Tarik Bazgour

@article{bazgour_1853,

title = {A defaultable bond model with cyclical fluctuations in the spread process},

author = {Tarik Bazgour and Federico Platania},

url = {https://link.springer.com/article/10.1007/s10479-021-04471-9},

year  = {2022},

date = {2022-01-01},

journal = {Annals Of Operations Research},

volume = {312},

pages = {647-672},

abstract = {This paper proposes a defaultable bonds pricing model extending the traditional spread process definition. The posited model is able to incorporate any potential cyclical, non- linear, or long-term process not fully captured by the stochastic behavior of the spot rate and the instantaneous default rate process. Under this framework, we analyze the empirical ability of our model to capture the spread dynamics of three different Investment-grade US Corporate bonds indexes. Our findings show that when compared to the Benchmark, our model improves the empirical performance reducing the yield spread mispricing by 35%, 37%, and 29% for the High grade, Upper medium grade, and Lower medium grade index, respectively.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bazgour_1190,

title = {How do Volatility Regimes Affect the Pricing of Quality and Liquidity in the Stock Market?},

author = {Tarik Bazgour and Cédric Heuchenne and Georges Hübner and Danielle Sougné},

url = {https://www.degruyter.com/document/doi/10.1515/snde-2018-0127/html},

year  = {2021},

date = {2021-06-01},

journal = {Studies In Nonlinear Dynamics And Econometrics},

volume = {25},

number = {1},

pages = {20180127},

abstract = {This paper shows how stock market volatility regimes affect the cross-section of stock returns along quality and liquidity dimensions. We find that, during crisis periods, low quality and low liquidity stocks experience relatively higher losses than predicted in normal times, while high quality and high liquidity stocks experience rather relatively lower losses. These findings lend strong support to the presence of cross-market and within-market flight-to-quality and to-liquidity episodes during crisis periods. During low volatility periods, however, low quality and low liquidity stocks earn relatively larger returns, while high quality and high liquidity stocks yield lower returns; suggesting that low volatility conditions benefit junk and illiquid stocks but not quality and liquid stocks. Finally, our results reveal that liquidity level dominates liquidity beta in explaining stock returns across the different market volatility regimes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bazgour_183,

title = {What style liquidity timing skills do mutual fund managers possess?},

author = {Tarik Bazgour and Laurent Bodson and Danielle Sougné},

url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/fire.12117},

year  = {2017},

date = {2017-10-08},

journal = {Financial Review},

volume = {52},

pages = {597-626},

abstract = {Recent studies claim that mutual fund managers demonstrate strong MARKET liquidity timing skills. We extend their liquidity timing tests to the four-factor case and investigate liquidity timing skills with respect to theMARKET, SIZE,VALUE andMOMENTUMfactors. Contrary to these claims, we find no evidence that fund managers adjust market exposure in anticipation of market liquidity changes. We find rather strong evidence that fund managers successfully overweight small stocks asmarket liquidity increases.Our study also demonstrates that it is easy to misidentify SIZE liquidity timing asMARKET liquidity timing in models that focus only on MARKET liquidity timing.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bazgour_184,

title = {Conditional portfolio allocation: Does aggregate market liquidity matter?},

author = {Tarik Bazgour and Cédric Heuchenne and Danielle Sougné},

url = {http://www.sciencedirect.com/science/article/pii/S0927539815001024},

year  = {2016},

date = {2016-01-01},

journal = {Journal Of Empirical Finance},

volume = {35},

number = {C},

pages = {110-135},

abstract = {This paper investigates how aggregate liquidity influences optimal portfolio allocations across various US characteristic portfolios. We consider short-term allocation problems, with single and multiple risky assets, and use the nonparametric approach of Brandt (1999) to directly express optimal portfolio weights as functions of aggregate liquidity shocks. We find, first, that the effect of aggregate liquidity is positive and decreasing with the investment horizon. Second, at daily and weekly horizons, this effect is weaker on allocations in large stocks and gets stronger as we move toward small stocks, regardless of the other stock characteristics, suggesting that liquidity is the main concern of very short-term investors. Third, conditional allocations in risky assets decrease and exhibit shifts toward more liquid assets as aggregate liquidity worsens. Overall, conditioning on aggregate liquidity yields empirical results that are consistent with the so-called flight-to-safety and flight-to-liquidity episodes. Finally, we propose a simple tactical investment strategy and show how aggregate liquidity information can be exploited to enhance the out-of-sample performance of long-term strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}