Do China's macro-financial factors determine the Shanghai crude oil futures market?

Existing studies have investigated the Chinese Shanghai crude oil futures (INE) from price efficiency, cross-futures transmission, etc., but neglected the potential links with China. This paper is committed to filling this gap by conducting an initial discussion from the perspective of macro-financial factors. Applying the dynamic model averaging (DMA) approach, we examine the time-varying importance of the six potential factors that drive the INE prices. The results based on the overall conditions of all determinants and based on individual predictors both support the crucial roles of some Chinese macro-financial factors. The pricing effects of these factors almost display upward features within 6 months since the INE establishment. Thereafter, it maintains an overall stable trend, though some abnormal turmoil is found after the COVID-19 outbreak. According to the multi-scale analysis, the importance of China's macro-financial factors mainly reveals the INE market at the low-frequency components. To confirm the robustness of the estimation and the uniqueness of such effects on the INE, we utilize an alternative forecast accuracy criterion to confirm stability, accommodate the DMA estimation on the WTI and Brent oil futures prices as comparisons, and discuss the frequency domain through another decomposition procedure. These all mirror our findings.     

Do oil futures prices predict stock returns?

This paper explores stock return predictability by exploiting the cross-section of oil futures prices. Motivated by the principal component analysis, we find the curvature factor of the oil futures curve predicts monthly stock returns: a 1% per month increase in the curvature factor predicts 0.4% per month decrease in stock market index return. This predictive pattern is prevailing in non-oil industry portfolios, but is absent for oil-related portfolios. The in- and out-of-sample predictive power of the curvature factor for non-oil stocks is robust and outperforms many other predictors, including oil spot prices. The predictive power of the curvature factor comes from its ability to forecast supply-side oil shocks, which only affect non-oil stocks and are hedged by oil-related stocks.     

What is the impact of wealth shocks on asset allocation?

I test the assumption of constant relative risk aversion using U.S. macroeconomic data and analyse the role of wealth shocks in generating transitory changes in asset portfolio composition. I show that the risky asset share exhibits cyclical behavior and it is significantly (and positively) affected by unexpected variation in wealth. Therefore, the empirical evidence suggests that risk aversion is counter-cyclical. I also find that the portfolio share of housing wealth falls when the agent is faced with a positive wealth shock, i.e. housing is a hedge against unfavorable wealth fluctuations. Finally, considering a variety of wealth definitions, the results show that: (i) wealth effects are stronger for direct holdings of risky assets than for indirect holdings, which highlights that investors do not typically trade some assets such as pension or mutual funds; (ii) although significant, wealth effects on asset allocation are mainly temporary as agents quickly rebalance the asset portfolio composition (i.e. there is weak evidence of inertia or slow adjustment in asset allocation); and (iii) changes in expected returns partially explain the variation in risky asset allocation.     

Do precious metals hedge crude oil volatility jumps?

In this study, we investigate the impacts of contemporaneous and lagged implied oil volatility (OVX) jumps on precious metals (gold, palladium, platinum, and silver) with the focus on hedging property of precious metals. Additionally, the impacts of OVX jumps on precious metals is investigated in returns and volatility. The results show that gold returns are relatively less responsive against contemporaneous and lagged OVX jumps, thus, gold acts as a weak hedge against OVX jumps. However, other metals (copper, palladium, platinum, and silver) do not serve as a hedge against contemporaneous OVX jumps. Nevertheless, these metals takeover the traditional hedging favourite ‘gold’ in the case of lagged OVX jumps and offers a strong hedge. It suggests that ignoring past information could severely undermine the investigation of OVX and the precious metal relationship. OVX jumps result in an increased volatility in precious metals, thereby indicating that all precious metals behave as a single asset class in terms of volatility transmissions. Moreover, gold is the contemporaneous metal of choice when risk perception is high or investors are averse to risk. Nevertheless, as information is diffused, other metals yield better performance as a hedge.     

How does the choice of Value-at-Risk estimator influence asset allocation decisions?

Considering the growing need for managing financial risk, Value-at-Risk (VaR) prediction and portfolio optimisation with a focus on VaR have taken up an important role in banking and finance. Motivated by recent results showing that the choice of VaR estimator does not crucially influence decision-making in certain practical applications (e.g. in investment rankings), this study analyses the important question of how asset allocation decisions are affected when alternative VaR estimation methodologies are used. Focusing on the most popular, successful and conceptually different conditional VaR estimation techniques (i.e. historical simulation, peak over threshold method and quantile regression) and the flexible portfolio model of Campbell et al. [J. Banking Finance. 2001, 25(9), 1789–1804], we show in an empirical example and in a simulation study that these methods tend to deliver similar asset weights. In other words, optimal portfolio allocations appear to be not very sensitive to the choice of VaR estimator. This finding, which is robust in a variety of distributional environments and pre-whitening settings, supports the notion that, depending on the specific application, simple standard methods (i.e. historical simulation) used by many commercial banks do not necessarily have to be replaced by more complex approaches (based on, e.g. extreme value theory).     

Forecasting volatility of crude oil futures using a GARCH–RNN hybrid approach

Volatility is an important element for various financial instruments owing to its ability to measure the risk and reward value of a given financial asset. Owing to its importance, forecasting volatility has become a critical task in financial forecasting. In this paper, we propose a suite of hybrid models for forecasting volatility of crude oil under different forecasting horizons. Specifically, we combine the parameters of generalized autoregressive conditional heteroscedasticity (GARCH) and Glosten–Jagannathan–Runkle (GJR)-GARCH with long short-term memory (LSTM) to create three new forecasting models named GARCH–LSTM, GJR-LSTM, and GARCH-GJRGARCH LSTM in order to forecast crude oil volatility of West Texas Intermediate on different forecasting horizons and compare their performance with the classical volatility forecasting models. Specifically, we compare the performances against existing methodologies of forecasting volatility such as GARCH and found that the proposed hybrid models improve upon the forecasting accuracy of Crude Oil: West Texas Intermediate under various forecasting horizons and perform better than GARCH and GJR-GARCH, with GG–LSTM performing the best of the three proposed models at 7-, 14-, and 21-day-ahead forecasts in terms of heteroscedasticity-adjusted mean square error and heteroscedasticity-adjusted mean absolute error, with significance testing conducted through the model confidence set showing that GG–LSTM is a strong contender for forecasting crude oil volatility under different forecasting regimes and rolling-window schemes. The contribution of the paper is that it enhances the forecasting ability of crude oil futures volatility, which is essential for trading, hedging, and purposes of arbitrage, and that the proposed model dwells upon existing literature and enhances the forecasting accuracy of crude oil volatility by fusing a neural network model with multiple econometric models.     

Do spot food commodity and oil prices predict futures prices?

Review of Quantitative Finance and Accounting - Futures prices reflect the price that both the buyer and the seller agree will be the price of a commodity upon delivery. Therefore, these prices...     

Volatility forecasting of crude oil futures market: Which structural change-based HAR models have better performance?

The paper focuses on the smooth and sharp structural changes in crude oil futures volatility and singles out the flexible Fourier form (FFF) and the modified ICSS algorithm to detect them, respectively, so as to explore whether different structural change-based HAR models exhibit significantly better performance for crude oil return volatility forecasting than traditional HAR-type models. The empirical results indicate that, on the one hand, crude oil market displays a strong evidence of breaks, and the incorporation of trigonometric terms can account for the structural changes in crude oil return volatility. On the other hand, the flexible Fourier form (FFF) based HAR-type models and the Structural Breakpoints (SB) based HAR-type models yield superior forecasting performance than traditional HAR-type models. Meanwhile, the forecasting results and economic performance of the former usually outperform the latter, particularly for the short- and medium-term forecasts.     

Which market dominates the price discovery in currency futures? The case of the Chicago Mercantile Exchange and the Intercontinental Exchange

This paper examines the relative contributions to the price discovery process of EUR/USD futures traded in the Chicago Mercantile Exchange (CME) and the Intercontinental Exchange (ICE). We find that the CME contributes 66.4%, 92.7%, and 97.3% to the price discovery process according to information share metrics suggested by Harris, McInish, and Wood (2002), Hasbrouck (1995), and Putninš (2013), respectively. The intraday information share metrics also show that the CME dominates the price discovery in most time periods. We attribute the CME's price discovery leadership to its higher trading activity, lower transaction costs, and higher volatility as compared to the ICE.     

Did crisis alter trading of two major oil futures markets?

The paper analyzes how traders in two major oil futures markets: New York Mercantile Exchange (NYMEX) and Intercontinental Exchange, reacted to the 2008 financial crisis, particularly whether they shifted their trading pattern and whether the relative information role of the two markets changed. Using trade-by-trade data, the paper analyzes several trading characteristics including trading volume, trade size, volatility, bid–ask spread, and relative information share. On average, NYMEX is characterized by greater volume, trade size and slightly greater spread. Before the crisis, NYMEX leads the process of price discovery, and volatility and trade size are significant factors explaining this leadership. However, following the financial crisis of 2008, the leadership role of NYMEX declines and trade size and volatility are no longer significant factors. Contrary to results of most equity market research, bid–ask spread is not a significant factor in information share and causality tests indicate that causality runs from spread to information share before the crisis but the opposite holds during the crisis period.     

What does futures market interest tell us about the macroeconomy and asset prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.     

Do capital buffers matter? Evidence from the stocks and flows of nonperforming loans

This paper investigates the determinants of the stocks and flows (both in- and outflows) of nonperforming loans (NPLs) by considering a bank-specific factor that is not adequately analysed in the literature, namely, bank capital buffers. Using unbalanced panel data with 6,087 bank-year observations for the 2006–2018 period and a two-step system generalised method of moments (GMM) estimation, we find that banks with higher levels of capital buffers (both in terms of Tier 1 and total capital) have fewer NPL stocks and generate fewer NPL inflows. When we control for the characteristics of the loan portfolio, real guarantees collected by the bank increase the stocks and flows of new, impaired loans, while personal guarantees favour the outflow of bad loans.     

Do different streams of capital flows affect asset prices differently?

This paper explores the impact of six types of gross capital flows (debt, equity, and banking gross inflows and outflows) on two dimensions: (1) extreme episodes of surges, stops, flights, and retrenchments, and (2) the probability of boom-busts in ASEAN-4 asset markets for the period 1993–2018. To this end, we first decompose gross capital inflows and outflows from Balance of Payments 5 and 6 and show that ASEAN-4 is largely dominated by portfolio flows and a relatively small magnitude of banking flows. However, when we link this decomposition to the extreme episodes, our findings show banking flows are volatile enough to cause greater occurrences of flight and retrenchment episodes while volatile debt flows tend to lead to surge and stop episodes. In the second part, we construct asset price index for ASEAN-4 that can detect boom-busts periods with a minimal noise-to-signal ratio eight quarters ahead. We use heteroscedasticity panel probit and ordinal generalized linear models to show that fundamental variables and banking inflows are statistically significant at increasing likelihood of boom-busts in asset markets. These two findings highlight that although largest percentage of capital flows come through debt and equity markets, the banking channel is of paramount importance in causing extreme episodes of flight and retrenchment as well as boom-busts of asset markets.     

Does technology-seeking OFDI improve the productivity of Chinese firms under the COVID-19 pandemic?

This paper empirically investigates the impact of technology-seeking outward foreign direct investment (OFDI) on firms' productivity under the influence of negative external shocks, taking as a sample the investment data of Chinese firms before and during COVID-19. The results show that technology-seeking OFDI improves productivity, but not under negative external shocks. The dampening effect of such shocks is more significant when the host country is a developed country and in firms with multiple branches. Technology-seeking OFDI particularly improves the productivity of research and development and processing firms, and (among the productivity measures tested) most prominently affects total factor productivity.     

The optimal asset allocation of the main types of pension funds: a unified framework

The existing literature deals with the optimal investment strategy of defined benefit (DB) or defined contribution (DC) pension plans. This article’s objective is to compare the optimal policies of different types of pension plans. This is done by first defining an original framework, which is based on the distinction between the nature of the guarantee—which can be internal or external—offered by or to a pension fund. This framework allows to establish links between optimization programs of DC, DB and targeted money purchase schemes. The case of an internal guarantee appears as a standard portfolio insurer’s problem. The second kind of guarantee, not analyzed in the literature yet with regard to the resulting optimal policy, is characterized by the existence of an option in the final wealth definition. Four funds are present in the internal guarantee optimal allocation: the speculative component, the preference independent guarantee- and contribution-hedge terms and the preference dependent state variable-hedge fund. The external guarantee program, solved with an original method using the principles of standard options theory, yields an optimal policy incorporating the delta of the option embodied in the final wealth definition. The conclusion is that the resulting optimal portfolio policy becomes riskier.

A leader of the world commodity futures markets in the making? The case of China's commodity futures

We use the daily data of 16 commodity futures contracts traded in China and corresponding foreign markets (the US, the UK, Japan, and Malaysia) to analyze the linkages between markets. Several findings are noteworthy. First, trading returns of foreign markets, such as the US, have significant impact on China's overnight (close-to-open) returns and vice-versa. Second, daytime (open-to-close) returns of many Chinese commodity futures contracts are not led by foreign daytime returns. Finally, the close-to-close returns analysis suggests that there are no significant lead-lag relationships between the Chinese and foreign markets. These results suggest that (1) the Chinese commodity futures markets are information-efficient, and (2) they are likely to be driven by local market dynamics occurring during the daytime trading session.     

Chinese jigsaw: Solving the equity market response to the COVID-19 crisis: Do alternative asset provide effective hedging performance?

Against COVID-19 risks, this paper examines the hedging performance of alternative assets including some financial assets and commodities futures for the Chinese stock market in a multi-scale setting. Dynamic conditional correlations and optimal hedge ratios of the Shanghai stock exchange with Bitcoin, Dow Jones Industrial Average, Gold, WTI, Bonds and VIX returns are estimated before and during the pandemic crisis. In the short-term, the use of wavelet decomposition shows that Bitcoin provides the best hedge to the Shanghai stock market. In the long-term, commodities dominate. Whereas WTI offers the highest hedging effectiveness, Gold ranks second by a slight margin. These results allow investors to choose the highest returns and protecting tail risk during the current sanitary crisis. Our findings suggest particularly more pronounced economic benefit of diversification including alternative financial assets while commodities futures serve as good hedge assets especially during unpredictable crisis like the current sanitary crisis relating to the covid-19.     

Would a Relaxation of the Exchange Rate Regime Increase the Independence of Chinese Monetary Policy? Evidence from China

Some policymakers and academic researchers suggest that relaxing the exchange rate regime will increase the independence of Chinese monetary policy. To test this argument, we estimate spot interest rate models with dummy variable sets and derive an economic interpretation. The empirical results suggest that a relaxation of the exchange rate regime increases the independence of market-based monetary policy; however, it weakens the independence of monetary policy for forecasting future normal events, and it also imposes an ambiguous impact on the independence of monetary policy for forecasting future rare events.     

Empirical evidence of the existence of speculative bubbles in the prices of stocks traded on the São Paulo Stock Exchange

Speculative price bubbles are defined as a significant deviation between an asset's intrinsic value and its market value and in this paper it refers to stock values. Literature about the theme has noted the existence of bubbles in various types of markets and their respective assets. A great deal of effort has been directed toward identifying bubbles in stock price indices. However, few research endeavors focus on assets as the unit of analysis. Studies about stocks in Brazil have identified the presence of bubbles in IBOVESPA (São Paulo Stock Exchange Index). Given this context and assuming that the speculative bubbles are present in the Brazilian stock market, this research is focused on the following question: Is there evidence of the existence of speculative bubbles in stock prices traded on the São Paulo Stock Exchange? Econometric tests were performed on twenty-seven stocks, based upon their positions each semester, for the period between the first semesters of 1990 until the first semester of 2010. The nominal values of the selected stocks were adjusted for inflation by the IPCA (Brazilian Consumer Price Index). In order to identify the presence of bubbles, we applied the Johansen non-cointegration test and/or the Granger non-causality test between the intrinsic value, dividends and interest on equity capital, and the market value (semester closing price) of the stocks. The primary findings reveal a presence of bubbles in twenty of the twenty-seven stocks, at a 5% significance level. Of the seven stocks not showing evidence of bubbles, six are financial institutions. In five stocks the tests reveal Granger causality stemming from the market value toward the intrinsic value. The study findings are consistent and contribute with previous research in the literature and, are useful for investors, financial institutions, academics, government agents, and traders.     

Do corporate managers believe in luck? Evidence of the Chinese zodiac effect

We study the responses of Chinese public firm chairpersons to their perceptions of bad luck pertaining to the Chinese zodiac year. We find that these perceptions of bad luck increase managers' sense of risk and lead them to increase their corporate cash holdings, even though the actual underlying risk remains unchanged. The effect is temporary and begins at the end of the quarter prior to the commencement of the zodiac year. When the zodiac year has passed, the level of risk perceived decreases and the bias disappears. The distortion between perceived and actual risk is significant, and the increase in cash holdings is both suboptimal and inefficient, in our view. Overall, these managerial reactions to the zodiac year are consistent with theories about belief in luck.