Moments of cross-sectional stock market returns and the German business cycle

Based on monthly data covering the period from 1987 to 2021, we analyse whether cross-sectional moments of stock market returns may provide information about the future position of the German business cycle. We apply in-sample forecasting regressions with and without leading indicators as control variables, pseudo-out-of-sample exercises, autoregressive distributed lag models, and impulse-response functions estimated by local projections. We find in-sample predictive power of the first and third cross-section moments for the future growth of industrial production, even if one controls for well-established leading indicators for the German business cycle. Out-of-sample tests show that these variables reduce the relative mean squared error compared with benchmark models. We do not find a long-run relation between the moment series and industrial production. The dynamic response of industrial production to a shock on the cross-section moments is in line with the other results.     

Asymmetric effects of industrial production,money supply and exchange rate changes on stock returns in Turkey

The aim of this article is twofold: First, it examines the asymmetric effects of industrial production, money supply and RER on stock returns in Turkey by using the non-linear autoregressive distributed lag (NARDL) model over the periods of 1994:01–2017:05 and 2002:01–2017:05. Second, it tries to determine whether there is a change of these macroeconomic variables’ effects on stock returns after the 2001 financial crisis since after 2002 period represents a structural break from the past in terms of economic, political and macroeconomic policy approaches. The study finds that the effects of the changes in industrial production, money supply and RER on stock returns are asymmetric, and the asymmetries are larger after the 2002 subsample compared to the full sample period. The empirical results further suggest that tight monetary policies appear to retard the stock returns more than easy monetary policies that stimulate them.     

The Pricing of Italian Equity Returns

In this paper, we investigate the relationship between common risk factors and average returns for Italian stocks. Our research has identified the Italian stock market's economic variables by using the results from factor analyses and time series regressions. We study several multi‐factor models combining the relevant macroeconomic variables with the mimicking equity portfolios SMB (small minus big) and HML (high minus low) proposed by Fama and French (1993). The key question we want to ask ourselves, is whether the influential role of the size and book‐to‐market equity factors in explaining average stock returns can stand up well when competing with some macroeconomic factors. In other words, do stock returns carry some risk premium that is independent of either the market return or the economic forces that underlie the common variation in returns? Our empirical work estimates risk premiums using both traditional two‐pass procedures and one‐pass (full information) methodologies. We show that only the market index and variables linked to interest rate shifts are consistently priced in the Italian stock returns. The role of other factors, and in particular both the size and the price‐to book ratio, are crucially dependent on the estimation procedure. (J.E.L.: G11, G12).     

The Stability of the Relation Between the Stock Market and Macroeconomic Forces

This paper identifies the macroeconomic factors that influence Italian equity returns and tests the stability of their relation with securities returns. The relation between stock returns and the macroeconomic factors is found to be unstable: not only are the factor loadings of individual securities virtually uncorrelated over time, but a high percentage of the shares experience a reversal of the sign of the estimated loadings. This result is not confined to single periods or to a small group of shares, but holds in different sub–periods and for securities in all risk classes. These findings suggest that research should carefully investigate the specification of the return generating process and the stability of the risk measures.
(J.E.L.: G12, E44).     

Forecasting stock market volatility: The role of technical variables

Accurate volatility forecasts are required by both market participants and policy makers. In this paper, we forecast stock return volatility by using a wide range of technical indicators constructed based on the past behavior of stock price, volatility and trading volume. Our out-of-sample results indicate that the incorporation of technical variables in the autoregression benchmark can produce significantly more accurate volatility forecasts. The forecasting performance of the combination of technical indicators is further compared with that of the popular economic indicators. Technical variables perform better than economic variables when the economy is an expansion, while the economic variables generate more accurate forecasts when the economy belongs a recession. These two types of variables provide complementary information over the business cycle. We obtain more reliable forecasts by combining all economic and technical information together than by combining either type of information alone.     

Daily Business and External Condition Indices for the Australian Economy

We estimate an unobservable domestic business conditions index for Australia using a variety of observable macroeconomic and financial variables, relating it to an unobservable external index involving external variables relevant to Australia. Our small open economy, dynamic factor model uses stock and flow variables arriving at mixed frequencies. We find important links between the domestic and external indices, consistent with the small open economy assumption.     

Macroeconomic performance and convergence in OECD countries

This paper investigates the robustness of the correlation between growth and a set of variables which comprises accumulation rates in human and physical capital and medium term macroeconomic indicators in OECD countries. We include these variables as additional regressors in the standard growth equation that comes from the human capital-augmented Solow model. Our results show that variables related to medium term macroeconomic performance affect both growth and convergence. In some periods these variables even outperform the explanatory power of the conventional growth variables such as the accumulation rates. Our results also suggest that it is difficult to analyse the contribution to growth of any particular macroeconomic indicator in an isolated way. Rather, these effects should be studied in a framework that accounts for the macroeconomic performance of a country.     

Idiosyncratic risk matters! A regime switching approach

The evidence on the inter-temporal relation between idiosyncratic risk and future stock returns is conflicting and confusing. We shed new light on the issue using a more flexible econometric approach based on [Hamilton, J.D. 1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357–384.] regime switching model that accommodates the parameter instability of the forecasting relation between returns and financial variables. We find strong evidence suggesting that idiosyncratic risk is related to future stock market returns only in the low variance regime.     

Non-falsified Expectations and General Equilibrium Asset Pricing: The Power of the Peso

We discuss the extent to which the expectation of a rare event which happens not to materialise over the sample period, but which is not rationally excludable from the set of possibilities – the peso problem –, can affect the behaviour of rational agents and the characteristics of market equilibrium. To that end we describe quantitatively the macroeconomic and financial properties of a standard equilibrium business cycle model modified to allow for a very small probability of a depression state. We produce a model specification for which both business cycle characteristics and mean financial returns are in accord with United States observations.This paper examines the possibility that the large equity premium observed in the United States may result from the expectations of a disaster event, or set of events, which happen not to have materialised in the sample period of observations. Such a possibility, which falls under the rubric of a peso phenomenon, is supported by recent empirical work of Goetzman and Jorion (1997). Using return data for a wide range of countries, these authors conclude that the high historical premium in the United States is unique, and they conjecture that it may be attributable to the fact that disastrous events affecting other financial markets (e.g. WWII for Japan, Germany, and other European countries) have largely bypassed the American economy.     

Predicting long-run risk factors of stock returns: Evidence from Australia

This study utilises the stock market data provided by the Australian Equity Database to analyse the long-run relationship between Australian stock returns and key macroeconomic variables over the period 1926–2017. To measure the diverse risk factors in the stock market, we examine the possible determinants in four main categories: real, financial, domestic and international. Our results reveal that historical stock returns are strongly connected to financial and international factors as compared to real and domestic factors. Both the 1973–1974 OPEC Oil Price Crisis and 2007–2008 Global Financial Crisis had dampening effects on stock returns. There is a positive association between the US and Australian stock markets in the long-run. These findings on stock market dynamics and their linkages with domestic and international macroeconomic policy changes in the long-run have important implications for traders and practitioners.     

OIL PRICE SHOCKS AND STOCK MARKET BOOMS IN AN OIL EXPORTING COUNTRY

This paper analyses the effects of oil price shocks on stock returns in Norway, an oil-exporting country, highlighting the transmission channels of oil prices for macroeconomic behaviour. To capture the interaction between the different variables, stock returns are incorporated into a structural VAR model. I find that following a 10% increase in oil prices, stock returns increase by 2.5%, after which the effect gradually dies out. The results are robust to different (linear and non-linear) transformations of oil prices. The effects on the other variables are more modest. However, all variables indicate that the Norwegian economy responds to higher oil prices by increasing aggregate wealth and demand. The results also emphasize the role of other shocks; monetary policy shocks in particular, as important driving forces behind stock price variability in the short term.     

Forecasting UK commercial real estate cycle phases with leading indicators: a probit approach

This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. Probit models are then estimated using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.     

A real business cycle model with tradable and non-tradable goods for the Spanish economy

Over the last years, the business cycles of the Spanish economy have been analyzed from different points of view. Under the paradigm of the real business cycles, the standard model has been extended in several dimensions. However, none of them have taken into account the fact that in this economy the presence of non-tradable goods is one of the largest in the world. When this feature is properly taken into account, the modeled real business cycle small open economy, calibrated for Spanish data, is able to explain several distinct stylized facts for this economy. In particular, it explains the larger than standard volatility of private consumption, and the different cyclical properties of inflation for non-tradable and tradable goods. Furthermore, the theoretical model is able to adequately explain some other cyclical properties of Spanish macroeconomic variables, both at the aggregate and sectoral levels.     

BUSINESS CYCLES IN SINGAPORE: STYLIZED FACTS FOR A SMALL OPEN ECONOMY

This paper sets out to discover the salient characteristics of economic fluctuations in the small open economy of Singapore. To this end, band‐pass filters and unobserved components models are first used to extract the cyclical components in macroeconomic variables. The extent to which domestic business cycles are influenced by foreign economic cycles with regards to their persistence, comovement and volatility properties are then assessed using time‐series statistics. The paper also documents how shocks originating from abroad are propagated to the broader economy. Although it is found that idiosyncratic features are present in Singapore's macroeconomic fluctuations, there are also stylized business cycle facts to be learnt about small open economies in general.     

Leading indicators of non-performing loans in Greece: the information content of macro-, micro- and bank-specific variables

We examine the information content of a unique set of macroeconomic, bank-specific, market and credit registry variables as regards their ability to forecast non-performing loans using a panel data set of nine Greek banks. We distinguish between business, consumer and mortgage loans and investigate their differences with respect to their optimal predictors. The quasi-AIM approach (Carson et al. in Int J Forecast 27:923–941, 2010) is utilized in order to take into account heterogeneity across banks and minimize estimation uncertainty. In addition, we calculate a number of forecasting measures in order to take into account the policy makers’ preferences. We find that market variables, specifically the supermarket sales, confidence indices for the services and construction sector and the business sentiment index represent good forecasting variables for most categories of NPLs. In addition, industrial production is the optimal predictor for consumer NPLs and imports for business NPLs. Finally, bank-specific variables represent top-performing leading indicators for business NPLs. Our results have significant implications for stress-testing credit risk in a top-down manner and for supervisory and macro-prudential policy design.     

Can oil prices help predict US stock market returns? Evidence using a dynamic model averaging (DMA) approach

Crude oil price behaviour has fluctuated wildly since 1973 which has a major impact on key macroeconomic variables. Although the relationship between stock market returns and oil price changes has been scrutinized excessively in the literature, the possibility of predicting future stock market returns using oil prices has attracted less attention. This paper investigates the ability of oil prices to predict S&P 500 price index returns with the use of other macroeconomic and financial variables. Including all the potential variables in a forecasting model may result in an over-fitted model. So instead, dynamic model averaging (DMA) and dynamic model selection (DMS) are applied to utilize their ability of allowing the best forecasting model to change over time while parameters are also allowed to change. The empirical evidence shows that applying the DMA/DMS approach leads to significant improvements in forecasting performance in comparison to other forecasting methodologies and the performance of these models are better when oil prices are included within predictors.     

Non linear and asymmetric linkages between real growth in the Euro area and global financial market conditions: New evidence

This paper deals with transition mechanisms through which financial market conditions affect real economic growth in the Euro area. The informational content of financial variables for predicting real economic growth is assessed, allowing for asymmetric responses to shocks. A nonlinear framework is developed based on a smooth transition model for which the effects of shocks can vary across business cycles when financial indicators modify both the endogenous and state variables. Global financial variables are shown to significantly affect real growth in the Euro area, particularly during periods of recession. Changes in stock market index and yield slope have asymmetric effects on real growth. In recessionary periods, the slope of the US yield curve does not have a significant impact on growth in the Euro area.     

Forecasting the aggregate stock market volatility in a data-rich world

ABSTRACT

In this article, we utilize the basic lasso and elastic net models to revisit the predictive performance of aggregate stock market volatility in a data-rich world. Motivated by the existing literature, we determine several candidate predictors that have 22 technical indicators and 14 macroeconomic and financial variables. Our out-of-sample results reveal several noteworthy findings. First, few macroeconomic and financial variables and most of technical indicators have superior performance relative to the benchmark model. Second, combination forecasts are able to significantly beat the benchmark and some signal predictors Third, the lasso and elastic models with all predictors can generate more accurate forecasts than the benchmark and some other predictors in both the statistical and economic sense. Fourth, the lasso and elastic models exhibit higher forecast accuracy during periods of expansions and recessions. Finally, our findings are robust to several tests, such as different forecasting windows, forecasting models, and forecasting evaluations.     

Pro-cyclical effect of sovereign rating changes on stock returns: a fact or factoid?

This article examines the effect of changes in sovereign credit ratings and their outlook on the stock market returns of European countries at different phases of business cycle. Using standard four-factor model, it records a significant average marginal effect of credit rating announcements on stock market returns. Both magnitude and significance of the effect vary with business cycle and across announcement types. However, we do not find evidence of pro-cyclical effect of sovereign rating and outlook changes on stock returns. Our results show that stock markets react more negatively to rating downgrades in recovery phases and more positively to rating upgrades in contractionary period. Both results are statistically significant and robust to various sensitivity tests.     

International macroeconomic dynamics: A factor vector autoregressive approach

In this paper international comovements among a set of key real and nominal macroeconomic variables in the US, UK, Canada, Japan and the Euro area have been investigated for the 1980–2005 period, using a factor vector autoregressive approach. We present evidence that comovements in macroeconomic variables do not concern only real activity, but are an important feature also of stock market returns, inflation rates, interest rates and, to a smaller extent, monetary aggregates. Both common sources of shocks and similar transmission mechanisms explain international comovements, with the only exception of Japan, where the idiosyncratic features seem to dominate. Finally, concerning the origin of global shocks, evidence of both global supply-side and demand-side disturbances is found.