We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models, and a range of linear specifications in addition to univariate models in which conditional heteroskedasticity is captured by GARCH type specifications and in which predicted volatilities appear in the conditional mean. The results demonstrate that U.K. asset returns require non-linear dynamics be modeled. In particular, the evidence in favor of adopting a Markov switching framework is strong. Our results appear robust to the choice of sample period, changes in the adopted loss function and to the methodology employed to test the null hypothesis of equal predictive accuracy across competing models.
This paper investigates the out-of-sample predictability of bond excess returns. We assess the economic value of the forecasting ability of empirical models based on long-term forward interest rates in a dynamic asset allocation strategy. The results show that the information content of forward rates does not generate systematic economic value to investors. Indeed, these models do not outperform the no-predictability benchmark. Furthermore, their relative performance deteriorates over time.
A growing body of empirical evidence suggests that investors’ behavior is not well described by the traditional paradigm of (subjective) expected utility maximization under rational expectations. A literature has arisen that models agents whose choices are consistent with models that are less restrictive than the standard subjective expected utility framework. In this paper we conduct a survey of the existing literature that has explored the implications of decision-making under ambiguity for financial market outcomes, such as portfolio choice and equilibrium asset prices. We conclude that the ambiguity literature has led to a number of significant advances in our ability to rationalize empirical features of asset returns and portfolio decisions, such as the empirical failure of the two-fund separation theorem in portfolio decisions, the modest exposure to risky securities observed for a majority of investors, the home equity preference in international portfolio diversification, the excess volatility of asset returns, the equity premium and the risk-free rate puzzles, and the occurrence of trading break-downs.
We use a simple partial adjustment econometric framework to investigate the effects of the crisis on the dynamic properties of a number of yield spreads. We find that the crisis has caused substantial disruptions revealed by changes in the persistence of the shocks to spreads as much as by in their unconditional mean levels. Formal breakpoint tests confirm that the financial crisis has been over approximately since the Spring of 2009. The financial crisis can be conservatively dated as a August 2007 – June 2009 phenomenon, although some yield spread series seem to point out to an end of the most serious disruptions as early as in December 2008. We uncover evidence that the LSAP program implemented by the Fed in the US residential mortgage market has been effective, in the sense that the risk premia in this market have been uniquely shielded from the disruptive effects of the crisis.
To address how technological progress in financial intermediation affects the economy, a costly state verification framework is embedded into the standard growth model. The framework has two novel ingredients. First, firms differ in the risk/return combinations that they offer. Second, the efficacy of monitoring depends upon the amount of resources invested in the activity. A financial theory of firm size results. Undeserving firms are over financed, deserving ones under funded. Technological advance in intermediation leads to more capital accumulation and a redirection of funds away from unproductive firms toward productive ones. With continued progress, the economy approaches its first-best equilibrium.
How important is financial development for economic development? A costly state verification model of financial intermediation is presented to address this question. The model is calibrated to match facts about the U.S. economy, such as the intermediation spreads and the firm-size distributions for 1974 and 2004. It is then used to study the international data using cross-country interest-rate spreads and per-capita GDPs. The analysis suggests a country like Uganda could increase its output by 116 percent if it could adopt the world’s best practice in the financial sector. Still, this amounts to only 29 percent of the gap between Uganda’s potential and actual output.
The information technology (IT) revolution coincided with the transformation of the U.S. unsecured credit market. From 1983 to 2004 households'''''''' unsecured borrowing increased rapidly and there was a even faster increase in the number of bankruptcy filings. To study the effect of information costs on debt and bankruptcy a risk of repu- diation model with asymmetric information and costly screening is introduced. When information costs are high, the design of contracts under private information prevents some households from borrowing with risk of default. As information costs drop, house- holds borrow more and the number of bankruptcy lings increase. A calibrated version of the model reproduces the main characteristics of the U.S. unsecured credit market in 1983 and 2004. Quantitative exercises suggest that the IT revolution may have played an important role in the transformation of the unsecured credit market.
The Federal Reserve’s unconventional monetary policy announcements in 2008-2009 substantially reduced international long-term bond yields and the spot value of the dollar. These changes closely followed announcements and were very unlikely to have occurred by chance. A simple portfolio choice model can produce quantitatively plausible changes in U.S. and foreign excess bond yields. The jump depreciations of the USD are fairly consistent with estimates of the impacts of previous equivalent monetary policy shocks. The policy announcements do not appear to have reduced yields by reducing expectations of real growth. Unconventional policy can reduce international long-term yields and the value of the dollar even at the zero bound.
Despite its role in monetary policy and finance, the expectations hypothesis (EH) of the term structure of interest rates has received virtually no empirical support. The empirical failure of the EH has been attributed to a variety of econometric biases associated with the single-equation models most often used to test it; however, none of these explanations appears to account for the massives failure reported in the literature. We note that traditional tests of the EH are based on two assumptions—the EH per se and an assumption about the expectations generating process (EGP) for the short-term rate. Arguing that convential tests of the EH could reject it because the EGP embedded in these tests is significantly at odds with the true EGP, we investigate this possibility by analyzing the out-of-sample predictive prefromance of several models for predicting interest rates and a model that assumes the EH holds. Using standard methods that take into account parameter uncertainty, the null hypothesis of equal predictive accuracy of each models relative to the random walk alternative is never rejected.
Using data for a large number of advanced and emerging market economies during 1985-2009, this paper documents the dynamics of financial integration and assesses whether advances in financial integration and globalization yield the beneficial real effects resulting from a more efficient resource allocation predicted by theory. We find that: (a) financial integration has progressed significantly worldwide, within regions, and particularly in emerging markets; (b) advances in financial integration and globalization predict higher growth, lower growth volatility, as well as lower probabilities of systemic real risk realizations; (c) financial integration fosters domestic financial development and the liquidity of equity markets; and (d) the quality of institutions and corporate governance are important determinants of the levels of financial integration and globalization. Thus, financial integration and globalization appear to yield direct as well as indirect benefits in the form of improved countries’ growth prospects and lower systemic real risk.
Academic research relies extensively on macroeconomic variables to forecast the U.S. equity risk premium, with relatively little attention paid to the technical indicators widely employed by practitioners. Our paper fills this gap by comparing the forecasting ability of technical indicators with that of macroeconomic variables. Technical indicators display statistically and economically significant in-sample and out-of-sample forecasting power, matching or exceeding that of macroeconomic variables. Furthermore, technical indicators and macroeconomic variables provide complementary information over the business cycle: technical indicators better detect the typical decline in the equity risk premium near business-cycle peaks, while macroeconomic variables more readily pick up the typical rise in the equity risk premium near cyclical troughs. Consistent with this behavior, we show that combining information from both technical indicators and macroeconomic variables significantly improves equity risk premium forecasts versus using either type of information alone. Overall, the substantial countercyclical fluctuations in the equity risk premium appear well captured by the combined information in technical indicators and macroeconomic variables.
This paper examines the impacts of banking market structure and regulation on economic growth using new data on banking market concentration and manufacturing industry-level growth rates for U.S. states during 1899-1929—a period when the manufacturing sector was expanding rapidly and restrictive branching laws segmented the U.S. banking system geographically. Unlike studies of developing and developed countries today, we find that banking market concentration generally had a positive impact on manufacturing sector growth in the early twentieth century United States, with a somewhat stronger impact on industries with smaller establishments, lower rates of incorporation, and less reliance on bond markets (and, hence, relatively more reliance on banks). Because regulations affecting bank entry varied considerably across states and the industrial organization of the U.S. banking system differs markedly from those of other countries, we consider the impact of other aspects of banking market structure and policy on growth. Even after controlling for differences in the prevalence of branch banking, deposit insurance, and other aspects of policy and market structure, we find that market concentration boosted industrial growth.
Recent research [e.g., DeMiguel, Garlappi and Uppal, (2009), Rev. Fin. Studies] has cast doubts on the out-of-sample performance of optimizing portfolio strategies relative to naive, equally weighted ones. However, existing results concern the simple case in which an investor has a one-month horizon and meanvariance preferences. In this paper, we examine whether their result holds for longer investment horizons, when the asset menu includes bonds and real estate beyond stocks and cash, and when the investor is characterized by constant relative risk aversion preferences which are not locally mean-variance for long horizons. Our experiments indicates that power utility investors with horizons of one year and longer would have on average benefited, ex-post, from an optimizing strategy that exploits simple linear predictability in asset returns over the period January 1995 - December 2007. This result is insensitive to the degree of risk aversion, to the number of predictors being included in the forecasting model, and to the deduction of transaction costs from measured portfolio performance.
We examine whether simple VARs can produce empirical portfolio rules similar to those obtained under a range of multivariate Markov switching models, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock bond strategic asset allocation problem on US data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those typical of non linear models that account for bull-bear dynamics and characterize the differences in the implied hedging demands for a long-horizon investor with constant relative risk aversion preferences. In a horse race in which models are not considered in their individuality but instead as an overall class, we find that a power utility investor with a constant coefficient of relative risk aversion of 5 and a 5-year horizon, would be ready to pay as much as 8.1% in real terms to be allowed to select models from the MS class, while analogous calculation for the whole class of expanding window VAR leads to a disappointing 0.3% per annum. We conclude that most (if not all) VARs cannot produce portfolio rules, hedging demands, or out-of-sample performances that approximate those obtained from equally simple non-linear frameworks.
Empirical studies showed that firm-level volatility has been increasing but the aggregate volatility has been decreasing in the US for the post-war period. This paper proposes a unified explanation for these diverging trends. Our explanation is based on a story of financial development - measured by the reduction of borrowing constraints because of greater access to external financing and options for risk sharing. By constructing a dynamic stochastic general-equilibrium model of heterogenous firms facing borrowing constraints and investment irreversibility, it is shown that financial liberalization increases the lumpiness of firm-level investment but decreases the variance of aggregate output. Hence, the model predicts that financial development leads to a larger firm-level volatility but a lower aggregate volatility. In addition, our model is also consistent with the observed decline in volatility of private held firms which do not have (or have only limited) access to external funds.
The 2007-2008 financial crises has made it painfully obvious that markets may quickly turn illiquid. Moreover, recent experience has taught us that distress and lack of active trading can jump “around” between seemingly unconnected parts of the financial system contributing to transforming isolated shocks into systemic panic attacks. We develop a simple two-period model populated by both standard expected utility maximizers and by ambiguity-averse investors that trade in the market for a risky asset. We show that, provided there is a sufficient amount of ambiguity, market break-downs where large portions of traders withdraw from trading are endogeneous and may be triggered by modest re-assessments of the range of possible scenarios on the performance of individual securities. Risk premia (spreads) increase with the proportion of traders in the market who are averse to ambiguity. When we analyze the effect of policy actions, we find that when a market has fallen into a state of impaired liquidity, bringing the market back to orderly functioning through a reduction in the amount of perceived ambiguity may cause further reductions in equilibrium prices. Finally, our model provides stark indications against the idea that policy makers may be able to “inflate” their way out of a financial crisis.
This paper investigates the source of predictability of bond risk premia by means of long-term forward interest rates. We show that the predictive ability of forward rates could be due to the high serial correlation and cross-correlation of bond prices. We show that the predictive ability of forward rates could be due to the high serial correlation and cross-correlation of bond prices. After a simple reparametrization of models used to predict spot rates or excess returns, we find that forward rates exhibit much less predictive power than previously recorded. Furthermore, our economic value analysis indicates that there are no economic gains to mean-variance investors who use the predictions of these models in a stylized dynamic asset allocation strategy.
Welfare gains to long-horizon investors may derive from time diversification that exploits non-zero intertemporal return correlations associated with predictable returns. Real estate may thus become more desirable if its returns are negatively serially correlated. While it could be important for long horizon investors, time diversification has been mostly investigated in asset menus without real estate and focusing on in-sample experiments. This paper evaluates ex post, out-of-sample gains from diversification when E-REITs belong to the investment opportunity set. We find that diversification into REITs increases both the Sharpe ratio and the certainty equivalent of wealth for all investment horizons and for both Classical and Bayesian (who account for parameter uncertainty) investors. The increases in Sharpe ratios are often statistically significant. However, the out-of sample average Sharpe ratio and realized expected utility of long-horizon portfolios are frequently lower than that of a one-period portfolio, which casts doubts on the value of time diversification.
This paper offers evidence on the design of subprime mortgages as bridge-financing products. We show that the viability of subprime mortgages was uniquely predicated on the appreciation of house prices over short-horizons. High rates of early prepayments on subprime mortgages are suggestive of the use of prepayments as an exit option. This paper argues that high early defaults on post-2004 originations can be explained when one considers high early prepayment rates for pre-2004 originations.
The Great Depression was the worst macroeconomic collapse in U.S. history. Sharp declines in household income and real estate values resulted in soaring mortgage delinquency rates. According to one estimate, as of January 1, 1934, fully one-half of U.S. home mortgages were delinquent and, on average, some 1000 home loans were foreclosed every business day. This paper documents the increase in residential mortgage distress during the Depression, and discusses actions taken by state governments and the federal government to reduce mortgage foreclosures and restore the functioning of the mortgage market. Many states imposed moratoria on both farm and nonfarm residential mortgage foreclosures. Although moratoria reduced farm foreclosure rates in the short run, they appear to have also reduced the supply of loans and made credit more expensive for subsequent borrowers. The federal government took a number of steps to relieve residential mortgage distress and to promote the recovery and growth of the national mortgage market. The Home Owners Loan Corporation (HOLC) was created in 1933 to purchase and refinance delinquent home loans as long-term, amortizing mortgages. Between 1933 and 1936, the HOLC acquired and refinanced one million delinquent loans totaling $3.1 billion. The HOLC refinanced loans on some 10 percent of all nonfarm, owner-occupied dwellings in the United States, and about 20 percent of those with an outstanding mortgage. The Great Depression experience suggests how foreclosures might be reduced during the present crisis.
This paper is an exploration of subprime mortgages over the cohorts from 2000 through 2006, especially those prior to 2004. In particular, this study contrasts subprime originations during the “boom years” of 2004-2006 with originations during an “early period” of 2000-2002. We develop a counterfactual technique to determine how originations during the early period would perform in a different environment, namely, the environment faced by originations in 2004, 2005, and 2006. We find that representative originations during the early period of 2000-2002 would not have performed significantly better than representative originations in 2004, 2005, and 2006. This result is robust to counterfactual exercises for originations with different LTVs. We conclude that mortgages of early cohorts were no less vulnerable to the environment faced by cohorts of 2004-2006.
This paper analyses the role of asset prices in comparison to other factors, in particular exchange rates, as a driver of the US trade balance. It employs a Bayesian structural VAR model that requires imposing only a minimum of economically meaningful sign restrictions. We find that equity market shocks and housing price shocks have been major determinants of the US current account in the past, accounting for up to 32% of the movements of the US trade balance at a horizon of 20 quarters. By contrast, shocks to the real exchange rate have been much less relevant, explaining less than 7% and exerting a more temporary effect on the US trade balance. Our findings suggest that sizeable exchange rate movements may not necessarily be a key element of an adjustment of today’s large current account imbalances, and that in particular relative global asset price changes could be a more potent source of adjustment.
The objective of this paper is to understand how loan structure affects (i) the borrower’s selection of a mortgage contract and (ii) the aggregate economy. We develop a quantitative equilibrium theory of mortgage choice where households can choose from a menu of long-term (nominal) mortgage loans. The model accounts for observed patterns in housing consumption, ownership, and portfolio allocations. We find that the loan structure is a quantitatively significant factor in a household’s housing finance decision. The model suggests that the mortgage structure preferred by a household is dependent on age and income and that loan products with low initial payments offer an alternative to mortgages with no downpayment. These effects are more important when inflation is low. The presence of inflation reduces the real value of the mortgage payment and the outstanding loan overtime reducing mobility. Changes in the structure of mortgages have implications for risk sharing.
This paper examines the association between inflation, monetary policy and U.S. stock market conditions during the second half of the 20th century. We use a latent-variable VAR to estimate the impact of inflation and other macroeconomic shocks on a latent index of stock market conditions. Our objective is to investigate the extent to which various shocks contribute to changes in market conditions, above and beyond their direct effects on real stock prices. We find that disinflation shocks promote market booms and inflation shocks contribute to busts. Further, we find that inflation shocks can explain more of the variation in real stock prices when stock market conditions are taken into account.
We systematically examine the comparative predictive performance of a number of alternative linear and non-linear models for stock and bond returns in the G7 countries. Besides Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STAR) regime switching (predictive) regression models, we also estimate univariate models in which conditional heteroskedasticity is captured through GARCH, TARCH and EGARCH models and ARCH-in mean effects appear in the conditional mean. Although we fail to find a consistent winner/out-performer across all countries and asset markets, it turns out that capturing non-linear effects is of extreme importance to improve forecasting performance. U.S. and U.K. asset return data are “special” in the sense that good predictive performance seems to loudly ask for models that capture non linear dynamics, especially of the Markov switching type. Although occasionally also stock and bond return forecasts for other G7 countries appear to benefit from non-linear modeling (especially of TAR and STAR type), data from France, Germany, and Italy express interesting predictive results on the basis of simpler benchmarks. U.S. and U.K. data are also the only two data sets in which we find statistically significant differences between forecasting models. Results appear to be remarkably stable over time, and robust to the specification of the loss function used in statistical evaluations as well as to the methodology employed to perform pairwise comparisons.
We explore the relationship between disaggregated trading flows, the Canada/U.S. dollar (CAD/USD) market and U.S. macroeconomic announcements with a novel data set of unprecedented breadth and length. Foreign financial trading flows appear to demand liquidity, contemporaneously driving the CAD/USD while commercial trading flows seem to be price sensitive, providing liquidity in response to exchange rate movements. Despite strong contemporaneous correlations with trading flows, exchange rate returns are generally not predictable, except for some intriguing success at long horizons. This failure contrasts with much, but not all, previous research on the topic. While two types of CAD trading flows and the CAD/USD appear to be cointegrated, such structure is probably spurious. There appear to be structural breaks in the order-flow-exchange rate VECM systems in 1994-1996 and 1998-1999. <a href="http://research.stlouisfed.org/econ/cneely/Data_Appendix_The_Dynamic_Interaction.pdf">Data Appendix</a>.
We use multivariate regime switching vector autoregressive models to characterize the time-varying linkages among short-term interest rates (monetary policy) and stock returns in the Irish, the US and UK markets. We find that two regimes, characterized as bear and bull states, are required to characterize the dynamics of returns and short-term rates. This implies that we cannot reject the hypothesis that the regimes driving the markets in the small open economy are largely synchronous with those typical of the major markets. We compute time-varying Sharpe ratios and recursive mean-variance portfolio weights and document that a regime switching framework produces out-of-sample portfolio performance that outperforms simpler models that ignore regimes. Interestingly, the portfolio shares derived under regime switching dynamics implies a fairly low committment to the Irish market, in spite of its brilliant unconditional risk-return trade-off.
This article discusses the microstructure of the U.S. Treasury securities market. Treasury securities are nominally riskless debt instruments issued by the U.S. government. Microstructural analysis is a field of economics/finance that examines the roles played by heterogenous agents, institutional detail, and asymmetric information in the trading process. The article describes types of Treasury issues; stages of the Treasury market; the major players, including the role of the Federal Reserve Bank of New York and the interdealer brokers; the structure of both the spot and futures markets; the findings of the seasonality/announcement and order book literature; and research on price discovery. We conclude by discussing possible future avenues of research.
We study optimal lending behavior under adverse selection in environments with hetero- geneous borrowers specifically, where the borrower’s reservation payoffs (outside options) increase with quality (creditworthiness). Our results show that factors affecting credit sup- ply can also affect lending standards either directly through lending costs or indirectly through borrower reservation payoffs. Lending to uncreditworthy borrowers can be pre- vented by lowering reservation payoffs, by raising lending costs, or both. Lenders seeking to attract creditworthy borrowers with high reservation payoffs would have to lower rates and, consequently, increase collateral requirements on offers that screen out uncreditworthy types. This leads to higher screening costs, thereby increasing the profitability of offers that pool uncreditworthy borrowers a veritable lowering of credit standards. In addition, equilibria in a competition version of the model can also explain the phenomenon of “cream-skimming” by outside (foreign) lenders. Surprisingly, we find that the presence of an informed rival actually aids “cream-skimming” behavior.
After three decades of being relatively constant, the homeownership rate increased over the period 1994 to 2005 to attain record highs. The objective of this paper is to account for the observed boom in ownership by examining the role played changes in demographic factors and innovations in the mortgage market which lessened downpayment requirements. To measure the aggregate and distributional impact of these factors, we construct a quantitative general equilibrium overlapping generation model with housing. We find that the long-run importance of the introduction of new mortgage products for the aggregate homeownership rate ranges from 56 and 70 percent. Demographic factors account for between 16 and 31 percent of the change. Transitional analysis suggests that demographic factors play a more important, but not dominant, role the further away from the long-run equilibrium. From a distributional perspective, mortgage market innovations have a larger impact explaining participation rate changes of younger households, while demographic factors seem to be the key to understanding the participation rate changes of older households. Our analysis suggests that the key to understand the increase in the homeownership rate is the expansion of the set of mortgage contracts. We test the robustness of this result by considering changes in mortgage financing after World War II. We find that the introduction of the conventional fixed rate mortgage, which replaced balloon contacts, accounts for at least fifty percent of the observed increase in homeownership during that period.