24 results found
Joenvaara J, Kauppila M, Kosowski R, et al., 2021, Hedge fund performance: are stylized facts sensitive to which database one uses?, Critical Finance Review, Vol: 10, Pages: 271-327, ISSN: 2164-5744
This paper proposes a novel database merging approach and re-examines the fundamental questions regarding hedge fund performance. Before drawing conclusions about fund performance, we form an aggregate database by exploiting all available information across and within seven commercial databases so that the widest possible data coverage is obtained and the effect of data biases is mitigated. Average performance is significantly lower but more persistent when these conclusions are inferred from the aggregate database than from some of the individual commercial databases. Although hedge funds deliver performance persistence, the average fund does not deliver significant risk-adjusted net-of-fee returns while the gross-of-fee returns remain significantly positive. Consistent with previous literature, we find a significant association between fund characteristics related to share restrictions as well as compensation structure and risk-adjusted returns.
Joenväärä J, Kosowski R, 2021, The effect of regulatory constraints on fund performance: new evidence from UCITS hedge funds, Review of Finance, Vol: 25, Pages: 189-233, ISSN: 1382-6662
This article examines the effect of regulatory constraints on fund performance and risk by comparing conventional and UCITS hedge funds. Using a matching estimator approach, we estimate the indirect cost of UCITS regulation to be between 1.06% and 4.05% per annum in terms of risk-adjusted returns. These performance differences are likely to stem from UCITS constraints such as those governing eligible assets, diversification, and short selling, and cannot be explained by differences in redemption terms or level of leverage. We confirm that our performance results are not driven by management company characteristics, fund manager characteristics, or unobserved confounder bias.
Adell P, Dubikovskyy V, JOUROVSKI A, et al., 2020, Forecasting beta using machine learning and equity sentiment variables, Machine Learning and Asset Management, Editors: Jurczenko
In this chapter, we apply machine learning, fundamental equity variables and big data equity sentiment variables to forecast equity beta. We find that machine learning algorithms are better at forecasting future stock beta than linear models. Big data variables such as stock level sentiment and news volume are significant in several models in addition to other fundamental variables. The results are statistically significant.
Baltas N, Kosowski R, 2020, Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations, Momentum, Editors: Satchell, Grant
Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time-series momentum strategies on their turnover and performance from 1984 until 2013. We show that more efficient volatility estimation and price trend detection can significantly reduce portfolio turnover by more than one third, without causing a statistically significant performance penalty. We shed light on the post-2008 underperformance of the strategy by linking it to the increased level of asset co-movement. We propose a novel implementation of the strategy that incorporates the pairwise signed correlations by means of a dynamic leverage mechanism. The correlation-adjusted variant outperforms the naive implementation of the strategy and the outperformance is more pronounced in the post-2008 period. Finally, using a transaction costs model for futures-based strategies that separates costs into roll-over and rebalancing costs, we show that our findings remain robust to the inclusion of transaction costs.
Joenvaara J, Kosowski R, Tolonen P, 2019, The effect of investment constraints on hedge fund investor returns, Journal of Financial and Quantitative Analysis, Vol: 54, Pages: 1539-1571, ISSN: 0022-1090
This paper examines the effect of real-world, investor-level investment constraints, including several that have not been studied before, on hedge fund performance and its persistence. Using a large consolidated database, we demonstrate that hedge fund performance persistence is significantly reduced when rebalancing rules reflect fund size restrictions and liquidity constraints but remains statistically significant at higher rebalancing frequencies. Hypothetical investor portfolios that incorporate additional minimum diversification constraints, minimum investment requirements, and focus on open funds suggest that the performance and its persistence documented in earlier studies of hedge funds is not easily exploitable, especially by large investors.
Joenvaara J, Kosowski R, Tolonen P, 2016, The effect of investment constraints on hedge fund investor returns
This paper examines the effect of investor-level real-world investment constraints, including several which had not been studied before, on hedge fund performance and its persistence. Using a large consolidated database, we demonstrate that hedge fund performance persistence is significantly reduced when rebalancing rules reflect fund size restrictions and liquidity constraints, but remains statistically significant at higher rebalancing frequencies. Hypothetical investor portfolios that incorporate additional minimum diversification constraints and minimum investment requirements suggest that the performance and its persistence documented in earlier studies of hedge funds is not easily exploitable, especially by large investors.
Della Corte P, Kosowski R, Wang T, 2015, Market Closure and Short-Term Reversal, SSRN Working paper
Baltas N, Kosowski R, 2015, Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations, Publisher: SSRN
Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time-series momentum strategies on their turnover and performance from 1974 until 2013. We show that more efficient volatility estimation and price trend detection significantly reduce portfolio turnover and therefore rebalancing costs. The poor performance of time-series momentum strategies during the post-2008 period is explained by an increased level of pairwise correlations. We propose a novel correlation-based leverage-adjustment to the strategy's weighting scheme and show that it improves performance by safeguarding against tail risk, even after accounting for realistic transaction costs.
Joenvaara J, Kosowski R, 2015, Effect of Regulatory Constraints on Fund Performance: New Evidence from UCITS Hedge Funds, SSRN Working paper
We economically motivate and then test a range of hypotheses regarding performance and risk differences between UCITS-compliant and other hedge funds. The latter exhibit more suspicious return patterns than doabsolute return UCITS (ARUs), but ARUs exhibit higher levels of operational risk. We find evidence of a strong liquidity premium: hedge funds offer investors less liquidity than do ARUs yet exhibit better risk-adjusted performance. Our findings are substantially unchanged under various robustness tests and adjustments for possible selection bias. The liquidity premium for ARUs and their lack of performance persistence have implications for both investors and policy makers.
Buraschi A, Kosowski R, Sritrakul W, 2014, Incentives and endogenous risk taking: a structural view of hedge funds alphas, The Journal of Finance, Vol: 69, Pages: 2819-2870, ISSN: 0022-1082
Hedge fund managers are subject to several nonlinear incentives: performance fee options (call); equity investors' redemption options (put); and prime broker contracts allowing for forced deleverage (put). The interaction of these option‐like incentives affects optimal leverage ex ante, depending on the distance of fund‐value from the high‐water mark. We study how these endogenous effects influence performance measures used in the literature. We show that reduced‐form measures that do not account for these features are subject to economically significant false discovery biases. The result is stronger for low‐quality funds. We propose an alternative structural methodology for conducting performance attribution in hedge funds.
Kosowski R, Neftci SN, 2014, Principles of Financial Engineering, Publisher: Academic Press, ISBN: 9780123870070
Three new chapters, numerous additions to existing chapters, and an expanded collection of questions and exercises make this third edition of Principles of Financial Engineering essential reading.
Biffis E, Kosowski R, 2014, Recreating Sustainable Retirement: Resilience, Solvency, and Tail Risk, Recreating Sustainable Retirement: Resilience, Solvency, and Tail Risk, Editors: Mitchell, Maurer, Hammond, Publisher: Oxford University Press, ISBN: 9780191029974
This book analyzes such challenges to retirement sustainability, and it explores ways to better manage and finance them. Insights provided help build retirement systems capable of withstanding what the future will bring.
Buraschi A, Kosowski R, Trojani F, 2014, When there is no place to hide: correlation risk and the cross-section of hedge funds returns, The Review of Financial Studies, Vol: 27, Pages: 581-616, ISSN: 0893-9454
Using a novel data set on correlation swaps, we study the relation between correlation risk, hedge fund characteristics, and their risk-return profile. We find that the ability of hedge funds to create market-neutral returns is often associated with a significant exposure to correlation risk, which helps to explain the large abnormal returns found in previous models. We also estimate a significant negative market price of correlation risk, which accounts for the cross-section of hedge fund excess returns. Finally, we detect a pronounced nonlinear relation between correlation risk exposure and the tail risk of hedge fund returns.
Avramov D, Barras L, Kosowski R, 2013, Hedge fund predictability under the magnifying glass, Journal of Financial and Quantitative Analysis, Vol: n/a, ISSN: 0022-1090
This paper develops a unified approach to comprehensively analyze individual hedge fund return predictability, both in- and out-of-sample. In-sample, we find that variation in hedge fund performance across changing market conditions is widespread and economically significant. The predictability pattern is consistent with economic rationale, and largely reflects differences in key hedge fund characteristics, such as leverage or capacity constraints. Out-of-sample, we show that a simple strategy that combines the funds’ return forecasts obtained from individual predictors delivers superior performance. We exploit this simplicity to highlight the drivers of this performance, and find that in- and out-of-sample predictability are closely related.
Baltas A-N, Kosowski R, 2013, Momentum Strategies in Futures Markets and Trend-following Funds, SSRN Working Paper
Joenvaara J, Kosowski R, Tolonen P, 2012, Hedge Fund Performance: What Do We Know?, SSRN Working Paper
Kosowski R, Breedon F, 2011, The Oxford Handbook of Quantitative Asset Management, The Oxford Handbook of Quantitative Asset Management, Editors: Scherer, Winston, Publisher: Oxford University Press, ISBN: 9780191624056
The Oxford Handbook of Quantitative Asset Management consists of seven sections that explore major themes in current theoretical and practical use. These themes span all aspects of a modern quantitative investment organization.
Kosowski R, 2011, Do Mutual Funds Perform When it Matters Most to Investors? US Mutual Fund Performance and Risk in Recessions and Expansions, Quarterly Journal of Finance, Vol: 1, Pages: 607-664
Avramov D, Kosowski R, Naik N, et al., 2011, Hedge funds, managerial skill, and macroeconomic variables, Journal of Financial Economics, Vol: 99, Pages: 672-692
Kosowski R, Browne S, 2010, Encyclopedia of Quantitative Finance, Encyclopedia of Quantitative Finance, Editors: Cont
Kosowski R, Naik N, Teo M, 2007, Do hedge funds deliver alpha? A Bayesian and bootstrap analysis, The Journal of Financial Economics, Vol: 84, Pages: 229-264, ISSN: 0304-405X
Kosowski R, Timmermann A, Wermers R, et al., 2006, Can mutual fund "stars" really pick stocks? New evidence from a bootstrap analysis, Journal of Finance, Vol: 61, Pages: 2551-2595, ISSN: 0022-1082
We apply a new bootstrap statistical technique to examine the performance of the US. open-end, domestic equity mutual fund industry over the 1975 to 2002 period. A bootstrap approach is necessary because the cross section of mutual fund alphas has a complex nonnormal distribution due to heterogeneous risk-taking by funds as well as nonnormalities in individual fund alpha distributions. Our bootstrap approach uncovers findings that differ from many past studies. Specifically, we find that a sizable minority of managers pick stocks well enough to more than cover their costs. Moreover, the superior alphas of these managers persist.
Bernard Dumas, Robert Kosowski, 2005, Rothschild Bank AG - Private Banking Case, Rothschild Bank AG Case, Publisher: INSEAD, 06/2005-5265
Bernard Dumas, Robert Kosowski, 2005, Rothschild Bank AG - Private Banking Teaching Note, Rothschild Bank AG Teaching Note, Publisher: INSEAD, 06/2005-5265
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