Asset pricing
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Risk-Neutral Moment-Based Estimation of Affine Option Pricing Models
This paper provides a novel methodology for estimating option pricing models based on risk-neutral moments. We synthesize the distribution extracted from a panel of option prices and exploit linear relationships between risk-neutral cumulants and latent factors within the continuous time affine stochastic volatility framework. -
Good Volatility, Bad Volatility and Option Pricing
Advances in variance analysis permit the splitting of the total quadratic variation of a jump diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions, and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. -
The Impacts of Monetary Policy Statements
In this note, we find that market participants react to an unexpected change in the tone of Canadian monetary policy statements. When the market perceives that the Bank of Canada plans to tighten (or alternatively, loosen) the monetary policy earlier than previously expected, the Canadian dollar appreciates (or depreciates) and long-term Government of Canada bond yields increase (or decrease). The tone of a statement is particularly relevant to the market when the policy rate has been unchanged for some time. -
On the Tail Risk Premium in the Oil Market
This paper shows that changes in market participants’ fear of rare events implied by crude oil options contribute to oil price volatility and oil return predictability. Using 25 years of historical data, we document economically large tail risk premia that vary substantially over time and significantly forecast crude oil futures and spot returns. -
Measuring Limits of Arbitrage in Fixed-Income Markets
We use relative value to measure limits to arbitrage in fixed-income markets. Relative value captures apparent deviations from no-arbitrage relationships. It is simple, intuitive and can be computed model-free for any bond. -
A Counterfactual Valuation of the Stock Index as a Predictor of Crashes
Stock market fundamentals would not seem to meaningfully predict returns over a shorter-term horizon—instead, I shift focus to severe downside risk (i.e., crashes). -
Optimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions
This paper proposes a novel asymptotic least-squares estimator of multi-country Gaussian dynamic term structure models that is easy to compute and asymptotically efficient, even when the number of countries is relatively large—a situation in which other recently proposed approaches lose their tractability. -
June 28, 2017
Markets Calling: Intelligence Gathering at the Bank of Canada
Deputy Governor Lynn Patterson discusses how the Bank gathers financial market intelligence and what it is learning. -
Small‐Sample Tests for Stock Return Predictability with Possibly Non‐Stationary Regressors and GARCH‐Type Effects
We develop a simulation-based procedure to test for stock return predictability with multiple regressors. The process governing the regressors is left completely free and the test procedure remains valid in small samples even in the presence of non-normalities and GARCH-type effects in the stock returns.