Risk-averse Investors Research Articles

A novel measure of sleep based on Google: the case for financial markets

ABSTRACT We address in this study the issue of how to proxy sleep and explore sleep’s significance for financial markets. We employ daily Google search activity on sleepiness terms (e.g. sleep deprivation) to develop an index and find that a one-day lagged sleepiness index is related negatively to US stock market returns. When investors lack sleep, stock market returns are relatively low. This pattern could be explained by sleep deprivation causing an increased level of investor anxiety and risk aversion. We find that this relation is most pronounced on days with high uncertainty in the market. Sleep is negatively related to stock market returns even after controlling for sentiment. Overall, our results highlight the application of Google Trend in a new field showing that investors’ sleep patterns influence their investment decisions.

A Competitive Search Theory of Asset Pricing

We develop an asset-pricing model with heterogeneous investors and search frictions. Trade is intermediated by risk-neutral dealers subject to capacity constraints. Risk-averse investors can direct their search towards dealers based on price and execution speed. Order flows affect the risk premium, volatility, and equilibrium interest rate. We propose a new solution method to characterize the equilibrium analytically. We assess the quantitative implications of the model in response to a large adverse shock. Consistent with the empirical evidence from the COVID-19 crisis, we find an increase in the risk premium and market illiquidity, and a decline in interest rates.

Hedge effectiveness of put replication, gold, and oil on ASEAN-5 equities

The previous studies have shown that capital market integration has increased in the ASEAN-5, implying that investors making investment diversification across ASEAN capital markets could only earn limited diversification advantages. To diversify their portfolios, equity investors must find other assets. The main focus of this research is to analyze the effectiveness of put replication, gold, and oil on hedge equities in the ASEAN-5 (Indonesia, Malaysia, Singapore, Thailand, and the Philippines). Protective put strategy, DCC-GARCH, and Markowitz optimization are used to measure hedge effectiveness, risk-adjusted-performance such as Sharpe ratio, drawdown, and Omega ratio. The result reveals that gold is a cheaper hedge than oil and oil-hedged strategy is more expensive in ASEAN-5 compared to oil exporting nations. Also, investors with big exposure to the oil-related portfolio should diversify to Philippine equity. From hedging effectiveness and risk-adjusted-performance perspectives, oil is less attractive than money market instruments and gold. This study also implies that risk-averse investors should prefer to put replication or guaranteed financial products compared to commodities-hedged strategy.

Modeling the Time-Varying Dynamic Term Structure of Interest Rates

We propose a new dynamic Nelson--Siegel yield curve model, in which the slope and curvature factor loadings are governed by two time-varying factor-specific decay parameters, and the factor shock variance-covariance (SV) follows a stochastic inverse Wishart process. The importance of incorporating the ensemble of the time-varying factor loadings and SV are demonstrated by comparing the proposed model with simpler specifications in terms of statistical and economic criteria. For the statistical evaluation, we examine the out-of-sample yield curve density forecasting performance. The economic value of the model is measured by the utility gain from the bond portfolio optimization of a Bayesian risk-averse investor. According to our out-of-sample experiment using U.S. monthly yield curve data, the time-varying factor loadings and stochastic variance-covariance accommodate gradual structural changes in the yield curve dynamics around an unconventional monetary policy period, thus improving the predictive accuracy and utility gain.

SPAC IPO waves

We examine the wave pattern of U.S. SPAC IPOs using a hand-collected data set of the entire SPAC population since their emergence in 2003. We find that both the SPAC volume and SPAC share of total IPOs are negatively related to market-wide uncertainty (VIX) and time-varying risk aversion (variance risk premium). We attribute our findings to risk-averse investors’ reluctancy to invest in opaque securities. In response, the SPAC sponsor can credibly signal the issue’s quality by increasing their “skin in the game” through the purchase of additional warrants.

Information Design in Financial Markets

We study the optimal disclosure policy of a firm that wishes to maximize its expected stock price in the classic setting in which its stock is traded by risk-averse investors and noise traders. The optimal policy is imprecise and leads to skewed posterior beliefs. This policy subjects short positions to tail risk, causing investors to demand a large increase in price to absorb noise-trader purchases and leading to overvaluation. Despite providing purely firm-specific information, this policy impacts the firm's expected returns. We further show the firm can inflate its price even when restricted to simple policies that withhold news lying above or below a threshold.

Convergence of utility indifference prices to the superreplication price in a multiple‐priors framework

AbstractThis paper formulates a utility indifference pricing model for investors trading in a discrete time financial market under nondominated model uncertainty. Investor preferences are described by possibly random utility functions defined on the positive axis. We prove that when the investors's absolute risk aversion tends to infinity, the multiple‐priors utility indifference prices of a contingent claim converge to its multiple‐priors superreplication price. We also revisit the notion of certainty equivalent for multiple‐priors and establish its relation with risk aversion.

Speculative bubbles under supply constraints, background risk and investment fraud in the art market

We examine the unexplored effects on art markets of artist death (asset supply constraints), collectors' wealth (background risk) and forgery risk (risk of investment fraud), under short-sale constraints and risk aversion. Speculative bubbles emerge and have the form of an option strangle (a put option and a call option), in which strike prices are affected by art supply constraints and the association of the artworks' emotional value with both collectors' wealth and forgery, while the options' underlying asset is the stochastic heterogeneous beliefs of agents. We show that speculative bubbles increase with four elements: art supply constraints; a more negative correlation between collectors' wealth and the artworks' emotional value; a more positive relationship between forgery and the artworks' emotional value; and more heterogeneous beliefs. These four sources of speculation increase the expected turnover rate; however, they also augment the variance of speculative bubbles, which generates price discounts (i.e. risk premiums) for holding artworks. Consequently, the net impact of speculation is not necessarily increased art prices. This study not only contributes to the art market literature, but also to studies about speculative bubbles in other financial markets under heterogeneous beliefs, short-sale constraints and risk-averse investors, since we additionally consider the simultaneous effect of asset supply constraints, investors' background risk and the risk of investment fraud.

Capacity Market Mechanism Analyses: a Literature Review

This paper focuses on providing an overview of research into different capacity market mechanisms. Beginning with the idea of the energy-only market and the resulting potential concerns of the missing money problem, this survey overviews a variety of studies of different capacity mechanisms, considering issues such as market power, risk attitudes, uncertainty, and pricing rules. Papers of specific interest to particular ISOs/RTOs are also discussed. Previous studies tend to show the advantages of utilizing capacity market mechanisms in lieu of relying solely upon energy-only markets, particularly in the presence of risk-averse investors or the potential exercise of market power. The findings discussed herein indicate the continued importance of studying capacity market mechanisms, particularly as electricity markets continue to evolve with the advent of increasing levels of renewable regeneration and the potential of storage.

Why Does the Fed Move Markets so Much? A Model of Monetary Policy and Time-Varying Risk Aversion

We build a new model integrating a work-horse New Keynesian model with investor risk aversion that moves with the business cycle. We show that the same habit preferences that explain the equity volatility puzzle in quarterly data also naturally explain the large high-frequency stock response to Federal Funds rate surprises. In the model, a surprise increase in the short-term interest rate lowers output and consumption relative to habit, thereby raising risk aversion and amplifying the fall in stocks. The model explains the positive correlation between changes in breakeven inflation and stock returns around monetary policy announcements with long-term inflation news.

The cross-impact between financial markets, Covid-19 pandemic, and economic sanctions: The case of Iran

The main financial markets in the Iranian Economy include the stock exchange, foreign exchange, oil, and gold markets. The sharp fluctuations in these markets, especially those caused by the severe sanctions imposed on Iran in May 2018, and the pandemic outbreak of Covid-19 have led to more confusion and uncertainty among investors. One of the effective approaches to examine such unstable conditions is to study the co-movement(s) between markets to identify the leading variable(s). Thus, in the present study, Wavelet Coherence Analysis was applied to examine the co-movements between markets in a time period from September 2014 to June 2020, as an intense period of uncertainty in Iran. In other words, in this study, the markets were investigated in different sub-periods. Also, the Segmented Regression was performed to estimate the impact of sanctions and the Covid-19 pandemic on the co-movements of financial markets in Iran.The results showed that the oil price had a low co-movement with the other three markets, i.e. stock exchange, exchange rate, and gold markets. Thus, the oil market can be a suitable alternative for risk aversion investors. Meanwhile, the oil market could also act as a source of finance for the government during the sanctions period. That possibly explains the recent decision by the Iranian government to use the oil market to finance its budget deficit. Between the exchange rate and gold price, the gold price was identified as the leading variable. While the exchange rate and gold price did not show a significant co-movement in stable conditions, they did show a significant co-movement in unstable conditions, as in times of sanctions or during a global pandemic and thus influenced the investors’ portfolio risk. This result is important from a policy-making perspective. Based on this result, the policymakers can, especially during crises and unstable conditions, control the gold market and make it more stable by managing the foreign exchange market.

A Simplified Measure of Investor Risk Aversion

This article introduces a simplified measure of investor risk aversion. The singleitem question combines elements from revealed preference and propensity measurement techniques in a way that matches traditional constant relative risk-aversion estimation procedures. Based on survey data from 500 investors living in the United States, scores from the proposed measure were found to correlate with other measures of risk aversion, as well as with indicators of risk-taking. A validity test showed that answers to the proposed measure were statistically associated with equity and cash ownership holdings in respondent portfolios. The simplicity and intuitive nature of the proposed measure and the alignment of question response categories to estimates of constant relative risk aversion make this a potentially valuable addition to the toolkit of researchers, financial educators, investors and those who provide advice to investors.JEL: C83, D10, D11, D14, D19, D81

Risk-aversion in data envelopment analysis models with diversification

We deal with data envelopment analysis models with diversification which can identify investment opportunities efficient with respect to several inputs and outputs represented by risk and return measures. Moreover, they enable to project the inefficient investment opportunity to the efficient frontier and suggest how to revise its structure. However, the current DEA models does not take into account the individual risk aversion of a particular investor. We will introduce several approaches based on the spectral risk measures which deal with this drawback. These approaches are then compared in the empirical study. Note that all considered models as well as risk aversion are consistent with the second order stochastic dominance.

Bank runs, portfolio choice, and liquidity provision

We examine the portfolio choice of banks in a micro-founded model of runs. To insure risk-averse investors against liquidity risk, competitive banks offer demand deposits. We use global games to link the probability of a run to the bank's portfolio management. Based upon interim information about risky investment, banks liquidate investments to hold a safe asset. This partial hedge against investment risk reduces the withdrawal incentives of investors for a given deposit rate. As a result, (i) banks provide more liquidity ex ante (so banks offer a higher deposit rate) and (ii) the welfare of investors increases. Our results highlight the management of both sides of a bank's balance sheet and a complementarity in the two forms of insurance that banks provide to investors.

Explaining the Disposition Bias among Investors: The Mediatory Role of Personality, Financial Literacy, Behavioral Bias and Risk Tolerance

Investors are frequently subjected to cognitive error. They often sell stocks that have increased in value, while keeping stocks that have dropped in value. We proposed a theoretical framework explaining what factors affect this disposition bias and how. According to the proposed theory, Disposition bias is affected by risk tolerance, financial literacy, and behavioral biases. Lower risk tolerance and low financial literacy can aggravate disposition bias. Similarly, those who are more prone to behavioral biases like Anchoring, Loss Aversion, Overconfidence, and Representativeness, also have a higher tendency of Disposition bias. We also proposed that personality factors such as Superego, Parsimony, Orderliness, and Obstinacy also influence both the level of financial literacy as well as behavioral biases that in turn affect disposition bias. Empirical validity was established by conducted a survey using a close-ended questionnaire. Data was collected from 182 investors trading through 3 brokerage firms in Karachi. Confirmatory factor analysis and structured equation modeling were used for analysis. The results suggested that financial literacy significantly affects all behavioral biases (except Representativeness) as well as Disposition Bias. Higher financial literacy will tend to show less disposition bias and they better can make portfolio decisions. Similarly, risk tolerance also affects disposition biases as risk-averse investors will tend to show more disposition bias. Among the behavioral factors, Anchoring, overconfidence, and loss aversion affect disposition biases. Overconfidence also seems to affect risk tolerance. Personality traits like superego and parsimony seem to affect almost all the behavioral biases. Similarly, superego and parsimony have an effect on risk tolerance. Similarly, Superego and obstinacy affected financial literacy. This finding will help investors to better manage their portfolio by mitigating these biases.

SPAC IPO Waves

We examine the wave pattern of U.S. SPAC IPOs using a hand-collected data set of the entire SPAC population since their emergence in 2003. We find that both the SPAC volume and SPAC share of total IPOs are negatively related to market-wide uncertainty (VIX) and time-varying risk aversion (variance risk premium). We attribute our findings to risk-averse investors' reluctancy to invest in opaque securities. In response, the SPAC sponsor can credibly signal the issue’s quality by increasing their “skin in the game” through the purchase of additional warrants.

Stochastic model to aid decision making on investments in renewable energy generation: Portfolio diffusion and investor risk aversion

Brazil has a different energy matrix from the world, from electricity generation with renewable resources. With the increase in energy demand, environmental problems of hydroelectric plants show a need to increase the installed capacity of renewable sources. Investments in renewable generation are required, decision affected by different aspects, such as variability in generation, uncertainties in the energy market and investor risk aversion, the company’s current portfolio. The paper presents a stochastic decision support model for renewable energy investments, maximizing the expected return for a given level of risk aversion. To assess uncertainties, the Conditional Value-at-Risk (CVaR) is used. Scenarios are generated based on past generation and NEWAVE output data. Simulations with the investment option are related in this energy complementation. The risk for intermittent source involves the company using CVaR assessment. The results conclude that the diversification of the firm’s assets and the complementary composition of the sources of generation reduce the investor’s portfolio’s financial risks and the risk aversion level of the decision maker influences the market position that the company must adopt. Model tending to more conservative solutions when risk aversion is higher, confirming the literature, the existence of a trade-off between risk aversion and expected return.

Downside Risk in the Oil Market: Does It Affect Stock Returns in China?

ABSTRACT In this paper, we investigate the impact of downside risk in the oil market on the expected stock returns in China’s A-share market, and find that downside risk positively influences the expected stock returns. This positive influence remains after controlling for various control variables. It is also robust under different stock market conditions and the financial crisis, and with high-frequency data as an alternative measure of downside risk. In addition, the positive relation is consistent across industries regardless of whether they are directly related to natural resources or only indirectly related to oil. We also find evidence of nonlinearity in the relation between the oil and stock markets. The positive relation can be explained by the global risk aversion of investors who are averse to downside risk in the oil market and thus demand compensation in the form of higher expected returns for holding stocks.

Commodities price cycles and their interdependence with equity markets

Abstract This study examines the time-scale connectedness between returns on nine African stock markets and commodities markets across energy, agriculture, metals, and beverage. First, we examine multi-scale (short-, medium-, and long-run) wavelet structural relationships between African stocks and commodities using the bivariate wavelet coherence. We establish that commodities and African stock returns co-move across multiple scales and co-integrate in the long run, albeit sparse. Second, we analyze the portfolio performance of the African stock markets with other commodities using wavelet-based diversified and undiversified portfolios in a translation-invariant manner to calculate the scale-specific Sharpe ratios over different sub-periods rather than giving a one-shot look for the entire sample. This enables us to examine how risk-adjusted returns vary across different periods. The results confirm that having a combined portfolio of commodities and equities improves performance over different investment horizons. Specifically, we observe that in non-crisis periods, particularly from 2001–2006 the equally weighted and optimally weighted portfolios show the greatest performances. However, as we enter into the crisis zones such as the Asian crisis of 1997–2000 and the global financial and Eurozone debt crisis the risk-aversion of investors become prominent as the risk-minimizing portfolios record the highest performances.

Return Predictability from Industry Network Effects: Evidence from Rolling Window Adaptive Lasso

The literature argues that industry network effects imply the predictability of industry returns, while the return predictability can estimate the industry network in reverse. The paper employs rolling window adaptive lasso regressions to test the robustness of return predictions, showing the inherent model instability of the industry network and raising caveats for using the adaptive lasso method to estimate the industry network with a long time series. The out-of-sample predictability is examined by creating long-short trading portfolios based on the predictions. With non-parametric tests, the paper discovers that the out-of-sample predictability exists but is primarily due to the momentum effect. The adaptive lasso portfolios perform significantly worse than the momentum portfolio before the adjustment of risks. Based on the multifactor models, the trading portfolios also fail to continuously generate significant alphas for risk-averse investors.