ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)最新文献

{"title":"Performance v. Turnover: A Story by 4,000 Alphas","authors":"Zurab Kakushadze, Igor Tulchinsky","doi":"10.2139/ssrn.2657603","DOIUrl":"https://doi.org/10.2139/ssrn.2657603","url":null,"abstract":"We analyze empirical data for 4,000 real-life trading portfolios (U.S. equities) with holding periods of about 0.7-19 trading days. We find a simple scaling C ~ 1/T, where C is cents-per-share, and T is the portfolio turnover. Thus, the portfolio return R has no statistically significant dependence on the turnover T. We also find a scaling R ~ V^X, where V is the portfolio volatility, and the power X is around 0.8-0.85 for holding periods up to 10 days or so. To our knowledge, this is the only publicly available empirical study on such a large number of real-life trading portfolios/alphas.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122625541","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":"A Comparison of the Impact of the Basel Standards Upon Islamic and Conventional Bank Risks in the Gulf State Region","authors":"M. Farooqi, John R. O'Brien","doi":"10.2139/ssrn.2647562","DOIUrl":"https://doi.org/10.2139/ssrn.2647562","url":null,"abstract":"\u0000Purpose\u0000This paper aims to provide a comparative study of the Islamic versus conventional banking sector risk by using market data generated from the sample of publicly listed Islamic and conventional banks in the Gulf Cooperation Council (GCC) region.\u0000\u0000\u0000Design/methodology/approach\u0000The authors introduce a market-based measure of bank stress and test this indicator against the Tier 1 Capital Ratio using Granger causality tests.\u0000\u0000\u0000Findings\u0000The authors find that the market-based measure is a leading indicator of banking stress when compared to the accounting-based Tier 1 ratio and thus is relevant to the Basel regulation’s Pillar 3.\u0000\u0000\u0000Research limitations/implications\u0000This paper only looks at Islamic vs conventional banks in the Gulf region, and the authors would like to extend this analysis to a broader range of financial institutions, especially in the European and North American markets.\u0000\u0000\u0000Social implications\u0000Developing a measure that signals bank stress ahead of typically used measures can help regulators, bank management and investors identify oncoming problems and issues before these become too big to manage.\u0000\u0000\u0000Originality/value\u0000The results from this analysis provides insight into the offsetting impact from two drivers (beta and book-to-market ratio) of the cost of equity capital for the conventional vs Islamic banking sectors.\u0000","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128112320","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":"Measuring Risk Appetite from Financial Assets' Excess Returns","authors":"Mathieu Gatumel, F. Ielpo","doi":"10.2139/ssrn.2334180","DOIUrl":"https://doi.org/10.2139/ssrn.2334180","url":null,"abstract":"We introduce a new meaure of risk appetite in financial markets, based on the cross sectional behavior of excess returns. Turning them into probabilities through a Markov Switching model, we define one global risk appetite measure as the cross-sectional average of the individual probabilities for each asset to be in a \"risk appetite\" regime. Given the probabilistic approach that comes naturally with this Markov Switching framework, we present various tests to gauge the interest of the risk appetite measure that is presented here. Using these tests we show that our index behaves well vs. various competitors, especially in out-of-sample results. We test for the information content of various assets and find that a core of asset allocation-related assets provide the best possible choice over various competing specifications.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058515","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 International CAPM Redux","authors":"Francesca Brusa, Tarun Ramadorai, Adrien Verdelhan","doi":"10.2139/ssrn.2520475","DOIUrl":"https://doi.org/10.2139/ssrn.2520475","url":null,"abstract":"We provide evidence that international equity investors are compensated for bearing currency risk. Three factors --- a global equity factor denominated in local currencies, and two currency factors, dollar and carry --- account for a wide cross-section of equity returns from 46 developed and emerging countries from 1976 to the present. They are also useful at explaining the risks of international mutual funds and hedge funds. A simple complete-markets model replicates our empirical findings. The model implies a novel perspective on optimal currency hedging.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"32 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131893960","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":"Non-Traditional Risk Sources and Financial System Resilience","authors":"T. Drost, B. J. Sikken","doi":"10.2139/ssrn.2637782","DOIUrl":"https://doi.org/10.2139/ssrn.2637782","url":null,"abstract":"This paper identifies 20 non-traditional risk sources that may test the resilience of the financial system in the longer term.Non-traditional risk sources refer to societal, technological, geopolitical and environmental factors that may undermine the resilience of the global financial system. In essence, financial system resilience can be defined as the capacity to continuously perform the primary functions, in particular supporting the real economy and enhancing societal well-being.Examples of these non-traditional risk sources include:- Societal factors, e.g. rapid ageing of populations may undermine the financial sustainability of retirement provisioning schemes which will challenge societal well-being. Pension schemes are key sources of capital within the global financial system.- Technological factors, e.g. data security issues and the risk of identity theft may undermine the trust of in the – largely electronic – financial system.- Environmental factors, e.g. severe carbon constraints may lead to stranded assets for oil companies and other industries that are highly dependent on fossil fuels. This will negatively affect the assets of institutional investors with large exposures in those sectors.- Geopolitical factors, e.g. major political and military conflicts, or lack of supranational regulation, may also challenge the resilience of the financial system.Many of these factors can be considered as “non-traditional risk sources” as most financial institutions and financial supervisors take these factors less into account in their conventional risk management processes. Admittedly, what is non-traditional for some sectors may be quite common for others. For example, analysing the risks of floods (climate change) or the outbreak of a virus may be relatively new for banks, but is standard practice in the casualty insurance industry.This report aims to broaden the perspective of risk managers, investors, supervisors and regulators of financial markets on where “the next financial crisis” may come from. Clearly, additional research is needed. For example, prioritising these risk sources (e.g. likelihood, impact, complexity) and defining risk mitigation mechanisms at organisational and system-wide level.The publication has been developed in close collaboration with the Executive Fellow community at Duisenberg school of finance (DSF). Executive Fellows are leading financial services executives, professionals and policymakers who are actively involved in DSF research and dialogue activities.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127925010","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":"Return-Based Risk Management for Hedge Fund Investments","authors":"C. Frei","doi":"10.2139/ssrn.2660382","DOIUrl":"https://doi.org/10.2139/ssrn.2660382","url":null,"abstract":"Return-based methods are frequently used by risk managers to estimate the exposures of hedge funds because of the limited transparency offered by such investment schemes. This paper proposes a method to assess the limitations of such methods using the Posterior Cramer-Rao Bound (PCRB). This PCRB allows one to quantify the achievable accuracy of exposure estimates without having to compare computed estimates to actual exposures. This approach is particularly useful in situations where exposure data is unavailable. The main determinants of the PCRB are shown to be the variance of the hedge fund exposures and the ratio of market variance to idiosyncratic error variance. The paper also discusses the effects of asset correlation, return frequency, and the use of return contributions on the PCRB. To illustrate the application of the methodology, we provide four examples in which we compare the PCRB to the computed estimation error using real hedge fund data.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115542840","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":"Electricity Futures Prices in an Emissions Constrained Economy: Evidence From European Power Markets","authors":"G. Daskalakis, L. Symeonidis, Raphael N. Markellos","doi":"10.5547/01956574.36.3.GDAS","DOIUrl":"https://doi.org/10.5547/01956574.36.3.GDAS","url":null,"abstract":"We investigate the economic factors that drive electricity risk premia in the European emissions constrained economy. Our analysis is undertaken for monthly baseload electricity futures for delivery in the Nordic, French and British power markets. We find that electricity risk premia are significantly related to the volatility of electricity spot prices, demand and revenues, and the price volatility of the carbon dioxide (CO2) futures traded under the EU Emissions Trading Scheme (EU ETS). This finding has significant implications for the pricing of electricity futures since it highlights for the first time the role of carbon market uncertainties as a main determinant of the relationship between spot and futures electricity prices in Europe. Our results also suggest that for the electricity markets under scrutiny futures prices are determined rationally by risk-averse economic agents.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117354505","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":"Estimating Fundamental Sharpe Ratios: A Kalman Filter Approach","authors":"Hayette Gatfaoui","doi":"10.2139/ssrn.2838935","DOIUrl":"https://doi.org/10.2139/ssrn.2838935","url":null,"abstract":"A wide community of practitioners still focuses on classic Sharpe ratio as a risk adjusted performance measure due to its simplicity and easiness of implementation. Performance is computed as the excess return relative to the risk free rate whereas risk adjustment is provided by the asset return’s volatility as a denominator. However, such risk/return representation is only relevant under a Gaussian world. Moreover, Sharpe ratio exhibits time variation and can also be biased by market trend and idiosyncratic risk. As an implementation, we propose to filter out classic Sharpe ratios (SR) so as to extract their fundamental component on a time series basis. Time-varying filtered Sharpe ratios are obtained while employing the Kalman filter methodology. In this light, fundamental/filtered Sharpe ratios (FSR) are free of previous reported biases, and reflect the pure performance of assets. A brief analysis shows that SR is strongly correlated with other well-known comparable risk-adjusted performance measures while FSR exhibits a low correlation. Moreover, FSR is a more efficient performance estimator than previous comparable risk adjusted performance measures because it exhibits a lower standard deviation. Finally, a comparative analysis combines GARCH modeling, extreme value theory, multivariate copula representation and Monte Carlo simulations. Based on 10 000 trials and building equally weighted portfolios with the 30 best performing stocks according to each considered performance measure, the top-30 FSR portfolio offers generally higher perspectives of expected gains as well as reduced Value-at-Risk forecasts (i.e. worst loss scenario) over one week and one-month horizons as compared to other performing portfolios.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123034896","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":"Combining Scenario and Historical Data in the Loss Distribution Approach: A New Procedure that Incorporates Measures of Agreement between Scenarios and Historical Data","authors":"Riaan de Jongh, T. de Wet, H. Raubenheimer, J. H. Venter","doi":"10.21314/JOP.2015.160","DOIUrl":"https://doi.org/10.21314/JOP.2015.160","url":null,"abstract":"Many banks use the loss distribution approach in their advanced measurement models to estimate regulatory or economic capital. This boils down to estimating the 99.9% value-at-risk of the aggregate loss distribution and is notoriously difficult to do accurately. Also, it is well-known that the accuracy with which the tail of the loss severity distribution is estimated is the most important driver in determining a reasonable estimate of regulatory capital. To this end, banks use internal data and external data (jointly referred to as historical data) as well as scenario assessments in their endeavor to improve the accuracy with which they estimate the severity distribution. In this paper, we propose a simple new method whereby the severity distribution may be estimated using both historical data and experts' scenario assessments. The way in which historical data and scenario assessments are integrated incorporates measures of agreement between these data sources, which can be used to evaluate the quality of both. In particular, we show that the procedure has definite advantages over traditional methods in which the severity distribution is modeled and fitted separately for the body and tail parts, with the body part based only on historical data and the tail part based on scenario assessments.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126350635","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":"Optimal Volatility, Covenants and Cost of Capital Under Basel III Bail-In","authors":"Kenji Hori, Jorge Ceron","doi":"10.2139/ssrn.2585401","DOIUrl":"https://doi.org/10.2139/ssrn.2585401","url":null,"abstract":"This paper investigates three consequences of the new financial regulation: the agency costs, the monitoring costs and the effect on banks’ cost of capital. For the first, the shareholders’ behaviour is analysed as a trade-off between the value of the bank and its volatility by using an indifference curve model of the bank’s choice of optimal risk. While the first-best optimal risk maximises the value of the bank, the shareholders select suboptimally high risks under bail-in structures. This leads to both the wealth transfer and the value destruction agency costs. For the second, as a result of these consequences of the DAPR (Deviation from the Absolute Priority Rule) the bondholders are forced to closely monitor the bank behaviour. Requiring higher rate of return for higher risk, reflecting the costs of monitoring, is shown to alleviate the agency problems. Different types of covenants are proposed as an efficient way of implementing this solution. For the third, the impact of the new bail-in structure and the monitoring costs on the WACC of 16 largest European banks is estimated, and is shown to increase the cost of capital by between 75% and 110%.","PeriodicalId":187811,"journal":{"name":"ERN: Other Econometric Modeling: Capital Markets - Risk (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124042221","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}