Daily market news sentiment and stock prices

In recent years there has been a tremendous growth in readily available news related to traded assets in international financial markets. This financial news is now available through real-time online sources such as Internet news and social media sources. The increase in the availability of financial news and investor’s ease of access to it has a potentially significant impact on market stock price movement as these news items are swiftly transformed into investors sentiment which in turn drives prices. In this study, we use the Thomson Reuters News Analytics (TRNA) data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index constituents. We use these daily DJIA market sentiment scores to study the influence of financial news sentiment scores on the stock returns of these constituents using a multi-factor model. We augment the Fama–French three-factor model with the day’s sentiment score along with lagged scores to evaluate the additional effects of financial news sentiment on stock prices in the context of this model using Ordinary Least Square (OLS) and Quantile Regression (QR) to analyse the effect around the tail of the return distribution. We also conduct the analysis using the seven-day simple moving average (SMA) of the scores to account for news released on non-trading days. Our results suggest that even when market factors are taken into account, sentiment scores have a significant effect on Dow Jones constituent returns and that lagged daily sentiment scores are often significant, suggesting that information compounded in these scores is not immediately reflected in security prices and related return series. The results also indicate that the SMA measure does not have a significant effect on the returns. The analysis using Quantile Regression provides evidence that the news has more impact on left tail compared to the right tail of the returns.     

Googling Investor’s Sentiment: Powerful Measure in Conventional and Islamic MENA Financial Markets

ABSTRACT

The objective of this paper is to investigate whether investors' sentiment measured by the Internet search behavior constitutes a valid measure of investor’s sentiment on Islamic and conventional indexes of emerging and frontier financial markets in MENA countries. In fact, we examine the relation between googling investor’s sentiment and monthly Islamic and conventional index returns during the period 2004–2016. Using the Dynamic Conditional Correlation, the BEKK-GARCH and the wavelet coherence models, we confirm that googling investor’s sentiment is a perfect indicator of investor’s sentiment measure. Indeed, we find that this measure has the ability to reflect major events such as subprime financial crisis, oil crisis and Arab spring revolution affecting MENA Islamic and conventional index markets. Our finding indicates that investors can use googling investor’s sentiment as an indicator to predict returns and volatility of emerging and frontier markets since it reflects the behavior and emotions of investors in MENA financial markets.     

Asset pricing in an Islamic economy

ABSTRACT

We define an Islamic economy as one with borrowing restrictions, no leverage, and no risk-free asset. We derive a consumption-based asset pricing model for this economy under standard preferences. We demonstrate that news to consumption growth is the main driver of Islamic financial markets, but the degree of borrowing constraints also affects the pricing of Islamic assets. Using Saudi Arabian data, simulations show that our model does a good job in matching the observed equity premium as well as the volatility of the market return. Our model implies that the price-dividend ratio predicts dividend growth, and as a result that prices are driven mainly by cash-flow news rather than by discount rate news. Empirical tests show that our model is consistent with the data.     

An entropy-based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series

This article features an analysis of the relationship between the DOW JONES Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry Research Centre of the Asia Pacific). The recent growth in the availability of on-line financial news sources, such as internet news and social media sources provides instantaneous access to financial news. Various commercial agencies have started developing their own filtered financial news feeds which are used by investors and traders to support their algorithmic trading strategies. TRNA is one such data set. In this study, we use the TRNA data set to construct a series of daily sentiment scores for DJIA stock index component companies. We use these daily DJIA market sentiment scores to study the relationship between financial news sentiment scores and the stock prices of these companies using entropy measures. The entropy and mutual information (MI) statistics permit an analysis of the amount of information within the sentiment series, its relationship to the DJIA and an indication of how the relationship changes over time.     

The impact of news,oil prices,and global market developments on Russian financial markets1

This paper analyses the impact of news, oil prices, and international financial market developments on daily returns on Russian bond and stock markets. First, regarding returns, energy news affects returns, while news from the war in Chechnya is not significant. Market volatility does not appear to be sensitive to either type of news. Second, a significant effect of the growth in oil prices on Russian stock returns is detected. Third, the international influence on Russian financial markets depends upon the degree of financial liberalization. The higher the degree of financial liberalization, the stronger is the impact of US stock returns on Russian financial markets. In addition, banking reform and interest rate liberalization efforts seem to dictate the globalization of Russian stock markets, while it is the progress in liberalizing securities markets and non‐bank financial institutions that matters more for the globalization of Russian bond markets.     

What matters when? The impact of ECB communication on financial market expectations

This article analyses financial markets’ reaction to European Central Bank's (ECB) communication. We apply a novel indicator that quantifies the contents of the ECB's introductory statements and allows disentangling ECB statements on prices, the real and the monetary sector. We provide evidence that it matters what issue the ECB is speaking about: especially, the ECB's statements on price developments represent important news to financial markets. It also matters when the ECB affects markets: communication drives maturities above 4 months.     

Beauty contest,bounded rationality,and sentiment pricing dynamics

We present a dynamic asset pricing model that incorporates investor sentiment, bounded rationality and higher-order expectations to study how these factors affect asset pricing equilibrium. In the model, we utilize a two-period trading market and investors make decisions based on the heterogeneous expectations principle and the “sparsity-based bounded rational” sentiment. We find that bounded rationality results in mispricing and reduces it in next period. Investor sentiment produces more significant effects than private signals, optimistic investor sentiment increases hedging demand, thus causing prices to soar. Higher-order investors are more rational and attentive to the strategies of other participants rather than private signals. This model also derives the dampening effect of higher-order expectations to price volatility and the heterogeneity expectation depicts inconsistent investor behavior in financial markets. In the model, investors' expectations about future price is distorted by their sentiment and bounded rationality, so they obtain a biased mean from the signal extraction.     

Speculative trading in Chinese housing market: a panel regression method

ABSTRACT

The major Chinese cities experienced dramatic increases in their house prices in the recent years. This paper derives the fundamental value of the housing markets based on the personal disposable income of individual cities. By controlling macroeconomic variables and government intervention, we detect speculative trading based on fundamental value and historical price movements. Fundamentalists expect house prices to converge to the fundamental values while chartists hold a momentum trading expectation. Further differentiating the cities into tier-1 and non-tier-1, the non-tier-1 cities are found to be subject to a risk of plummeting arising from the interaction terms between the fundamentalists and chartists.     

News sentiment and overshooting of exchange rates

In a globalized world, the volume of international trade is based on both import and export prices, thereby making a country’s economy highly dependent on exchange rates. In order to study exchange rate movements, one frequently exploits the so-called Dornbusch overshooting model. However, the model is controversial from a theoretical point of view: it explains exchange rate movements by a number of fundamental variables but ignores how novel information in the form of news can enter the market. As a remedy, this article adjusts for information dissemination by performing a multivariate analysis to compare the classical overshooting model with an extended variant that includes news sentiment. Our results show that news sentiment has a substantial explanatory power of 11% of the exchange rate forecasting error variance. In addition, we also find statistical evidence that a shock in news sentiment may lead to overshooting.     

Feedback effects between credit ratings and financial markets

Credit rating agencies often make sharp adjustments in their pronouncements during times of stress in financial markets. These adjustments typically happen with a delay relative to shocks in market prices. Since prices convey information about what market participants are doing and thinking, it is likely that rating agencies take into account market prices when issuing their pronouncements.In order to understand the relationship between credit ratings and financial prices, we develop a model of debt roll-over in which rating agencies incorporate information publicly available in financial markets. We find that (1) rating agencies respond to market prices, i.e. nonfundamental price volatility can shift financing conditions from a low risk spread and high credit rating equilibrium to an equilibrium with high spread and low rating, and (2) rating agencies can anchor expectations about the equilibrium in financial markets, thus serving as an antidote to nonfundamental price volatility.     

The Role of Market Sentiment in Asset Allocations and Stock Returns

Abstract

The authors investigate the role of mutual fund flows in incorporating market sentiment into asset prices. They show that retail investors adjust their investments among mutual fund categories in response to changes in market sentiment. Consistent with sentiment-induced price pressure through fund flows, they further find that firms favored by mutual funds, such as large-cap, dividend payers, and firms with high institutional ownership are sensitive to market sentiment. The authors construct a pricing factor representing sentiment risk and find that the sentiment factor is significant in standard asset pricing models and robust to various sorting procedure.     

Is the corn futures market noisier? The impact of high frequency quoting

ABSTRACT

The paper pioneers research on high frequency (HF) quoting noise in electronically traded agricultural futures markets. HF quoting – quickly cancelling posted limit orders and replacing them with new ones – emerges as a strategy for liquidity-providing traders. HF quoting can generate noise in price quotes which adds uncertainty to order execution and impairs the informational value of bid and ask prices. It can also lead to the perception that markets cannot be trusted for commercial transactions. Using intraday Best Bid Offer data for 2008–2013 and wavelet-based measures of volatility, we investigate the excess variance and co-movement discrepancies in the bid and ask prices. We find excess HF quoting variance exists. It is the highest at 250-ms scale – 90% higher than the variance implied by a random walk – but declines quickly to 7% at the 32 s scale. But its economic magnitude is negligibly small. Bid and ask price co-movements show a low degree of discrepancy with average correlations at 0.67 at 250 ms and reaching 0.95 at 8 s. All measures indicate that HF quoting noise has declined through the period. Overall, HF quoting has not caused excess variance during the transition to electronic trading in the liquid corn futures market.     

Investor sentiment,variance risk premium and delta-hedged gains

Delta-hedged gains are supposed to be negative and represent a volatility risk premium. Using a sample of Standard & Poor 500 index options from 2006 to 2009, this study documents two anomalies that cannot be explained by the volatility risk premium. First, delta-hedged gains are more negative for out-of-money options than for at-the-money options. Second, delta-hedged gains are significantly positive during financial crisis period. We propose a behavioural explanation in which both option prices and stock prices are affected by investor’s sentiment, but pessimistic sentiment has a greater impact on stock market than option market. This asymmetric response to pessimistic mood in turn affects the relative expensiveness of option prices.     

Stock returns and mutual fund flows in the korean financial markets: a system approach

ABSTRACT

This paper investigates dynamic and causal relations between stock returns and mutual fund flows in Korea using a system method that utilizes information from the stock, bond, and money markets. For this purpose, we employ the Dynamic Seemingly Unrelated Regression, the Seemingly Unrelated Regression Error Correction Model, and two causality tests in a system method to account for cross-equation correlations among markets that have a close relationship with one another. Furthermore, we use the information in the variance-covariance matrix of residual to improve the efficiency of the statistical estimates. The empirical evidence from the system method indicates that fund flows do not respond to eliminate deviations from long-run equilibrium, and stock prices cause net fund flows in the Korean market, implying that investors move their money to the securities that yield higher returns to rebalance their investment portfolios in the short-run. Thus, our findings do not support the popular notion of mutual fund flows as the driving force behind rallies in the Korean financial markets.     

Financialization and commodity prices – an empirical analysis for coffee,cotton, wheat and oil

Commodity prices have crucial implications for developing countries. The question whether the financialization of commodity derivative markets has contributed to high and volatile commodity prices has been controversially debated. Building on limitations in the empirical literature, we estimate a multivariate Vector Autoregressive (VAR) model to assess the effect of different groups of financial investors (index investors and money managers) as well as fundamental and macroeconomic variables on the prices of coffee, cotton, wheat and oil. We find that, in contrast to index investors, money managers’ net long positions have a large statistically significant effect on commodity prices. This calls for policy interventions as commodity derivative markets may cease to perform their fundamental developmental roles.     

EMU-related news and financial markets in the Czech Republic,Hungary and Poland

We analyse the impact of news on five financial markets in the Czech Republic, Hungary and Poland using a newly constructed data set in a Generalized Autoregressive Conditional Heteroscedastic (GARCH) framework. Macroeconomic shocks (on Gross Domestic Product (GDP), inflation rate, current account and trade balance) are constructed as deviations from expected values. Economic and Monetary Union (EMU)-related political and fiscal news is captured as news dummies. Macroeconomic shocks significantly affect short-term interest rates and, to a lesser extent, other financial variables. Political and fiscal news has an impact on long-term bond yields and exchange rates. News displayed prominently in our media sources has a greater impact on financial markets than other news and, in addition, the sources of news themselves matter. We also discover asymmetric effects of news within markets. Finally, using a pooled GARCH model we find that macroeconomic shocks have the strongest impact on financial markets in Hungary, while political news has the largest influence in both Hungary and Poland.     

Foreign Direct Investment,Sectoral Effects and Economic Growth in Africa

Abstract

Many small, frontier equity markets in regions such as Africa and Eastern Europe have opened in recent years. As in other larger emerging markets, important issues for investors are the extent of financial integration with exchanges in other countries and, if some reasonable degree of integration is found, whether such markets still provide diversification opportunities. Here, we will examine a frequently used metric of integration by testing for the existence of common trends, or cointegration, in these frontier markets. While common stochastic trends are found, results show that coefficients on cointegrating vectors are at times negative, and reaction to deviations from the long-run trend are often slow, thus indicating that frontier markets are a good source of diversification opportunities despite a degree of integration.     

Macroeconomic expectations and time varying heterogeneity:evidence from individual survey data

ABSTRACT

The goal of this paper is to investigate forecast heterogeneity and time variability in the formation of expectations using disaggregated monthly survey data on macroeconomic indicators provided by Bloomberg from June 1998 to August 2017. We show that our panel of forecasters are not rational and are moderately heterogeneous and thus confirm that previously well-established results on asset prices hold for macroeconomic indicators. We propose a flexible hybrid forecast model defined at any time as a combination of the extrapolative, regressive, adaptive and interactive heuristics. Controlling for endogenous structural breaks, we find that experts adjust their forecast behaviour at any time with some inertia in extrapolative and adaptive profiles. Changes in the formation of expectations are triggered mostly by financial shocks, and uncertainty is dealt with by using complex processes in which the fundamentalist component overweighs chartist activity. Forecasters whose models combine different relevant rules and display high temporal flexibility provide the most accurate forecasts. Authorities can then stabilize the domestic markets by encouraging fundamentalists’ forecasts through increased transparency policy.     

The relationship between stock prices and exchange rates in South Africa and Nigeria: structural breaks analysis

The relationship between stock prices and exchange rates has continued to generate interest from both the academia and financial industry players for many years. This study conducts an empirical investigation into the relationship between stock prices and exchange rates for the two largest economies in Sub-Saharan Africa – South Africa and Nigeria. Our methodology accounts for structural breaks in the data and the long-run relationship between stock and foreign exchange markets. The results of multivariate causality tests with structural breaks showed that causality runs from exchange rates to domestic stock prices in Nigeria (flow channel) while in South Africa, no causality exists between domestic stock prices and exchange rates. The results also reveal that there is causality from the London stock market to both countries’ stock markets, thus showing that international stock markets are driving both the Nigerian and South African stock markets.     

Stochastic investor sentiment,crowdedness and deviation of asset prices from fundamentals

This study constructs a theoretical model to address how stochastic investor sentiment affects investor's crowdedness, and how stochastic investor sentiment and crowdedness affect asset prices. An asset pricing model incorporating stochastic investor sentiment and crowdedness is developed, which can provide efficient explanations for the deviations of asset prices from fundamentals and the maverick risk of investors. This model indicates that the optimistic (pessimistic) investor sentiment and the long (short) crowdedness caused by optimistic (pessimistic) sentimental investors can push asset price above (below) fundamental value. Also, the sentimental investors who are wrong and alone would take the maverick risk. Our results are consistent with the idea that investor sentiment and investor behavior matter for the asset prices and the deviations of asset prices from fundamentals.