The influence of ETFs on the price discovery of gold, silver and oil

In this study we examine gold, silver and oil exchange traded funds (ETFs) and their relation to their respective futures instruments and underlying commodities by using intradaily data. We find that the gold, silver and oil ETFs closely track the performance of their underlying assets by using tracking error and pricing deviation metrics. It has been documented in the finance literature that price discovery occurs in the futures market. We test whether in recent times the existence of ETFs has changed the dominating role of the futures market in price discovery. We find that the availability of ETFs has shifted price discovery for gold and silver to the ETF market, while the oil market has price discovery occurring still predominantly in the futures market.     

Pricing behavior of exchange traded funds

We attempt to determine whether characteristics found to be effective indicators of individual stock price performance are effective indicators of exchange traded fund (ETF) price performance. Specifically, we test the performance of investing strategies based on separately categorizing ETFs into deciles according to size, trading volume, and momentum. When analyzing the entire sample, we find that the indicators can effectively signal differences in future performance. However, the indicators appear to be indirect proxies for the types of ETFs (broad-based, sector, or international). When we isolate each type of ETF, the indicators are not as effective. The indicators are not as useful for signaling unusual stock price performance of ETFs as they have been for individual stocks. We attribute the distinctly different results found here for ETFs to the unusual characteristics of ETFs that distinguish them from individual stocks. Investing strategies that rely on these indicators for selecting individual stocks may be indirectly driven by stock-specific fundamentals. However, fundamentals are not as meaningful for stock indexes (represented by ETFs) as for individual stocks.

Machine over Mind? Stock price clustering in the era of algorithmic trading

Given the rise of automated trading in the post-decimalization era, we examine time trends in price clustering for exchange traded funds (ETFs) and individual stocks during the post decimalization era. There is limited prior evidence on price clustering for portfolio securities such as ETFs. A striking feature of the evidence is the substantial reduction in clustering over the sample period for ETFs as well as for individual stocks. This decline occurs for trades of all sizes. We attribute the decline in clustering to the increasing prominence of algorithmic trading, which is immune to psychological biases.     

Enterprise systems in financial sector – an application in precious metal trading forecasting

The use of enterprise systems has become increasingly popular in the financial service industry. This paper discusses the applications of enterprise systems in the financial sectors and presents an application in gold price forecasting. We carefully examine the impacts of a few most widely assumed factors that have significant impact on the long-term gold price using statistical regression techniques. The analysis on our proposed linear regression mode indicates that the United States ultra scale of M2 money supply has been the most important catalyst for the rising price of gold, and the CRB index upward trend has also been the weighty factor for pushing up the gold price. In addition, the gold price has a low negative correlation with the Dow Jones Industrial Average, and low positive correlations with the US dollar index and the gold ETFs holdings.     

Volatility, trade size, and order imbalance in China and Japan exchange traded funds

In recent years there have been reports of excessive price volatility and value differences between prices of exchange traded funds (ETFs) and their underlying asset values. The objective of our study is to shed light on these facts by taking a closer look at the relationship between return volatility, trade size, and order imbalance for international ETFs. Even after controlling for order imbalance, volume as represented by number of trades in one of five trade size categories continues to have a significant and predominantly positive impact on volatility. Both trade size and order imbalance are important determinants of the Japan and China ETFs’ price volatility.     

Impact of leveraged ETF trading on the market quality of component stocks

We investigate the effect of leveraged ETF trading on the trading activity and market quality of their component stocks. The results show that both quoted and effective spreads of component stocks increase about 0.2–3.0 basis points after the inception of leveraged ETFs, while other liquidity measures do not show significant changes. The trading volume of component stocks is positively and significantly correlated with the trading volume of leveraged ETFs, but the volatility of component stocks is not affected by ETF trading either at the daily level or during the last hour of trading. In addition, the volatility of component stocks decreases slightly after ETF inception. These findings do not support the previous claim that the trading of leveraged ETFs increases price volatility of component stocks.     

The impact of security concentration on adverse selection costs and liquidity: an examination of exchange traded funds

We examine the determinants of liquidity and adverse selection costs in a sample of basket securities. Using Exchange Traded Funds (ETFs), we find evidence that adverse selection costs are decreasing in the number of equities held in the underlying portfolio, but adverse selection costs do not increase as the concentration among the securities increases. We find no evidence that industry concentration increases basket security adverse selection costs or reduces liquidity. We also document significantly lower levels of adverse selection costs in ETFs versus a matched sample of equities. In addition, ETFs have quoted dollar depth that is 35 times larger than a matched sample of equities, but ETFs also have higher effective and quoted spreads. However, when considering spreads and depth in a single metric, ETFs have significantly higher levels of liquidity.     

Bid-ask dynamic pricing in financial markets with transaction costs and liquidity risk

According to the classic no arbitrage theory of asset pricing, in a frictionless market a No Free Lunch dynamic price process associated with any essentially bounded asset is a martingale under an equivalent probability measure. However, real financial markets are not frictionless. We introduce an axiomatic approach of Time Consistent Pricing Procedure (TCPP), in a model free setting, to assign to every financial position a dynamic ask (resp. bid) price process. Taking into account both transaction costs and liquidity risk this leads to the convexity (resp. concavity) of the ask (resp. bid) price. We prove that the No Free Lunch condition for a TCPP is equivalent to the existence of an equivalent probability measure R that transforms a process between the bid price process and the ask price process of every financial instrument into a martingale. Furthermore we prove that the ask (resp. bid) price process associated with every financial instrument is then a R super-martingale (resp. R sub-martingale) which has a càdlàg version.     

Inter-market competition for exchange traded funds

We examine how the different mix of informed and liquidity trading in the market for ETFs affects the nature of inter-market competition. We find that both the characteristics of the securities and the structures of the competing markets jointly determine the nature of inter-market competition. Given the superior execution quality on the ECNs and the low adverse selection costs in the ETF market, anonymous market such as the ECNs, attract both liquidity and informed traders. We also find that markets compete in a subset of ETFs. In addition, we find that quotebased competition is prevalent in the market for ETFs.     

How do stock price indices absorb the COVID-19 pandemic shocks?

To assess the resiliency of stock price indices during the COVID-19 crisis, this study provides a distinctive perspective; that is, we evaluate the ability of stock price indices to absorb COVID-19 shocks. We construct the measures of absorptive intensity and duration to identify a stock price’s absorptive capacity. We then employ the Granger causality test and a topology network approach to investigate the interactions of absorptivity among stock price indices. Our results show that stock price absorptivity varies over time and across countries and industries. The US and the Brazil stock indices have relatively high absorptive intensity while short duration. The health care industry shows distinctive trend in absorptive intensity from the other industries. The intensity of the non-cyclical industries such as utilities and consumer staples is high, while the cyclical industries such as banking, real estate, and energy have lower absorptive intensity. Moreover, the utilities, consumer staples, and financials industries are the main resiliency transmitters.     

Investor sentiment and country exchange traded funds: Does economic freedom matter?

Using unbalanced panel data of 27 iShares MSCI country-specific exchange traded funds (ETFs) over the period 1996–2014, this paper applies quantile regression to examine the impacts of global, foreign, and U.S. investor sentiments on the returns of the ETFs traded in the U.S. markets. We further investigate whether a country’s economic freedom affects the relationship between investor sentiments and ETF returns. We find that ETF returns are strongly determined by investor sentiments and the ETF expense ratio. The quantile regression approach reveals that high-return ETFs are positively sensitive to changes in global sentiment (measured by market turnover, VIX, U.S. federal funds rate), foreign sentiment (measured by current account balance, inflation, market turnover, public debt), U.S. sentiment, currency exchange ratio, and expense ratio, while negatively influenced by economic freedom and Asian proxy. The effects of VIX and foreign inflation are a reversal; that is, returns from lower (higher) quantiles have a negative (positive) relation with VIX and foreign inflation. Not all components of economic freedom affect returns equally.     

The dynamic connectedness and hedging opportunities of implied and realized volatility: Evidence from clean energy ETFs

This paper aims to examine dynamic connectedness and hedging opportunities between the realized volatilities of clean energy ETFs and energy implied volatilities through Time-Varying Parameter Vector Autoregression Model (TVP-VAR) and Asymmetric Dynamic Conditional Correlation (ADCC) GARCH models. TVP-VAR analysis results show that dynamic connectedness increases during turbulence periods. We also determine that clean energy ETFs such as PBW, QCLN, SMOG, and TAN are net volatility transmitters. Surprisingly, OVX is a net volatility receiver, especially with the developments after the Paris Agreement in 2016.As a result of the ADCC GARCH analysis, we determine that the conditional correlation between clean energy ETFs and implied volatility ETFs is asymmetric, and negative information shocks increase the conditional correlation. Although OVX is a cheap alternative for hedging long position risks in clean energy ETFs, VXXLE is more effective than OVX in terms of hedging effectiveness. These findings provide insight for individual and institutional investors, and portfolio managers on how negative and positive shocks change the conditional correlation between assets at different levels.     

Independent component analysis for realized volatility: Analysis of the stock market crash of 2008

This paper investigates the factors that drove the U.S. equity market returns from 2007 to early 2010. The period was highlighted by volatile energy and commodity prices, the collapse of insurance and banking firms, extreme implied volatility and a subsequent rally in the overall market. To extract the driving factors, we decompose the returns of the S&P500 sector ETFs into statistically independent signals using independent component analysis. We find that the generated factors have interesting financial interpretations and are consistent with the major economic themes of the period. We find that there are two sets of general market betas during the period along with a dominant factor for energy and materials sector. In addition, we find that the EGARCH model which accommodates asymmetric responses between returns and volatility can plausibly fit the high levels of variance during the crash. Finally, estimated correlations dropped when commodity prices moved higher, but then spiked when the S&P500 crashed in late 2008.     

Revisiting the roles of gold: Does gold ETF matter?

This study investigates whether the role of gold changes due to the introduction of gold exchange-traded funds (ETFs) using sample data of seven countries in which physically-backed gold ETFs have been issued. The results show that the traditional roles of gold do change after the introduction of gold ETFs, particularly in the corresponding stock markets. The functions of hedge and safe haven provided by gold wear off during the post-ETF period in stock markets. In currency markets, however, gold still serves as a hedge and safe haven asset, and such effects become stronger during the post-ETF period. Moreover, gold ETFs play a role of relative strong safe haven than the physical gold does while the leading (lagged) stock returns extremely decline. Like the purposes of using physical gold assets, gold ETFs also provide hedge and safe haven effects to the exchange rate risks. Therefore, we might confirm that physical gold could be largely replaced by gold ETFs and investors could utilize gold ETFs to avoid potential risks in financial markets.     

Location of trade,return comovements,and diversification benefits: Evidence from Asian country ETFs

Using data from the Asian country ETFs and their MSCI indices, this paper examines whether trading location affects return comovements and diversification benefits. Our empirical results show that the magnitude of return comovements for the Asian country ETFs is higher than the corresponding MSCI indices. Moreover, our empirical findings indicate that the factors, including investor sentiment, market conditions, and economic fundamentals of the U.S. market, have greater effects on the return comovements for the Asian country ETFs than their underlying MSCI indices. Finally, the evidence presents a higher diversification benefit for the Asian MSCI indices than the Asian country ETFs.     

Multifrequency jump-diffusions: An equilibrium approach

This paper proposes that equilibrium valuation is a powerful method to generate endogenous jumps in asset prices. We specify an economy with continuous consumption and dividend paths, in which endogenous price jumps originate from the market impact of regime-switches in the drifts and volatilities of fundamentals. We parsimoniously incorporate regimes of heterogeneous durations and verify that the persistence of a shock endogenously increases the magnitude of the induced price jump. As the number of frequencies driving fundamentals goes to infinity, the price process converges to a novel stochastic process, which we call a multifractal jump-diffusion.     

Variance trading and market price of variance risk

This paper develops a new approach for variance trading. We show that the discretely-sampled realized variance can be robustly replicated under very general conditions, including when the price can jump. The replication strategy specifies the exact timing for rebalancing in the underlying. The deviations from the optimal schedule can lead to surprisingly large hedging errors. In the empirical application, we synthesize the prices of the variance contract on S&P 500 index over the period from 01/1990 to 12/2009. We find that the market variance risk is priced, its risk premium is negative and economically very large. The variance risk premium cannot be explained by the known risk factors and option returns.     

A model of information diffusion with asymmetry and confidence effects in financial markets

We present a model of multi-period continuous information diffusion in financial markets. We show that price and trading volume exhibit asymmetric term structures to information flow, where the diffusion rate accelerates more slowly at short horizons than it decelerates at long horizons. Bounded rationality is modelled by an endogenous trader confidence index which declines as stock price information becomes noisier, where lower confidence translates into lower trading volume and slower price accretion. Information diffusion slows and asymmetries are accentuated as traders lose confidence in information accuracy. Our empirical findings support the model's predictions of asymmetric momentum patterns and confidence effects.     

Testing the Markov property with high frequency data

This paper develops a framework to nonparametrically test whether discrete-valued irregularly spaced financial transactions data follow a Markov process. For that purpose, we consider a specific optional sampling in which a continuous-time Markov process is observed only when it crosses some discrete level. This framework is convenient for it accommodates the irregular spacing that characterizes transactions data. Under such an observation rule, the current price duration is independent of a previous price duration given the previous price realization. A simple nonparametric test then follows by examining whether this conditional independence property holds. Monte Carlo simulations suggest that the asymptotic test has huge size distortions, though a bootstrap-based variant entails reasonable size and power properties in finite samples. As for an empirical illustration, we investigate whether bid–ask spreads follow Markov processes using transactions data from the New York Stock Exchange. The motivation lies on the fact that asymmetric information models of market microstructures predict that the Markov property does not hold for the bid–ask spread. We robustly reject the Markov assumption for two out of the five stocks under scrutiny. Finally, it is reassuring that our results are consistent with two alternative measures of asymmetric information.     

A Gaussian approximation scheme for computation of option prices in stochastic volatility models

We consider European options on a price process that follows the log-linear stochastic volatility model. Two stochastic integrals in the option pricing formula are costly to compute. We derive a central limit theorem to approximate them. At parameter settings appropriate to foreign exchange data our formulas improve computation speed by a factor of 1000 over brute force Monte Carlo making MCMC statistical methods practicable. We provide estimates of model parameters from daily data on the Swiss Franc to Euro and Japanese Yen to Euro over the period 1999–2002.