International Journal of Financial Markets and Derivatives
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International Journal of Financial Markets and Derivatives (5 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.