{"title":"A least discrimination method for portfolio optimization: an alternative to the Black–Litterman approach","authors":"J. Pezier","doi":"10.21314/JOIS.2012.015","DOIUrl":"https://doi.org/10.21314/JOIS.2012.015","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"2 1","pages":"3-38"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705731","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":"Jointly modeling the prices of American depository receipts, the local stock and the US dollar","authors":"D. Madan","doi":"10.21314/JOIS.2012.009","DOIUrl":"https://doi.org/10.21314/JOIS.2012.009","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":"3-19"},"PeriodicalIF":0.0,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705455","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 existing literature shows that cross-sectional stock returns exhibit both price momentum and earnings momentum. In this paper, we examine whether commonly used style and sector indexes also have momentum patterns. We show that style indexes exhibit strong price momentum, but give little evidence of earnings momentum. On the other hand, sector indexes exhibit both significant price momentum and earnings momentum. Moreover, we provide evidence that price momentum in style indexes can be explained by individual stock return momentum, whereas price momentum in sector indexes is driven by earnings momentum. Finally, we show that a dynamic momentum strategy can further enhance the performance of style investment even after adjusting for transaction costs.
{"title":"Momentum strategies for style and sector indexes","authors":"Linda H. Chen, G. Jiang, Kevin X. Zhu","doi":"10.21314/JOIS.2012.007","DOIUrl":"https://doi.org/10.21314/JOIS.2012.007","url":null,"abstract":"The existing literature shows that cross-sectional stock returns exhibit both price momentum and earnings momentum. In this paper, we examine whether commonly used style and sector indexes also have momentum patterns. We show that style indexes exhibit strong price momentum, but give little evidence of earnings momentum. On the other hand, sector indexes exhibit both significant price momentum and earnings momentum. Moreover, we provide evidence that price momentum in style indexes can be explained by individual stock return momentum, whereas price momentum in sector indexes is driven by earnings momentum. Finally, we show that a dynamic momentum strategy can further enhance the performance of style investment even after adjusting for transaction costs.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":"67-89"},"PeriodicalIF":0.0,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705341","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 majority of risk adjusted performance measures (RAPM) currently in use – e.g., Treynor ratio, (?/?)) ratio, Omega index, RoVaR, ‘coherent’ preference criteria, etc. – are incompat- ible with any sensible utility function and would be best avoided. We argue instead for the assessment of a maximum certainty equivalent excess return (CER*) criterion, or equivalent criteria, adapted to investment circumstances: alternative investments, return forecasts, and risk attitude. We explain the assessment of CER*s and give three applications: performance comparisons among traditional and alternative funds, optimal design of structured products, and explanation of the credit risk premium puzzle.
{"title":"Rationalization of Investment Preference Criteria","authors":"J. Pezier","doi":"10.21314/JOIS.2012.008","DOIUrl":"https://doi.org/10.21314/JOIS.2012.008","url":null,"abstract":"The majority of risk adjusted performance measures (RAPM) currently in use – e.g., Treynor ratio, (?/?)) ratio, Omega index, RoVaR, ‘coherent’ preference criteria, etc. – are incompat- ible with any sensible utility function and would be best avoided. We argue instead for the assessment of a maximum certainty equivalent excess return (CER*) criterion, or equivalent criteria, adapted to investment circumstances: alternative investments, return forecasts, and risk attitude. We explain the assessment of CER*s and give three applications: performance comparisons among traditional and alternative funds, optimal design of structured products, and explanation of the credit risk premium puzzle.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":"3-65"},"PeriodicalIF":0.0,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705399","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":"Perspectives on systemic risk","authors":"Dean Curnutt, George Lam","doi":"10.21314/JOIS.2011.074","DOIUrl":"https://doi.org/10.21314/JOIS.2011.074","url":null,"abstract":"","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":"107-114"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67704882","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 present a set of log-price integrated variance estimators, equal to the sum of open-high-low-close bridge estimators of spot variances within $n$ subsequent time-step intervals. The main characteristics of some of the introduced estimators is to take into account the information on the occurrence times of the high and low values. The use of the high's and low's of the bridge associated with the original process makes the estimators significantly more efficient that the standard realized variance estimators and its generalizations. Adding the information on the occurrence times of the high and low values improves further the efficiency of the estimators, much above those of the well-known realized variance estimator and those derived from the sum of Garman and Klass spot variance estimators. The exact analytical results are derived for the case where the underlying log-price process is an It^o stochastic process. Our results suggests more efficient ways to record financial prices at intermediate frequencies.
{"title":"Time-Bridge Estimators of Integrated Variance","authors":"A. Saichev, D. Sornette","doi":"10.21314/JOIS.2013.019","DOIUrl":"https://doi.org/10.21314/JOIS.2013.019","url":null,"abstract":"We present a set of log-price integrated variance estimators, equal to the sum of open-high-low-close bridge estimators of spot variances within $n$ subsequent time-step intervals. The main characteristics of some of the introduced estimators is to take into account the information on the occurrence times of the high and low values. The use of the high's and low's of the bridge associated with the original process makes the estimators significantly more efficient that the standard realized variance estimators and its generalizations. Adding the information on the occurrence times of the high and low values improves further the efficiency of the estimators, much above those of the well-known realized variance estimator and those derived from the sum of Garman and Klass spot variance estimators. The exact analytical results are derived for the case where the underlying log-price process is an It^o stochastic process. Our results suggests more efficient ways to record financial prices at intermediate frequencies.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"2 1","pages":"71-108"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705763","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}
Based on two hundred years of annual data of the Netherlands , Germany , US and Japan we analyse the mean reversion of long-term interest rates, by unit root tests over rolling windows and taking into account structural breaks and regime changes. While short-term rates and the yield curve tend to revert to their long-term average value, long-term rates can persistently deviate from it. At the outside, we only find weak statistical evidence for mean reversion of long-term rates. Outcomes of smooth transition autoregressive ( STAR ) models for long-term interest rates, indicate that the speed of mean reversion is regime dependent, being stronger when rates are far from their equilibrium value.
{"title":"Statistical Evidence on the Mean Reversion of Interest Rates","authors":"Jan Willem van den End","doi":"10.2139/ssrn.1950596","DOIUrl":"https://doi.org/10.2139/ssrn.1950596","url":null,"abstract":"Based on two hundred years of annual data of the Netherlands , Germany , US and Japan we analyse the mean reversion of long-term interest rates, by unit root tests over rolling windows and taking into account structural breaks and regime changes. While short-term rates and the yield curve tend to revert to their long-term average value, long-term rates can persistently deviate from it. At the outside, we only find weak statistical evidence for mean reversion of long-term rates. Outcomes of smooth transition autoregressive ( STAR ) models for long-term interest rates, indicate that the speed of mean reversion is regime dependent, being stronger when rates are far from their equilibrium value.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67809453","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 study, both analytically and numerically, an ARCH-like, multiscale model of volatility, which assumes that the volatility is governed by the observed past price changes on different time scales. With a power-law distribution of time horizons, we obtain a model that captures most stylized facts of financial time series: Student-like distribution of returns with a power-law tail, long-memory of the volatility, slow convergence of the distribution of returns towards the Gaussian distribution, multifractality and anomalous volatility relaxation after shocks. At variance with recent multifractal models that are strictly time reversal invariant, the model also reproduces the time assymmetry of financial time series: past large scale volatility influence future small scale volatility. In order to quantitatively reproduce all empirical observations, the parameters must be chosen such that our model is close to an instability, meaning that (a) the feedback effect is important and substantially increases the volatility, and (b) that the model is intrinsically difficult to calibrate because of the very long range nature of the correlations. By imposing the consistency of the model predictions with a large set of different empirical observations, a reasonable range of the parameters value can be determined. The model can easily be generalized to account for jumps, skewness and multiasset correlations.
{"title":"On a multi-timescale statistical feedback model for volatility fluctuations","authors":"L. Borland, J. Bouchaud","doi":"10.21314/JOIS.2011.075","DOIUrl":"https://doi.org/10.21314/JOIS.2011.075","url":null,"abstract":"We study, both analytically and numerically, an ARCH-like, multiscale model of volatility, which assumes that the volatility is governed by the observed past price changes on different time scales. With a power-law distribution of time horizons, we obtain a model that captures most stylized facts of financial time series: Student-like distribution of returns with a power-law tail, long-memory of the volatility, slow convergence of the distribution of returns towards the Gaussian distribution, multifractality and anomalous volatility relaxation after shocks. At variance with recent multifractal models that are strictly time reversal invariant, the model also reproduces the time assymmetry of financial time series: past large scale volatility influence future small scale volatility. In order to quantitatively reproduce all empirical observations, the parameters must be chosen such that our model is close to an instability, meaning that (a) the feedback effect is important and substantially increases the volatility, and (b) that the model is intrinsically difficult to calibrate because of the very long range nature of the correlations. By imposing the consistency of the model predictions with a large set of different empirical observations, a reasonable range of the parameters value can be determined. The model can easily be generalized to account for jumps, skewness and multiasset correlations.","PeriodicalId":90597,"journal":{"name":"Journal of interaction science","volume":"1 1","pages":"65-104"},"PeriodicalIF":0.0,"publicationDate":"2005-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67705326","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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