Analyzing data from 3,616 Chinese listed firms, we find a strong positive relationship between policy uncertainty and firms’ exchange rate exposure. This result remains robust after controlling for macroeconomic conditions and addressing endogeneity issues. Notably, policy uncertainty’s impact is significantly stronger for firms with a higher degree of international involvement and for poorly-governed firms. Interestingly, firms use financial hedging more intensively and reduce their operational hedging in high-uncertainty periods. Our results suggest that policy uncertainty exacerbates the impact of currency movements on firms’ financial performance, as firms become increasingly involved in international operations. Consequently, firms should strengthen their corporate governance and make effective use of hedging tools.

This study investigates the relationship between trade policy uncertainty (TPU) and market diversification with risk-averse firms. We build a model to demonstrate how a risk-averse firm diversifies risks stemming from escalating TPU through entering new markets whose trade policies are negatively correlated with ones in its alreadyentered markets. The positive effect of TPU on market diversification is moderated if the firm has lower risk hedging ability and/or is less risk-averse. Conditional on the TPU in the already-entered markets, there is an inverted-U relationship between TPU in the new market and the probability of entering it. Using a unique firm-productlevel dataset on Chinese exporters, we find robust evidence supporting our theoretical predictions.

Based on high-frequency data of China's commodity market from 2017 to 2022, this article examines the intraday momentum effect. The results indicate that China's commodity futures and options have significant intraday reversal effects, and the overnight opening factor and opening to last half hour factor are more significant. These effects are driven, in part, by liquidity factors. This trend aligns with market makers' behavior, passively accepting orders during low liquidity and actively closing positions amid high liquidity. Furthermore, our examination of cross-predictive ability shows strong futures-to-options predictability, while the reverse is weaker. We posit options traders' Vega hedging as a key factor in this phenomenon, our study finds futures volatility changes can predict options’ return.

Owing to the liberalisation of financial markets, the impact of international capital flows on the Chinese stock market has become substantial. This study investigates the effects of economic policy uncertainty (EPU), geopolitical risk (GPR), consumer sentiment (CCI), macroeconomic fundamentals (MECI), and money supply (M2) on the correlations between the stock and exchange rate markets. The negative correlation between these two markets has become more pronounced in recent years. Moreover, EPU, GPR, CCI, and MECI negatively impact long-term stock-exchange rate correlations, while M2 has a positive impact. Portfolios of stock-exchange rates effectively reduce risk, especially when considering structural breaks.

We present a novel methodology for constructing portfolios to hedge economic and financial risks arising from climate change. We utilize ChatGPT-4 to identify climate-related conversations during earnings conference calls and connect these time-stamped transcripts with high-frequency stock price data pinpointed to the conversation level. This approach allows us to assess a company’s dynamic exposure to climate change risks by analyzing real-time stock price responses to discussions about climate issues between managers and analysts. Our proposed portfolio, constructed by taking long (short) positions in stocks with positive (negative) market responses to climate conversations, appreciates in value during future periods with negative aggregate climate news shocks. Compared to portfolios constructed using alternative methods, our real-time market response-based portfolios demonstrate superior out-of-sample hedge performance. A key advantage of our approach is its ability to capture time-series and cross-sectional variations in stocks’ rapidly-evolving exposures to climate risk, relying on the timing of when climate-related issues become salient topics that warrant conference call discussions and real-time market responses to such conversations. Additionally, we showcase the versatility of our approach in hedging other types of dynamic risks: namely political risk and pandemic risk.

This study investigates the relationship between trade policy uncertainty (TPU) and market diversification with risk-averse firms. We build a model to demonstrate how a risk-averse firm diversifies risks stemming from escalating TPU through entering new markets whose trade policies are negatively correlated with ones in its already-entered markets. The positive effect of TPU on market diversification is moderated if the firm has lower risk hedging ability and/or is less risk-averse. Conditional on the TPU in the already-entered markets, there is an inverted-U relationship between TPU in the new market and the probability of entering it. Using a unique firm-product-level dataset on Chinese exporters, we find robust evidence supporting our theoretical predictions.

An optimal tax and borrowing plan determines the marginal cost of servicing government debt, p', and makes the government’s debt risk-free. An option to default restricts debt capacity. Optimal debt-GDP ratio dynamics are driven by 1) a primary deficit, 2) interest payments, 3) GDP growth, and 4) hedging costs. Hedging influences debt capacity and debt transition dynamics. For plausible parameter values, we make comparative dynamic quantitative statements about debt-GDP ratio transition dynamics, debt capacity, and how long it would take our example economy to attain that calibrated equilibrium debt capacity.

We examine empirically and theoretically the effects of industrial robot adoption on corporate financing. Empirically, using firm-level panel data on robot deployment in China, staggered across both provinces and industries, we find that robot adoption reduces the cost of debt and increases leverage. We hypothesize that the underlying reason is that being a substitute for labor, robots provide a hedge against fluctuations in labor costs. A model based on this hedging argument delivers additional testable predictions concerning determinants of the relation between robot adoption and corporate financing, which are borne out in the data, providing support for the proposed mechanism. Our evidence is inconsistent with alternative channels behind the observed relations.

Using both the onset of the US-China trade war in 2018 and the most recent Russia-Ukraine conflict and associated trade tensions, we show that government-linked firms increase their importing activity by roughly 33% (t=4.01) following the shock, while non-government linked firms trading to the same countries do the opposite, decreasing activity. These increases appear targeted, in that we see no increase for government-linked supplier firms generally to other countries (even countries in the same regions) at the same time, nor of these same firms in these regions at other times of no tension. In terms of mechanism, government supplier-linked firms are nearly twice as likely to receive tariff exemptions as equivalent firms doing trade in the region who are not also government suppliers. More broadly, these effects are increasing in level of government connection. For example, firms that are geographically closer to the agencies to which they supply increase their imports more acutely. Using micro-level data, we find that government supplying firms that recruit more employees with past government work experience also increase their importing activity more – particularly when the past employee worked in a contracting role. Lastly, we find evidence that this results in sizable accrued benefits in terms of firm-level profitability, market share gains, and outsized stock returns.

In this study, we examine the resilience of Bitcoin (BTC) to hedge Chinese aggregate and sectoral equity markets and the returns spillover to Altcoins onset the Novel Coronavirus outbreak. We observe that BTC is a weak hedge during the overall period and a weak safe haven onset the crisis. Besides, BTC is a weak hedge, diversifier and a weak safe haven for the sectoral equity indexes. Overall, gold outperforms BTC in hedging and safe haven perspectives with respect to Chinese equity markets. Lastly, we find that the rise in Altcoin prices are majorly due to spillover from BTC prices.