No Sparsity in Asset Pricing: Evidence from a Generic Statistical Test
We present a novel test to determine sparsity in characteristic-based factor models. Applying the test to industry and pseudo-random portfolios, we reject the null hypothesis that fewer than ten factors are sufficient to explain returns, and show that at least forty factors are needed for the various sample periods examined. We find that dense models outperform sparse ones in both pricing and investing. Testing with tree-based portfolios also indicates no sparsity. Our results suggest that most existing factor models, which have fewer than six factors, are questionable, and that future research on such low-dimensional models is unlikely to be fruitful.
Junnan He, Lingxiao Zhao, Guofu Zhou
Working Paper | No. 20241202 |
Keywords: factor models, characteristic-based factors, sparsity, test
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Monetary Policy in Open Economies with Production Networks
This paper studies the design of monetary policy in small open economies with domestic and cross-border production networks and nominal rigidities. The monetary policy that closes the domestic output gap is nearly optimal and is implemented by stabilizing the aggregate inflation index that weights sectoral inflation according to the sector’s roles as a supplier of inputs and a net exporter of products within the international production networks. To close the output gap, monetary policy should assign large weights to inflation in sectors with small direct or indirect (via the downstream sectors) import shares and failing to account for the cross-border production networks overemphasizes inflation in sectors that export intensively directly and indirectly (via the downstream sectors). We validate our theoretical results using the World Input-Output Database and show that the monetary policy that closes the output
Zhesheng Qiu, Yicheng Wang, Le Xu, Francesco Zanetti
Working Paper | No. 20240906 |
Keywords: ESG, Mutual fund family, Spillover effect, Fund flows, Affection-based judgement, Fund proliferatio
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Transcontinental Railways and Hinterland Development
The dominant role of maritime shipping in international trade has led to the imbalance between coastal and inland regions. We study whether transcontinental railways, an alternative mode that opens up vast heartlands of a continent to trade and business, can boost inland development. Using the post-2010 expansion of China-Europe Railway Express as a natural experiment and rich Chinese firm-level data, we find that exports to Europe, manufacturing production, and firm entry increase in areas surrounding the transcontinental railway stations. We present supportive evidence on the increase in producer services, freight agencies, nightlight intensity, capital inflow and the slowdown of outmigration.
Siwei Cao, Mi Dai, Yizhen Gu, Kui Zhao
Working Paper | No. 20240905 |
Keywords: ESG, Mutual fund family, Spillover effect, Fund flows, Affection-based judgement, Fund proliferatio
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How do Multinationals Impact China’s Technology? The Role of Quid Pro Quo Policy and Technology Spillovers
Multinationals play a crucial role in international knowledge diffusion. Using comprehensive patent data, we document: (1) multinational affiliates and their foreign parent firms comprise a significant portion of patents filed with China’s patent office; and (2) there are subsequent transfers and spillovers of these technologies to domestic firms. Guided by this evidence, we develop a model of multinational production featuring cross-country idea flows, transfers, and spillovers. Quantitatively, we find that without multinational production and knowledge spillovers, the idea stock owned by China would drop by 27%. Furthermore, due to the externalities of multinationals through technology transfers and spillovers, subsidizing multinationals will at most increase real income by 8% in China.
Xiao Ma, Yiran Zhan
Working Paper | No. 20240902 |
Keywords: multinational activities, technology transfers, knowledge spillovers
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Overnight Learning, Price Discovery, and Macroeconomic Announcements
We show fast price discovery at the market opening after macroeconomic announcements released overnight even when investors do not trade and learn from quotes while the stock market is closed. Leveraging a unique feature of unscheduled macroeconomic announcements arriving outside of regular trading hours of Chinese stock markets, our paper identifies the large impacts of learning from alternative sources other than prices on price discovery. We document that investors’ overnight learning from social media in the period between macro news arrival and market opening enhances the price discovery once market reopens for trades. Overnight learning among investors helps level the playing field across investors and mitigates reversals of overnight and intraday returns.
Haozhe Han, Grace Xing Hu, Calvin Dun Jia*
Working Paper | No. 20240904 |
Keywords: overnight learning, macroeconomic announcements, price informativeness, social media
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A High-Frequency Measure of Chinese Monetary Policy Shocks
We develop a daily measure of Chinese monetary policy shocks that incorporates both quantity and interest rate-based policy changes. Our shock measure serves as a sufficient statistic tailored to the Chinese market, addressing the common issue in emerging markets of lacking a key proxy for monetary policy stance due to multi-dimensional objectives and complex toolkits. We validate its effectiveness in capturing unexpected monetary policy changes in China. Shedding light on monetary policy transmission, our shock series reveals that Chinese monetary policy significantly affects the equity and credit risk of non-financial firms and shifts real macroeconomic variables.
Jianyao He, Dun Jia, Kai Li, Wenbin Wu*
Working Paper | No. 20240903 |
Keywords: monetary policy, inter-bank market, macroeconomic announcements, asset prices, China
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The Incident-Driven Green Products
We employ the ChatGPT model to identify green products in the US product markets. Approximately 3.7% of US product announcements from 2002 to 2022 qualify as green products. Using a stacked Difference-in-Differences approach, we find that firms involved in severe environmental incidents launch 40% more green products within two years following the incidents. These incident-driven green products are notably novel, supported by high-quality green patents, and result in substantial environmental improvements for both producers and consumers. In contrast, green products introduced without the impetus of environmental incidents do not demonstrate meaningful environmental gains and often raise concerns of greenwashing.
Yifei Zhang*
Working Paper | No. 20240901 |
Keywords: green products, environmental incidents, environmental performance, green patents, greenwashing, ChatGPT, machine learning
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Gold is a Hedging Asset
While industry investors commonly view gold as a hedging asset, academic studies often find the opposite. We show that gold is a prominent hedging asset via three different approaches: a state-space model, predictive regressions, and principal component analyses. We find that, ceteris paribus, gold prices increase with expected stock market return μₜ and expected dividend growth rate gₜ. In bad times, μₜ rises while gₜ declines. It thus may seem that gold prices fall in bad times and that gold prices insignificantly or even negatively predict stock returns. However, after addressing the omitted-variable-bias introduced by gₜ, we find that gold prices significantly and positively predict stock returns.
Aoxiang Yang*
Working Paper | No. 20240605 |
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