International Journal of Financial Markets and Derivatives (7 papers in press)
VOLATILITY ESTIMATION FOR CRYPTOCURRENCIES USING MARKOV-SWITCHING GARCH MODELS
by Paulo Vitor Jordão Da Gama Silva, Marcelo Cabus Klotzle, Antonio Carlos Figueiredo Pinto, Leonardo Lima Gomes
Abstract: In the 21st century, digital currencies have become a disruptive technology that is shaking up both financial markets and academic environment. Investors, politicians, companies, and academics are attempting to improve their understanding of these currencies for future investment possibilities and technological applications. This study aims to evaluate changes in different volatility states of eight digital currencies (BTC, ETH, LTC, XRP, XMR, NEM, LISK, and STEEM) that showed the highest liquidity and market capitalization from 2013 to 2017. The methodology involved the MSGARCH model, using SGARCH, EGARCH, GJRGARCH, and TGARCH models. Our study demonstrated that two volatility regimes, that is, one with a larger volatility and another with a smaller one, clearly exist for all the analyzed cryptocurrencies. What differs between the currencies is the probability of a second regime occurring. Moreover, we concluded that for both the first and second state, the asymmetry coefficient (gamma) is positive for all currencies.
Keywords: Cryptocurrencies; GARCH; Markov-switching model; Volatility.
Post Global Financial Crisis Modelling: Credit Risk For Firms That Are Too Big To Fail
by Ephraim Clark, Sovan Mitra, Octave Jokung
Abstract: rnSince the start of the Global Financial Crisis the validity of all financial models have come under serious questioning, with firms that are `too big to fail' being frequently discussed in the media. Such firms are systemically too important to the economy to allow them to fail, as well as posing significant contagion risk. In such firms, the standard credit risk models are not sufficient because systemically important firms do not default under standard circumstances. In fact it was frequently observed during the Global Financial Crisis that such firms were able to continue borrowing when other firms would normally default.rnrnrnIn this paper we propose a new model for credit risk for firms that are too big to fail. We propose a structural model of credit risk but model credit risk as a real option. We derive a closed form solution for the option to default and take into account the borrowing practices of systemically important firms. We develop our model to take into account economic factors using regime switching, and derive an option pricing solution under such a process. Finally we obtain solutions for hedging the option to default, which takes into account the market incompleteness of such options. We conduct numerical experiments to calculate the option to default at different debt values and volatility.
Keywords: credit risk; real options; too big to fail; financial crisis; hedging.
OPTIONS PRICING MODELS OF INTEREST RATE INDEX: A COMPARATIVE OF PRICING METHODOLOGIES APPLIED TO THE BRAZILIAN MARKET
by João Luiz Chela, Rodolfo Rosina
Abstract: This paper proposes to compare two Options pricing models of interest rate index used in the Brazilian market and verify the best performance model. The models compared are those of Heath-Jarrow-Merton (HJM) of Musiela (1994) and Black Model with expectations of theMonetary Policy Committee Meeting (Comit
Keywords: Interest Derivatives; IDI options; Interest Rate Index.
Concentration measures in emerging banking
by Triki Mohamed Bilel, Maktouf Samir
Abstract: In this study, we investigate the sensitivity of different concentration measures, such as classical index concentration and spatial index concentration, to varying regimes for Zipfs exponent (∝) for the Pareto-type distribution of bank sizes. We establish relationships between each concentration measure and Zipfs exponent by introducing the Riemann Zeta function and calculating the elasticity for each index. We prove that the spatial concentration index is the most robust for varying regimes. Therefore, the choice of an appropriate concentration index must be carefully considered before drawing inferences about the relationship between concentration and banking fragility.
Keywords: Emerging banking; Zipf’s law; classical index concentration; spatial index concentration.
Predictable risks and returns: further evidence from the UK stock market.
by Catherine Georgiou, Chris Grose, Fragiskos Archontakis
Abstract: This paper examines whether the most cited performance models can explain variation in the UK stock returns. The data set includes securities of the FTSE 100 from January 2000 to December 2016. Securities are classified based on their market capitalization and their industry. Also, valuation ratios are put to the test so as to help us retrieve evidence of predictability. Finally, the January effect is included in our analysis as indicated particularly for the UK data. The authors find that during this short time period in which a financial crisis is also evident, all performance models are equally capable of assisting us interpreting UK predictability. Secondly, lagged markets excess returns capture most of the forecasting ability in returns, while the valuation ratios employed manage to partly predict returns in this specific sample. The papers novelty lies in the fresh evidence presented in the case of the UK returns for the most recent data set available.
Keywords: Performance models; Time series forecasting; predictive variables; FTSE 100.
INSTITUTIONAL INVESTORS' STOCKS PORTFOLIO STRATEGIES AND COMMODITY PRICES: A CROSS-CORRELATION ANALYSIS IN A FINANCIALIZATION CONTEXT
by Antonio Focacci
Abstract: New institutional players entered the futures markets with additional important capital inflows from 2000s onwards. Generally labeled by the term financialisa
Keywords: financialisation; commodity prices; cross-correlation analysis; lead-lag relationship.
Measuring portfolio risk of non-energy commodity using Time-Varying Vine Copula
by Zeineb Attafi, Ahmed Ghorbel
Abstract: Few works in litterature that have used the Vine copula to measure and analyse the risk of stock indices, energetic products or cryptocurrencies portfolio (Zhang et al., 2014, Shahzad et al.,2018 and Boako et al., 2019) but there arent works that measure the risk of a portfolio composed of non-energy commodities by VaR and ES using different versions of Vine copula. Our aim in this work is to model the dependence between non-energy commomdities returns by modelling standardized residuals obtained from univariate GARCH model by different versions of time varying vine copula, to quantify risk of N-dimensional non-energy commodity portfolio by VaR and ES and to compare the predictive performance of this method with traditional and competitve traditional univariate VaR methods. Empirical results suggest that risk quantifies generated by AR-GARCH vine copula methods with Student-t distribution are sufficiently accurate at both low and high confidence levels. Given these re-sults, we recommend the application of Vine copula method to understanding the non-energy commodity behaviors which are very important to investors, producers, consumers, and poli-cymakers.
Keywords: Non-energy commodity; portfolio; vine copulas; Value at Risk; Expected Shortfall and risk management.