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Found 15 papers, 5 papers with code
Forecasting Volatility of Oil-based Commodities: The Model of Dynamic Persistence
Time variation and persistence are crucial properties of volatility that are often studied separately in oil-based volatility forecasting models.
Learning Probability Distributions of Day-Ahead Electricity Prices
We propose a novel machine learning approach to probabilistic forecasting of hourly day-ahead electricity prices.
Common Firm-level Investor Fears: Evidence from Equity Options
We identify a new type of risk, common firm-level investor fears, from commonalities within the cross-sectional distribution of individual stock options.
The Dynamic Persistence of Economic Shocks
This paper presents a model for smoothly varying heterogeneous persistence of economic data.
Common Idiosyncratic Quantile Risk
We identify a new type of risk that is characterised by commonalities in the quantiles of the cross-sectional distribution of asset returns.
Learning Probability Distributions in Macroeconomics and Finance
We propose a deep learning approach to probabilistic forecasting of macroeconomic and financial time series.
Risks of heterogeneously persistent higher moments
Using intraday data for the cross-section of individual stocks, we show that both transitory and persistent fluctuations in realized market and average idiosyncratic volatility, skewness and kurtosis are differentially priced in the cross-section of asset returns, implying a heterogeneous persistence structure of different sources of higher moment risks.
Currency Network Risk
This paper identifies new currency risk stemming from a network of idiosyncratic option-based currency volatilities and shows how such network risk is priced in the cross-section of currency returns.
Dynamic industry uncertainty networks and the business cycle
We argue that uncertainty network structures extracted from option prices contain valuable information for business cycles.
Deep Learning, Predictability, and Optimal Portfolio Returns
We study dynamic portfolio choice of a long-horizon investor who uses deep learning methods to predict equity returns when forming optimal portfolios.
Persistence in Financial Connectedness and Systemic Risk
This paper characterises dynamic linkages arising from shocks with heterogeneous degrees of persistence.
Investment Disputes and Abnormal Volatility of Stocks
Dramatic growth of investment disputes between foreign investors and host states rises serious questions about the impact of those disputes on investors.
Dynamic Network Risk
This paper examines the pricing of short-term and long-term dynamic network risk in the cross-section of stock returns.
Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists
We propose how to quantify high-frequency market sentiment using high-frequency news from NASDAQ news platform and support vector machine classifiers.
Asymmetric Network Connectedness of Fears
This paper introduces forward-looking measures of the network connectedness of fears in the financial system, arising due to the good and bad beliefs of market participants about uncertainty that spreads unequally across a network of banks.
