"Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio"

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986,1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional volatility estimated with the GARCH model. We apply our models to Canadian short-term interest rates. When comparing the profile of the interest rate stochastic volatility to the conditional one, we find that the omission of a constant term in the stochastic volatility model might have a perverse effect leading to a scaling problem, a problem often overlooked in the literature. Stochastic volatility seems to be a better forecasting tool than GARCH(1,1) since it is less conditioned by autoregressive past information. Second, we filter the S&P500 price-earnings(P/E) ratio in order to forecast its value. To make this forecast, we postulate a rational expectations process but our method may accommodate other data generating processes. We find that our forecast is close to a GARCH(1,1) profile.Stochastic volatility, Kalman filter, P/E ratio forecast, Interest rate forecast

The Effects of IFRS on Financial Ratios: Early Evidence in Canada

This paper provides preliminary evidence of the impact on financial ratios caused by the transition to International Financial Reporting Standards (IFRS) in Canada. The main features of IFRS are explained in the context of a shift from Canadian Generally Accepted Accounting Principles (GAAP) while the main differences between the two sets of rules are underscored – heavier reliance of IFRS on fair value accounting and comprehensive income, and the use of the entity theory for consolidation. The effects of IFRS on financial ratios in the areas of liquidity, leverage, coverage and profitability are discussed and verified using a sample cohort of early adopters in Canada. The preliminary evidence reveals significantly higher volatility to most of the ratios under IFRS when compared to those derived under pre-changeover Canadian GAAP. While the means and medians of IFRS ratios differ from the means and medians of the same ratios under pre-changeover Canadian GAAP, the differences are not statistically significant overall. However, important individual discrepancies are in some cases observed. Naturally, analysts using ratios for analytical purposes during the transition period need to be vigilant as ratios computed under IFRS are not directly comparable with those derived under pre-changeover Canadian GAAP. It is recommended that heightened attention be directed to the new feature – comprehensive income – which incorporates unrealized gains and losses that bypass the income statement. The suggested analytical tools best suited to mitigate the contributing effect include reliance on comprehensive-Return on Assets (ROA) and comprehensive-Return on Equity (ROE).IFRS, financial ratios, first application of IFRS

"Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio"

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986,1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional volatility estimated with the GARCH model. We apply our models to Canadian short-term interest rates. When comparing the profile of the interest rate stochastic volatility to the conditional one, we find that the omission of a constant term in the stochastic volatility model might have a perverse effect leading to a scaling problem, a problem often overlooked in the literature. Stochastic volatility seems to be a better forecasting tool than GARCH(1,1) since it is less conditioned by autoregressive past information. Second, we filter the S&P500 price-earnings(P/E) ratio in order to forecast its value. To make this forecast, we postulate a rational expectations process but our method may accommodate other data generating processes. We find that our forecast is close to a GARCH(1,1) profile

"Forecasting stochastic Volatility using the Kalman filter: an application to Canadian Interest Rates and Price-Earnings Ratio"

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986,1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional volatility estimated with the GARCH model. We apply our models to Canadian short-term interest rates. When comparing the profile of the interest rate stochastic volatility to the conditional one, we find that the omission of a constant term in the stochastic volatility model might have a perverse effect leading to a scaling problem, a problem often overlooked in the literature. Stochastic volatility seems to be a better forecasting tool than GARCH(1,1) since it is less conditioned by autoregressive past information. Second, we filter the S&P500 price-earnings(P/E) ratio in order to forecast its value. To make this forecast, we postulate a rational expectations process but our method may accommodate other data generating processes. We find that our forecast is close to a GARCH(1,1) profile

The Emotional Edge of Financial Predators: a Four Group Longitudinal Study

En los últimos años, los inversionistas han sido engañados por sus propios expertos financieros. A pesar de las advertencias de las organizaciones reguladoras, como la Comisión de Seguridad de Valores Mobiliarios o los informes publicados por periódicos y revistas especializados, muchas personas se sienten atrapadas en los esquemas de Ponzi. La pregunta es ¿por qué? En este trabajo se plantea la hipótesis de que gran parte de los inversionistas basó sus decisiones en torno a los asesores o agentes financieros poco escrupulosos que capitalizaron la emoción primitiva. Se realiza una investigación longitudinal con cuatro grupos para un periodo de seis meses en donde se muestra que la gente se involucra en la negociación financiera con el corazón, no sólo con sus pensamientos y calculadoras.In the last few years, a number of investors from all walks of life have been duped by their once-trusted financial advisors. Despite warnings by regulatory bodies such as the Security Exchange Commission or educated reports published by newspapers and magazines, people still get caught in the likes of Ponzi schemes. The question is why? This paper hypothesizes that a large part of the blind eye turned onto financial advisors and brokers finds its source in primitive emotion. A four-group longitudinal study spread over six months shows that people engage in financial negotiation with their hearts and guts, not only with their thoughts and calculators

Finance computationnelle et gestion des risques: ingénierie financière avec applications Excel (Visual Basic) et Matlab

Ce manuel propose un exposé rigoureux de la gestion des risques en finance. Les aspects théoriques de la question sont abordés par des démonstrations claires et des rappels élaborés des bases mathématiques de la finance computationnelle. Le texte est émaillé de nombreux programmes écrits en langages Visual Basic (Excel), Matlab et EViews qui prépareront l'étudiant à sa carrière de spécialiste en ingénierie financière

On Optimal Instrumental Variables Generators: An Application to Hedge Funds Returns

Instrumental variables generators, Hedge funds returns, Financial models, C10, F39, G10, G20,

Risk Procyclicality and Dynamic Hedge Fund Strategies: An Application of Kalman Filter to Time-Varying Alpha and Beta

Traditional financial institutions like banks follow procyclical risk strategies, i.e. they increase their leverage in economic expansions and reduce it in contractions, which leads to a procyclical behaviour for their betas and other risk and financial performance measures (Rajan, 2005, 2009; Shin, 2009; Jacque, 2010; Gennaioli et al., 2011). Consistent with the returns spectrum of many hedge fund strategies which displays a high volatility at business cycle frequencies, we study, in this paper, the cyclical aspects of hedge fund strategies, a subject quite neglected in the literature. To do so we rely on two procedures: conditional modelling and Kalman filtering of hedge funds alpha and beta. We find that hedge funds betas are usually procyclical. Our results also show that the alpha is often high at the beginning of a market upside cycle but as the demand pressure increases, it progressively shrinks, which suggests that the alpha puzzle documented in the financial literature is questionable when cast in a dynamic setting

A correlational study of Finding a balance point" in family caregiving process for frail elders."

International audienc