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ChatGPT 能否预测股价走势？收益可预测性与大语言模型AI 解读

We document the capability of large language models (LLMs) like ChatGPT to predict stock market reactions from news headlines without direct financial training. Using post-knowledge-cutoff headlines, GPT-4 captures initial market responses, achieving approximately 90% portfolio-day hit rates for the non-tradable initial reaction. GPT-4 scores also significantly predict the subsequent drift, especially for small stocks and negative news. Forecasting ability generally…

债券与股票共同定价的因子动物园AI 解读

We analyze 18 quadrillion models for the joint pricing of corporate bond and stock returns. Strikingly, we find that equity and nontradable factors alone suffice to explain corporate bond risk premia once their Treasury term structure risk is accounted for, rendering the extensive bond factor literature largely redundant for this purpose. While only a handful of factors, behavioral and nontradable, are likely robust sources of priced risk, the true latent stochastic discount…

玻璃盒机器学习与公司债券收益AI 解读

Machine learning methods in asset pricing are often criticized for their black box nature. We study this issue by predicting corporate bond returns using interpretable machine learning on a high-dimensional bond characteristics data set. We achieve state-of-the-art performance while maintaining an interpretable model structure, overcoming the accuracy–interpretability trade-off. The estimation uncovers nonlinear relationships and economically meaningful interactions in bond…

CRISK：衡量金融体系的气候风险暴露AI 解读

We develop a market-based methodology to assess banks’ resilience to climate-related risks and study the climate-related risk exposure of large global banks. We introduce a new measure, CRISK, which is the expected capital shortfall of a bank in a climate stress scenario. To estimate CRISK, we construct climate risk factors and dynamically measure banks’ stock return sensitivity (that is, climate beta) to the climate risk factor. We validate the climate risk factor…

价格对分析师现金流预期的影响：主观信念数据与理性贴现率变动的协调AI 解读

I show that prices impact analyst cash flow expectations and argue this impact can partially reconcile subjective beliefs data with asset pricing models in which investors have rational expectations and discount rate variation drives prices. Previous work argues that correlations of biased analyst cash flow expectations with prices and future returns contradict rational models and imply biased investor expectations distort prices. However, using two instrumental variables…

投资型资产定价模型的估计与检验AI 解读

Investment-based asset pricing models typically predict a close link between a firm’s stock return and its characteristics at any point in time. Yet, previous studies have primarily focused on the weaker prediction that this link holds on average, finding substantial empirical support. We show how to incorporate the time-series predictions in the estimation and testing of investment-based models using the generalized method of moments. We find that standard specifications of…

个人税收是否影响投资决策与股票收益？AI 解读

This paper studies the causal effects of personal investment taxes on stock returns and the financial decisions of companies. I exploit a change in legislation in 2013 which allowed stocks listed on the Alternative Investment Market, a sub-market of the London Stock Exchange, to be held in capital gains and dividend tax-exempt investment accounts for the first time. Using a difference-in-differences approach, I find that excess stock returns decreased by their…

动态期限结构模型中的波动率建模AI 解读

We propose no-arbitrage term structure models with volatility factors that follow GARCH processes. The models’ tractability is similar to canonical affine term structure models, but they fit yield volatility much better, especially for long-maturity yields. This improvement does not come at the expense of a deterioration in yield fit. Because of the improved volatility fit, the model performs substantially better in pricing Treasury futures options. We conclude that the…

多因子资产定价模型的样本内与样本外夏普比率AI 解读

Using available return data, many multi-factor asset pricing models present impressive in-sample Sharpe ratios, significantly surpassing that of the market portfolio. Such a performance, however, contradicts the conventional wisdom in finance. Investors cannot realistically attain the in-sample Sharpe ratios. They obtain the out-of-sample Sharpe ratios, which are significantly lower. Estimation risk is one reason for this performance deterioration. We theoretically study the…

金融市场对细节的有限关注：约化式与结构估计证据AI 解读

We show that firm valuations fell after a key expense became more visible in financial statements. FAS 123-R required firms to deduct option compensation costs from earnings, instead of disclosing them in footnotes. Firms that granted high option pay experienced earnings reductions, while fundamentals remained unchanged. These firms were more likely to miss earnings forecasts, and they experienced recommendation downgrades and valuation declines. Our findings suggest that…

是 alpha 还是 beta？模型误设下的对冲基金收益分解AI 解读

We develop a novel approach to separate alpha and beta under model misspecification. It comes with formal tests to identify less misspecified models and sharpen the return decomposition of individual funds. Our hedge fund analysis reveals that: (i) prominent models are as misspecified as the CAPM, (ii) several factors (time-series momentum, variance, carry) capture alternative strategies and lower performance in all investment categories, (iii) fund heterogeneity in alpha…

学习企业的消费风险暴露AI 解读

We structurally estimate an investment-based asset pricing model, in which firms' exposure to macroeconomic risk is unknown. Bayesian beliefs about this parameter are updated from firms' and industry peers' comovement between their productivity and consumption growth. The model implies that discount rates rise endogenously with the perceived risk exposure of firms, thereby depressing investment and valuation ratios. We test these predictions in the data and find strong…

内生增长与收益可预测性AI 解读

The component of the volatility of total factor productivity (TFP) that is orthogonal to the dividend price ratio is shown to have long-run predictive ability for excess market returns. This finding implies that TFP volatility should also predict real cash flows and/or real interest rates: it is found to mainly predict real cash flows through inflation. A model with endogenous growth, Epstein-Zin preferences and price rigidities reconciles both TFP volatility-driven long-run…

跳跃杠杆风险溢价AI 解读

Jumps in asset prices are ubiquitous, yet the apparent high price of jump risk observed empirically is commonly viewed as puzzling. We develop new model-free short-time risk-neutral variance expansions, allowing us to clearly delineate the importance of jumps in generating both price and variance risks. We find that simultaneous jumps in the price and the stochastic volatility and/or jump intensity of the market commands a sizeable risk premium. The existence of “jump…

用机器学习识别共同基金经理的技能AI 解读

We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, before and after fees. The outperformance persists for more than three years. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment. Our…

债务动态与信用风险AI 解读

We investigate how the dynamics of corporate debt policy affect the pricing of corporate bonds. We find empirically that debt issuance has a significant stochastic component that is imperfectly correlated with shocks to asset value. As a consequence, the volatility of leverage is significantly higher than asset volatility over short horizons. At long horizons, the relation between leverage and asset volatility is reversed due to mean reversion in leverage. We incorporate…

基本价值市值比与价值溢价的下降AI 解读

Recent evidence indicates the value premium declined over time. We argue this decline happened because book equity, BE, is no longer a good proxy for fundamental equity, FE, defined as the present value of cash flows under a common discount rate across firms. Specifically, we estimate FE for public US firms over time and find that the premium associated with the fundamental-to-market ratio, FE/ME, subsumes the BE/ME premium and has been relatively stable while the…

过度设定资产定价模型的实证评价AI 解读

Empirical asset pricing models with possibly unnecessary risk factors are increasingly common. Unfortunately, they can yield misleading statistical inferences. Unlike previous studies, we estimate the identified set of SDFs and risk prices compatible with a given model’s asset pricing restrictions. We also propose tests that detect problematic situations with economically meaningless SDFs unrelated to the test assets. Empirically, we estimate linear subspaces of SDFs…

哪些事件撼动世界？全球共同波动率的测量与对冲AI 解读

Some events impact volatilities of most assets, asset classes, sectors and countries, causing serious damage to investment portfolios. The magnitude of such shocks is defined as global COVOL which is an abbreviation for global common volatility, a broad measure of all types of global financial risk. This paper introduces a statistical formulation of such events as common volatility innovations in both a multivariate volatility and an asset pricing context. Simulations verify…

全球外汇市场的流动性AI 解读

We study the liquidity of the global currency market by analyzing the price impact of trading volume. We analyze a decade of CLS intraday data representative of global foreign exchange (FX) trading by developing a refinement of the popular Amihud (2002) illiquidity measure that we call realized Amihud, which is the ratio between realized volatility and trading volume. Inversely related to market depth, price impact increases with transaction costs, money market stress,…

什么推动了美国国债收益率变动？AI 解读

We identify a yield news shock as an innovation that does not move Treasury yields contemporaneously but explains a maximum share of their future variation. Yields do not immediately respond to the news shock as the initial reaction of term premiums and expected short rates offset each other. While the impact on term premiums fades quickly, expected short rates and thus yields decline persistently. As a result, the shock explains a staggering 50% of Treasury yield variation…

风险溢价消失了吗？AI 解读

We apply a new methodology for identifying pervasive and discrete changes (“breaks”) in cross-sectional risk premia. Size, value, and investment risk premia have fallen off to the point where they are insignificantly different from zero at the end of the sample period. The market risk premium has also declined systematically over time but remains significant and positive as do the momentum and profitability risk premium. We construct a new instability risk factor from…

大数据时代的市场有效性AI 解读

Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our equilibrium model, N assets have cash flows that are linear in J characteristics, with unknown coefficients. Risk-neutral Bayesian investors learn these coefficients and determine market prices. If J and N are comparable in size, returns are…

We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that rely on staggered treatment timing, and can result in Type-I and Type-II errors. We summarize three alternative estimators developed in the econometrics and applied literature for addressing these biases,…