ERN: Portfolio Optimization (Topic)最新文献

Buy Low Sell High: A High Frequency Trading Perspective 低买高卖:高频交易视角

ERN: Portfolio Optimization (Topic) Pub Date : 2014-04-15 DOI: 10.2139/ssrn.1964781

Á. Cartea, S. Jaimungal, Jason Ricci

引用次数: 192

The Strategy Approval Decision: A Sharpe Ratio Indifference Curve Approach 战略批准决策:一种夏普比率无差异曲线方法

ERN: Portfolio Optimization (Topic) Pub Date : 2013-01-01 DOI: 10.2139/ssrn.2003638

D. Bailey, M. L. Prado, Eva del Pozo

{"title":"The Strategy Approval Decision: A Sharpe Ratio Indifference Curve Approach","authors":"D. Bailey, M. L. Prado, Eva del Pozo","doi":"10.2139/ssrn.2003638","DOIUrl":"https://doi.org/10.2139/ssrn.2003638","url":null,"abstract":"The problem of capital allocation to a set of strategies could be partially avoided or at least greatly simplified with an appropriate strategy approval decision process. This paper proposes such a procedure. We begin by splitting the capital allocation problem into two sequential stages: strategy approval and portfolio optimization. Then we argue that the goal of the second stage is to beat a naive benchmark, and the goal of the first stage is to identify which strategies improve the performance of such a naive benchmark. We believe that this is a sensible approach, as it does not leave all the work to the optimizer, thus adding robustness to the final outcome. We introduce the concept of the Sharpe ratio indifference curve, which represents the space of pairs (candidate strategy's Sharpe ratio, candidate strategy's correlation to the approved set) for which the Sharpe ratio of the expanded approved set remains constant. We show that selecting strategies (or portfolio managers) solely based on past Sharpe ratio will lead to suboptimal outcomes, particularly when we ignore the impact that these decisions will have on the average correlation of the portfolio. Our strategy approval theorem proves that, under certain circumstances, it is entirely possible for firms to improve their overall Sharpe ratio by hiring portfolio managers with negative expected performance. Finally, we show that these results have important practical business implications with respect to the way investment firms hire, layoff and structure payouts.","PeriodicalId":178382,"journal":{"name":"ERN: Portfolio Optimization (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114315761","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}

引用次数: 5

Risk Management and Portfolio Budgeting Based on ARMA-GARCH Non-Gaussian Multivariate Model 基于ARMA-GARCH非高斯多元模型的风险管理与投资组合预算

ERN: Portfolio Optimization (Topic) Pub Date : 2012-03-15 DOI: 10.2139/ssrn.2022513

N. Nooshi, Y. S. Kim, S. Rachev, F. Fabozzi

{"title":"Risk Management and Portfolio Budgeting Based on ARMA-GARCH Non-Gaussian Multivariate Model","authors":"N. Nooshi, Y. S. Kim, S. Rachev, F. Fabozzi","doi":"10.2139/ssrn.2022513","DOIUrl":"https://doi.org/10.2139/ssrn.2022513","url":null,"abstract":"In this work, we propose an ARMA(1,1)-GARCH(1,1) model with standard classical tempered stable (CTS) innovations for historical daily returns of 29 selected stocks. The non-Gaussian nature of the innovations captures the fat-tail property observed in data. The dependency between different assets is modeled by a student’s t copula. We fit the data and estimate the parameters of the model and perform statistical goodness-of-fit tests for fitted parameters. Based on the multivariate model consisting of standard CTS marginals and student’s t copula, we construct ARMA-GARCH Monte-Carlo paths for daily returns of each single stock. Daily VaR is computed for an equally weighted portfolio, and for a time span of 250 trading days, the model is being backtested. It is shown that in comparison with the Gaussian model, the proposed CTS-t copula offers more realistic estimation for the portfolio risk. Moreover we study the portfolio selection problem. We compute the marginal VaR and Component VaR of single stocks for the VaR optimized portfolio. We consider an active portfolio budgeting method, where we change the portfolio composition according to marginal VaR measurements. We show that the resulting portfolio converges to the VaR minimized portfolio in the 29 dimensional space of portfolio weight vectors. We perform a return to VaR ratio, performance test, to realize the ”costs” of this risk reduction action in terms of potential return suppression. Little transaction costs due to limited and relatively small position modification in portfolio, presents an efficient management scenario for pension funds and other investment organization, where relative changes in investment positions are restricted.","PeriodicalId":178382,"journal":{"name":"ERN: Portfolio Optimization (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130071923","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}

引用次数: 0

Constant Proportion Portfolio Insurance Under Regime Switching Exponential L evy Process 制度切换指数L -每过程下的常比例投资组合保险

ERN: Portfolio Optimization (Topic) Pub Date : 2012-03-03 DOI: 10.2139/ssrn.2015852

Chengguo Weng

引用次数: 15

Ensemble Properties of High Frequency Data and Intraday Trading Rules 高频数据和日内交易规则的集成特性

ERN: Portfolio Optimization (Topic) Pub Date : 2012-02-09 DOI: 10.2139/ssrn.2001981

F. Baldovin, F. Camana, M. Caporin, M. Caraglio, A. Stella

{"title":"Ensemble Properties of High Frequency Data and Intraday Trading Rules","authors":"F. Baldovin, F. Camana, M. Caporin, M. Caraglio, A. Stella","doi":"10.2139/ssrn.2001981","DOIUrl":"https://doi.org/10.2139/ssrn.2001981","url":null,"abstract":"Regarding the intraday sequence of high frequency returns of the S&P index as daily realizations of a given stochastic process, we first demonstrate that the scaling properties of the aggregated return distribution can be employed to define a martingale stochastic model which consistently replicates conditioned expectations of the S&P 500 high frequency data in the morning of each trading day. Then, a more general formulation of the above scaling properties allows to extend the model to the afternoon trading session. We finally outline an application in which conditioned forecasting is used to implement a trend-following trading strategy capable of exploiting linear correlations present in the S&P dataset and absent in the model. Trading signals are model-based and not derived from chartist criteria. In-sample and out-of-sample tests indicate that the model-based trading strategy performs better than a benchmark one established on an asymmetric GARCH process, and show the existence of small arbitrage opportunities. We remark that in the absence of linear correlations the trading profit would vanish and discuss why the trading strategy is potentially interesting to hedge volatility risk for S&P index-based products.","PeriodicalId":178382,"journal":{"name":"ERN: Portfolio Optimization (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114526414","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}

引用次数: 9

The Two-Block Covariance Matrix and the CAPM 二块协方差矩阵与CAPM

ERN: Portfolio Optimization (Topic) Pub Date : 2012-01-24 DOI: 10.2139/ssrn.1963124

David J. Disatnik, S. Benninga

引用次数: 2

Indonesian Stock Market Crisis Observation with Spectral and Composite Index 用光谱和综合指数观察印尼股市危机

ERN: Portfolio Optimization (Topic) Pub Date : 2012-01-14 DOI: 10.2139/ssrn.1985714

Hokky Situngkir

引用次数: 0

Forecasting the Size Premium Over Different Time Horizons 预测不同时间范围内的规模溢价

ERN: Portfolio Optimization (Topic) Pub Date : 2011-10-31 DOI: 10.2139/ssrn.1951931

Valeriy Zakamulin

引用次数: 18

P-Rise (Probability of Rise) Calculated From Moving Averages P-Rise(上升概率)由移动平均线计算

ERN: Portfolio Optimization (Topic) Pub Date : 2011-10-10 DOI: 10.2139/ssrn.1922456

M. Iqbal

引用次数: 1

Determination of Optimal Contribution Rate and Optimal Investment Portfolio of Defined Benefit Pension Plan Under the Expected Shortfall Constraint 期望缺口约束下固定收益养老金计划最优缴费率和最优投资组合的确定

ERN: Portfolio Optimization (Topic) Pub Date : 2011-10-09 DOI: 10.2139/ssrn.1941458

Krzysztof Ostaszewski

引用次数: 7