The evolution of stock market efficiency in the US: a non-Bayesian time-varying model approach

A non-Bayesian time-varying model is developed by introducing the concept of the degree of market efficiency that varies over time. This model may be seen as a reflection of the idea that continuous technological progress alters the trading environment over time. With new methodologies and a new measure of the degree of market efficiency, we examine whether the US stock market evolves over time. In particular, a time-varying autoregressive (TV-AR) model is employed. Our main findings are: (i) the US stock market has evolved over time and the degree of market efficiency has cyclical fluctuations with a considerably long periodicity, from 30 to 40 years; and (ii) the US stock market has been efficient with the exception of four times in our sample period: during the long recession of 1873–1879; the recession of 1902–1904; the New Deal era; and the recession of 1957–1958 and soon after it. It is then shown that our results are partly consistent with the view of behavioural finance.     

Fiscal policy and stock market efficiency: An ARDL Bounds Testing approach

The aim of this paper is to investigate the semi-strong market efficiency hypothesis with respect to fiscal policy information, in the context of the Bucharest Stock Exchange. Taking into account that macroeconomic data series of emerging countries usually have a limited size and may be plagued by inconsistencies and structural breaks, this paper proposes an ARDL Bounds testing approach for studying the relationship between stock returns and lagged macroeconomic variables. Moreover, this approach allows us to examine both the long and short-term relationship between fiscal policy and stock returns. The results indicate that, in the long run, stock prices fully and efficiently reflect information on past fiscal policy. However, in the short run, the Romanian stock market reacts efficiently only to unexpected fiscal policy news, while anticipated fiscal policy information displays a significant lagged relationship with current stock returns. In addition, the results also showed that monetary policy information is not incorporated efficiently into stock prices, both in the short and the long run, and its impact on stock returns is larger than the one exerted by fiscal policy.     

Oil shocks and stock volatility: new evidence via a Bayesian,graph-based VAR approach

ABSTRACT

This article examines the temporal dependence between three oil shocks and realized volatility in the stock markets of G20 countries between 1994 and 2019. By applying a novel, graphical, Bayesian VAR (BGVAR) model, we calculate unidirectional linkages of oil and stock volatility with a full and segmented sample. The results suggest an overall causality from stock volatility to oil shocks. For certain short, specific periods, the causal direction reverses. Depending on the country and the source of an oil shock, the magnitude and type of the effect can vary considerably. Specific oil-market shocks occur most often in our full sample. In a time-varying structure, oil supply shocks’ impact on stock volatility is more prominent, and net oil-importing countries’ responses to these shocks are greater than for oil-exporting countries. In addition, we find that relationship dynamics can capture market information, such as global economic growth during the 2008–2009 financial crisis.     

An evolutionary approach to the examination of capital market efficiency

The paper investigates capital market efficiency on basis of an evolutionary model of asset pricing. Participants of capital markets are considered as organizations in the sense of Nelson and Winter (1982). Behavior of these organizations is described by routines. Routines are regular and predictable behavioral patterns, which determine how individuals gather information, form expectations, and order assets. The participants change their behavior by innovating new routines or by imitating routines of other participants.     

Macroeconomic shocks and stock market returns: the case of Korea

This study examines the effects of macroeconomic shocks on key macro variables, including stock market returns in Korea, using the structural vector autoregression (SVAR) model. We suggest a three-variable SVAR model incorporating inflation, output growth and stock returns. We adopt a nonzero z-ratio restriction for the long-run identifying assumption to allow for economically meaningful relationships among variables. While our results support the negative (positive) relation of demand (supply) shocks to stock returns, we also find that demand shocks influence stock market variance more significantly than supply shocks do. The sub-period analysis finds that global market fluctuations during the global financial crisis have relatively little effect on Korean stock market performance. We also examine a generalized five-variable model that includes the foreign exchange rate and interest rate, confirming the results from the three-variable case.     

Expectation formation in the foreign exchange market: a time-varying heterogeneity approach using survey data

Using Consensus Economics survey data on JPY/USD and GBP/USD exchange rate expectations for the 3- and 12-month horizons over the period November 1989–December 2012, we first show that expectations fail the conventional tests of unbiasedness and do not exhibit a learning process towards rationality. Our approach is consistent with the economically rational expectations theory (Feige and Pearce, 1976), which states that information costs and agents’ aversion to misestimating future exchange rates determine the optimal amounts of information on which they base their expectations. The time variability of the cost/aversion ratios justifies at the aggregate level a representation of expectations as a linear combination of the traditional extrapolative, adaptive and regressive processes augmented by a forward market component, whose parameters are allowed to change over time. This mixed expectation model with unstable heterogeneity is validated by our Kalman filter estimation results for the two currencies and the two horizons considered. Although the relative importance of the ‘fundamentalists’ (‘chartists’) is found to increase (decrease) with the time-horizon, chartist behaviour appears to dominate fundamentalist behaviour for both horizons. Central bank intervention is then effective in stabilizing the foreign exchange markets if it encourages fundamentalist activity.     

Asset price momentum and monetary policy: time-varying parameter estimation of Taylor Rules

In this article, we consider two new independent variables as inputs to the Taylor Rule. These are the equity and housing momentum variables and are introduced to investigate the potential usefulness of these two variables in guiding the Fed to lean against potential bubbles. Such effectiveness cannot adequately be evaluated if the Taylor Rule estimation follows the standard regression methodology that has been criticized in the literature to be econometrically incorrect. Using a time-varying parameter estimation methodology, we find that equity momentum as an input in the Taylor Rule does not contribute to changes in Fed Funds. However, the housing momentum plays an important role econometrically and can be a useful tool in setting Fed Funds rates.     

Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices

We propose a novel test to measure market efficiency while estimating the time-varying risk premiums of commodity futures, given that the prices are heteroscedastic. The risk premium is estimated using a state-space model with a Kalman filter modified for heteroscedasticity. Using 79 commodity futures traded on 16 exchanges during the period 2000–2014 and a Monte Carlo simulation, we demonstrate that the proposal produces robust results compared with conventional approaches. The global financial crisis has improved the efficiency and affected the trading volumes of commodity futures, but it has had no effect on the average or the volatility of risk premiums.     

Identifying the dynamic home market effect in a three-country model

The home market effect (HME) is a distinguishing feature of the “new” trade theory. It is customarily defined as disproportionate positive causation from expenditure to production. Recently it has been argued that this dynamic definition of the HME is problematic in a multi-country framework, because it neglects third country effects. In this paper, we show that more than one exogenous parameter change is needed to overturn the dynamic HME. An isolated increase in the size of the home country will unambiguously lead to an over-proportional domestic industry expansion. We then illustrate with some specific scenario what type of third country effects can “swamp” the HME.      

Technological forecasting at the Korean stock market: A dynamic competition analysis using Lotka–Volterra model

The purpose of this paper is to attempt to analyze the dynamic relationship between the Korean Stock Exchange (KSE) and Korean Securities Dealers Automated Quotation (KOSDAQ), two competing markets at the Korean stock market, in the viewpoint of technological forecasting of competition. The Lotka–Volterra system of equations, one well-known competitive diffusion models, is adopted to represent the competitive situations of the Korean stock market and it is estimated using daily empirical index data of KSE and KOSDAQ during 1997–2001. The results show that there existed a predator–prey relationships between two markets in which KSE acted as a prey for the time being after the emergence of KOSDAQ. This interaction was altered to symbiotic relationship and finally to pure competition relationship. We also perform an equilibrium analysis of the estimated Lotka–Volterra equations. As a result, we find that there is an equilibrium point in a dynamic sense. However, the equilibrium point could be unstable in the latest pure competition relationship.     

Currency exposures of the oil and natural gas stock prices in the Hushen-300 stock market： A nonlinear model approach

The paper embarks to investigate the relationship between currency risk and stock prices of the oil and natural gas exploitation industry in the value-weighted Hushen-300 stock market, by applying the standard Capital Asset Pricing Model （CAPM） and nonlinear exchange rate exposure model to the Renminbi against US dollar. The results show that the currency exposure does vary in the oil-gas stock prices throughout the bull and bear market. The study suggests that the models of the equilibrium exchange rate exposure must be extended to considering the nonlinear exchange rate exposure, the regime periods of bull and bear market, and the industry types that is sensitive to the currency exposures. The nonlinear dynamic relationship between the exchange rate changes and the Chinese energy stock prices throughout the bull and bear market add to the recent empirical evidences that foreign exchange markets and stock markets are closely correlated.     

Services inflation dynamics and persistence puzzle in Brazil: a time-varying parameter approach

This article analyses services inflation dynamics in Brazil, focusing on the Services Inflation Persistence Puzzle, for monthly data from January 2004 to February 2016. We apply a time-varying parameter (TVP) approach, via a Kalman filter, to estimate hybrid Phillips curves and compare inflation inertia for tradable goods and services inflation. Aggregate Brazilian Extended Consumer Price Index inflation serves as a benchmark. To justify the TVP analysis, parameter instability and structural change tests are implemented, based on OLS and Generalized Method of Moments (GMM) frameworks. The main results are as follows: (i) the TVP approach is relevant due to observed instability in some parameters estimated; (ii) inflation expectation coefficients are higher than lagged inflation in all calculations, but inflation inertia is not negligible at all; (iii) services inflation persistence ranges from 27 to 36%, whereas tradable goods inflation persistence ranges from 36 to 47%, providing evidence of the Services Inflation Persistence Puzzle in Brazil; (iv) from 2009 onwards an increase in one percentage point in real wages raises monthly services inflation rate by 0.02 to 0.03 percentage point; (v) there is evidence that cost-push pressures, due to wage increases in the service sector, are more important to explain services inflation than demand pressures from early 2009 to mid-2014.     

Volatility transmission between stock and foreign exchange markets: a connectedness analysis

ABSTRACT

This paper empirically investigates volatility transmission among stock and foreign exchange markets in seven major world economies during the period July 1988 to May 2018. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each market. To gain further insights, we examine the time-varying behaviour of net pair-wise directional connectedness during the financial turmoil periods experienced in the sample period Our results suggest that slightly more than half of the total variance of the forecast errors is explained by shocks across markets rather than by idiosyncratic shocks. Furthermore, we find that volatility connectedness varies over time, with a surge during periods of increasing economic and financial instability.     

Testing for weak-form efficiency of crude palm oil spot and future markets: new evidence from a GARCH unit root test with multiple structural breaks

There is a sizeable literature that tests for weak-form efficiency in commodity and energy spot and future prices. While many studies now allow for multiple structural breaks to address the criticism that conventional unit root tests have low power to reject the unit root null in the presence of structural change, the extant literature overlooks the fact that conventional unit root tests are biased in the presence of conditional heteroscedasticity. We apply a recently developed generalized autoregressive conditional heteroscedasticity (GARCH) unit root test with multiple structural breaks to crude palm oil spot and future prices and find much more evidence against weak-form efficiency than that found using tests that fail to allow for conditional heteroscedasticity. Our results point to the importance of allowing for heteroscedasticity when testing for efficiency in commodity and energy spot and future prices.     

Accounting and the formation of share market prices over time: a mathematical institutional economic analysis through simulation and experiment

This article develops a heterogeneous agents-based model to examine the emergent dynamic properties of share market price formation over time, with a view on financial market stability under alternative accounting regimes. In the model, individual heterogeneous investors interact with each other and with institutional devices which are an accounting system (related to the business firm) and a price system (related to the Share Exchange). These interactions provide mechanisms for transmission through which firm-specific (accounting signal) and market-driven (aggregate price) factors can act. A baseline simulation analysis assesses the financial market stability under three alternative accounting designs, namely two kinds of historical cost accounting regime and one kind of fair-value (mark-to-market) accounting regime. The former prove to better stabilize the financial system in terms of market volatility and exuberance in perfectly balanced conditions between speculative and fundamentalist beliefs and intentions. An evolutionary analysis is then developed by varying the relative degree of speculative attitudes between the two sides of the market. Historical cost accounting regimes further prove to make the financial system more resilient to speculative waves occurring at inter-individual level. Baseline findings are further corroborated through experimental analysis in twelve artificial financial systems. This mathematical institutional economic analysis has general implications for both designing accounting systems aimed at enhancing financial market stability and preventing procyclicality, and the study of accounting information process in the formation of share market prices over time.     

Empirical research on time-varying characteristics and efficiency of the Chinese economy and monetary policy: evidence from the MI-TVP-VAR model

Based on the general time-varying parameter vector autoregressive model and data mining technology, this study proposes a new extension mixed innovation time-varying parameter stochastic volatility vector autoregressive model and investigates time-varying characteristics and efficiencies of different shock effects on China’s monetary policy towards inflation and GDP. Using sample monthly data for 1979–2014, we utilize typical time points to illustrate the mechanisms between different economic variables via the Markov Chain Monte Carlo method and impulse response function. The empirical results show that the monetary transmission mechanism in China can be effective in the real economy, but with delay and efficiency leakage. The average delay and maximum efficiency can be measured through the MI model, which can capture accurate information of economic variables, effectively improving the precision of macroeconomic regulation and control. Meanwhile, the difference between the impacts of different channels is obvious; while the impact of interest rates is not significant, the impact of stock market is significant. The action mechanism between GDP and the inflation rate undergoes a gradual structural change, evidently displaying time-varying characteristics and a gradually weakening impact over time.     

Performance of moving average trading strategies over varying stock market conditions: the Finnish evidence

This article examines the profitability of dual moving average crossover (DMAC) trading strategies in the Finnish stock market over the period 1996 to 2012. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC trading portfolios of individual stocks to the performance of index trading strategies based on trading on an index that consists of the same stocks. The results show that their relative performance varies over time, whereas previous studies have documented outperformance of index trading strategies over trading strategies of stock portfolios. Moreover, the great majority of 3020 DMAC strategies examined in this article outperform the corresponding buy-and-hold (B and H) strategy for both trading targets (i.e., OMX Helsinki 25 index and individual stocks included in the index) in out-of-sample tests. In addition, the decomposition of the full-sample-period performance into separate bull- and bear-period performance shows clearly that the outperformance of DMAC strategies over B and H strategy is mostly attributable to their better performance during bearish periods.     

Nonlinear predictability of stock market returns: Evidence from nonparametric and threshold models

Recent empirical evidence suggests that stock market returns are predictable from a variety of financial and macroeconomic variables. However, with two exceptions this predictability is based upon a linear functional form. This paper extends this research by considering whether a nonlinear relationship exists between stock market returns and these conditioning variables, and whether this nonlinearity can be exploited for forecast improvements. General nonlinearities are examined using a nonparametric regression technique, which suggest possible threshold behaviour. This leads to estimation of a smooth-transition threshold type model, with the results indicating an improved in-sample performance and marginally superior out-of-sample forecast results.     

Exploring the interaction between stock price index and exchange rates: an asymmetric threshold approach

This article examines the impact of stock market news on the foreign exchange markets of USA, Canada and UK, employing an innovative extension of the asymmetric threshold model of Apergis and Miller (2006). Under this framework we can disentangle the reaction of foreign exchange market to bad or good news and small or large news of stock returns. Our comprehensive daily data-set spans the period from January 1990 to June 2014. Using a cointegration and error correction model, we document the existence of a causal relationship between stock market and foreign exchange markets. Most interestingly, our results derived from the asymmetric threshold model confirm that the relationship between stock and foreign exchange markets is sensitive to short-term good or bad news and short-term small or large news. Our findings entail significant implications for policymakers, governments, risk managers and international investors.     

The impact of trading floor closure on market efficiency: evidence from the Toronto Stock Exchange

On 23 April 1997, the Toronto Stock Exchange closed its trading floor, making it at that time the second-largest stock exchange in North America to choose a purely electronic trading environment for its equities. Exploiting this natural experiment, we find that the move to electronic trading resulted in a higher cost of immediacy (bid–ask spreads), increased information asymmetry and an overall deterioration of short-horizon return predictability from past order flows, reducing the efficiency of price discovery. Our results suggest that the human element plays an important role in order execution and complements automated electronic trading by improving the efficiency of incorporating new information into prices.