{"title":"Sensitivity Analysis of Portfolio Credit Derivatives by Conditional Monte Carlo Simulation","authors":"Lei Lei, Yijie Peng, M. Fu, Jianqiang Hu","doi":"10.2139/ssrn.3404231","DOIUrl":"https://doi.org/10.2139/ssrn.3404231","url":null,"abstract":"We study sensitivity analysis of portfolio credit derivatives, including basket default swaps and collateralized debt obligations. An unbiased estimator is derived using conditional Monte Carlo for sensitivities with respect to systemic parameters (parameters that influence some or all the entities). Copula-based methods are used to model the joint distribution of the default times. Simulation experiments demonstrate the advantages of the proposed derivative estimator over other methods.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117036253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The TSLL Model: A Simple, Parametric Fit for the Implied Volatilities of VIX Options Inspired by the Shifted Lognormal Model","authors":"Michael Kamal","doi":"10.2139/ssrn.3403126","DOIUrl":"https://doi.org/10.2139/ssrn.3403126","url":null,"abstract":"The standard shifted lognormal model, defined by just two parameters, provides a remarkably good fit to the market implied volatilities of VIX options.<br><br>Inspired by an analytic approximation derived by Lee and Wang, we propose a simple, intuitive extension that provides better empirical fits while retaining analytical tractability.<br><br>In essence, by introducing a third parameter that controls the tilt of the surface beyond the shifted lognormal baseline we can better control the behavior of the fit for large strikes. We call this extended model TSLL: tilted and shifted lognormal-like.<br><br>Finally, we suggest an alternative parameterization in terms of the ATM volatility, volatility floor and tilt parameter that is better suited to help set cutoffs and to rule out arbitrage violations.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114561086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Antonakakis, J. Cuñado, G. Filis, David Gabauer, F. D. de Gracia
{"title":"Oil And Asset Classes Implied Volatilities: Dynamic Connectedness And Investment Strategies","authors":"N. Antonakakis, J. Cuñado, G. Filis, David Gabauer, F. D. de Gracia","doi":"10.2139/ssrn.3399996","DOIUrl":"https://doi.org/10.2139/ssrn.3399996","url":null,"abstract":"Building on the increased interest in the spillover effects among oil prices and other financial assets, this paper examines dynamic connectedness and contagion effects of their implied volatility shocks. We then proceed to the examination of the optimal hedging strategies and optimal portfolio weights for implied volatility portfolios between oil and financial assets. The results suggest that oil implied volatility (OVX) is a net volatility receiver of shocks, whereas implied volatilities indices by the stock markets (mature or emerging) are net volatility transmitters. Hedge ratios indicate that VIX is the least useful implied volatility index to hedge against oil implied volatility. Finally, we show that investors can benefit substantially by adjusting their portfolios based on the dynamic weights and hedge ratios obtained from the dynamic conditional correlation models, although a trade-off exists between the level of risk reduction and portfolio profitability.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133794123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Metals' Price Elasticity of Normalized Excess Supply","authors":"Ali Bashiri, Y. Lawryshyn","doi":"10.2139/ssrn.3696499","DOIUrl":"https://doi.org/10.2139/ssrn.3696499","url":null,"abstract":"We extend the model of Bashiri and Lawryshyn (2018) to the metals market and measure the significance of the relationship between metals' prices and normalized excess supply. We utilize Commodity Exchange prices, the World Bureau of Metal Statistics production and consumption data, as well as inventory data from the London Metal Exchange, Commodity Exchange, and Shanghai Futures Exchange from 1997 to 2017. We find significant relationships for copper, nickel, zinc, lead, and tin, while aluminum exhibits no relationship due to deficient inventory data. We find that during certain intervals of the 2009-2011 period, there exist deviations from the long-term relationship for the metals' prices possibly due to speculation, financialization, price stickiness, and increase of liquidity as a result of central banks' quantitative easing programs.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130218585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hedging Strategy Influencing Derivative Investment on Investors","authors":"D. Rekha, Lavanya N.","doi":"10.31142/IJTSRD23769","DOIUrl":"https://doi.org/10.31142/IJTSRD23769","url":null,"abstract":"The paper titled “Hedging Strategy influence Derivative Investment on Investors�?. Generally Speaking in India Derivative contracts have not been majorly focused by investors, because of certain myths in the minds of people. Therefore Derivative Investment is not taken largely as on investment option by Individual investors. Many authors stated that derivative market is the marketplace in which traders come to exchange risks. In worldwide economy with divergent hazard exposures, derivatives permit businesses and traders to defend themselves from rapid price fluctuations and negative events. The aim of the article is to identify the major risk and hedging strategy in derivative market. In Derivative Contracts as a high risk that are Market risk, Liquidity risk, Credit risk, Counterparty risk, Legal risk and Transaction Risk. Pricing risk and systematic risk is also very important. Derivative investor must analyze the market and make the decisions while trading this will undergoes the uncertainty. Derivatives plays a major role for minimizing the risk involved in the marking an investment in futures contracts by expecting to get good result. The investors should also invest in options contracts which help to reduce the risk by use of hedging strategy. Hedging strategy is used for reducing the risk and maximization of profits. Though the futures contracts are subjected to high level the loss can be reduced to an extent by using the hedging strategy.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134551408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bias Reduction in Nonlinear and Dynamic Panels in the Presence of Cross-Section Dependence","authors":"Cavit Pakel","doi":"10.2139/ssrn.2157212","DOIUrl":"https://doi.org/10.2139/ssrn.2157212","url":null,"abstract":"Fixed effects estimation of nonlinear dynamic panel models is subject to the incidental parameter issue, leading to a biased asymptotic distribution. While this problem has been studied extensively in the literature, a general analysis allowing for both serial and cross-sectional dependence is missing. In this paper we investigate the large-N,T theory of the profile and integrated likelihood estimators, allowing for dependence across both dimensions. We show that under stronger dependence types the asymptotic bias disappears, but a Op(1∕T) small-sample bias remains. We provide bias correction and inference methods, and also obtain primitive conditions for asymptotic normality under various dependence settings.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131631315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Smiling Hyperbolas","authors":"A. Polishchuk","doi":"10.2139/ssrn.2878034","DOIUrl":"https://doi.org/10.2139/ssrn.2878034","url":null,"abstract":"We propose using hyperbolic splines for arbitrage free interpolation of implied volatilities in the strike domain. Hyperbolic splines allow for perfect fit to input data and have carry computational cost since there is no root finding or calibration: spline parameters are expressed directly in terms of elementary mathematical functions. We demonstrate that hyperbolic splines work just as well in the extrapolation region providing a tool for fixing wings produced by arbitrage prone methods. Finally we present a family of global hyperbolic splines that have time-dependent extensions with an intuitive interpretation in terms of local diffusions coupled with a jump to default.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124202211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Equity Autocalls and Vanna Negative Carries: Pricing and Hedging with a Simple Add-On","authors":"G. Salon","doi":"10.2139/ssrn.3383122","DOIUrl":"https://doi.org/10.2139/ssrn.3383122","url":null,"abstract":"Autocall products: a toxic best-seller. \u0000 \u0000Over the past twenty years, the autocall pay-off has been the most traded exotic equity product. Outstandingly popular, it is mainly sold to final customers in Europe and Asia trough notes: its average yearly volumes reaches 100 billion euros. Nevertheless, it is responsible for major losses suffered by banks’ Exotic trading desks. Roughly, when the spot remains in a [80%,105%] area around the recall barrier, daily carry loss is worth 1 to 3 basis points (depending on the product complexity, as several variations exist). \u0000 \u0000Indeed, it shows a strong model-dependency due to the cancellation feature: when the spot moves, books need dynamic rehedging via vanilla options, forward contracts, correlation products. As such, it requires the use of a pricing model which correctly combines market data dynamics (volatility, repo, equity correlations, quanto drifts…) and spot dynamic, in order to price properly the cost of daily rehedging. \u0000 \u0000In practice, building a pricing model complex enough to calibrate the relevant covariances while remaining numerically stable and computationally reasonable has proved to be a very serious challenge. Not mentioning ultimately the need for comprehensive interpretations of outputs. Escaping this issue, we exhibit here, a convenient way to price and hedge autocalls toxic behaviors through an additional and corrective pay-off. \u0000 \u0000There are approximations throughout the building of such an approach that have been tested numerically and justified qualitatively. Nonetheless, this is cheaper in terms of model complexity and development, and it provides a comprehensive and efficient pricing scheme combined with a hedging strategy which tackles the issue of negative carries generated by an autocall replication strategy.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"22 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131725891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Residual Shape Risk on Natural Gas Market with Mixed Jump Diffusion","authors":"K. Janda, J. Kouřílek","doi":"10.2139/ssrn.3389599","DOIUrl":"https://doi.org/10.2139/ssrn.3389599","url":null,"abstract":"This paper introduces residual shape risk as a new subclass of energy commodity risk. Residual shape risk is caused by insufficient liquidity of energy forward market when retail energy supplier has to hedge his short sales by a non-flexible standard baseload product available on wholesale market. Because of this inflexibility energy supplier is left with residual unhedged position which has to be closed at spot market. The residual shape risk is defined as a difference between spot and forward prices weighted by residual unhedged position which size depends on the shape of customers’ portfolio of a given retail energy supplier. We evaluated residual shape risk over the years 2014 - 2018 with a real portfolio of a leading natural gas retail supplier in the Czech Republic. The size of residual shape risk in our example corresponds approximately to 1 percent of profit margin of natural gas retail supplier.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125002391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Omishwary Bhatoo, A. Peer, E. Tadmor, D. Tangman, Aslam Aly El Faidal Saib
{"title":"Efficient Conservative Second-Order Central-Upwind Schemes for Option-Pricing Problems","authors":"Omishwary Bhatoo, A. Peer, E. Tadmor, D. Tangman, Aslam Aly El Faidal Saib","doi":"10.21314/JCF.2019.363","DOIUrl":"https://doi.org/10.21314/JCF.2019.363","url":null,"abstract":"The conservative Kurganov–Tadmor (KT) scheme has been successfully applied to option-pricing problems by Germán I. Ramírez-Espinoza and Matthias Ehrhardt. These included the valuation of European, Asian and nonlinear options as Black–Scholes partial differential equations, written in the conservative form, by simply updating fluxes in the black box approach. In this paper, we describe an improvement of this idea through a fully vectorized algorithm of nonoscillatory slope limiters and the efficient use of time solvers. We also propose the application of second-order extensions of KT to option-pricing problems. Our test problems solve one-dimensional benchmark and convection-dominated European options as well as digital and butterfly options. These demonstrate the robustness and flexibility of the pricing methods and set a basis for complex problems. Further, the computation of option Greeks ensures the reliability of these methods. Numerical experiments are performed on barrier options, early exercisable American options and two-dimensional fixed and floating strike Asian options. To the authors’ knowledge, this is the first time American options have been priced by applying the early exercise condition on the semi-discrete formulation of central-upwind schemes. Our results show second-order, nonoscillatory and high-resolution properties of the schemes as well as computational efficiency.","PeriodicalId":293888,"journal":{"name":"Econometric Modeling: Derivatives eJournal","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115260405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}