Abstract
Controlling thickness and tightness of surface passivation shells is crucial for many applications of core–shell nanoparticles (NP). Usually, to determine shell thickness, core and ...core/shell particle are measured individually requiring the availability of both nanoobjects. This is often not fulfilled for functional nanomaterials such as many photoluminescent semiconductor quantum dots (QD) used for bioimaging, solid state lighting, and display technologies as the core does not show the application-relevant functionality like a high photoluminescence (PL) quantum yield, calling for a whole nanoobject approach. By combining high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS), a novel whole nanoobject approach is developed representatively for an ultrabright oleic acid-stabilized, thick shell CdSe/CdS QD with a PL quantum yield close to unity. The size of this spectroscopically assessed QD, is in the range of the information depth of usual laboratory XPS. Information on particle size and monodispersity were validated with dynamic light scattering (DLS) and small angle X-ray scattering (SAXS) and compared to data derived from optical measurements. In addition to demonstrating the potential of this novel whole nanoobject approach for determining architectures of small nanoparticles, the presented results also highlight challenges faced by different sizing and structural analysis methods and method-inherent uncertainties.
Cd-free I-III-VI group semiconductor quantum dots (QDs) like Ag-In-S and Cu-In-S show unstructured absorption spectra with a pronounced Urbach tail, rendering the determination of their band gap ...energy (
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) and the energy structure of the exciton difficult. Additionally, the origin of the broad photoluminescence (PL) band with lifetimes of several hundred nanoseconds is still debated. This encouraged us to study the excitation energy dependence (EED) of the PL maxima, PL spectral band widths, quantum yields (QYs), and decay kinetics of AIS/ZnS QDs of different size, composition, and surface capping ligands. These results were then correlated with the second derivatives of the corresponding absorption spectra. The excellent match between the onset of changes in PL band position and spectral width with the minima found for the second derivatives of the absorption spectra underlines the potential of the EED approach for deriving
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values of these ternary QDs from PL data. The PL QY is, however, independent of excitation energy in the energy range studied. From the EED of the PL features of the AIS/ZnS QDs we could also derive a mechanism of the formation of the low-energy electronic structure. This was additionally confirmed by a comparison of the EED of PL data of as-synthesized and size-selected QD ensembles and the comparison of these PL data with PL spectra of single QDs. These results indicate a strong contribution of intrinsic inhomogeneous PL broadening to the overall emission features of AIS/ZnS QDs originating from radiative transitions from a set of energy states of defects localized at different positions within the quantum dot volume, in addition to contributions from dimensional and chemical broadening. This mechanism was confirmed by numerically modelling the absorption and PL energies with a simple mass approximation for spherical QDs and a modified donor-acceptor model, thereby utilizing the advantages of previously proposed PL mechanisms of ternary QDs. These findings will pave the road to a deeper understanding of the nature of PL in quantum confined I-III-VI group semiconductor nanomaterials.
We develop a new systematic tail risk measure for equity-oriented hedge funds to examine the impact of tail risk on fund performance and to identify the sources of tail risk. We find that tail risk ...affects the cross-sectional variation in fund returns and that investments in both tail-sensitive stocks and options drive tail risk. Moreover, leverage and exposure to funding liquidity shocks are important determinants of tail risk. We find evidence of some funds being able to time tail risk exposure prior to the 2008–2009 financial crisis.
This article examines whether investors receive compensation for holding crash-sensitive stocks. We capture the crash sensitivity of stocks by their lower-tail dependence (LTD) with the market based ...on copulas. We find that stocks with strong LTD have higher average future returns than stocks with weak LTD. This effect cannot be explained by traditional risk factors and is different from the impact of beta, downside beta, coskewness, cokurtosis, and Kelly and Jiang’s (2014) tail risk beta. Hence, our findings are consistent with the notion that investors are crash-averse.
This paper investigates whether multivariate crash risk (MCRASH), defined as exposure to extreme realizations of multiple systematic factors, is priced in the cross-section of expected stock returns. ...We derive an extended linear model with a positive premium for MCRASH, and we empirically confirm that stocks with high MCRASH earn significantly higher future returns than stocks with low MCRASH. The premium is not explained by linear factor exposures, alternative downside risk measures, or stock characteristics. Extending market-based definitions of crash risk to other well-established factors helps to determine the cross-section of expected stock returns without further expanding the factor zoo.
We suggest a risk-based explanation of the momentum anomaly. Controlling for the exposure to systematic crash risk reduces the momentum effect from a significant 11.94% p.a. to an insignificant 1.84% ...p.a. Similar results are obtained in a broad sample of international equity markets.
•The paper proposes a risk-based explanation of the momentum anomaly on equity markets.•Regressing the momentum strategy return on the return of a self-financing portfolio going long (short) in stocks with high (low) crash sensitivity in the USA from 1963 to 2012 reduces the momentum effect from a highly statistically significant 11.94% p.a. to an insignificant 1.84% p.a.•We find additional supportive out-of sample evidence for our risk-based momentum explanation in a sample of 23 international equity markets.
We merge the literature on downside return risk and liquidity risk and introduce the concept of extreme downside liquidity (EDL) risks. The cross-section of stock returns reflects a premium if a ...stock’s return (liquidity) is lowest at the same time when the market liquidity (return) is lowest. This effect is not driven by linear or downside liquidity risk or extreme downside return risk and is mainly driven by more recent years. There is no premium for stocks whose liquidity is lowest when market liquidity is lowest.
We investigate whether value-relevant foreign information only gradually dilutes into stock prices of multinational firms worldwide. Using an international sample of firms from twenty-two developed ...countries, we find that a portfolio strategy based on firms' foreign sales information yields future returns of more than 10% p.a. globally. The return spread due to foreign information is substantial across different geographical regions and cannot be explained by traditional risk factors, firm characteristics, and industry momentum. Our results are in line with limited attention of investors to foreign information being the main driver of this effect worldwide.
Abstract
Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and ...stock characteristics in predicting future option returns. The nonlinear machine learning models generate statistically and economically sizable profits in the long-short portfolios of equity options even after accounting for transaction costs. Although option-based characteristics are the most important standalone predictors, stock-based measures offer substantial incremental predictive power when considered alongside option-based characteristics. Finally, we provide compelling evidence that option return predictability is driven by informational frictions and option mispricing.
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
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