Search results

This analysis seeks to deal with the emerging economies and to reveal that, if the fiscal authority is accountable with a policy that stabilizes the public debt/GDP ratio, the consequence is a low Treasury bond risk premium.

Based on the purpose of this paper, a theoretical model is developed and empirical evidence through an autoregressive distributed lag (ADL) model, taking into account the Brazilian experience, is made.

The findings denote that domestic variables are responsible for determining the risk premium. Moreover, a correct management of the public debt and the use of primary surplus targets make for a good strategy for promoting a fall in the Treasury bond risk premium.

Primary surplus and public debt/GDP ratio can be used as important tools for mitigating the Treasury bond risk premium.

The results of the paper give some new insights about the management of fiscal policy for developing countries.

Theory suggests that as long as a country runs a balanced budget regime, there is no linkage between fiscal variables and the interest rates. In the case of fiscal expansion that is not sufficiently covered by government revenues, however, the government has two options to finance its deficit: printing money or additional borrowing. Both options lead to an increase in the risk premia on government bonds. One strand of literature focuses on a currency crisis that emerges as a necessary outcome in light of contradictions between fixed exchange rate, and fiscal and financial fundamentals. If government bonds are denominated in domestic currency, the government can reduce their real value by higher inflation or by devaluation of the national currency. In order to bear this risk foreign investors require a currency risk premium. Governments can eliminate the risk of currency devaluation by issuing bonds denominated in foreign currencies, but the default risk remains and it depends on public finances. Another strand of the literature looks at the relation between fiscal variables and government bond yields in the framework of portfolio balance model.

This paper aims to study the asset pricing implications for stock and bond markets in a long-run risks (LRR) model with regime shifts. This general equilibrium framework can not only generate sign-switching stock-bond correlations and bond risk premium, but also quantitatively reproduce various other salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.

The researchers study the joint determinants of stock and bond returns in a LRR model framework with regime shifts in consumption and inflation dynamics. In particular, the means, volatilities, and the correlation structure between consumption growth and inflation are regime-dependent.

The model shows that the term structure of interest rates and stock-bond correlation are intimately related to business cycles, while LRR play a more important role in accounting for high equity premium than do business cycle risks.

This paper studies the joint determinants of stock and bond returns in a Bansal and Yaron (2004) type of LRR framework. This rational expectations general equilibrium framework can (1) jointly match the dynamics of consumption, inflation and cash flow; (2) generate time-varying and sign-switching stock and bond correlations, as well as generating sign-switching bond risk premium; and (3) coherently explain another long list of salient empirical features in stock and bond markets, including time-varying equity and bond return premia, regime shifts in real and nominal yield curves, the violation of the expectations hypothesis of bond returns.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

The authors analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. They study how the existence of non-tradable assets impacts optimal asset allocation decisions of investors who own such assets and of investors who do not have access to non-tradable assets.

In this theoretical analysis, the authors analyze a model with tradable and non-tradable asset classes whose cash flows are jointly normally distributed. There are two types of investors, with and without access to non-tradable assets. All investors have constant absolute risk aversion preferences. The authors derive closed form solutions for optimal investor demand and equilibrium asset prices. They calibrated the model using US data for listed equity, bonds and private equity. Further, the authors illustrate the sensitivities of quantities and prices with respect to the main parameters.

The study finds that the existence of non-tradable assets has a large impact on optimal asset allocation. Investors with (without) access to non-tradable assets tilt their portfolios of tradable assets away from (toward) assets to which non-tradable assets exhibit positive betas.

The model provides important insights not only for investors holding non-tradable assets such as private equity but also for investors who do not have access to non-tradable assets. Investors who ignore the effect of non-tradable assets when reverse-engineering risk premia from asset covariances and market capitalizations might severely underestimate the equity risk premium.

The authors provide the first comprehensive analysis of the equilibrium effects of non-tradability of some assets on optimal policy portfolios. Thus, this paper goes beyond analyzing the effects of market imperfections on individual portfolio choices.

In the light of past financial and economic turmoil, there has been a marked increase in the volatility in real estate markets. This has impacted on the pricing of property assets, partly through market sentiment and particularly concerning risk. It also limits modelling accuracy model accuracy. The purpose of this paper is to create a new variable and model to enhance analysis of what drives real estate yields incorporating market sentiment to risk.

This paper specifically considers the modelling of property pricing within a volatile economic environment. The theoretical context begins by analysing the relationship between property yields and government bonds. The analytical context then moves on to specifically include a measurement of risk which stresses its role and importance in investment markets since the Global Financial Crisis. The model thus incorporates macroeconomic and real estate data, together with an international risk multiplier, which is calculated within the paper.

The paper finds the use of measurements of market sentiment and risk are more powerful tools for modelling yields than previous techniques alone.

This is an initial paper outlining the creation of sentiment and risk measurements in the financial market and showing an example of its application to a commercial real estate market. The implication is that this could add a major new explanatory variable to modelling of yields.

The paper highlights the importance of risk in the pricing of commercial real estate, over and above normal variables. It highlights how this can help explain over and undershooting of yields within commercial real estate which would be of great importance in the investment world.

This paper attempts to explicitly measure market sentiment, pricing of risk and how this impacts real estate pricing.

Recently the world economy was confronted to the worst financial crisis since the great depression. This unprecedented crisis started in mid-2007 had a huge impact on the European government bond market. But what are the main drivers of this “perfect storm” that since 2009 affects EU government bond market as well? To answer this question, we propose an empirical study of the determinants of the sovereign bond spreads of EU countries with respect to Germany during the period 2003–2010. Technically, we address two main questions. First, we ask what share of the change in sovereign bond spreads is explained by changes in the fundamentals, liquidity, and market risks. Second, we distinguish between EU member states within and outside the Euro area and question whether long-term determinants of spreads affect EU members uniformly. To these ends, we employ panel data techniques in a regression model where spreads to Germany (with virtually no default risk) are explained by set of traditional variables and a number of policy variables. Results reveal that large fiscal deficits and public debt as well as political risks and to a lesser extent the liquidity are likely to put substantial upward pressures on sovereign bond yields in many advanced European economies.

Following Ang and Piazzesi’s (2003) study, the authors use an affine term structure model to study the relevance of macroeconomic (domestic and foreign) factors for Peru’s sovereign yield curve in the period from November 2005 to December 2015. The paper aims to discuss this issue.

Risk premia are modeled as time-varying and depend on both observable and unobservable factors; and the authors estimate a vector autoregressive model considering no-arbitrage assumptions.

The authors find evidence that macro factors help to improve the fit of the model and explain a substantial amount of variation in bond yields. However, their influence is very sensitive to the specification model. Variance decompositions show that macro factors explain a significant share of the movements at the short and middle segments of the yield curve (up to 50 percent), while unobservable factors are the main drivers for most of the movements at the long end of the yield curve (up to 80 percent). Furthermore, the authors find that international markets are relevant for the determination of the risk premium in the short term. Higher uncertainty in international markets increases bond yields, although this effect vanishes quickly. Finally, the authors find that no-arbitrage restrictions with the incorporation of macro factors improve forecasts.

To the authors’ knowledge this is the first application of this type of models using data from an emerging country such as Peru.