Idiosyncratic Market Research Articles

Market Risk Measures Impact on Systemic Risk in Indonesia Banking Industry

This study investigates the relationship between market risk measures and systemic risk in Indonesia's banking sector. It aims to inform policymakers and regulators in promoting financial stability. By examining how market risk measures, specifically total risk encompassing systematic and idiosyncratic components, influence systemic risk in Indonesia's banking system, this study addresses a notable research gap, particularly in emerging markets like Indonesia. This research contributes to the understanding of systemic risk dynamics in an emerging market context, offering insights into how market risk measures contribute to systemic risk. Employing a quantitative approach, this study utilizes secondary data from the Indonesia Stock Exchange and Datastream Refinitiv Eikon. Non-probability sampling selects banks listed on the Indonesia Stock Exchange, with daily stock price data used to construct market risk measures. Systemic risk is measured using both CoVaR and MES, and regression analysis is employed to explore the relationship between market risk and systemic risk. The study reveals a significant positive association between total risk and systemic risk, highlighting the crucial role of idiosyncratic risk in this relationship. These findings underscore the importance of considering both systematic and idiosyncratic market risk when assessing systemic risk in Indonesia's banking sector. The study emphasizes the need for robust risk management practices and regulatory measures to ensure financial stability in emerging markets.

An Emotion-based Explanation for Bitcoin’s High-frequency Price Crash Risk

ABSTRACT We characterize the high-frequency price crash risk of Bitcoin. Using advanced text-mining techniques, we quantify emotional factors in the cryptocurrency market and investigate whether the proliferation of emotions in the cryptocurrency profession predicts the frequent occurrence of instant market crashes. We find that the cross-sectional dispersion of a catalogue of emotions is positively associated with high-frequency crash risk in the cryptocurrency market. These results are more salient for negative emotions. Differences in negative emotions may increase conflicts within a profession, resulting in idiosyncratic market outcomes.

Hedging inflation expectations in the cryptocurrency futures market

This paper finds the first evidence of time variation in the relationship between inflation expectations and the price of cryptocurrency futures. Daily data on the futures markets of Bitcoin – starting in December 2017 – and Ethereum – available since February 2021 – reveal responses to inflation expectations that are consistently positive across both measures in a full sample encompassing 2022. These results hold for a sample that precedes the Luna crash in May 13, 2022. However, the response turns negative in the period between the failures of the Luna and FTX crypto exchanges. We find cryptocurrency futures provide an effective hedge against inflation expectations and may provide a hedge against idiosyncratic market risk if the ensuing uncertainty is embraced by traders leading them to search-for-yield behavior. Risk that is more systemic – and not properly digested by financial markets – may lead futures contract holders to exit their positions ahead of expiration, leading to a bid down of futures prices and an erosion of their hedging ability. This may have contributed to the turbulence in cryptocurrencies experienced during the latter part of 2022.

The Carbon Risk Premium

This article provides an overview of compliance carbon markets that trade carbon emission allowances and analyzes the properties of carbon as an investable asset class. The authors discuss how local supply and demand factors determine allowance prices, focusing on abatement costs and policy adjustments. They then construct a novel total-return time series for four liquid carbon markets and develop an equally-weighted Carbon Composite. They found that individual carbon markets are uncorrelated to each other and commodities and asset classes unrelated to idiosyncratic market fundamentals. The Carbon Composite generated an annualized excess return of 26.63% and a Sharpe Ratio of 1.50 over 2013–2021, suggesting that carbon as an investable asset class could provide tangible diversification benefits to investors. The authors then explore the outlook for carbon as an asset class and identify theoretical and practical justifications for a prospective carbon risk premium.

QuantNet: transferring learning across trading strategies

Systematic financial trading strategies account for over 80% of trade volume in equities and a large chunk of the foreign exchange market. In spite of the availability of data from multiple markets, current approaches in trading rely mainly on learning trading strategies per individual market. In this paper, we take a step towards developing fully end-to-end global trading strategies that leverage systematic trends to produce superior market-specific trading strategies. We introduce QuantNet: an architecture that learns market-agnostic trends and use these to learn superior market-specific trading strategies. Each market-specific model is composed of an encoder-decoder pair. The encoder transforms market-specific data into an abstract latent representation that is processed by a global model shared by all markets, while the decoder learns a market-specific trading strategy based on both local and global information from the market-specific encoder and the global model. QuantNet uses recent advances in transfer and meta-learning, where market-specific parameters are free to specialize on the problem at hand, whilst market-agnostic parameters are driven to capture signals from all markets. By integrating over idiosyncratic market data we can learn general transferable dynamics, avoiding the problem of overfitting to produce strategies with superior returns. We evaluate QuantNet on historical data across 3103 assets in 58 global equity markets. Against the top performing baseline, QuantNet yielded 51% higher Sharpe and 69% Calmar ratios. In addition, we show the benefits of our approach over the non-transfer learning variant, with improvements of 15% and 41% in Sharpe and Calmar ratios. A link to QuantNet code is made available in the appendix.

A scoping review of market links between value chain actors and small-scale producers in developing regions

Sustainable Development Goal 2 aims to end hunger, achieve food and nutrition security and promote sustainable agriculture by 2030. This requires that small-scale producers be included in, and benefit from, the rapid growth and transformation under way in food systems. Small-scale producers interact with various actors when they link with markets, including product traders, logistics firms, processors and retailers. The literature has explored primarily how large firms interact with farmers through formal contracts and resource provision arrangements. Although important, contracts constitute a very small share of smallholder market interactions. There has been little exploration of whether non-contract interactions between small farmers and both small- and large-scale value chain actors have affected small farmers’ livelihoods. This scoping review covers 202 studies on that topic. We find that non-contract interactions, de facto mostly with small and medium enterprises, benefit small-scale producers via similar mechanisms that the literature has previously credited to large firms. Small and medium enterprises, not just large enterprises, address idiosyncratic market failures and asset shortfalls of small-scale producers by providing them, through informal arrangements, with complementary services such as input provision, credit, information and logistics. Providing these services directly supports Sustainable Development Goal 2 by improving farmer welfare through technology adoption and greater productivity.

The Entrepreneurial Propensity for Market Analysis and the Intention-Action Gap

Evaluating and exploiting imagined opportunities involves gathering and processing idiosyncratic market knowledge, but individuals differ in their abilities and propensities in this task. We propose a new construct, the entrepreneurial propensity for market analysis (EPMA), and argue that this propensity mediates the relationship between entrepreneurial intention and action. We test these relationships in a study of 213 prospective entrepreneurs from science and technology parks (STPs) in Iran. Results support the mediating effect of EPMA on the entrepreneurial act.

A jump model for credit default swaps with hierarchical clustering

The return time series of Credit Default Swaps (CDS) display possibly the highest excess kurtosis and skewness of any asset class in capital markets. Capturing this requires a departure from classical modeling techniques. Here, the premise is that CDS prices jump and those jumps cluster. Initially, a model is proposed that is driven by a diffusion and a Hawkes process to reproduce the clustering of shocks. The new element of the model is the use of hierarchical clustering to calibrate the distribution of the jumps. Partitioning the shocks identifies shifts in the volatility regime of the CDS through time, which are shown to consistently correspond to both systemic and idiosyncratic market events. A piecewise definition of a double exponential distribution for the jumps, corresponding to the identified clusters, is employed to replicate the regime switching. Subsequently, this demonstrably improves the accuracy of the calibration. The model is fitted to all CDS with more than 2000 closing prices from 2001 to 2014; a total of 1652 individual time series. For each credit, a peak-over-threshold approach is applied to the return series to separate the data into those returns that can broadly be classified as log-normal and those that can be characterized as jumps. By explicitly linking the results to market traded volumes, the results indicate a clear split of the CDS into liquid and illiquid names. A key finding is that for the illiquid CDS, it is difficult to justify the continuous component of the model. For the low liquidity names, the Hawkes process is shown to capture the price-action without a diffusion. A Markov chain is then introduced into the simulation to replicate the clustering and regime switching.

Market Volatility Risk and Stock Returns around the World: Implication for Multinational Corporations*

AbstractWe investigate the pricing of market volatility risk as a risk factor—the innovation risk and as a characteristic risk—the level risk. We find that the pricing of the country‐level (local) market volatility risk factor is not robust across 21 developed markets and that the global market volatility risk factor prices 21 developed market portfolios after controlling for global market, value, and size factors. Capturing various market information, idiosyncratic market volatility as a country‐specific characteristic risk dominates global market, value, size, and market volatility risk factors in predicting returns of market portfolios. Countries with higher investor protection and accounting standards have higher country‐specific market volatility. Market volatility is higher in these countries because corporate managers take higher risks on innovative projects that benefit economic growth.

A Jump Model for Credit Default Swaps with Hierarchical Clustering

The return time series of Credit Default Swaps (CDS) display possibly the highest excess kurtosis and skewness of any asset class in capital markets. Capturing this requires a departure from classical modelling techniques. Here, the premise is that CDS prices jump and those jumps cluster. Initially, a model is proposed that is driven by a diffusion and a Hawkes process to reproduce the clustering of shocks. The new element of the model is the use of hierarchical clustering to calibrate the distribution of the jumps. Partitioning the shocks identifies shifts in the volatility regime of the CDS through time, which are shown to consistently correspond to both systemic and idiosyncratic market events. A piecewise definition of a double exponential distribution for the jumps, corresponding to the identified clusters, is employed to replicate the regime switching. Subsequently, this demonstrably improves the accuracy of the calibration. The model is fitted to all CDS with more than 2000 closing prices from 2001 to 2014; a total of 1652 individual time series. For each credit, a peak-over-threshold approach is applied to the return series to separate the data into those returns that can broadly be classified as log-normal and those that can be characterized as jumps. By explicitly linking the results to market traded volumes, the results indicate a clear split of the CDS into liquid and illiquid names. A key finding is that for the illiquid CDS, it is difficult to justify the continuous component of the model. For the low liquidity names, the Hawkes process is shown to capture the price-action without a diffusion. A Markov chain is then introduced into the simulation to replicate the clustering and regime switching.

Entrepreneurship is Manifested in Action

In this essay I discuss that because of the attribute errors linked to entrepreneurial opportunity, action contributes more insights on creating a venture than a strong idea or opportunity per se. Action can provide idiosyncratic market knowledge as a basis for sound judgment (in opposed to lousy judgment) and the subsequent decisions on whether to invest on an opportunity or not, mainly for the entrepreneurs with limited resources and experience.

Recognizing Changes in the Chinese Outbound Tourism Source Market

This study presents a geographic market segmentation and evolutionary approach by examining regional differences in Chinese outbound market and its distribution. To do this, two well-known empirical regularities that are used in urban geography—the primate city and rank-size rule—are employed to measure changes and trends. The research findings show that as the scale of the core region (mega in size with respect to tourist volume) increases, peripheral regions (small and medium sized), with ununiform speed, respond quickly to this change. The results also show how the market has evolved over the time period as well as the trends of development between core and peripheral regions. Understanding such implications may help Western providers better serve this unique and idiosyncratic market.

Aggregate idiosyncratic volatility and stock return predictability: Evidence from the Korean stock market

ABSTRACTEmploying various proxies of idiosyncratic volatility, we investigate the relationship between aggregate idiosyncratic volatility and future market returns in Korea. We find a positive association between aggregate idiosyncratic volatility and subsequent market returns, and especially, that the idiosyncratic volatility measure proposed by Garcia, Mantilla-García, and Martellini (2014) has a striking forecasting power for future market excess returns. The predictive power of aggregate idiosyncratic volatility is robust to several considerations including weighting schemes, market variance and trading exchanges. Overall, our empirical results indicate that aggregate idiosyncratic volatility plays an important role in predicting future stock returns in the Korean stock market.

A re-examination of firm, industry and market volatilities

Abstract In updating Campbell et al. (2001) we find evidence that the level of idiosyncratic volatility, industry-specific volatility, and market volatility have increased to their highest levels in 50 years during the 21st century. Our findings show that while the 2007–2008 Financial Crisis led to large spikes in all three measures of volatility, the Tech Bubble of early 2000’s led to an even greater increase in firm and industry volatilities than the Financial Crisis. By 2010, volatilities mostly returned to their pre-crisis levels. We also find evidence that the average correlation among stocks, which decreased during 1960–2000 period, has been increasing steadily since early 2000’s.

THE INFLUENCE OF IDIOSYNCRATIC VOLATILITY, MARKET RISK, AND SIZE ON STOCK RETURN OF A NON-FINANCIAL COMPANY REGISTERED IN INDONESIA STOCK EXCHANGE IN THE PERIOD OF 2012 – 2016

The objective of this research is to examine the effect of idiosyncratic volatility, market risk, and size, as the independent variable on stock return on non-financial firm (eight sectoral) listed on Indonesia Stock Exchange. This research uses quantitative perspective with linier regression and model in a panel data for all of the research’s observation used in this research. The number of observation in this research is 1440, consisting of 288 firms that have been enlisted on Indonesia Stock Exchange during 2012-2016 period. The result shows that idiosyncratic volatility has a negative significant effect on stock return. Market risk and size appear to have no significant effect on stock return.

Dynamics of Idiosyncratic Volatility and Market Volatility: An Emerging Market Perspective

Estimating idiosyncratic volatility (IVOL) using various model-dependent and model-independent measures, we investigate the characteristics of aggregate IVOL in Malaysia over the period 1990–2008. The IVOL estimated in all models have similar patterns and has no trend over the sample period. There is evidence of episodic phenomenon. During financial crisis periods, market volatility is relatively higher than IVOL – a plausible reason is high correlation between firms' returns. Small firms and low-priced stocks appear to influence IVOL more than large firms and high-priced stocks. In Malaysia, market volatility and IVOL may predict GDP growth.

Nineteenth- and Twentieth-Century Greek Art in Primary and Secondary Markets: Some Observations

The collocation “Greek Art” in museum language and in the secondary market usually refers to antiquity and, less frequently, to byzantine art. But is there a market for more recent Greek art creations? On what basis is this market organized and to which public does it appeal? Historically seen, galleries in Greece specialized in nineteenth- and twentieth-century Greek production have operated since the 1930s and flourished after the 1950s, particularly in the 1980s, since Greece joined the European Community. It was at that time that a rather “stable” regional art market developed, in order to promote local artists. Modern and Contemporary Greek Art was a new, unexplored and profitable area for the world art market and, in the 1990s, well-established international auction houses began selling Greek artworks more consistently. What is the state-of-the-art in the Greek art market? Are there differences between the secondary market inside and outside Greece's national borders? How can these differences be explained? This paper aims at presenting the difficulties and peculiarities of an as yet underdeveloped and, at a high degree, idiosyncratic market.

A New Test for the Detection of the Pricing Role of Aggregate Idiosyncratic Risk in the Predictive Regression

The standard test for the pricing role of aggregate idiosyncratic risk in the conventional predictive regression considers aggregate total idiosyncratic risk a reasonable proxy for its undiversified component, which should be priced as theory suggests. However, when the priced component is relatively small, the test has little statistical power to reject the null hypothesis that idiosyncratic risk does not matter, even when the priced component, albeit small, explains an economically large portion of future excess return variation. We propose a simple regression-based method that can, under certain conditions, substantially improve the power of the test when economically important alternative hypotheses are true, but sacrifices little in the size of the test for the improved power. Based on the new test, we strongly reject the proposition that idiosyncratic risk does not matter and uncover a significantly positive relationship between aggregate undiversified idiosyncratic risk and future market excess returns.

Are Investors Compensated for Bearing Market Volatility in a Country?

We investigate whether market volatility risk is a systematic pricing factor for stocks and market portfolios and whether it is a factor risk or a country-specific characteristic risk to investors in 21 developed countries. We find that local market volatility risk factor negatively prices stock returns in Belgium, Canada, Spain, Norway, the U.K., and the U.S. and that global market volatility risk factor systematically prices 21 market portfolios after controlling for global market, value, and size factors. Idiosyncratic market volatility as a country-specific characteristic risk dominates global market, value, size, and market volatility risk factors in predicting the return of market portfolios. Countries with higher investor protection and accounting standards have higher country-specific market volatility. We interpret this as consistent with the good volatility hypothesis of Bartram, Brown, and Stulz (2012); that market volatility is higher in these countries with good corporate governance because they encourage corporate managers to take higher risks on innovative projects, which can in turn generate higher returns for shareholders and thus benefit economic growth.

Golden Handcuffs: CEO Employment Contracts When the Firm May Benefit from Anticipated Retention

The relative performance evaluation hypothesis postulates that market-wide and industry-wide performance should not affect the likelihood of CEO involuntary turnover. However, recent academic literature has documented that following poor industry and market performance the likelihood of CEO involuntary turnover increases. This paper presents a model that explains how the lack of relative performance evaluation in CEO turnover can emerge as an efficient result. I analyze a learning model of managerial ability; the model assumes that the firm benefits from stakeholders' anticipation of the retention of its CEO. The model is consistent with several other features of the labor market for CEOs such as observations that CEO compensation correlates with both idiosyncratic firm performance and market performance; that CEOs rarely change employers; and that the value of a firm may increase following a CEO turnover announcement in which the departing CEO accepts employment at another firm. To support this last assertion, I document that in almost half of the cases in a sample of CEO moves to a larger firm the value of the old firm increases following the turnover announcement.