Asset pricing
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Generalized Autoregressive Gamma Processes
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does. -
It takes a panel to predict the future: What the stock market says about future economic growth in Canada
Valuation ratios in the Canadian stock market can help reveal investors’ expectations about future economic growth because the impact of economic growth on valuation ratios can vary across industries. We find that this variation helps produce accurate forecasts of future growth of real gross domestic product in Canada. The forecasts from our model declined by just over 3 percentage points between January 2022 and February 2023—a period when the Bank of Canada rapidly increased the overnight rate. As well, we find that interest-rate-sensitive industries had an outsized contribution to this expected slowdown in growth. -
Pricing Indefinitely Lived Assets: Experimental Evidence
We study the trading of an asset with bankruptcy risk. The traded price of the asset is, on average, 40% of the expected total dividend payments. We investigate which economic models can explain the low traded price. -
What we can learn by linking firms’ reported emissions with their financial data
We analyze the financial statements and stock prices of publicly traded firms incorporated in Canada that report greenhouse gas emissions. We find that these firms primarily use equity financing. We also find that equity investors increasingly account for firms’ emissions when making investment decisions but the impact appears small. This suggests that assets exposed to climate change remain at risk of a sudden repricing.