Thomas Dimpfl

Financial market spillovers around the globe

This article investigates the transmission of return and volatility spillovers around the globe. It draws on index futures of three representative indices, namely the Dow Jones Euro Stoxx 50, the S&P 500 and the Nikkei 225. Devolatized returns and realized volatilities are modelled separately using a Structural Vector Autoregressive (SVAR) model, thereby accounting for the particular sequential time structure of the trading venues. Within this framework, we test hypotheses in the spirit of Granger causality tests, investigate the short-run dynamics in the three markets using Impulse Response (IR) functions, and identify leadership effects through variance decomposition. Our key results are as follows. We find weak and short-lived return spillovers, in particular from the USA to Japan. Volatility spillovers are more pronounced and persistent. The information from the home market is most important for both returns and volatilities; the contribution from foreign markets is less pronounced in the case of returns than in the case of volatility. Possible gains in terms of forecasting precision when applying our modelling strategy are illustrated by a forecast evaluation.

A Note on Cointegration of International Stock Market Indices

Cointegration has frequently been used in the financial econometrics literature to assess the degree of interdependence of financial markets. We show that if individual stock prices are generated by random walks with possibly contemporaneously correlated innovations, the resulting indices cannot be cointegrated as they are a combination of n random walks which itself is non-stationary by construction. This result holds if (as in factor models) an additional common global or local random walk is allowed for. There will, however, never be less than n random walk components, as otherwise company specific characteristics would be ruled out to affect the stock price permanently. To substantiate the theoretical propositions we simulate stock prices (allowing for heteroscedasticity, correlated innovations and common factors), construct indices and test whether these indices are cointegrated. We show that while heteroscedasticity alone is able to mislead cointegration tests, it is not sufficient to explain at the same time the empirically found high correlation between stock market indices. A common stochastic factor as well as correlated price innovations are necessary to reproduce the empirical characteristic features. We conclude that cointegration is not a suitable method to analyze stock market interdependence.

Labor income risk and households’ risky asset holdings

Purpose - Financial theory suggests that with increasing labor income risk, the reluctance of households to hold stocks increases. Therefore, this paper aims to investigate the determinants of a household’s decision on whether to invest in risky financial assets. Design/methodology/approach - Income risk is measured as the observed variation of household income over a five-year period. The authors use both the time and the cross-sectional dimension of the German socio-economic panel to control for unobserved heterogeneity. Findings - The authors find that indeed higher variation, i.e. higher income risk, reduces the propensity to invest in risky assets. However, when controlling for household heterogeneity, as well as subjective measures of a household’s financial situation (income satisfaction, worries about financial situation), the impact of observed labor income variation vanishes. It is therefore concluded that in particular the perception of investment risk and of the riskiness of the environment determines the investment decision to a great extent. Originality/value - The paper contributes to a better understanding of a household’s investment decision-making process. To the best of the authors’ knowledge, it is the first to fully exploit the panel structure of the data to control for unobserved heterogeneity which leads to novel conclusions with respect to the effect of labor income.

Bitcoin Market Microstructure

Bitcoin is traded on exchanges which use an open limit order book. This paper investigates the microstructure of various bitcoin markets with respect to liquidity and private information processing. The markets are found to be fairly liquid, providing liquidity at a stable rate throughout the 24 hours trading period. The spread itself as well as the proportion attributed to adverse selection costs are high suggesting that private information is an important aspect in the bid-ask spread.

Investor Pessimism and the German Stock Market: Exploring Google Search Queries

Abstract We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.

Knitting Daily Google Trends -- With an Application to Augur Cryptocurrency Returns

We evaluate the usefulness of Google search volume to predict returns and volatility of multiple cryptocurrencies. The analysis is based on a new algorithm which allows to construct mulit-annual, consistent time series of Google search volume indices (SVIs) on various frequencies. As cryptocurrencies are actively traded on a continuous basis and react very fast to new information, we conduct the analysis initially on a daily basis, lifting the data imposed restriction faced by previous research. In line with the literature on financial markets, we find that returns are not predictable while volatility is predictable to some extent. We discuss a number of reasons why the predictive power is poor. One aspect is the observational frequency which is therefore varied. The results of unpredictable cryptocurrency returns holds on higher (hourly) and lower (weekly) frequencies. Volatility, in contrast, is predictable on all frequencies and we document an increasing accuracy of the forecast when the sampling frequency is lowered.

A Storm But No Damage? A Two-Country Equity and Currency Market Perspective of Brexit

This paper analyses the impact of the June 23, 2016 Brexit vote on the British and Australian currency and equity markets. The two markets are particularly interesting as they were both strongly impacted by the Brexit vote, have cross-listed stocks and non-overlapping trading hours. Whilst the currency changes were immediate in both countries due to continuous 24-hour trading, the equity market effects occurred sequentially, led by the ASX and followed by the LSE. The analysis demonstrates that equity markets (in contrast to the currency markets) overreacted to the Brexit vote as the initial market reaction was fully corrected within five trading days. More importantly perhaps, the findings also indicate that non-synchronous trading can distort and delay price adjustments.

Realized Bitcoin Volatility

Bitcoin is a digital currency and designed to have typical functions of a currency such as being a medium of exchange, a unit of account and a store of value. Each of these functions is adversely affected by the volatility of the currency. If a currency exhibits extreme fluctuations, its usage as a currency is limited, in particular if the currency is not backed by any government as is the case for Bitcoin. By means of an in-depth analysis of Bitcoin realized volatility, we show that the volatility of Bitcoin prices is extreme (up to 30 times larger) compared to major currencies (US dollar, the euro and the yen). The positive volume - volatility relationship further suggests that the majority of trading is noise trading. Our findings imply that Bitcoin cannot function as a currency.

Price discovery in the markets for credit risk: a Markov switching approach

Abstract We examine price discovery in the Credit Default Swap and corporate bond market. Using a Markov switching framework enables us to analyze the dynamic behavior of the information shares during tranquil and crisis periods. The results show that price discovery takes place mostly on the CDS market. The importance of the CDS market even increases during the more volatile crisis periods. According to a cross sectional analysis liquidity is the main determinant of a market’s contribution to price discovery. During the crisis period, however, we also find a positive link between leverage and CDS market information shares. Overall the results indicate that price discovery measures and their determinants change during tranquil and crisis periods, which emphasizes the importance of more flexible frameworks, such as Markov switching models.

Inter-Quantile Ranges and Volatility of Financial Data

We propose to estimate the variance of a time series of financial returns through a quantile autoregressive model (QAR) and demonstrate that the return QAR model contains all information that is commonly captured in two separate equations for the mean and variance of a GARCH-type model. In particular, QAR allows to characterize the entire distribution of returns conditional on a positive or negative return of any given size. We show theoretically and in an empirical application that the inter-quantile range spanned by conditional quantile estimates identifies the asymmetric response of volatility to lagged returns, resulting in broader conditional densities for negative returns than for positive returns. Finally, we estimate the conditional variance based on the estimated conditional density and illustrate its accuracy with an evaluation of Value-at-Risk and variance forecasts.