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9410 Results

Trading on Long-term Information

Staff Working Paper 2020-20 Corey Garriott, Ryan Riordan
Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading.

The Term Structures of Loss and Gain Uncertainty

We investigate the uncertainty around stock returns at different investment horizons. Since a return is either a loss or a gain, we categorize return uncertainty into two components—loss uncertainty and gain uncertainty. We then use these components to evaluate investment.
Content Type(s): Staff research, Staff working papers Research Topic(s): Asset pricing, Econometric and statistical methods JEL Code(s): G, G1, G12

Networking the Yield Curve: Implications for Monetary Policy

We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff Working Paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.
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