Asset pricing - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-28T08:33:56+00:00Variance Premium, Downside Risk and Expected Stock Returns
https://www.bankofcanada.ca/2017/12/staff-working-paper-2017-58/
We decompose total variance into its bad and good components and measure the premia associated with their fluctuations using stock and option data from a large cross-section of firms.2017-12-19T14:27:16+00:00enVariance Premium, Downside Risk and Expected Stock Returns2017-12-19Asset pricingFinancial marketsStaff Working Paper 2017-58https://www.bankofcanada.ca/wp-content/uploads/2017/12/swp2017-58.pdfVariance Premium, Downside Risk and Expected Stock ReturnsBruno FeunouRicardo Lopez AliouchkinRoméo TedongapLai XiDecember 2017GG1G12Risk-Neutral Moment-Based Estimation of Affine Option Pricing Models
https://www.bankofcanada.ca/2017/12/staff-working-paper-2017-55/
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.2017-12-08T11:59:51+00:00enRisk-Neutral Moment-Based Estimation of Affine Option Pricing Models2017-12-08Asset pricingEconometric and statistical methodsStaff Working Paper 2017-55https://www.bankofcanada.ca/wp-content/uploads/2017/12/swp2017-55.pdfRisk-Neutral Moment-Based Estimation of Affine Option Pricing ModelsBruno FeunouCédric OkouDecember 2017GG1G12Good Volatility, Bad Volatility and Option Pricing
https://www.bankofcanada.ca/2017/12/staff-working-paper-2017-52/
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.2017-12-07T15:19:43+00:00enGood Volatility, Bad Volatility and Option Pricing2017-12-07Asset pricingEconometric and statistical methodsStaff Working Paper 2017-52https://www.bankofcanada.ca/wp-content/uploads/2017/12/swp2017-52.pdfGood Volatility, Bad Volatility and Option PricingBruno FeunouCédric OkouDecember 2017GG1G12The Impacts of Monetary Policy Statements
https://www.bankofcanada.ca/2017/11/staff-analytical-note-2017-22/
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.2017-11-24T09:18:40+00:00enThe Impacts of Monetary Policy Statements2017-11-24On the Tail Risk Premium in the Oil Market
https://www.bankofcanada.ca/2017/11/staff-working-paper-2017-46/
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.2017-11-20T07:47:32+00:00enOn the Tail Risk Premium in the Oil Market2017-11-20Asset pricingEconometric and statistical methodsFinancial marketsStaff Working Paper 2017-46https://www.bankofcanada.ca/wp-content/uploads/2017/11/swp2017-46.pdfOn the Tail Risk Premium in the Oil MarketReinhard EllwangerNovember 2017CC5C53C58DD8D84EE4E44GG1G12G13QQ4Q43Measuring Limits of Arbitrage in Fixed-Income Markets
https://www.bankofcanada.ca/2017/10/staff-working-paper-2017-44/
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.2017-10-12T14:26:21+00:00enMeasuring Limits of Arbitrage in Fixed-Income Markets2017-10-12Asset pricingFinancial marketsInternational financial marketsStaff Working Paper 2017-44https://www.bankofcanada.ca/wp-content/uploads/2017/10/swp2017-44.pdfMeasuring Limits of Arbitrage in Fixed-Income MarketsJean-Sébastien FontaineGuillaume NolinOctober 2017GG1G12A Counterfactual Valuation of the Stock Index as a Predictor of Crashes
https://www.bankofcanada.ca/2017/09/staff-working-paper-2017-38/
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).2017-09-20T11:43:44+00:00enA Counterfactual Valuation of the Stock Index as a Predictor of Crashes2017-09-20Asset pricingFinancial stabilityStaff Working Paper 2017-38https://www.bankofcanada.ca/wp-content/uploads/2017/09/swp2017-38.pdfA Counterfactual Valuation of the Stock Index as a Predictor of CrashesTom RobertsSeptember 2017GG0G01G1G12G17G19Optimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions
https://www.bankofcanada.ca/2017/08/staff-working-paper-2017-33/
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.2017-08-10T07:38:59+00:00enOptimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear Regressions2017-08-10Asset pricingEconometric and statistical methodsExchange ratesInterest ratesStaff Working Paper 2017-33https://www.bankofcanada.ca/wp-content/uploads/2017/08/swp2017-33.pdfOptimal Estimation of Multi-Country Gaussian Dynamic Term Structure Models Using Linear RegressionsAntonio Diez de los RiosAugust 2017EE4E43FF3F31GG1G12G15Markets Calling: Intelligence Gathering at the Bank of Canada
https://www.bankofcanada.ca/2017/06/markets-calling-intelligence-gathering-bank-canada/
Deputy Governor Lynn Patterson discusses how the Bank gathers financial market intelligence and what it is learning.2017-06-28T14:05:46+00:00Markets Calling: Intelligence Gathering at the Bank of Canada2017-06-28Lynn PattersonSmall‐Sample Tests for Stock Return Predictability with Possibly Non‐Stationary Regressors and GARCH‐Type Effects
https://www.bankofcanada.ca/2017/03/staff-working-paper-2017-10/
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.2017-03-10T08:29:32+00:00enSmall‐Sample Tests for Stock Return Predictability with Possibly Non‐Stationary Regressors and GARCH‐Type Effects2017-03-10Asset pricingEconometric and statistical methodsFinancial marketsStaff Working Paper 2017-10https://www.bankofcanada.ca/wp-content/uploads/2017/03/swp2017-10.pdfSmall‐Sample Tests for Stock Return Predictability with Possibly Non‐Stationary Regressors and GARCH‐Type EffectsSermin GungorRichard LugerMarch 2017CC1C12C3C32GG1G14