Forecasting and Managing Correlation Risks
References
- (2010) High-frequency covariance estimates with noisy and asynchronous financial data. J. Amer. Statist. Assoc. 105(492):1504–1517.Crossref, Google Scholar
- (2024) Forecasting large realized covariance matrices: The benefits of factor models and shrinkage. J. Financial Econometrics 22(3):696–742.Crossref, Google Scholar
- (2000) Great realizations. Risk 13:105–108.Google Scholar
- (2003) Modeling and forecasting realized volatility. Econometrica 71(2):579–625.Crossref, Google Scholar
- (2014) Connected stocks. J. Finance 69(3):1099–1127.Crossref, Google Scholar
- (2016) Passive investors, not passive owners. J. Financial Econom. 121(1):111–141.Crossref, Google Scholar
- (2016) Lassoing the HAR model: A model selection perspective on realized volatility dynamics. Econom. Rev. 35(8–10):1485–1521.Crossref, Google Scholar
- (2011) A general multivariate threshold GARCH model with dynamic conditional correlations. J. Bus. Econom. Statist. 29(1):138–149.Crossref, Google Scholar
- (2010) Asset Pricing and Portfolio Choice Theory (Oxford University Press, Oxford, UK).Google Scholar
- (2023) Option return predictability with machine learning and big data. Rev. Financial Stud. 36(9):3548–3602.Crossref, Google Scholar
- (2022) Predicting corporate bond returns: Merton meets machine learning. Working paper, Georgetown University, Washington, DC.Google Scholar
- (2008) Using high-frequency data in dynamic portfolio choice. Econom. Rev. 27(1–3):163–198.Crossref, Google Scholar
- (2005) Comovement. J. Financial Econom. 75(2):283–317.Crossref, Google Scholar
- (2004) Econometric analysis of realized covariation: High-frequency based covariance, regression, and correlation in financial economics. Econometrica 72(3):885–925.Crossref, Google Scholar
- (2010) Measuring downside risk: Realised semivariance. Bollerslev T , Russell J , Watson M , eds. Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle (Oxford University Press, Oxford, UK), 117–136.Crossref, Google Scholar
- (1990) Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. Rev. Econom. Statist. 72(3):498–505.Crossref, Google Scholar
- (2022) Realized semi(co)variation: Signs that all volatilities are not created equal. J. Financial Econometrics 20(2):219–252.Crossref, Google Scholar
- (2019) High-dimensional multivariate realized volatility estimation. J. Econom. 212(1):116–136.Crossref, Google Scholar
- (2018a) Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions. J. Econom. 207(1):71–91.Crossref, Google Scholar
- (2020a) Multivariate leverage effects and realized semicovariance GARCH models. J. Econom. 217(2):411–430.Crossref, Google Scholar
- (2022a) Equity clusters through the lens of realized semicorrelations. Econom. Lett. 211:110245.Crossref, Google Scholar
- (2018b) Risk everywhere: Modeling and managing volatility. Rev. Financial Stud. 31(7):2729–2773.Crossref, Google Scholar
- (2020b) Realized semicovariances. Econometrica 88(4):1515–1551.Crossref, Google Scholar
- (2022b) From zero to hero: Realized partial (co)variances. J. Econom. 231(2):348–360.Crossref, Google Scholar
- (2024) Option-implied dependence and correlation risk premium. J. Financial Quant. Anal. 59(7):3139–3189.Crossref, Google Scholar
- (2011) Style-related comovement: Fundamentals or labels. J. Finance 66(1):307–332.Crossref, Google Scholar
- (2020) Realized volatility forecasting with neural networks. J. Financial Econometrics 18(3):502–531.Crossref, Google Scholar
- (2014) When there is no place to hide: Correlation risk and the cross-section of hedge fund returns. Rev. Financial Stud. 27(2):581–616.Crossref, Google Scholar
- (2012) Measuring equity risk with option-implied correlations. Rev. Financial Stud. 25(10):3113–3140.Crossref, Google Scholar
- (2006) Asymmetric dynamics in the correlations of global equity and bond returns. J. Financial Econometrics 4(4):537–572.Crossref, Google Scholar
- (1999) On portfolio optimization: Forecasting covariances and choosing the risk model. Rev. Financial Stud. 12(5):937–974.Crossref, Google Scholar
- (2022) Open source cross-sectional asset pricing. Critical Finance Rev. 27:207–264.Crossref, Google Scholar
- (2024) Deep learning in asset pricing. Management Sci. 70(2):714–750.Link, Google Scholar
- (2019) Empirical investigation of an equity pairs trading strategy. Management Sci. 65(1):370–389.Link, Google Scholar
- (2023) A machine learning approach to volatility forecasting. J. Financial Econometrics 21(5):1680–1727.Crossref, Google Scholar
- (2024) Characteristics and the cross-section of covariances. Working paper, North Carolina State University, Raleigh.Google Scholar
- (2025) Growing the efficient frontier on panel trees. J. Financial Econom. 167:104024.Crossref, Google Scholar
- (2026) Mosaics of predictability. Working paper, Nanyang Technological University, Singapore.Google Scholar
- (2009) A simple approximate long-memory model of realized volatility. J. Financial Econometrics 7(2):174–196.Crossref, Google Scholar
- (2016) Estimating security betas using prior information based on firm fundamentals. Rev. Financial Stud. 29(4):1072–1112.Crossref, Google Scholar
- (1995) Comparing predictive accuracy. J. Bus. Econom. Statist. 13(3):253–263.Crossref, Google Scholar
- (1997) An artificial neural network-GARCH model for international stock return volatility. J. Empirical Finance 4(1):17–46.Crossref, Google Scholar
- (2022) Anomalies and expected market return. J. Finance 77(1):639–681.Crossref, Google Scholar
- (2009) The price of correlation risk: Evidence from equity options. J. Finance 64(3):1377–1406.Crossref, Google Scholar
- (2013) Option-implied correlations and the price of correlation risk. Working paper, Tilburg University, Tilburg, Ethiopia.Google Scholar
- (2002) Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. J. Bus. Econom. Statist. 20(3):339–550.Crossref, Google Scholar
- (2019) Large dynamic covariance matrices. J. Bus. Econom. Statist. 37(2):363–375.Crossref, Google Scholar
- (1979) Comovements in stock prices in the very short run. J. Amer. Statist. Assoc. 74(366):291–298.Crossref, Google Scholar
- (1993) Common risk factors in the returns on stocks and bonds. J. Financial Econom. 33(1):3–56.Crossref, Google Scholar
- (2015) A five-factor asset pricing model. J. Financial Econom. 116(1):1–22.Crossref, Google Scholar
- (2020) Comparing cross-section and time-series factor models. Rev. Financial Stud. 33(5):1891–1926.Crossref, Google Scholar
- (2016) Incorporating global industrial classification standard into portfolio allocation: A simple factor-based large covariance matrix estimator with high-frequency data. J. Bus. Econom. Statist. 34(4):489–503.Crossref, Google Scholar
- (2003) The economic value of volatility timing using “realized” volatility. J. Financial Econom. 67(3):473–509.Crossref, Google Scholar
- (2022) A critical review of LASSO and its derivatives for variable selection under dependence among covariates. Internat. Statist. Rev. 90(1):118–145.Crossref, Google Scholar
- (2006) Predicting volatility: Getting the most out of return data sampled at different frequencies. J. Econom. 131(1–2):59–96.Crossref, Google Scholar
- (2007) MIDAS regressions: Further results and new directions. Econometric Rev. 26(1):53–90.Crossref, Google Scholar
- (2022) Factor models, machine learning, and asset pricing. Annual Rev. Financial Econom. 14:337–368.Crossref, Google Scholar
- (2013) The supraview of return predictive signals. Rev. Accounting Stud. 18:692–730.Crossref, Google Scholar
- (2020) Empirical asset pricing via machine learning. Rev. Financial Stud. 33(5):2223–2273.Crossref, Google Scholar
- (2015) Information, analysts, and stock return comovement. Rev. Financial Stud. 28(11):3153–3187.Crossref, Google Scholar
- (2005) A realized variance for the whole day based on intermittent high-frequency data. J. Financial Econometrics 3(4):525–554.Crossref, Google Scholar
- (2014) Realized beta GARCH: A multivariate GARCH model with realized measures of volatility. J. Appl. Econometrics 29(5):774–799.Crossref, Google Scholar
- (2016) The common factor in idiosyncratic volatility: Quantitative asset pricing implications. J. Financial Econom. 119(2):249–283.Crossref, Google Scholar
- (2010) Product market synergies and competition in mergers and acquisitions: A text-based analysis. Rev. Financial Stud. 23(10):3773–3811.Crossref, Google Scholar
- (2016) Text-based network industries and endogenous product differentiation. J. Political Econom. 124(5):1423–1465.Crossref, Google Scholar
- (2015) Digesting anomalies: An investment approach. Rev. Financial Stud. 28(3):650–705.Crossref, Google Scholar
- (2016) Does common analyst coverage explain excess comovement? J. Financial Quant. Anal. 51(4):1193–1229.Crossref, Google Scholar
- (2003) Risk reduction in large portfolios: Why imposing the wrong constraints helps. J. Finance 58(4):1651–1683.Crossref, Google Scholar
- (2023) A simple method for predicting covariance matrices of financial returns. Foundations Trends Econometrics 12(4):324–407.Crossref, Google Scholar
- (2023) Machine-learning the skill of mutual fund managers. J. Financial Econom. 150(1):94–138.Crossref, Google Scholar
- (2024) The virtue of complexity in return prediction. J. Finance 79(1):459–503.Crossref, Google Scholar
- (2009) Correlation risk. J. Empirical Finance 16(3):353–367.Crossref, Google Scholar
- (2006) Retail investor sentiment and return comovements. J. Finance 61(5):2451–2486.Crossref, Google Scholar
- (2003) Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. J. Empirical Finance 10(5):603–621.Crossref, Google Scholar
- (2004a) Honey, I shrunk the sample covariance matrix. J. Portfolio Management 30(4):110–119.Crossref, Google Scholar
- (2004b) A well-conditioned estimator for large-dimensional covariance matrices. J. Multivariate Anal. 88(2):365–411.Crossref, Google Scholar
- (2025) Selecting mutual funds from the stocks they hold: A machine learning approach. Working paper, Wuhan University, Wuhan, China.Google Scholar
- (2025) Automated volatility forecasting. Management Sci. 71(7):6248–6274.Link, Google Scholar
- (2025) Systematic momentum: A new class of price patterns. Management Sci. , ePub ahead of print November 25, https://doi.org/10.1287/mnsc.2024.08236.Link, Google Scholar
- (1965) The valuation of risky assets and the selection of risky investments in stock portfolios and capital budgets. Rev. Econom. Statist. 47(1):13–37.Crossref, Google Scholar
- (2023) Do common factors really explain the cross-section of stock returns? Working paper, University of Florida, Gainesville.Google Scholar
- (2010) Market segmentation and cross-predictability of returns. J. Finance 65(4):555–1580.Crossref, Google Scholar
- (2017) International correlation risk. J. Financial Econom. 126(2):270–299.Crossref, Google Scholar
- (2014) Sell-side analyst research and stock comovement. J. Accounting Res. 52(4):911–954.Crossref, Google Scholar
- (2012) Multivariate high-frequency-based volatility (HEAVY) models. J. Appl. Econometrics 27(6):907–933.Crossref, Google Scholar
- (2016) High-dimensional copula-based distributions with mixed frequency data. J. Econom. 193(2):349–366.Crossref, Google Scholar
- (2020) Geographic lead-lag effects. Rev. Financial Stud. 33(10):4721–4770.Crossref, Google Scholar
- (2015) Good volatility, bad volatility: Signed jumps and the persistence of volatility. Rev. Econom. Statist. 97(3):683–697.Crossref, Google Scholar
- (1993) The comovement of stock prices. Quart. J. Econom. 108(4):1073–1104.Crossref, Google Scholar
- (2006) Does corporate headquarters location matter for stock returns? J. Finance 61(4):1991–2015.Crossref, Google Scholar
- (2010) Average correlation and stock market returns. J. Financial Econom. 96(3):364–380.Crossref, Google Scholar
- (2022) Asset pricing: Time-series predictability. Banerjee A , ed. Oxford Research Encyclopedia of Economics and Finance (Oxford University Press, Oxford, UK).Crossref, Google Scholar
- (2013) International stock return predictability: What is the role of the United States? J. Finance 68(4):1633–1662.Crossref, Google Scholar
- (1984) A simple implicit measure of the effective bid-ask spread in an efficient market. J. Finance 39(4):1127–1139.Crossref, Google Scholar
- (1964) Capital asset prices: A theory of market equilibrium under conditions of risk. J. Finance 19(3):425–442.Google Scholar
- (2017) Mispricing factors. Rev. Financial Stud. 30(4):1270–1315.Crossref, Google Scholar
- (2012) The short of it: Investor sentiment and anomalies. J. Financial Econom. 104(2):288–302.Crossref, Google Scholar
- (1996) Regression shrinkage and selection via the LASSO. J. Roy. Statist. Soc. Ser. B 58(1):267–288.Crossref, Google Scholar
- (2006) Forecast combinations. Elliott G , Granger CWJ , Timmermann A , eds. Handbook of Economic Forecasting , vol. 1 (Elsevier, Amsterdam), 135–196.Crossref, Google Scholar
- (2002) A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. J. Bus. Econom. Statist. 20(3):351–362.Crossref, Google Scholar
- (2008) A comprehensive look at the empirical performance of equity premium prediction. Rev. Financial Stud. 21(4):1455–1508.Crossref, Google Scholar

