and implementation. From the investors’ point of view, knowledge of the risk profile, risk appetite and risk management are key elements in making sound portfolio investment decisions. This paper examines the relationships between corporate governance mechanisms and risk disclosure behavior using a sample of Canadian publicly-traded companies (TSX 230). Results show that Canadian public companies are more likely to disclose risk management information over and above the mandatory risk disclosures, if they are larger in size and if their boards of directors have more independent members. Minority voting control ownership structures appear to negatively impact risk disclosure and CEO incentive compensation shows mixed results. The paper concludes that more research is needed to further assess the impact of various governance mechanisms on corporate risk management and disclosure behavior.Journal of Risk and Financial Management2009-12-3121Article10.3390/jrfm2010094941171911-80742009-12-31doi: 10.3390/jrfm2010094Kaouthar Lajili<![CDATA[JRFM, Vol. 2, Pages 75-93: The Nexus between Analyst Forecast Dispersion and Expected Returns Surrounding Stock Market Crashes]]>
http://www.mdpi.com/1911-8074/2/1/75
The performance of analysts’ forecasts has attracted increasing attention in recent years. However, as yet, no empirical study has investigated the nexus between the analyst forecast dispersion (AFD) and excess returns surrounding stock market crashes in any depth. This paper attempts to fill this void by estimating a Fama-French model regression with AFD as a factor. Instead of an expected linear relationship, a nonlinear U-shape relationship between the AFD and excess returns is found.Journal of Risk and Financial Management2009-12-3121Article10.3390/jrfm201007575931911-80742009-12-31doi: 10.3390/jrfm2010075Terence ChongXiaolei Wang<![CDATA[JRFM, Vol. 2, Pages 38-74: China’s Stock Market Integration with a Leading Power and a Close Neighbor]]>
http://www.mdpi.com/1911-8074/2/1/38
Current integration and co-movement among international stock markets has been boosted by increased globalization of the world economy, and profit-chasing capital surfing across borders. With a reputation as the fastest growing economy in the world, China’s stock market has continued gaining momentum during recent years and incurred growing attention from academicians, as well as practitioners. Taking into account economic and geographical considerations, the US and Hong Kong are considerably the most comparable stock markets to China. The usual vector error correction model (VECM) could overlook the long memory feature of cointegration residual series, which can in turn exert bias on the resulting inferences. To overcome its limitations, we employ a fractionally integrated VECM (FIVECM) in this paper to investigate the long-term cointegration relations binding China’s stock market to the aforementioned stock markets. In addition, by augmenting the FIVECM with multivariate GARCH model, the return transmission and volatility spillover between market return series were revealed simultaneously. Our empirical results show that China’s stock market is fractionally cointegrated with the two markets, and it appears that China’s stock market has stronger ties with its neighboring Hong Kong market than with the world superpower, the US market.Journal of Risk and Financial Management2009-12-3121Article10.3390/jrfm201003838741911-80742009-12-31doi: 10.3390/jrfm2010038Zheng YiChen HengWing-Keung Wong<![CDATA[JRFM, Vol. 2, Pages 1-37: Mergers and Acquisitions (M&AS) by R&D Intensive Firms]]>
http://www.mdpi.com/1911-8074/2/1/1
In this study, we evaluate the impact of R&amp;D intensity on acquiring firms’ abnormal returns by examining 925 Canadian completed deals between 1993 and 2002 that have information on R&amp;D expenditures. While examining the returns to acquiring firm shareholders in the R&amp;D intensive firms we evaluate two competing hypotheses: ‘growth potential hypothesis’ and ‘integration failure hypothesis’. According to the ‘growth potential hypothesis’, in light of the growth potential of the targets acquired by R&amp;D intensive firms, investors are likely to react positively. ‘Integration failure hypothesis’ focuses on integration difficulties of a target by an R&amp;D intensive firms and suggests that investor might be skeptical of such acquisitions and react negatively. Our results show that R&amp;D intensity (i.e. R&amp;D expenditure by sales) has a positive and significant effect on cumulative abnormal returns of the acquiring firms around the announcement dates. This implies that market generally favors the M&amp;A deals by R&amp;D intensive firms. An analysis of the differentiating characteristics reveal that R&amp;D firms have a significantly higher growth potential and undertake more stock financed deals compared to the non R&amp;D firms. Further, our results show that there is no significant change in long-term operating performance subsequent to the M&amp;A deals for both R&amp;D firms and non R&amp;D firms. In general, our results show support for ‘growth potential hypothesis’.Journal of Risk and Financial Management2009-12-3121Article10.3390/jrfm20100011371911-80742009-12-31doi: 10.3390/jrfm2010001Shantanu DuttaVinod Kumar<![CDATA[JRFM, Vol. 1, Pages 129-162: Financial Distress Comparison Across Three Global Regions]]>
http://www.mdpi.com/1911-8074/1/1/129
Globalization has precipitated movement of output and employment between regions. We examine factors related to corporate financial distress across three continents. Using a multidimensional definition of financial distress we test three hypotheses to explain financial distress using historical financial data. A null hypothesis of a single global model was rejected in favor of a fully relaxed model which created individual financial distress models for each region. This result suggests that despite other indications of worldwide convergence, international differences in accounting rules, lending practices, managements skill levels, and legal requirements among others has kept corporate decline from becoming commoditized.Journal of Risk and Financial Management2008-12-3111Article10.3390/jrfm10101291291621911-80742008-12-31doi: 10.3390/jrfm1010129Harlan PlattMarjorie Platt<![CDATA[JRFM, Vol. 1, Pages 100-128: Active Versus Passive Investing - An Analysis of UK Equity Markets, 1991-2005]]>
http://www.mdpi.com/1911-8074/1/1/100
This study examines the pattern of active versus passive trading in UK equities over the period 1991-2005. We describe a metric to analyse trading activity and volumes in the UK FTSE350 and AIM markets, with emphasis on industrial and size-based effects. Our findings indicate that active stock picking has been consistently declining in the UK market over the period studied for all markets, size quintiles and in virtually every industrial sector. Moreover, trading patterns reveal a pronounced size effect with significantly less stock picking in larger capitalisation stocks vis-à-vis smaller stocks. Patterns of investment in the AIM suggest an increase in index trading over time but higher overall levels of stock picking relative to the FTSE350 list.Journal of Risk and Financial Management2008-12-3111Article10.3390/jrfm10101001001281911-80742008-12-31doi: 10.3390/jrfm1010100Edel BarnesM. Scott<![CDATA[JRFM, Vol. 1, Pages 77-99: The Intra-Industry Effects of Life Insurance Company Demutualizaton]]>
http://www.mdpi.com/1911-8074/1/1/77
We examine the impact of demutualization announcements by 13 life insurance companies during 1996-2000 on the value of existing stock-owned life insurance companies and companies in other segments of the insurance industry. Demutualization announcements are associated with negative stock price reactions in the days around the announcement, and with larger and positive stock price reactions in the days following announcement. Overall, the results support the contention that life insurance company demutualizations signal favorable future industry conditions and/or increased likelihood of future acquisitions for all segments of the insurance industry. Active-minded investors may use these results to develop alpha-generating investment strategies.Journal of Risk and Financial Management2008-12-3111Article10.3390/jrfm101007777991911-80742008-12-31doi: 10.3390/jrfm1010077Joseph MeadorEmery Trahan<![CDATA[JRFM, Vol. 1, Pages 41-76: Effective Basemetal Hedging: The Optimal Hedge Ratio and Hedging Horizon]]>
http://www.mdpi.com/1911-8074/1/1/41
This study investigates optimal hedge ratios in all base metal markets. Using recent hedging computation techniques, we find that 1) the short-run optimal hedging ratio is increasing in hedging horizon, 2) that the long-term horizon limit to the optimal hedging ratio is not converging to one but is slightly higher for most of these markets, and 3) that hedging effectiveness is also increasing in hedging horizon. When hedging with futures in these markets, one should hedge long-term at about 6 to 8 weeks with a slightly greater than one hedge ratio. These results are of interest to many purchasing departments and other commodity hedgers.Journal of Risk and Financial Management2008-12-3111Article10.3390/jrfm101004141761911-80742008-12-31doi: 10.3390/jrfm1010041Michaël DewallyLuke Marriott<![CDATA[JRFM, Vol. 1, Pages 1-40: Do REITs Outperform Stocks and Fixed-Income Assets? New Evidence from Mean-Variance and Stochastic Dominance Approaches]]>
http://www.mdpi.com/1911-8074/1/1/1
This paper re-examines the performance of REITs, stocks, and fixed-income assets based on the preferences of risk-averse and risk-seeking investors using mean-variance and stochastic dominance approaches. Our findings indicate no first-order stochastic dominance and no arbitrage opportunity among these assets. However, our stochastic dominance results reveal that in order to maximize their expected utility, the risk-averse prefer fixed-income assets over real estate, which, in turn, is preferable to stocks. On the other hand, to maximize their expected utility, all risk-seeking investors would prefer to invest in stocks than in real estate, but real estate, in turn, is preferable to fixed-income assets.Journal of Risk and Financial Management2008-12-3111Article10.3390/jrfm10100011401911-80742008-12-31doi: 10.3390/jrfm1010001Thomas ChiangHooi Hooi LeanWing-Keung Wong