教师简介

山东大学经济学院副研究员,硕士生导师(金融学硕/专硕),中央财经大学数量经济学博士,美国加州大学河滨分校国家公派联合培养博士研究生。入选山东大学青年学者未来支持计划(第六批)。研究领域为实证金融,包括气候金融、波动率建模和混频数据建模等。主要成果发表在《中国社会科学》《数量经济技术经济研究》等国内期刊以及Journal of Empirical Finance, Economics Letters, Journal of Forecasting和International Review of Financial Analysis等SSCI检索期刊,并被中国人民大学复印报刊资料多次全文转载。主持山东省自然科学基金、山东省社科规划基金、山东大学青年学者未来计划等课题,参加国家社科基金重大项目、国家自然科学基金面上项目等。担任《管理科学学报》《数量经济技术经济研究》《系统工程理论与实践》《经济与管理研究》和International Review of Economics and Finance,International Review of Financial Analysis,Finance Research Letters等期刊匿名审稿人。


欢迎对气候金融、金融波动率建模等研究感兴趣的同学与我联系(I am not a advisor for international students, please do not send any emails to me)


  • 更新日期:2023-01


联系方式/Contact information

  • 电子邮箱:fangtong1990@outlook.com

  • 通讯地址:山东省济南市山大南路27号,250100

  • 办公地址:山东大学洪家楼校区2号楼318

  • 其他主页:Github; Researchgate

  • ORCiD:0000-0002-9507-9668


研究方向/Research interests

  • 气候金融:气候变化与资产定价;气候变化与金融稳定等(当前主要研究方向

  • 金融预测:金融波动与收益预测

  • 混频数据建模与应用:混频GARCH族模型建模和预测

  • 国家文化的经济金融效应:非正式制度在经济金融领域的应用


讲授课程/Teaching courses

  • 本科生:国际金融;公司理财;投资银行学(国际金融与公司理财均已上线中国大学Mooc

  • 研究生:数量经济与实证金融方法导论;资产定价文献导读与研究方法;金融学前沿


工作论文/Working papers

  • Gold price ratios and aggregate stock returns(In progress)

  • Working paper:SSRN

  • Top ten downloads from Oct 6 to Dec 5 on SSRN for ERN: Asset Price Forecasts (Topic), ERN: Precious Metals (Topic), Econometric Modeling: Capital Markets - Forecasting eJournal and Econometric Modeling: Commodity Markets eJournal

  • Abstract: We examine whether gold price ratios, which represent the relative valuations of gold, predict aggregate stock returns. We find that gold price ratios positively predict future stock returns in-sample, but fail to generate significant out-of-sample forecasting performance, except for the gold-oil price ratio (GO). GO is the most powerful predictor both in-sample and out-of-sample. The predictive ability of GO remains significant after controlling for traditional predictors and other gold price ratios. We find that GO drives stock returns through the cash flow channel, and is also associated with future bad economic conditions. The GO movement is determined by rare disaster concerns instead of economic fundamentals. Our results are robust to a series of tests.


  • Gold-oil price ratio and index futures return(Submitted)

  • Abstract: We show that the gold-oil price ratio (GO), which is calculated as the natural logarithm of the gold to oil price ratio, positively and significantly predicts the S&P 500 Futures Index return in-sample. A one-standard-deviation increase in GO is associated with a 6.396% increase in the annual index futures return for the next month. Compared to traditional economic predictors, GO generates the most sizable out-of-sample R^2 and utility gains for a mean-variance investor. GO also outperforms several newly proposed predictors. Our results are robust to a series of tests.


  • Global trade network and the cross-section of international stock market returns (Under review)

  • Abstract: We investigate the relationship between global trade network centrality and international stock market returns. Our empirical results show that trade network centrality negatively and significantly predicts international stock market returns, indicating that central (peripheral) economies have lower (higher) stock returns. The predictive power remains significant after controlling for traditional predictors. A centrality-based long-short trading strategy generates a significant centrality premium, which cannot be fully explained by the international risk factors of Fama and French (2012). We provide several potential and interesting explanations and find that international consumption risk-sharing, conflict risk and information asymmetry are helpful in understanding the relationship between trade network centralities and stock market return differentials.

  • Working paper: SSRN


  • National culture and central bank independence: International evidence (Under Review)

  • Working paper: SSRN


  • Climate change risk, residential housing prices and adaptations (In progress)

  • Abstract: In this paper, we use the Palmer drought severity index (PDSI) to measure climate change risk and evaluate its effect on city-level residential housing prices in China. Our results indicate that drought risk is significantly priced in residential housing markets. Cities with more severe droughts tend to have lower housing prices, and no heterogeneous effect on housing prices is found. Real estate regulations, which are implemented by the Chinese central and local governments to restrain speculations and market bubbles, can mitigate the negative effect of drought risk on housing prices. We also reveal that people adapt to climate change by migrating away from cities with severe droughts, which explains housing price dynamics in the era of climate change. Our results are robust to a series of tests.


  • Temperature shocks and foreign direct investment: City-level evidence in China (Under review)

  • Abstract: We investigate the impact of temperature shocks, calculated as temperatures deviating from historical temperatures, on the foreign direct investment (FDI) of Chinese prefecture-level cities. The empirical results indicate that increases in temperature significantly and negatively affect FDI, and the impact lasts for two years. Although the impact is found to be not heterogeneous among developed and developing cities, FDI in developed cities responds more quickly to temperature shocks. We provide three possible channels, namely, economic development, financial development and demographics, to explain how temperature shocks affect FDI. Our results are robust to a series of tests. These findings provide evidence on the relationship between temperature and economic activities from a new pespective of foreign investment and furthre reveal a climatic determinant of FDI locations.


  • 不确定性信息溢出能否提高股票市场波动预测精度?(Under review)

  • 通货膨胀全球联动的内在逻辑——基于国内实现环境视角(Under review)

  • 个人投资者持股是否增加股价崩盘风险?基于中国股票市场的证据(Submitted)

  • 气候变化对银行风险承担的影响研究:基于事前和事后风险承担视角(Submitted)

  • 金融发展与经济增长的关联性:基于文化属性的新视角(In progress)

  • Temperature shocks and the influence of monetary policy (In progress)

  • An index-tracking approach to constructing climate change risk hedge portfolios (In progress)


学术论文/Publications(按时间倒序,*通讯作者)

  • Tong Fang*, Libo Yin, 2023. National culture and international business cycle co-movements. Applied Economics, accept.

  • Xiaoni Song, Tong Fang*, 2023. Temperature shocks and bank systemic risk: Evidence from China. Finance Research Letters, 51: 103447. -Link-

  • Tong Fang, Deyu Miao, Zhi Su, Libo Yin*, 2022. Uncertainty-driven oil volatility risk premium and international stock market volatility forecasting. Journal of Forecasting, online. -Link-

  • Zhi Su, Peng Liu, Tong Fang, 2022. Uncertainty matters in US financial information spillovers: Evidence from a directed acyclic graph approach. Quarterly Review of Economics and Finance, 84: 229-242. -Link-

  • 方彤、苏治:《一种基于LASSO的多变量混频GARCH模型设计与优化算法研究》,《数量经济技术经济研究》2021年第12期,146-163页。-Link-

  • Libo Yin, Zhi Su, Tong Fang*, 2021. Do stock prices react to announcements of corporate executives’ first-time elections as congress deputies: New evidence from the Chinese political system. Finance Research Letters, 46(B):102446. -Link-

  • Zhi Su, Peng Liu, Tong Fang*, 2021. Pandemic-induced fear and stock market returns: Evidence from China. Global Finance Journal, 54:100644. -Link-

  • Tong Fang, Zhi Su, and Libo Yin*, 2021. Does the green inspiration effect matter for stock returns? Evidence from the Chinese stock market. Empirical Economics, 60: 2155-2176. -Link-

  • Tong Fang, Zhi Su. 2020, Does uncertainty matter for US financial market volatility spillovers? Empirical evidence from a nonlinear Granger causality network. Applied Economics Letters incorporating Applied Financial Economics Letters 28: 1877-1883. -Link-

  • Tong Fang, Zhi Su, Libo Yin*, 2020. Economic fundamentals or investor perception? The role of uncertainty in predicting cryptocurrency volatility. International Review of Financial Analysis 71: 101566. -Link-

  • Tong Fang*, Tae-Hwy Lee, and Zhi Su, 2020. Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection. Journal of Empirical Finance 58: 36-49. -Link-

  • Zhi Su, Tong Fang, and Libo Yin, 2019. Understanding stock market volatility: What is the role of US uncertainty? The North American Journal of Economics and Finance 48: 582-590.

  • 苏治、方彤、马景义:《一类包含不同权重函数的混频GARCH族模型及其应用研究》,《数量经济技术经济研究》2018年第10期,126-143页。

  • Zhi Su, Tong Fang, and Libo Yin*, 2018. Does NVIX matter for volatility? Evidence from Asia-Pacific markets. Physica A: Statistical Mechanics and Its Applications 492: 506-516. 

  • 苏治、方彤、尹力博:《中国虚拟经济与实体经济的关联性——基于规模和周期视角的实证研究》,《中国社会科学》2017年第8期,87-109页。(被中国人民大学复印报刊资料《国民经济管理》2018年第1期全文转载)

  • Zhi Su, Tong Fang, and Libo Yin*, 2017. The role of news-based implied volatility among US financial markets. Economics Letters 157: 24-27.

  • 马景义、单璐琪、方彤:《一种增强型指数追踪模型设计:GLAR与折衷路径》,《数量经济技术经济研究》2017年第5期,107-121页。

  • 苏治、方彤、秦磊:《一种基于规则化方法的最优稀疏指数追踪模型设计》,《数量经济技术经济研究》2016年第4期,145-160页。(被中国人民大学复印报刊资料《统计与精算》2016年第4期全文转载)

  • 苏治、胡迪、方彤:《人民币加入SDR的国际影响——基于情景假设的量化测算》,《中国工业经济》2015年第12期,5-19页。(被中国人民大学复印报刊资料《世界经济导刊》2016年第3期全文转载)

  • 苏治、秦磊、方彤:《含有图结构约束的稀疏最小方差资产组合模型》,《中国管理科学》2015年第9期,65-70页。

  • 苏治、尹力博、方彤:《量化宽松与国际大宗商品市场:溢出性、非对称性和长记忆性》,《金融研究》2015年第3期,68-82页。

  • 苏治、李进、方彤:《人民币区域接受程度:指数构建与影响因子计量——以东盟及中国香港为例》,《经济理论与经济管理》2014年第7期,51-63页。(被中国人民大学复印报刊资料《世界经济导刊》2014年第10期全文转载)


教育经历
  • 2009-7 — 2012-6
    山东大学
    经济学
  • 2008-9 — 2012-6
    山东大学
    统计学
  • 2012-9 — 2014-6
    中央财经大学
    应用统计
  • 2015-10 — 2019-6
    中央财经大学
    数量经济学
研究方向
论文

(1) 方彤.Uncertainty-driven oil volatility risk premium and international stock market volatility forecasting.JOURNAL OF FORECASTING.2022 (0)

(2) 方彤.Temperature shocks and bank systemic risk: Evidence from China.FINANCE RESEARCH LETTERS.2022 (51)

(3) 方彤.Does the green inspiration effect matter for stock returns? Evidence from the Chinese stock market.Empirical Economics.2021,60 (5):2155-2176

(4) 方彤.Uncertainty matters in US financial information spillovers: Evidence from a directed acyclic graph approach.Quarterly Review of Economics and Finance.2022 (84)

(5) 方彤.一种基于LASSO的多变量混频GARCH模型设计与优化算法研究.数量经济技术经济研究.2021 (12)

(6) 方彤.Do stock prices react to announcements of coporate executives' first-time elections as congress deputies? New evidence from the Chinese political system.FINANCE RESEARCH LETTERS.2021 (102446)

(7) 方彤.Does uncertainty matter for US financial market volatility spillovers? Empirical evidence from a nonlinear Granger causality network.Applied Economics Letters.2021 (28):1877

(8) 方彤.Pandemic-induced fear and stock market returns: Evidence from China.Global Finance Journal.2021 (100644)

(9) Political connections and firm values in China.Finance Research Letters.2021

(10) 方彤.Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility.International Review of Financial Analysis.2020 (71)

(11) Network centrality and cross-section of stock returns.IEIS 2020 Proceedings, Springer.2021

(12) Pandemic-induced fear and stock market returns: Evidence from China.Global Finance Journal.2021

(13) Does uncertainty matter for US financial market volatility spillovers? Empirical evidence from a nonlinear Granger causality network.Applied Economics Letters incorporating Applied Financial Economics Letters.2020

(14) 方彤.Does the green inspiration effect matter for stock return? Evidence from the Chinese stock market.Empirical Economics.2020

(15) 方彤.Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection.Journal of Empirical Finance.2020

(16) Understanding stock market volatility: What is the role of US uncertainty?.North American Journal of Economics and Finance (48):582-590

(17) 一类包含不同权重函数的混频GARCH族模型及其应用研究.数量经济技术经济研究.2018 (10)

(18) 中国虚拟经济与实体经济的关联性——基于规模和周期视角的实证研究.中国社会科学.2017

(19) Does NVIX matter for volatility? Evidence from Asia-Pacific markets.Phsyica A

(20) The role of news-based implied volatility among US financial markets.Economics Letters

(21) 一种基于规则化方法的最优稀疏指数追踪模型设计.数量经济技术经济研究

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