{"title":"Lifecycle investing with the profitable dividend yield strategy: simulations and nonparametric analysis","authors":"W. Fong","doi":"10.21314/JOIS.2017.088","DOIUrl":"https://doi.org/10.21314/JOIS.2017.088","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48384089","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 aim of this work is to create systematic trading strategies built upon several financial crisis indicators based on the spectral properties of market dynamics. Within the limitations of our framework and data, we will demonstrate that our systematic trading strategies are able to make money, not as a result of pure luck but, in a reproducible way and while avoiding the pitfall of over fitting, as a result of the skill of the operators and their understanding and knowledge of the financial market. Using singular value decomposition (SVD) techniques in order to compute all spectra in an efficient way, we have built two kinds of financial crisis indicators with a demonstrable power of prediction. Firstly, there are those that compare at every date the distribution of the eigenvalues of a covariance or correlation matrix to a distribution of reference representing either a calm or agitated market reference. Secondly, we have those that merely compute at every date a chosen spectral property (trace, spectral radius or Frobenius norm) of a covariance or correlation matrix. Aggregating the signals provided by all the indicators in order to minimize false positive errors, we then build systematic trading strategies based on a discrete set of rules governing the investment decisions of the investor. Finally, we compare our active strategies to a passive reference as well as to random strategies in order to prove the usefulness of our approach and the added value provided by the out-of-sample predictive power of the financial crisis indicators upon which our systematic trading strategies are built.
{"title":"Winning Investment Strategies Based on Financial Crisis Indicators","authors":"Antoine Kornprobst","doi":"10.21314/JOIS.2018.102","DOIUrl":"https://doi.org/10.21314/JOIS.2018.102","url":null,"abstract":"The aim of this work is to create systematic trading strategies built upon several financial crisis indicators based on the spectral properties of market dynamics. Within the limitations of our framework and data, we will demonstrate that our systematic trading strategies are able to make money, not as a result of pure luck but, in a reproducible way and while avoiding the pitfall of over fitting, as a result of the skill of the operators and their understanding and knowledge of the financial market. Using singular value decomposition (SVD) techniques in order to compute all spectra in an efficient way, we have built two kinds of financial crisis indicators with a demonstrable power of prediction. Firstly, there are those that compare at every date the distribution of the eigenvalues of a covariance or correlation matrix to a distribution of reference representing either a calm or agitated market reference. Secondly, we have those that merely compute at every date a chosen spectral property (trace, spectral radius or Frobenius norm) of a covariance or correlation matrix. Aggregating the signals provided by all the indicators in order to minimize false positive errors, we then build systematic trading strategies based on a discrete set of rules governing the investment decisions of the investor. Finally, we compare our active strategies to a passive reference as well as to random strategies in order to prove the usefulness of our approach and the added value provided by the out-of-sample predictive power of the financial crisis indicators upon which our systematic trading strategies are built.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"7 1","pages":"27-49"},"PeriodicalIF":0.0,"publicationDate":"2017-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42962321","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 brings together Black-Litterman optimization, exotic betas, and varying starting portfolios into one complete, symbiotic framework. The approach is unique because these techniques are often viewed as alternatives, and not as complements to each other. The paper is comprised of two main sections. The first section demonstrates using exotic beta as the “views” in the Black-Litterman optimization. This approach benefits investors who already utilize the classic Black-Litterman approach and appreciate advances in the exotic beta research, and also those who focus on practical implementation of exotic betas. The second section explores using the risk parity portfolio as an efficient starting portfolio for Black-Litterman optimization on both theoretical and practical grounds. This paper demonstrates that risk parity is a highly effective starting point in many situations. Finally, as part of our discussion, we derive conditions under which almost any completely diversified portfolio may be used as a starting portfolio in the Black-Litterman process. The integrated methodology developed is robust, flexible, and easily implemented, which means that a wide range of investors can benefit from this framework.
{"title":"Black–Litterman, exotic beta and varying efficient portfolios: an integrated approach","authors":"Ricky Cooper, Marat Molyboga","doi":"10.21314/JOIS.2017.084","DOIUrl":"https://doi.org/10.21314/JOIS.2017.084","url":null,"abstract":"This paper brings together Black-Litterman optimization, exotic betas, and varying starting portfolios into one complete, symbiotic framework. The approach is unique because these techniques are often viewed as alternatives, and not as complements to each other. The paper is comprised of two main sections. The first section demonstrates using exotic beta as the “views” in the Black-Litterman optimization. This approach benefits investors who already utilize the classic Black-Litterman approach and appreciate advances in the exotic beta research, and also those who focus on practical implementation of exotic betas. The second section explores using the risk parity portfolio as an efficient starting portfolio for Black-Litterman optimization on both theoretical and practical grounds. This paper demonstrates that risk parity is a highly effective starting point in many situations. Finally, as part of our discussion, we derive conditions under which almost any completely diversified portfolio may be used as a starting portfolio in the Black-Litterman process. The integrated methodology developed is robust, flexible, and easily implemented, which means that a wide range of investors can benefit from this framework.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"6 1","pages":"13-30"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47982191","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}
Interconnectedness is an alternative risk concept that so far has earned little attention in the asset management academia and industry. In this paper, we show that this neglect is not justified, as interconnectedness risk (i) has only moderate or no connection to conventional portfolio optimization inputs and (ii) active investment strategies based on interconnectedness information outperform their conventional peers. Utilizing a multi asset dataset, we measure interconnectedness risk by the embeddedness intensity, i.e. centrality, of assets in a correlation network, a concept from graph theory. Using the most common centrality measures, we first conduct empirical similarity studies analyzing how different centrality scores relate to each other and to conventional portfolio optimization inputs. Next, we outline how centrality can be incorporated in a risk-based as well as in a risk-return-based framework. Out-of-sample performance studies of centrality-optimized portfolios prove their competitiveness.
{"title":"Interconnectedness Risk and Active Portfolio Management","authors":"Eduard Baitinger, Jochen Papenbrock","doi":"10.2139/SSRN.2796443","DOIUrl":"https://doi.org/10.2139/SSRN.2796443","url":null,"abstract":"Interconnectedness is an alternative risk concept that so far has earned little attention in the asset management academia and industry. In this paper, we show that this neglect is not justified, as interconnectedness risk (i) has only moderate or no connection to conventional portfolio optimization inputs and (ii) active investment strategies based on interconnectedness information outperform their conventional peers. Utilizing a multi asset dataset, we measure interconnectedness risk by the embeddedness intensity, i.e. centrality, of assets in a correlation network, a concept from graph theory. Using the most common centrality measures, we first conduct empirical similarity studies analyzing how different centrality scores relate to each other and to conventional portfolio optimization inputs. Next, we outline how centrality can be incorporated in a risk-based as well as in a risk-return-based framework. Out-of-sample performance studies of centrality-optimized portfolios prove their competitiveness.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46882793","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":"Risk constraints for portfolio optimization with fixed-fee transaction cost","authors":"M. Hirsch, N. Navarro","doi":"10.21314/JOIS.2017.082","DOIUrl":"https://doi.org/10.21314/JOIS.2017.082","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42867254","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":"Investing across periods with Mahalanobis distances","authors":"Edouard Sénéchal, Brian D. Singer","doi":"10.21314/JOIS.2017.080","DOIUrl":"https://doi.org/10.21314/JOIS.2017.080","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41815853","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}
Pub Date : 2016-12-01DOI: 10.1186/s40166-016-0015-5
G. S. Bahr, C. Stary
{"title":"What is interaction science? Revisiting the aims and scope of JoIS","authors":"G. S. Bahr, C. Stary","doi":"10.1186/s40166-016-0015-5","DOIUrl":"https://doi.org/10.1186/s40166-016-0015-5","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"4 1","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40166-016-0015-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65837064","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":"Equal risk allocation with carry, value and momentum","authors":"B. Gnedenko, Igor Yelnik","doi":"10.21314/JOIS.2016.075","DOIUrl":"https://doi.org/10.21314/JOIS.2016.075","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67706487","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}
T. Heckel, Raul Leote de Carvalho, Xiao Lu, Romain Perchet
{"title":"Insights into robust optimization: decomposing into mean–variance and risk-based portfolios","authors":"T. Heckel, Raul Leote de Carvalho, Xiao Lu, Romain Perchet","doi":"10.21314/JOIS.2016.076","DOIUrl":"https://doi.org/10.21314/JOIS.2016.076","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67706755","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 applies a forward looking approach to the minimum variance portfolio optimisation problem for a selection of 100 stocks. The purpose is to determine which market conditions favour this strategy of using option implied information. Out-of-sample volatility, Sharpe ratio, and certainty equivalent return is measured against eight benchmarks, including the equal weighted 1/N and minimum variance portfolio based on historical estimates. Equivalent or superior performance is evident in terms of reduced volatility and higher certainty equivalent return. However, strict outperformance of the best benchmarks is only seen when option-to-stock volume ratios are high and information signals in the options market are strongest.
{"title":"The effect of market conditions on forward-looking portfolio performance","authors":"Binam Ghimire, L. Perrott, D. Karki","doi":"10.21314/JOIS.2016.073","DOIUrl":"https://doi.org/10.21314/JOIS.2016.073","url":null,"abstract":"This paper applies a forward looking approach to the minimum variance portfolio optimisation problem for a selection of 100 stocks. The purpose is to determine which market conditions favour this strategy of using option implied information. Out-of-sample volatility, Sharpe ratio, and certainty equivalent return is measured against eight benchmarks, including the equal weighted 1/N and minimum variance portfolio based on historical estimates. Equivalent or superior performance is evident in terms of reduced volatility and higher certainty equivalent return. However, strict outperformance of the best benchmarks is only seen when option-to-stock volume ratios are high and information signals in the options market are strongest.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67706297","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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