Future Returns Research Articles

Functional classification and dynamic prediction of cumulative intraday returns in crude oil futures

Predicting the movement of crude oil futures is crucial for investors to identify opportunities and for the efficient functioning of financial markets. This paper applies functional classification and dynamic prediction (FCDP) to forecast the cumulative intraday returns of INE and Brent crude oil futures for every 5 min, to address the characteristics of high-frequency data and complex change patterns of crude oil futures market. The primary goal of FCDP is to classify trading days with the same volatility pattern employing probabilistic functional classification based on the artificial distinction between the daytime and nighttime trading hours, and then to generate forecasts using the classification results. The robustness test compares the forecasting results of FCDP with ARIMA, OLS and RW methods. According to the findings, FCDP outperforms other methods when it comes to making predictions concerning crude oil futures. Due to the FCDP's incorporation of the concept of dynamic updating, which is not reflected in conventional prediction methods, the prediction error gradually lowers as the amount of seen data increases. INE and Brent crude oil futures market trading patterns at night are more intricate than they are during the day. This study supports flexible trading strategy adjustments for both investors and policymakers.

Treasury option returns and models with unspanned risks

We document the phenomenon that average excess returns of out-of-the-money puts and calls on bond futures are negative, both unconditionally and conditionally on economic states. To explain these findings, we develop economically motivated restrictions in the context of a theory in which the pricing kernel is a general diffusion process with spanned and unspanned components. Our reconciliation is a framework that introduces market incompleteness and priced unspanned volatility risks, allowing for time-varying downside and upside futures risk premiums. The estimated model shows consistency with data on bond yields, yield volatilities, bond futures return volatilities, option prices, and option risk premiums.

Risk factors in the Indonesian stock market

This paper identifies the relevant risk factors that determine the cross-section of returns in the Indonesian stock market. We examine 152 factors using the Bayesian framework developed in Jensen et al. (2022). Our results show that size, value, quality, and profitability are the characteristics themes that explain future cross-sectional stock returns during the period 1991–2022. Momentum is not significant. We document differences in factor returns for stocks that adhere to Sharia law (i.e. Islamic finance principles). Value and size return patterns occur across all stocks, but significant posterior alphas for quality and profitability reliably exist only within non-Sharia stocks.

Breadth of Ownership and the Cross-Section of Corporate Bond Returns

Using breadth of corporate bond fund ownership to proxy for the combination of short-sale constraints and divergence of opinions in the corporate bond market, this paper investigates whether and to what extent Miller’s overpricing theory holds for corporate bonds. Consistent with the theory, we document a significant and positive relation between changes in breadth and the cross-section of future corporate bond returns. Because of the bounded upside of debt, the ability of changes in breadth to predict returns appears to be less pronounced for corporate bonds relative to stocks. Furthermore, this predictability is stronger among bonds with higher credit risk, indicating that the effect of short-sale constraints and divergence of opinions on bond mispricing tends to be larger for riskier bonds with more upside potential and, thus, more scope for overvaluation. This paper was accepted by Lukas Schmid, finance. Supplemental Material: The internet appendix and data are available at https://doi.org/10.1287/mnsc.2023.4950 .

From Shanghai to Wall Street: The Influence of Chinese News Sentiment on US Stocks

This study explores the influence of Chinese news sentiment on US stocks, focusing on the potential policy shift granting Chinese retail traders direct access to US markets. Analyzing the flow of information between Chinese news sentiment and global news sentiment using transfer entropy, the findings reveal a significant influence of Chinese news sentiment on global news sentiment. Moreover, the study identifies a predominant unidirectional flow of information from news sentiment to stock returns, with Chinese news sentiment having a more substantial impact on future returns of US stocks compared to global news sentiment. This suggests that if the proposed policy changes succeed, Chinese retail traders may rely on Chinese news sentiment, potentially leading to increased volatility in the US market. Policymakers and market participants should be aware of these implications to prepare for changes in the US stock market dynamics. Further research can provide deeper insights into the interplay between news sentiment, investor behavior, and market volatility.

Mood seasonality around the globe

This paper examines the existence of mood seasonality, documented by Hirshleifer et al. (2020, JFE) for the cross-section of US equity returns, in an international setting. First, we confirm the results of the original study. Next, we extend these findings to non-US markets and show that they are not sample-specific. A stock's relative historical seasonal returns are positively correlated with its relative future seasonal returns during similar or congruent mood periods and negatively related with its relative future seasonal returns during dissimilar or non-congruent mood periods. Moreover, both regression and portfolio analyses indicate that mood beta, the sensitivity of equity returns to aggregate investor mood, helps explain these mood seasonality effects.

Futures contract collateralization and its implications

Defining a futures return as the rate of change of futures prices, as done in many empirical studies, implicitly implies that a futures contract is fully collateralized. We adjust futures’ returns to explicitly account for the holding of minimum margin (collateral) and the return to this collateral. Collateralization adjustment affects the dynamic properties of returns and modifies the risk profile of futures contracts. In our empirical study, we document the effect of such adjustment under full and partial collateralization. The effect is minimal except when the futures prices and minimum margins are volatile. Our analysis calls for a review on the extent of diversification benefits offered by futures.

Life as debt, or debt to life? Water, finance and infrastructure

This paper explores the forms of debt that come into play as public water utilities are privatized and financialized. On the one hand, the financialization of water utilities sets in motion a politics of frantic municipal debt repayment. As infrastructures become financial assets, they also become vehicles for future financial returns. On the other hand, the financialization of water infrastructures often provokes a very different calculus of debt, articulated by people mobilized into protecting ‘their water’ from privatization – that of the human debt to water as life. Based on research conducted in Europe, particularly Italy, I show how water movements insist on a very different kind of value – an incalculable, that is to say transcendent value that derives from life’s indebtedness to water. I argue that water movements’ insistence on the human debt to water as life opens up powerful pathways for a critique of capitalism’s extraction of value from life, and of the financialization of value as such.

The profitability of lead–lag arbitrage at high frequency

Any lead–lag effect in an asset pair implies that future returns on the lagging asset have the potential to be predicted from past and present prices of the leader, thus creating statistical arbitrage opportunities. We utilize robust lead–lag indicators to uncover the origin of price discovery, and we propose an econometric model exploiting that effect with level 1 data of limit order books (LOBs). We also develop a high-frequency trading strategy based on the model predictions to capture arbitrage opportunities. The framework is then evaluated on six months of DAX 30 cross-listed stocks’ LOB data obtained from three European exchanges in 2013: Xetra, Chi-X, and BATS. We show that a high-frequency trader can profit from lead–lag relationships because of predictability, even when trading costs, latency, and execution-related risks are considered.

DEVELOPMENT OF EXPECTED MONETARY VALUE USING BINOMIAL STATE PRICE IN DETERMINING STOCK INVESTMENT DECISIONS

Stock investment is an investment opportunity. This stock investment carries relatively high risk and therefore requires additional analysis to minimize losses and maximize profits. Expected Monetary Value (EMV) is a simple modeling method for estimating the value of an investment that will provide the greatest future return. The expected monetary value (EMV) method involves multiplying the total value of each scenario by the probability of that scenario occurring. However this method has weaknesses in terms of how many cases occur what is the value of each case and what is the probability of each case occurring. Binomial State Price is a method commonly used to calculate stock options and real options but includes the step of modeling the value of an investment in many situations and opportunities that arise in the future. In this paper, our objective is to develop the EMV method with the binomial state pricing model to determine the investment that offers the most favorable payoff. In short, we can develop the expected monetary value (EMV) method and the binomial state pricing model. It was found that this model always recommends stocks which have high dividens.

FINANCIAL LITERACY & FINANCIAL PLANNING FOR RETIREMENT IN PAKISTAN: CASE OF ACADEMICIANS IN PUBLIC UNIVERSITIES OF KP

This study aimed to analysis financial literacy level and financial planning for retirement willingness of academicians in public universities of KP. Financial planning for the retirement and financial literacy has been a discussionable topic among researcher in the recent times because of their contribution in planning for peaceful life after retirement. In this paper researcher analyze financial planning for retirement and level of financial literacy academicians in public universities of KP, Pakistan. Quantitative research design was used and data was collected by using survey approach via convenient sampling. Questionnaire was distributed among sampled population of 275 different scale teachers. After analysis by using SPSS 25v findings elaborates positive and significant association among the study variables. The findings reveals that academicians who have enough financial knowledge are worried & steps forward for future financial strategies for life after retirement. They are looking for investment which will give them good & save returns in future. Results of study are helpful for financial institutions & government to divert focus toward financial literacy of individuals which helps them in making financial plans for retirement effectively. Faculty could use study's findings to develop curriculum that addresses impact of financial literacy on financial planning for retirement outcomes.

Emotion expression and cooperation under collective risks

The difficulties associated with solving Humanity's major global challenges have increasingly led world leaders and everyday citizens to publicly adopt strong emotional responses, with either mixed or unknown impacts on others' actions. Here, we present two experiments showing that non-verbal emotional expressions in group interactions play a critical role in determining how individuals behave when contributing to public goods entailing future and uncertain returns. Participants' investments were not only shaped by emotional expressions but also enhanced by anger when compared with joy. Our results suggestthat global coordination may benefit from interaction in which emotion expressions can be paramount.

Liquidity shocks and the negative premium of liquidity volatility around the world

We find that liquidity volatility negatively affects stock returns across international markets. This association remains consistent across various liquidity metrics and cannot be attributed to the influence of idiosyncratic volatility. Further analysis shows that the omitted liquidity decrease variable is the key driver of the negative premium of liquidity volatility. Considering the asymmetrical impact of liquidity decrease and increase on future stock returns, stocks displaying high liquidity volatility tend to experience significant liquidity decreases, which lead to lower average returns. Once the liquidity decrease is integrated into the pricing model, the negative return premium of liquidity volatility dissipates. Subsequent analysis underscores that the effect of liquidity decrease on returns is more pronounced in markets and periods characterized by diminished efficiency and heightened arbitrage costs.

How Market Intervention can Prevent Bubbles and Crashes: An Agent Based Modelling Approach

Using a previously validated agent-based model with fundamentalists and chartists, we investigate the usefulness and impact of direct market intervention. The policy maker diagnoses bubbles by forming an expectation of the future returns, then invests in burgeoning bubbles to develop a sufficient inventory of the risky asset in order to be able to sell adequate amounts of the overpriced asset later countercyclically to fight market exuberance. Preventing bubbles and crashes, this market intervention improves all analysed market return metrics, volatility, skewness, kurtosis and VaR, without affecting long-term growth. This increases the Sharpe ratios of noise traders and of fundamentalists by approximately 28% and 45% respectively. The results are robust even for substantially miscalibrated long-term expected returns.

Climate change news risk and corporate bond returns in China

By constructing a climate change news index based on the textual analysis of newspapers and estimations of the covariance of bond returns, this paper investigates whether climate change news risk is “priced in” in Chinese corporate bonds. We find that bonds with a higher climate change news beta are associated with lower future returns. Moreover, the low climate change news beta premium originates from the transition news beta. Additionally, the low climate change news beta premium is more obvious during times of heightened climate change news risk, which is consistent with the asset pricing theory of intertemporal hedging demand.

Climate change economics and the determinants of carbon emissions’ futures returns: A regime-driven ARDL model

This paper employs a Markov Switching Regime (MSR) ARDL model to investigate the determinants of future carbon emission returns, considering distinct regimes of mean and volatility. Utilizing daily data from January 16, 2009, to July 1, 2021, we analyze carbon emissions allowances and returns of major energy commodities. We identify two persistent regimes: high returns with low volatility and low returns with increased volatility. Fluctuations in oil prices significantly influence carbon emissions prices during specific states. Impulse Response Functions (IRFs) reveal short-term fluctuations in carbon emissions returns due to shocks in energy commodity returns, with varying effects between the regimes.

Do the rich gamble in the stock market? Low risk anomalies and wealthy households

Contrary to the theoretical principle that higher risk is compensated with higher expected return, the literature shows that low-risk stocks outperform high-risk stocks. Using a large-scale household dataset, we provide an explanation for this puzzling result that the anomalous negative risk-return relation is only confined to those stocks predominantly held by rich households, whereas the anomaly disappears for stocks held by non-rich households and institutional investors. We find that social status concern of rich households and the induced lottery preference explain wealthy investors’ demand for high-risk stocks, leading to overpricing and low future returns for such stocks.

Interest Rate Skewness and Biased Beliefs

ABSTRACTConditional skewness of Treasury yields is an important indicator of the risks to the macroeconomic outlook. Positive skewness signals upside risk to interest rates during periods of accommodative monetary policy and an upward‐sloping yield curve, and vice versa. Skewness has substantial predictive power for future bond excess returns, high‐frequency interest rate changes around Federal Open Market Committee announcements, and survey forecast errors for interest rates. The estimated expectational errors, or biases in beliefs, are quantitatively important for statistical bond risk premia. These findings are consistent with a heterogeneous‐beliefs model in which one of the agents is wrong about consumption growth.

Disclosure Similarity and Future Stock Return Comovement

Existing research often assumes that firms’ financial reporting choices influence their return comovement with other firms. We examine the validity of that assumption. First, we provide initial evidence suggesting that similarity in two firms’ disclosures not only predicts but influences future return comovement between those two firms. Second, we show that this predictive ability aggregates to the market level; disclosure similarity can be used to estimate more accurate forward-looking market betas. Taken together, these two results suggest that firms’ reporting decisions can influence their firms’ betas even in the absence of changes to capital structure or operations. This paper was accepted by Suraj Srinivasan, accounting. Funding: The authors are grateful for financial support from the Brigham Young University Marriott School of Business and the Fisher College of Business, Ohio State University. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4915 .

DNA sequencing at the picogram level to investigate life on Mars and Earth

DNA is an incontrovertible biosignature whose sequencing aids in species identification, genome functionality, and evolutionary relationships. To study life within the rocks of Earth and Mars, we demonstrate, in an ISO5 clean room, a procedure based on nanopore technology that correctly identifies organisms at picogram levels of DNA without amplification. Our study with E. coli and S. cerevisiae DNA samples showed that MinION sequencer (Oxford Nanopore Technologies) can unequivocally detect and characterise microbes with as little as 2 pg of input with just 50 active nanopores. This result is an excellent advancement in sensitivity, immediately applicable to investigating low biomass samples. This value is also at the level of possible background contamination associated with the reagents and the environment. Cultivation of natural and heat-treated Martian analogue (MMS-2) regolith samples, exposed to atmospheric water vapour or in increasing water concentrations, led to the extraction of 600–1000 pg of DNA from 500 mg of soil. Applying the low detectability technology enabled through MinION sequencer for a natural low biomass setting, we characterised the dry MMS-2 and found few soil-related organisms and airborne contaminants. The picogram detection level and the procedure presented here, may be of interest for the future Mars sample Return program, and the life research and planetary protection studies that will be implemented through the sample safety assessment.