PSN: Computational Models (Quantitative) (Topic)最新文献

{"title":"The Impact of Initial Margin on Derivatives Pricing with an Application of Machine Learning","authors":"Matthias Vierkoetter","doi":"10.2139/ssrn.3427230","DOIUrl":"https://doi.org/10.2139/ssrn.3427230","url":null,"abstract":"In this paper we consider the impact of bilateral initial margin on derivatives pricing. We first introduce the background of bilateral initial margin. Then, we focus on how initial margin effects counterparty credit exposures, capital requirements and funding costs. Nowadays, besides risk-neutral valuation principles, these components are included when pricing derivatives through so-called valuation adjustments (xVAs). Based on this, we present an approach which incorporates initial margin into existing xVA frameworks. Then, we give an overview of the most common methods for calculating future initial margin. Moreover, we present a regression model which is based on machine learning methods. Finally, we show some numerical results for a cross currency swap, an fx option and a Bermudan swaption including a scenario analysis. Here, it turns out that it is much more important to consider margin agreement, regulatory or non-modellable parameters in detail than implementing a most accurate dynamic initial margin model.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121126028","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":"3 Persons, 2 Cuts: A Maximin Envy-Free and a Maximally Equitable Cake-Cutting Algorithm","authors":"S. Brams, P. Landweber","doi":"10.2139/ssrn.3126935","DOIUrl":"https://doi.org/10.2139/ssrn.3126935","url":null,"abstract":"We describe a 3-person, 2-cut envy-free cake-cutting algorithm, inspired by a continuous moving-knife procedure, that does not require that the players continuously move knifes across the cake. By having the players submit their value functions over the cake to a referee—rather than move knives according to these functions—the referee can ensure that the division is not only envy-free but also maximin. In addition, the referee can use the value functions to find a maximally equitable division, whereby the players receive equally valued shares that are maximal, but this allocation may not be envy-free.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123512164","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":"We Don't Know What We Don't Know: When and How the Use of Twitter's Public APIs Biases Scientific Inference","authors":"Rebekah Tromble, A. Storz, D. Stockmann","doi":"10.2139/ssrn.3079927","DOIUrl":"https://doi.org/10.2139/ssrn.3079927","url":null,"abstract":"Though Twitter research has proliferated, no standards for data collection have crystallized. When using keyword queries, the most common data sources—the Search and Streaming APIs—rarely return the full population of tweets, and scholars do not know whether their data constitute a representative sample. This paper seeks to provide the most comprehensive look to-date at the potential biases that may result. Employing data derived from four identical keyword queries to the Firehose (which provides the full population of tweets but is cost-prohibitive), Streaming, and Search APIs, we use Kendall’s-tau and logit regression analyses to understand the differences in the datasets, including what user and content characteristics make a tweet more or less likely to appear in sampled results. We find that there are indeed systematic differences that are likely to bias scholars’ findings in almost all datasets we examine, and we recommend significant caution in future Twitter research.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"461 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121231225","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":"Agents with Multiple Monies: Can the Monetary Policy Trilemma Be Solved?","authors":"Vishal Wilde","doi":"10.2139/ssrn.3282658","DOIUrl":"https://doi.org/10.2139/ssrn.3282658","url":null,"abstract":"An Agent-based Model (ABM) of an economy and/or economies was implemented to investigate whether the Monetary Policy Trilemma can be solved. Money-demanding agents with heterogeneous preferences over interest rates and exchange rates can freely use multiple monies (with each money corresponding to money-supplying agents with heterogeneous preferences). There were no restrictions on capital movement so the hypothesis tests primarily focused on simultaneous monetary autonomy and fixed exchange rates. The ABM uses an extended version of the interest-parity condition. Adaptive expectations w.r.t exchange/interest rates were used by money-demanding agents (using perfectly rational expectations would have been too computationally intensive) and decisions were made according to the money-suppliers’ and money-demanders’ rationality regarding the impact upon their heterogeneous utility functions. A key finding was that the Trilemma can be solved: monetary autonomy and fixed exchange rates are simultaneously possible in various circumstances. The success rate typically increases over time steps and settles/fluctuates around a certain level. Success generally sharply decreases when ‘Helicopter Money’ is implemented (a more ‘extreme’ monetary autonomy test). The monies with fixed exchange rates often also correspond with money-supply expansions (even when Helicopter Money is implemented). Ceteris paribus, more monies in the system decreases the success rate but increases economic growth.Higher economic growth is correlated with less inequality. Ceteris paribus, the number of money-demanders does not have a discernible impact upon economic growth. An alternative interpretation of all these findings is that the Trilemma should not even theoretically exist or be a problem if there are no capital restrictions – contemporary institutional restrictions are briefly discussed. However, the model is demand-driven and the trading mechanisms, protocol, rationality behind money-creation etc. could be more sophisticated still. Nevertheless, the results are still insightful; they offer food for thought in contemporary debates on macroeconomic and monetary policy. The ABM itself is also a rudimentary formalisation of the theory that “money is an instrument of expectations-management.” The ABM is generalisable – it could apply, for example, to cities, conurbations, regions, countries, multiple countries, industries, continents, the world, transnational communities etc. It was implemented using Python and MESA (ABM framework).","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128194592","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":"Improving the Early Warning Function of Civil War Onset Models Using Automated Event Data","authors":"H. Roos, Artur N. Usanov, N. Farnham, T. Sweijs","doi":"10.2139/ssrn.2948293","DOIUrl":"https://doi.org/10.2139/ssrn.2948293","url":null,"abstract":"This research note explains our approach to political violence forecasting employing a combination of structural and automated event data. We have created four civil war onset models using data from 1979-1999 (in sample), which we then use to predict the onset of civil war from 2000-2015 (out-of-sample). Our time horizon is one month into the future. The predictive performance of our best model as measured by its area under the receiver operating characteristic (ROC) curve is 0.881. All 24 conflict onsets between 2000-2015 occurred within countries in the top half of our risk ranking, with 79% of these onsets falling in the top 20% category, and 58% in the top 10% category. Our findings suggest that models incorporating both structural and automated event data have significantly stronger predictive power than those that rely exclusively on structural data. Conclusions and guidelines for future research are provided on the basis of our results.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131942622","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":"Kuomintang, Chinese Nationalist Party, and the Disputed Assets","authors":"Eric Lin","doi":"10.2139/ssrn.2029959","DOIUrl":"https://doi.org/10.2139/ssrn.2029959","url":null,"abstract":"KMT, often translated as the Chinese Nationalist Party, seized assets from the Japanese colonial government and private business at the end of World War II. As the current ruling party, KMT remains one of the richest political organizations in the world. The entire KMT property and division of wealth in Taiwan after WW II is often referred to as the “disputed assets.” Under the early years of the authoritarian regime, the Chinese Nationalist Party (KMT) was able to conceal most of its stolen assets by setting its own set of rules and regulation. Outside of the KMT organization, political parties and social groups have all demanded that KMT accept more social and political responsibility by releasing a complete history of all its assets and transactions, including the documentation of title transfers, account management, and account transfers. There are several dimensions to this issue: politics, policy, history, and law. This research predicts how KMT will solve the issue, and the ultimate result is very close to that predicted in advance, with an expected utility model.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114514497","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":"An Ecological Item-Response Model for Multiple Subsets of Respondents with Application to the European Court of Justice","authors":"Michael Malecki","doi":"10.2139/ssrn.1441414","DOIUrl":"https://doi.org/10.2139/ssrn.1441414","url":null,"abstract":"The European Court of Justice (ECJ) has fostered the development of a common European legal order, and in doing so, has asserted itself and its supremacy more, and more successfully, than any other international court. It has maintained features of international courts such as its composition of one judge per member state, while employing other tools of national high courts such as en banc decisions and organization into chambers, that together hide internal dissent and shield the ECJ from direct monitoring or curbing by the member states. The same shield has frustrated efforts to quantify the court's responsiveness to member states, with limited evidence that the ECJ yields to some member-state interest some of the time, but nonetheless has advanced integration beyond national governments' wishes. This equivocation arises at least in part from a failure to include relevant information about the court's composition and organization.In fact, the six-year renewable terms of judges, their previous qualifications and affiliations, and the internal organization into chambers all provide prior information that can and should be incorporated into a more complete model of judicial behavior. I develop an extension of the well-studied item-response model to infer judges' preferences, using the structured ecological data from the cases they heard and relevant prior information about judges and the national governments that appoint them as well as information about cases. I offer new, more rigorous tests for existing theoretical hypotheses about the ECJ's deference to certain actors and preference for integration. The model is applicable to other settings of structured ecological data. Many other national and international courts hear cases in subset chambers, and relevant prior information should be included rather than ignored in models of judicial behavior.","PeriodicalId":169291,"journal":{"name":"PSN: Computational Models (Quantitative) (Topic)","volume":"2677 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444137","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}