Applied Finance Letters (E-Journal - Auckland Centre for Financial Research)
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149 research outputs found
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COVID-19 PANDEMIC AND HERDING BEHAVIOUR IN CRYPTOCURRENCY MARKET
Full text linkIn this paper, we examine the presence of herding in cryptocurrency market for four distinct sub-periods (Pre and During COVID-19 period, bear and bull markets) using daily closing prices of 5 largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, XRP, Stellar and Tether) from April 20, 2019 to January 31, 2021. The study employs cross-sectional absolute deviations (CSAD) model to test herd behavior and the results of the study provide evidence of herd behavior in the whole market for the selected period under study. The study also proofs the presence of herding during COVID-19 period and in positive market returns. These indicate that, investors in the cryptocurrency market, during COVID-19 periods, and in bullish market are inclined to the investment behavior of other peer investors in the market. The study is significant to investors, regulators and players in the cryptocurrency market so as to deepen their understanding of herding behavior since herding is thought to increase the volatility of the market.
The study is significant to investors, regulators and players in the cryptocurrency market so as to deepen their understanding of herding behavior since herding is thought to increase the volatility of the market
INVESTOR ATTENTION AND HERDING IN THE CRYPTOCURRENCY MARKET DURING THE COVID-19 PANDEMIC
Full text linkThis study examines the relationship between investor attention and herding effects in the cryptocurrency market by employing the vector autoregression and quantile regression models. Furthermore, we examine whether the COVID-19 pandemic affected herding behaviour in cryptocurrencies. Using the daily closing price and Google search volume of the five leading cryptocurrencies, the paper finds that herding in the cryptocurrency market decreases with an increase in investor attention for the overall sample. The results for the COVID-19 period indicate that the impact of investor attention on the herding effect decreases due to increased attention to the pandemic. This study is one of the initial attempts to examine the impact of investor attention on herding in cryptocurrencies
Impact of Managerial Ability and Power on CEOs Compensation: An Empirical Evidence from Indian Companies
Full text linkThe present study aims to test whether the rent extraction or efficient contracting which significantly influences the compensation of CEOs in Indian companies. By drawing the sample from all the listed companies providing data on CEO characteristics from the year 2006 to 2018, the study tests the empirical model using ordinary least squares regression and quantile regression. The results of analysis reveal that CEO compensation is tenure-variant and there is a trivial difference between the impact of CEO power and CEO tenure. It is in line with the bargaining theory of managerial ability view on CEO compensation. It supports efficient contracting in CEO compensation. The results of the analysis also reveal that impact of CEO power is comparatively less for long-tenured CEOs. It implies that managerial ability view is maintained and CEO compensation is influenced by their bargaining power. The results also prove that power premium is more in case of group companies compared to non-group companies.
Key words: CEO compensation, rent extraction theory, efficient contracting theory, CEO Power, CEO Tenure, Indian companies
Time-varying risk aversion and the profitability of momentum trades
Full text linkWe show that time-varying risk aversion serves as a significant predictor of stock market momentum in the U.S. and globally. Risk aversion is found to be a robust predictor of momentum returns even after controlling for various well established stock market predictors and absorbs the predictive power of market volatility. The findings imply that momentum strategies can be enhanced by conditioning trades on the degree of risk aversion in the marketplace
Fund Managers Adding Values? Measuring Performance without Benchmark – A Study of Indian Mutual Fund Schemes
Full text linkThis paper calculates the Portfolio Change Measure (PCM) developed by Grinblatt and Titman for a sample of 744 equity schemes of Indian mutual funds over a minimum period of more than 2 years and less than 11 years. PCM, based on holding of assets, is a measure which is free from ‘benchmark’ biases arising out of usage of a ‘benchmark’ portfolio. So by using PCM as a measure, this paper, without using any benchmark, attempts to assess whether the selected mutual fund managers were able to add value and exhibit superior skills on the average and thus making a case for active fund management over a passive buy and hold strategy. Using the monthly holding statement of each individual scheme’s portfolio, rolling PCM has been calculated on a monthly basis with a rolling window of one year. The results of our analysis, supported by robustness checks, which includes time periods of pre-and post-Global Financial Crisis, shows strong evidence of active fund management adding value in the stock selection and hence in return generating process, thus justifying the possession of superior skill or superior information of fund managers at an aggregate level. Finally, using Quantile Regression we identify some characteristics of the scheme like scheme size and ownership category, which influence PCM significantly
A Network Analysis of the Asia-Pacific and Other Developed Stock Markets: Pre and Post Global Financial Crisis
Full text linkThis paper examines the volatility spillover and connectedness between Asia-Pacific, US, UK, and eurozone stock markets. A spillover index is built using forecast error variance decomposition in a vector autoregression framework and the spillover index is used to build network diagrams. It shows evidence of how the increase in risk transfer (volatility spillover) between the markets led to the global financial crisis and of the higher level of connectedness since. Network diagrams show the direction and strength of the connectedness. The network strength estimation enables us to understand the risk associated with connectedness across the markets in the event of a trigger and its influence in portfolio management decisions of international funds. The Chinese market appears to be the most insulated, while the South Korean, Hong Kong, and Singapore stock markets dominate in terms of risk transfer. The US, UK, EU, Singapore and Hong Kong are the top five volatility spillover recipient markets, both during pre and post global financial crisis periods. We find the market size to be irrelevant in the determination of the level of connectedness, whereas the role of geographical proximity cannot be ruled out. The findings are relevant to multinational investment strategies and in understanding the relative risk of investment in the Asia-Pacific region
Does herding exist in lottery stocks? Evidence from the Indian stock market
Full text linkIn this paper, we investigate the presence of herd behaviour among lottery stocks using Max, skewness and idiosyncratic volatility in the Indian stock market during the period January 2000 to December 2018. We demonstrate that the herd behaviour is non-existent across proxies of lottery-stocks MAX and skewness and find that the herd behaviour is present among highly idiosyncratic stocks. This sheds light on why herding is not detected in the prior studies as it may be concentrated among stocks with certain characteristics. Further, it provides evidence of adverse herding
Responsible Investing: A Study on Non-Economic Goals and Investors’ Characteristics
Full text linkThe notion of rational investment is not attuned with the idea of socially responsible investment. Incongruence with conventional investments, the SRI/sustainable investment/ethical investment is pertained to ethical, environmental and social criteria (Eccles and Viviers,2011). All investors are not single-minded for an objective of wealth creation. The welfare of society and the environment are among the other drivers of investment. In certain cases, investors do prefer sustainable development to personal financial aspects (Beal et al., 2005). The present study has primarily focused on assessing the relationship between individual investors’ attributes and their noneconomic goal in order to comprehend their socially responsible investment behaviour specifically in Indian scenario. The findings of study are useful for fund managers, regulators and researchers as study has provided useful insights regarding behaviour of Indian investors for responsible investments
Responses of Economic News on Asset Prices: A Study of Indian Stock Index Futures
Full text linkThe study examines the role of economic news surprises on the volatility of the returns of the Indian Index futures market. Theoretical literature posits that news arrivals influence price discovery. In similar lines, we investigated the relationship between economic news releases, trading activity variables, and returns volatility. We find that economic news surprises and trading activity variables significantly affect returns volatility. However, among volume and news surprises, economic news surprises are much stronger informational signals, and the news surprises effects are found seemingly asymmetric in the index futures contract
Real-Time Detection of Volatility in Liquidity Provision
Full text linkPrevious research has found that high-frequency traders will vary the bid or offer price rapidly overperiods of milliseconds. This is a benefit to fast traders who can time thier trades with microsecondprecision, however it is a cost to the average market participant due to increased trade execution priceuncertainty. In this analysis we attempt to construct real-time methods for determining whether theliquidity of a security is being altered by high-frequency traders. We find a four-state Markov switchingmodel identifies a state consistent with high-frequency traders affecting liquidity. Moreover, we find thisstate is positicely corrrelated with the prediction error from a deep neural network. This state can beused as a signal to delay market participant orders until the price volatility subsides. This delay wouldonly last tens of milliseconds, and so would not be noticable by the average market participant