Macroeconomic News Research Articles

Month-end effect on Chinese stock returns: explanation of the liquidity hypothesis

ABSTRACT This study focuses on an anomaly in the intramonth pattern of stock returns and defines it as the ‘month-end effect’. The mean return for stocks is negative for the month-end days. Moreover, this study provides an economically plausible explanation for the month-end effect, namely, the liquidity hypothesis. It is suggested that the increase in the liquidity demand of commercial banks at the month-end days generally induces a fall in stock returns at the end of each month. Finally, additional evidence is provided that the window dressing hypothesis and macroeconomic news announcements hypothesis have limited explanation for the month-end effect.

Macroeconomic news and acquirer returns in M&As: The impact of investor alertness

We investigate the extent to which the scheduled release of macroeconomic indicators affects the acquirer's value in Mergers and Acquisitions (M&As). We find that M&As announced on days of the release of key macroeconomic indicators (i.e. indicator days) realize higher announcement period risk-adjusted returns compared to counterparts announced on non-indicator days. The positive wealth effect is due to the higher market attention on indicator days, which is particularly relevant for smaller M&As that are not usually exposed to significant investor scrutiny. The results hold after addressing self-selection bias concerns. We also find that firms announcing M&As on indicator days are more likely to “listen” to the market's feedback.

The determinants of price discovery on bitcoin markets

AbstractThis paper investigates whether market quality, uncertainty, investor sentiment and attention, and macroeconomic news affect bitcoin price discovery in spot and futures markets. Over the period December 2017–March 2019, we find significant time variation in the contribution to price discovery of the two markets. Increases in price discovery are mainly driven by relative trading costs and volume, and uncertainty to a lesser extent. Additionally, medium‐sized trades contain most information in terms of price discovery. Finally, higher news‐based bitcoin sentiment increases the informational role of the futures market, while attention and macroeconomic news have no impact on price discovery.

The effect of US macroeconomic news announcements on the Canadian stock market: Evidence using high-frequency data

We analyze the impact of US macroeconomic news announcements on the Canadian benchmark stock index return and volatility using high-frequency 5-min data. Our findings reveal that several US news releases exert a statistically significant influence on the Canadian stock market return and volatility. Moreover, we show that during the 2008 US recession, slightly more US news announcements exhibit significant impacts on the Canadian equity returns, with relatively pronounced effects. Overall, our results support previous findings by suggesting that US macroeconomic fundamentals form a linkage between Canadian and US financial markets.

The stock market’s reaction to macroeconomic news under ambiguity

We investigate the quality of the information that macroeconomic news conveys to the stock market about future business conditions. Our econometric approach is consistent with the decision problem of an investor concerned with ambiguity, which allows us to recover a theoretically motivated and empirically tractable proxy of time-varying ambiguity in the stock market. We find the stock market reacts more strongly to negative rather than positive real and monetary macroeconomic news, which is consistent with the predictions of the ambiguity literature. Further, the indirect effect of ambiguous news on investors’ loss of confidence in the signal can contribute up to 80% of the stock market’s reaction. Our findings offer a potential explanation for the weak results of the prior early literature using low-frequency data; they also offer an alternative explanation for the apparent counterintuitive results of the more recent literature using high-frequency data.

Macroeconomic Content of Characteristics-Based Asset Pricing Models: A Machine Learning Analysis

We explore whether the empirical success of seven characteristics-based asset pricing models can be explained by their ability to identify macroeconomic risks. We find that although the stochastic discount factors (SDFs) of some models are weakly related to macroeconomic shocks, the SDFs' non-market components are totally unrelated to them. The result also holds for macroeconomic news and real-time macroeconomic shocks. Our analysis involves a comprehensive set of more than 100 macroeconomic indicators and uses machine learning techniques to mitigate the overfitting problem caused by a large number of explanatory variables. Our paper illustrates how machine learning can be used for analyzing the explainability of one variable by many others.

The relationship between European Brent crude oil price development and US macroeconomy

Abnormal volatility has a damaging effect on the macroeconomy and is seen as a measure of risk in asset and commodity markets. This investigation had the aim to analyze the supposed transatlantic volatility inducing effect of the most prominent scheduled macroeconomic news announcements from the United States (US) on Brent Blend crude oil price intraday volatility over a period of seven years from 2012 to 2018. The objective was to generate a ranking list of scheduled US macroeconomic news that forecast high intraday volatility episodes at precise points in time. A total of 38 US news was analyzed using a data mining workflow. Data modeling was conducted using a simple ordinary least squares regression model and performed with programming language Python. A one hour window of rolling standard deviation based on one minute high-frequency closing prices were applied. As a result, 20 scheduled US macroeconomic news was successfully identified to significantly impact Brent crude oil price volatility. The model strongly supports the forecast of high price fluctuations and provides an opportunity for market players to adjust their risk management strategies right in time.

When is Bad News Good News? U.S. Monetary Policy, Macroeconomic News, and Financial Conditions in Emerging Markets

Rises in U.S. interest rates are often thought to generate adverse spillovers to emerging market economies (EMEs). We show that what appears to be bad news for EMEs might actually be good news, or at least not-so-bad news, depending on the source of the rise in U.S. interest rates. We present evidence that higher U.S. interest rates stemming from stronger U.S. growth generate only modest spillovers, while those stemming from a more hawkish Fed policy stance or inflationary pressures can lead to significant tightening of EME financial conditions. Our identification of the sources of U.S. rate changes is based on high-frequency moves in U.S. Treasury yields and stock prices around FOMC announcements and U.S. employment report releases. We interpret positive comovements of stocks and interest rates around these events as growth shocks and negative comovements as monetary shocks, and estimate the effect of these shocks on emerging market asset prices. For economies with greater macroeconomic vulnerabilities, the difference between the impact of monetary and growth shocks is magnified. In fact, for EMEs with very low levels of vulnerability, a growth-driven rise in U.S. interest rates may even ease financial conditions in some markets.

The Impact of Macroeconomic News on Bitcoin Returns

This paper examines the relationship between news coverage and Bitcoin returns. Previous studies have provided evidence to suggest that macroeconomic news affects stock returns, commodity prices, and interest rates. We construct a sentiment index based on news stories that follow the announcements of four macroeconomic indicators: GDP, unemployment, Consumer Price Index (CPI) and durable goods. By controlling for a number of potential biases we determine as to whether each of the series’ has a significant impact on Bitcoin returns. While an increase in positive news surrounding unemployment rates and durable goods would typically result in a corresponding increase in equity returns, we observe the opposite to be true in the case of Bitcoin. Increases in positive news after unemployment and durable goods announcements result in a decrease in Bitcoin returns. Conversely, an increase in the percentage of negative news surrounding these announcements is linked with an increase in Bitcoin returns. News relating to GDP and CPI are found not to have any statistically significant relationships with Bitcoin returns. Our results indicate that this developing cryptocurrency market is further maturing through interactions with macroeconomic news.

Monetary Policy and Asset Price Overshooting: A Rationale for the Wall/Main Street Disconnect

We analyze optimal monetary policy when asset prices influence aggregate demand with a lag. In this environment, when there is a current or anticipated output gap, the central bank optimally overshoots asset prices (i.e., significantly reduces discount rates to increase asset prices). Asset price overshooting leads to a temporary disconnect between the performance of financial markets and the real economy, but it also accelerates the recovery. A more intense overshooting policy weakens the relationship between inflation and the output gap (i.e., it flattens the Phillips curve). We quantify the policy-induced overshooting through risk-free rates in the Covid-19 recession and find that actual overshooting significantly exceeded the overshooting implied by a Taylor rule benchmark. Our calibrated model suggests this additional overshooting substantially accelerated the recovery. Finally, we show that policy-induced overshooting, along with monetary policy constraints, can shed light on the cyclical variation in the response of asset prices to macroeconomic news.

Do Monetary Policy Announcements Shift Household Expectations?

We use a decade of daily survey data from Gallup to study how monetary policy influences households’ beliefs about economic conditions. We first document that public confidence in the state of the economy reacts instantaneously to certain types of macroeconomic news. Next, we show that surprises to the federal funds target rate are among the news that have statistically significant and instantaneous effects on economic confidence. Specifically, we find that a surprise increase in the target rate robustly leads to an immediate decline in household confidence, at odds with previous findings that suggest consumers are largely inattentive to economic developments. Monetary policy news about forward guidance and asset purchases does not have similarly clear and robust immediate effects on household beliefs. We document heterogeneity across demographics in the responsiveness of macroeconomic beliefs to aggregate news, and we relate our findings to existing evidence on informational rigidities.

Macro News and Long-Run Volatility Expectations

I propose a new model-free method for estimating long-run changes in expected volatility using VIX futures contracts. The method is applied to measure the effect on stock market volatility of scheduled macroeconomic news announcements. I find that looking at long-run changes gives qualitatively different results compared to previous studies that only look at realized variance and the VIX. I further find that FOMC announcements on average resolve uncertainty, but only during times when policy uncertainty is higher than average. Real side macro announcements increase long-run volatility during times of low policy uncertainty, but the effect is reversed during times of high policy uncertainty.

Macroeconomic news, public communications, and foreign exchange jumps around U.S. and European financial crises

AbstractJumps in the Euro, Pound, and Yen, based on 5‐minute returns for the period 2004–2015, are shown to be state dependent between recessions and expansions in their response to macroeconomic news announcements and speeches by treasury and central bank senior officials. We find evidence of large jumps and cojumps response to the Federal Open Market Committee rate decision consistently over economic states. U.S. news is more important than EU news and jump magnitude and probability exhibit positive responses. Federal Reserve senior officials' speeches generate more jumps during the U.S. mortgage crisis and the EU sovereign debt recession. Although public communications of some European Central Bank and Bank of England senior officials cause fewer jumps, they produce significant cojumps of the three major currency markets.

Volatility term structures in commodity markets

AbstractIn this study, we comprehensively examine the volatility term structures in commodity markets. We model state‐dependent spillovers in principal components (PCs) of the volatility term structures of different commodities, as well as that of the equity market. We detect strong economic links and a substantial interconnectedness of the volatility term structures of commodities. Accounting for intra‐commodity‐market spillovers significantly improves out‐of‐sample forecasts of the components of the volatility term structure. Spillovers following macroeconomic news announcements account for a large proportion of this forecast power. There thus seems to be substantial information transmission between different commodity markets.

Are Cryptocurrencies Affected by Their Asset Class Movements or News Announcements?

This study analyses whether returns of top market capitalised cryptocurrencies are affected by their movements or major global macroeconomic news. Daily data are collected for the leading 10 cryptocurrencies from July 2017–December 2018. This study, (i) tests whether lagged variables can help predict other variables’ returns through a vector autoregression (VAR) model, (ii) analyses the response of cryptocurrencies to one standard deviation shock on Bitcoin’s returns, and (iii) decomposes factors that contribute to variance and tests for structural breaks. Findings show that most cryptocurrencies do not significantly affect other variances, except for Monero, which represented between 19% and 45% of the variances of five cryptocurrencies. Autoregressive (AR) models are superior in forecasting one day ahead return forecasts, compared to the VAR model, whereas the random walk (RW) model ranked last. Although remarkable structural breaks are observed via impulse response functions during December 2017–January 2018, no major news announcements were released on the same day the breaks occurred. Overall, this study suggests the need for high-frequency cryptocurrency prices to tackle the issue of the relationship between intraday news release and cryptocurrencies.

Do Jumps and Co-jumps Improve Volatility Forecasting of Oil and Currency Markets?

This paper aims at modeling and forecasting volatility in both oil and USD exchange rate markets using high frequency data. We test whether extreme co-move-ments (co-jumps) between these markets, as well as intraday unexpected news, help to improve volatility forecasting or not. Accordingly, we propose different extensions of Corsi (2009)’s model by including co-jumps and news. Our analysis provides two interesting findings. First, we find that both markets exhibit significant co-jumps driven by unexpected macroeconomic news. Second, we show that our model outperforms Corsi (2009)’s model and provides more accurate forecasts. In particular, while co-jumps constitute a key variable in forecasting oil price volatility, the unexpected news is relevant to forecasts of USD exchange rate volatility.

OPEC production decisions, macroeconomic news, and volatility in the Canadian currency and oil markets

We examine the simultaneous effect of OPEC production decisions and press releases, oil and gasoline inventory surprises, as well as US and Canadian macroeconomic news announcements on oil and Canadian dollar volatilities around US and European financial crises. We use a multivariate volatility model and implement an impulse response analysis to decompose the exogenous impacts into direct and indirect effects induced by volatility spillover. We find evidence of context-specific impacts and show that 67% of the total accumulated effect of OPEC decision to maintain production on oil volatility is induced by volatility spillover from the Canadian foreign exchange rate.

Connecting the dots: Market reactions to forecasts of policy rates and forward guidance provided by the Fed

AbstractThis paper compares market reactions to forecasts of the policy rate path by the Federal Open Market Committee (FOMC) participants with those to forward guidance from the FOMC post‐meeting statements. The forecasts are those by FOMC participants in the quarterly Summary of Economic Projections (SEP; the “dots”). We conduct the analysis during the period when the FOMC's policy rate was at the zero lower bound. We find that market expectations of the time to lift‐off from the zero lower bound are significantly affected in the expected direction by surprises in SEP dots and in forward guidance. We also find a significant impact of macroeconomic news on market participants' expectations of time to lift‐off. These results are consistent with forward guidance about policy rates and SEP forecasts each contributing to the public's understanding of future Federal Reserve monetary policy and with the conditionality of both forms of communication about future policy rates being understood. We also present evidence that market expectations concerning the time to lift‐off are influenced by the maximum time to lift‐off implied by forward guidance, the SEP, and the economic outlook. An appendix provides the FOMC's forward guidance after each meeting from January 2012 to September 2015 and our interpretation of the implied days to lift‐off.

Economic News Releases and Financial Markets in South Africa

We examine the impact of economic news releases on returns, volatility and jumps of the stock and foreign exchange markets of South Africa. We also assess the impact of macroeconomic determinants. The dataset range is fifteen years covering the period from January, 2000 to December, 2014. Results are robust to different sub-periods before and after the global financial crisis of 2008. Volatility is estimated with the use of the median realized variance estimator. Jumps are also detected. The impact of the announcements is assessed building using regression techniques. Returns, volatility and jumps of both stock and foreign exchange markets are significantly explained nationally by macroeconomic fundamentals and economic news releases.

Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets

This paper examines the liquidity dynamics around intraday price jumps in the Chinese stock index futures markets by identifying the specific intraday timing of the jumps. The contributions of the liquidity shocks and some pre-scheduled macroeconomic news announcements to intraday jumps are further explored. Three key measures, the number of trades, the open interest change, and the ratio of trading volume to open interest, are found to be the key drivers for intraday jumps. It is the largely increased trading demand, not the withdrawing of market participants, that causes price jumps. Positive jumps seem to bring more speculative trades in the futures market than negative jumps do. The pre-scheduled macro announcements fail to show their significance in driving the intraday jumps.