A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
- Topic classification is ongoing.
- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 6,024 resources
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We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price‐to‐estimate ratios and lower buy‐in rates, pointing to estimates' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers' prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.
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This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on a composite model that integrates over competing factor models weighted by posterior probabilities. Evidence shows that unconditional models record near‐zero probabilities, while postearnings announcement drift, quality‐minus‐junk, and intermediary capital are potent factors in conditional asset pricing. Out‐of‐sample, the integrated model performs well, tilting away from subsequently underperforming factors. Model uncertainty makes equities appear considerably riskier, while model disagreement about expected returns spikes during crash episodes. Disagreement spans all return components involving mispricing, factor loadings, and risk premia.
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We build a cross‐sectional factor model for investors' direct stockholdings and estimate it using data from almost 10 million retail accounts in the Indian stock market. Our model identifies strong investor clienteles for stock characteristics, most notably firm age and share price, and for particular clusters of stock characteristics. These clienteles are intuitively associated with investor attributes such as account age, size, and diversification. Coheld stocks tend to have higher return covariance, inconsistent with simple models of diversification but suggestive that clientele demands influence stock returns.
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We show that over the past half‐century, innovative disruptions were central to understanding corporate defaults. In a given year, industries experiencing abnormally high venture capital or initial public offering activity subsequently see higher default rates, higher segment exits by conglomerates, and higher yields on bonds issued by the firms in these industries. Overall, we find that disruption is a broad phenomenon, negatively affecting incumbent firms across the spectrum of age, valuation, and levers, with the exception of very large and low‐leverage firms, in line with our central hypothesis.
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We offer a general equilibrium analysis of cryptocurrency pricing. The fundamental value of the cryptocurrency is its stream of net transactional benefits, which depend on its future prices. This implies that, in addition to fundamentals, equilibrium prices reflect sunspots. This in turn implies multiple equilibria and extrinsic volatility, that is, cryptocurrency prices fluctuate even when fundamentals are constant. To match our model to the data, we construct indices measuring the net transactional benefits of Bitcoin. In our calibration, part of the variations in Bitcoin returns reflects changes in net transactional benefits, but a larger share reflects extrinsic volatility.
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Measures of private equity (PE) performance based on cash flows do not account for a discount‐rate risk premium that is a component of the capital asset pricing model (CAPM) alpha. We create secondary market PE indices and find that PE discount rates vary considerably. Net asset values are too smooth because they fail to reflect variation in discount rates. Although the CAPM alpha for our index is zero, the generalized public market equivalent based on cash flows is large and positive. We obtain similar results for a set of synthetic funds that invest in small cap stocks. Ignoring variation in PE discount rates can lead to a misallocation of capital.
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We propose a novel framework for analyzing linear asset pricing models: simple, robust, and applicable to high‐dimensional problems. For a (potentially misspecified) stand‐alone model, it provides reliable price of risk estimates for both tradable and nontradable factors, and detects those weakly identified. For competing factors and (possibly nonnested) models, the method automatically selects the best specification—if a dominant one exists—or provides a Bayesian model averaging–stochastic discount factor (BMA‐SDF), if there is no clear winner. We analyze 2.25 quadrillion models generated by a large set of factors and find that the BMA‐SDF outperforms existing models in‐ and out‐of‐sample.
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We study how a fiscal expansion via infrastructure investment influences the dynamic impacts of monetary stimulus on credit allocation. We develop a two‐stage approach and apply it to the Chinese economy with a confidential loan‐level data set that covers all sectors. We find that infrastructure investment significantly weakened monetary policy's transmission to credit allocated to private firms, while reinforcing the monetary effects on loans to state‐owned firms. This fiscal‐monetary interaction channel is key to understanding the preferential credit access enjoyed by state‐owned firms during the stimulus period. Consequently, monetary stimulus crowded out private investment and decreased capital allocation efficiency.
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The currency depreciation rate is often computed as the ratio of foreign to domestic pricing kernels. Using bond prices alone to estimate these kernels leads to currency puzzles: the inability of models to match violations of uncovered interest parity and the volatility of exchange rates. This happens because of the FX bond disconnect, the inability of bonds to span exchange rates. Incorporating innovations to the pricing kernel that affect exchange rates but not bonds helps resolve the puzzles. This approach also allows one to relate news about cross‐country differences between international yields to news about currency risk premiums.
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The currency market features a small cross‐section, and conditional expected returns can be characterized by few signals: interest differential, trend, and mean reversion. We exploit these properties to construct the ex ante mean‐variance efficient portfolio of individual currencies. The portfolio is updated in real time and prices all prominent currency trading strategies, conditionally and unconditionally. The fraction of risk in these assets that does not affect their risk premiums is at least 85%. Extant explanations of carry strategies based on intermediary capital or global volatility are related to these unpriced components, while consumption growth is related to the priced component of returns.
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Journals
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- Bond (325)
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- CEO (69)
- Capital Structure (32)
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Between 1900 and 1999
(4,309)
- Between 1940 and 1949 (67)
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