We extend the Hull-White short rate model to include the integrated short rate as a separate independent variable and incorporate credit default risk, governed by a Black-Karasinski model, into cash flows. We derive an analytic representation of the associated pricing kernel and apply it to the pricing of risky compounded interest rate payments, including with caps and floors. We illustrate our results numerically applying them to the pricing of extinguishing fix-float swaps.
{"title":"Risky Caplet Pricing with Backward-Looking Rates","authors":"C. Turfus","doi":"10.2139/ssrn.3713880","DOIUrl":"https://doi.org/10.2139/ssrn.3713880","url":null,"abstract":"We extend the Hull-White short rate model to include the integrated short rate as a separate independent variable and incorporate credit default risk, governed by a Black-Karasinski model, into cash flows. We derive an analytic representation of the associated pricing kernel and apply it to the pricing of risky compounded interest rate payments, including with caps and floors. We illustrate our results numerically applying them to the pricing of extinguishing fix-float swaps.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131778435","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}
The present work proposes a methodology for the representation of performance scenario in Packaged Retail and Insurance-based Investment Products (PRIIPS), by the means of a no-arbitrage probability table easy to understand for the retail investor. A statistical reconstruction via the method of moments allows to capture the main properties of the PRIIP market implied distribution by identifying the minimum number of descriptive moments needed. A reasonable quantile partition that is effective for representing to the retail investor the complex distributions of structured products characterized by non-linear pay-offs is then proposed.
{"title":"Probability Performance Scenarios Are Better: An Efficient Disclosure of Higher Moments Information From No-Arbitrage Market Implied Distributions","authors":"M. Minenna","doi":"10.2139/ssrn.3709849","DOIUrl":"https://doi.org/10.2139/ssrn.3709849","url":null,"abstract":"The present work proposes a methodology for the representation of performance scenario in Packaged Retail and Insurance-based Investment Products (PRIIPS), by the means of a no-arbitrage probability table easy to understand for the retail investor. A statistical reconstruction via the method of moments allows to capture the main properties of the PRIIP market implied distribution by identifying the minimum number of descriptive moments needed. A reasonable quantile partition that is effective for representing to the retail investor the complex distributions of structured products characterized by non-linear pay-offs is then proposed.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129020876","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}
This paper studies quantile-based moment premiums. The quantile-based approach delivers robust and flexible alternatives to premiums for variance, skewness and kurtosis risk and enhances our understanding of the pricing of risks in derivatives markets. To quantify these premiums, the paper introduces a new class of synthetic derivatives contracts: quantile swaps. Such contracts mimic quantile-based moment measures from robust statistics. An empirical study of index options detects two distinct premiums for dispersion and asymmetry, but no premium for steepness. This finding is in clear contrast to results obtained through traditional moment swaps and warns us to interpret moment premiums carefully.
{"title":"Quantile Risk Premiums","authors":"Felix Brinkmann, Julian Dörries, O. Korn","doi":"10.2139/ssrn.3706678","DOIUrl":"https://doi.org/10.2139/ssrn.3706678","url":null,"abstract":"This paper studies quantile-based moment premiums. The quantile-based approach delivers robust and flexible alternatives to premiums for variance, skewness and kurtosis risk and enhances our understanding of the pricing of risks in derivatives markets. To quantify these premiums, the paper introduces a new class of synthetic derivatives contracts: quantile swaps. Such contracts mimic quantile-based moment measures from robust statistics. An empirical study of index options detects two distinct premiums for dispersion and asymmetry, but no premium for steepness. This finding is in clear contrast to results obtained through traditional moment swaps and warns us to interpret moment premiums carefully.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129918412","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}
In this study, I analyze the impact of the aggregate, income, corporate, and social security tax revenues on both the U.S. output and the stock market return in a structural vector autoregression (SVAR) framework between 1960:Q1 and 2015:Q4. Unlike some of the other studies, I use not only aggregate but also disaggregated tax revenue variables to examine the impact of fiscal policy. Results show that an exogenous increase in aggregate tax revenue reduces both the output and the market return. In addition, an increase in income, corporate, and social security tax revenues reduces both output and the market return significantly at varying degrees.
{"title":"The Impact of Fiscal Policy on the U.S. Stock Market Return","authors":"Ilhami Gunduz","doi":"10.2139/ssrn.3691278","DOIUrl":"https://doi.org/10.2139/ssrn.3691278","url":null,"abstract":"In this study, I analyze the impact of the aggregate, income, corporate, and social security tax revenues on both the U.S. output and the stock market return in a structural vector autoregression (SVAR) framework between 1960:Q1 and 2015:Q4. Unlike some of the other studies, I use not only aggregate but also disaggregated tax revenue variables to examine the impact of fiscal policy. Results show that an exogenous increase in aggregate tax revenue reduces both the output and the market return. In addition, an increase in income, corporate, and social security tax revenues reduces both output and the market return significantly at varying degrees.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131962362","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}
This paper proposes an empirical model for analyzing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010-2017 and 2010-2019. Price discovery is achieved through the Gonzalo-Granger permanent-transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin, and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalized by individuals’ search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018-2019 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.
{"title":"Analysis of Bitcoin Prices Using Market and Sentiment Variables","authors":"Burcu Kapar, Jose Olmo","doi":"10.2139/ssrn.3691756","DOIUrl":"https://doi.org/10.2139/ssrn.3691756","url":null,"abstract":"This paper proposes an empirical model for analyzing the dynamics of Bitcoin prices. To do this, we consider a vector error correction model over two overlapping periods: 2010-2017 and 2010-2019. Price discovery is achieved through the Gonzalo-Granger permanent-transitory decomposition. The pricing factors are endogenous linear combinations of the S&P 500 index, gold price, a Google search variable associated to Bitcoin, and a fear index proxied by the FED Financial Stress Index. Our empirical analysis shows that during the first period a linear combination of four pricing factors describes the efficient Bitcoin price. The S&P 500 index and Google searches have a positive effect whereas gold prices and the fear index have a negative effect. In contrast, during the second period, the efficient price behaves idiosyncratically and can be only rationalized by individuals’ search for information on the cryptocurrency. These findings provide empirical evidence on the presence of a correction in Bitcoin prices during the period 2018-2019 uncorrelated to market fundamentals. We also show that standard empirical asset pricing models perform poorly for explaining Bitcoin prices.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127197887","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}
In the Chinese stock market, we find that the cross-sectional relation between value-at-risk (VaR) and expected returns is unclear, which is different from the recent findings in the United States. Additionally, VaR is negatively related with expected returns and cannot be explained by idiosyncratic volatility, momentum, short-term reversal, or maximum daily return during a high consumer confidence period. In contrast, no significant relation is observed between VaR and expected returns during a period of low consumer confidence.
{"title":"Value at Risk and the Cross-Section of Expected Returns: Evidence from China","authors":"Pingshu Gui, Yifeng Zhu","doi":"10.2139/ssrn.3579848","DOIUrl":"https://doi.org/10.2139/ssrn.3579848","url":null,"abstract":"In the Chinese stock market, we find that the cross-sectional relation between value-at-risk (VaR) and expected returns is unclear, which is different from the recent findings in the United States. Additionally, VaR is negatively related with expected returns and cannot be explained by idiosyncratic volatility, momentum, short-term reversal, or maximum daily return during a high consumer confidence period. In contrast, no significant relation is observed between VaR and expected returns during a period of low consumer confidence.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130639921","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}
This essay discusses LIBOR based rates and how they are used to value financial instruments in the fixed income market. The essay also analyzes potential gaps that could be created by transitioning from LIBOR based rates that are forward-looking to alternative reference rates that are historical in nature. Finally, the essay proffers some suggestions on alternative methodologies and techniques that could be used to value fixed income should the world transition to a new set of rates that are entirely historical in nature. The main takeaway is that in order to ensure a seamless transition, market stakeholders need to work out modalities on the methodologies and techniques that will be used to value financial instruments going forward in order to prevent distortions to the financial system.
{"title":"London Interbank Offered Rate (LIBOR) Transition – Matters Arising","authors":"Oluwaseyi (Tony) Awoga CPA, PRM","doi":"10.2139/ssrn.3740806","DOIUrl":"https://doi.org/10.2139/ssrn.3740806","url":null,"abstract":"This essay discusses LIBOR based rates and how they are used to value financial instruments in the fixed income market. The essay also analyzes potential gaps that could be created by transitioning from LIBOR based rates that are forward-looking to alternative reference rates that are historical in nature. Finally, the essay proffers some suggestions on alternative methodologies and techniques that could be used to value fixed income should the world transition to a new set of rates that are entirely historical in nature. The main takeaway is that in order to ensure a seamless transition, market stakeholders need to work out modalities on the methodologies and techniques that will be used to value financial instruments going forward in order to prevent distortions to the financial system.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123052151","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}
We have seen China’s growing role in the past decades, and the world economy has become more exposed to the influence of China. This paper explores emerging China's impact on the global equity market through the lens of asset pricing. We study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns can significantly predict other markets' stock returns, but not vice versa. We augmented the predictive model with Chen, Roll, and Ross (1986)'s macroeconomic risk factors, and find that the macro fundamentals cannot explain the predictive power of the lagged China returns. We also documented that the information diffusion of the US market occurs at the short-horizons (e.g. one-week) while the information diffusion of the China market occurs at the longer-horizons (e.g. one-month). Further evidence shows the lagged China returns during the low investor-attention period have stronger predictability compared to performance during the high attention period, which is in line with the information friction theory that the attention-constrained investors fail to allocate attention to certain economic state variables when making decisions, meanwhile cause the slow information diffusion across markets. Overall, our results indicate that the lagged China returns should be regarded as a global state variable that helps us predict future stock returns.
在过去的几十年里，我们看到中国的作用越来越大，世界经济越来越受到中国的影响。本文从资产定价的角度探讨了新兴中国对全球股票市场的影响。我们研究了中国滞后收益对全球股票收益的预测特性，发现中国滞后收益可以显著预测其他市场的股票收益，反之则不能。我们用Chen, Roll, and Ross(1986)的宏观经济风险因素对预测模型进行了扩充，发现宏观基本面不能解释滞后的中国收益的预测能力。我们还记录了美国市场的信息扩散发生在短期(如一周)，而中国市场的信息扩散发生在较长期(如一个月)。进一步的证据表明，相对于高关注度时期的表现，低关注度时期的滞后中国收益具有更强的可预测性，这符合信息摩擦理论，即注意力受限的投资者在决策时未能将注意力分配到某些经济状态变量上，同时导致信息在市场间扩散缓慢。总体而言，我们的结果表明，滞后的中国回报应被视为一个全球性的状态变量，帮助我们预测未来的股票回报。
{"title":"China Markets, Information Diffusion, and Global Stock Return Predictability","authors":"Yulong Sun","doi":"10.2139/ssrn.3683475","DOIUrl":"https://doi.org/10.2139/ssrn.3683475","url":null,"abstract":"We have seen China’s growing role in the past decades, and the world economy has become more exposed to the influence of China. This paper explores emerging China's impact on the global equity market through the lens of asset pricing. We study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns can significantly predict other markets' stock returns, but not vice versa. We augmented the predictive model with Chen, Roll, and Ross (1986)'s macroeconomic risk factors, and find that the macro fundamentals cannot explain the predictive power of the lagged China returns. We also documented that the information diffusion of the US market occurs at the short-horizons (e.g. one-week) while the information diffusion of the China market occurs at the longer-horizons (e.g. one-month). Further evidence shows the lagged China returns during the low investor-attention period have stronger predictability compared to performance during the high attention period, which is in line with the information friction theory that the attention-constrained investors fail to allocate attention to certain economic state variables when making decisions, meanwhile cause the slow information diffusion across markets. Overall, our results indicate that the lagged China returns should be regarded as a global state variable that helps us predict future stock returns.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131652283","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}
By defining a back-test residual for an empirical short-term drift-diffusion model, we are able to use a distribution of these residuals from long term historical back-tests to adjust or correct the drift and diffusion parameters of the short-term model for improved back-tests. In other words, we can use drift-diffusion predict steps into withheld historical data regions to then compute corrections of the drift-diffusion models themselves. Corrections may be of drift only, diffusion only, or both, and corrections can be additive or multiplicative, depending on modeler judgement or post-corrected back-test quality metrics. These adjustments by definition correct poor back-tests often seen in drift-diffusion models, especially over longer time ranges (e.g. the corrections make the models more historically realistic) and may yield improved price- probability forecasts ex ante. While this predictor-corrector method does not replace other model calibration methods, it provides a quick way to provide information feedback from long term back-tests and get models into the ballpark of historical accuracy.
{"title":"A Predictor-Corrector Method for Drift-Diffusion Asset Price Models","authors":"B. Kachnowski","doi":"10.2139/ssrn.3654426","DOIUrl":"https://doi.org/10.2139/ssrn.3654426","url":null,"abstract":"By defining a back-test residual for an empirical short-term drift-diffusion model, we are able to use a distribution of these residuals from long term historical back-tests to adjust or correct the drift and diffusion parameters of the short-term model for improved back-tests. In other words, we can use drift-diffusion predict steps into withheld historical data regions to then compute corrections of the drift-diffusion models themselves. Corrections may be of drift only, diffusion only, or both, and corrections can be additive or multiplicative, depending on modeler judgement or post-corrected back-test quality metrics. These adjustments by definition correct poor back-tests often seen in drift-diffusion models, especially over longer time ranges (e.g. the corrections make the models more historically realistic) and may yield improved price- probability forecasts ex ante. While this predictor-corrector method does not replace other model calibration methods, it provides a quick way to provide information feedback from long term back-tests and get models into the ballpark of historical accuracy.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131920820","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}
Initial Coin Offerings (ICOs) have grown substantially in recent years. They involve issuing coins that are recorded on a block-chain. These can be used to purchase the service or good that the firm they finance produces. The coins can be exchanged for currency on cryptocurrency exchanges. Although many ICOs are fraudulent, most studies find positive average and median returns. Theoretical analyses suggest they can have several advantages compared to Initial Public Offerings (IPOs). They are regulated in widely differing ways with the UK, Switzerland and Singapore having regimes that make them easier to undertake than other countries.
{"title":"Initial Coin Offerings, Corporate Finance and Financial Regulation","authors":"Franklin Allen","doi":"10.2139/ssrn.3664684","DOIUrl":"https://doi.org/10.2139/ssrn.3664684","url":null,"abstract":"Initial Coin Offerings (ICOs) have grown substantially in recent years. They involve issuing coins that are recorded on a block-chain. These can be used to purchase the service or good that the firm they finance produces. The coins can be exchanged for currency on cryptocurrency exchanges. Although many ICOs are fraudulent, most studies find positive average and median returns. Theoretical analyses suggest they can have several advantages compared to Initial Public Offerings (IPOs). They are regulated in widely differing ways with the UK, Switzerland and Singapore having regimes that make them easier to undertake than other countries.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114510497","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}
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