The emotional cost-of-carry: Chinese investor sentiment and equity index futures basis

PurposeWhile the classic futures pricing tool works well for capital markets that are less affected by sentiment, it needs further modification in China's case as retail investors constitute a large portion of the Chinese stock market participants. Their expectations of the rate of return are prone to emotional swings. This paper, therefore, explores the role of investor sentiment in explaining futures basis changes via the channel of implied discount rates.Design/methodology/approachUsing Chinese equity market data from 2010 to 2019, the authors augment the cost-of-carry model for pricing stock index futures by incorporating the investor sentiment factor. This design allows us to estimate the basis in a better way that reflects the relationship between the underlying index price and its futures price.FindingsThe authors find strong evidence that the measure of Chinese investor sentiment drives the abnormal fluctuations in the basis of China's stock index futures. Moreover, this driving force turns out to be much less prominent for large-cap stocks, liquid contracting frequencies, regulatory loosening periods and mature markets, further verifying the sentiment argument for basis mispricing.Originality/valueThis study contributes to the literature by relying on investor sentiment measures to explain the persistent discount anomaly of index futures basis in China. This finding is of great importance for Chinese investors with the intention to implement arbitrage, hedging and speculation strategies.

Price efficiency and safe-haven property of Bitcoin in relation to stocks in the pandemic era

Purpose When investors experience extreme uncertainty, they seek “safe havens” to reduce their risk, to limit their losses and to protect the value of their portfolios. The purpose of this paper is to examine the safe-haven properties of Bitcoin compared to the stock market. Design/methodology/approach Based on intraday data, this study compares the price efficiencies of Bitcoin and Morgan Stanley Capital Index (MSCI) using Multifractal Detrended Fluctuation Analysis for the second half of 2020. This study then evaluates Bitcoin’s safe-haven property using Detrended Partial-Cross-Correlation Analysis (DPCCA). Findings This study finds that the price efficiency of Bitcoin is lower than that of MSCI. Further, Bitcoin was not a safe haven at any time for the MSCI index. The net cross-correlations between Bitcoin and MSCI are weak and they vary at different time scales. Research limitations/implications The behavior of market prices varies over time. Therefore, it is important to replicate this study for other time periods. Social implications The paper sheds light on the price behavior of Bitcoin during a period of instability. The results suggest that the construction of portfolios should differ based on the time horizons of the investors. Originality/value The authors compare Bitcoin against a global equity index instead of a specific country index or commodity. They also demonstrate the applicability of DPCCA in finance research.

Financial Analysis: A Study on the Liquidity and Indebtedness of Brazilian Companies Listed on the Bovespa Index in the Period of Social Isolation Caused by Covid-19

The present work aimed to carry out a study on the variation of liquidity and indebtedness of companies listed on the Bovespa Index of B3, for the four quarters of 2020, a period in which the world economy went through instabilities and imbalances due to the pandemic of Covid-19. Financial management is essential for companies, as without it managers can make inefficient decisions, which can negatively impact the company and its finances. The absence of good financial management can cause negative impacts on the company, especially in times of crisis, such as the period of the first year of the COVID-19 pandemic. Therefore, for a business to have good results, it is necessary to create strategies to manage the company's finances, including periodic liquidity and indebtedness analysis. Thus, the Current Liquidity Ratio (ILC) and the Cash Ratio(CI) were used to determine the liquidity of companies and their transformations for the period analyzed. For indebtedness, we sought to analyze the Liabilities/Assets Index and the Third-Party Capital/Equity Index. Data were collected from the Standardized Financial Statements (DFP) and Quarterly Information (ITR) available on the B3 page. In the analysis of this work, companies from the financial sector were excluded due to the incompatibility of accounting standards and the methodology addressed in the work. It was verified in the results that, on average, companies underwent a substantial increase in liquidity in 2020, mainly in the second quarter, in which there was an average increase, among the companies analyzed, of 33.18% in the Cash ratio. The Industrial Goods, Oil, Gas and Biofuels and Public Utilities sector had the greatest increases in liquidity in the period. In terms of indebtedness, it could be seen that there was an increase in the participation of third-party capital, but less significant than the increase in liquidity of companies. This suggests that liquidity was financed by reallocation of company assets and policies aimed at exchanging the companies' current liabilities for non-current liabilities. It is concluded that in periods of uncertainty, such as the COVID-19 Pandemic, one of the priorities of companies is in fact to strengthen cash through asset reallocation, liability refinancing and contracting of credit lines.

Influence of Capital Markets, Inflation, and Demographics on the Growth of Pension Fund Assets in the State Organization of Islamic Cooperation

The percentage of pension receipts that is still low is experienced by many developing countries in the continent of Asia and Africa in terms of providing pension funds for their citizens. This study seeks to analyze the effect of growth in pension fund assets in OIC member countries. The measurement of the growth of pension fund assets is viewed through the aspects of the number of stock traded, the equity index, the inflation rate, male labor force participation, female labor force participation, the working age, and the retirement age. In addition, this study uses a panel data regression analysis method with the period 2010 to 2019. The results show that there are variables of male labor force participation, female labor force participation, working-age, and retirement age that have a significant effect. Male labor force participation, working-age, and retirement age have a positive effect on the growth of pension fund assets, while female labor force participation has a negative effect on pension fund assets. It can be said that the demographic aspects can influence the growth of pension fund assets in OIC member countries in the period 2010 to 2019.

U.S. REIT INDUSTRY PROFITABILITY: A BENNET DECOMPOSITION OF INDUSTRY DYNAMICS

This paper considers the aggregate profitability performance of the REIT industry. The aggregate performance depends on the underlying microeconomic dynamics within an industry – the growth of individual REITs (the within effect), the reallocation between existing REITs (the between effect), the entry of new REITs (the entry effect), and the exit of the existing REITs (the exit effect). We apply an extended Bennet (1920) dynamic decomposition on the REIT industry’s return on equity (ROE) and study the annual data on U.S. Equity REITs for the 1989 to 2015 period and various REIT industry specific sub-sample periods. Bailey et al.’s (1992) and Haltiwanger’s (1997) dynamic industry performance decompositions are special cases of the Bennet decomposition. The “within” and “between” effects dominate the annual changes in this industry’s ROE. To the extent that our Equity REIT sample proxies for the FTSE NAREIT All Equity Index, our conclusions also relate to this index’s profitability performance between 1989 and 2015.

Regime-Switching Behaviour In US Equity Indices: Two State Model With Kalman Filter Tracking And Finite State Machine Trading System

This thesis presents a time varying regime-switching model for US equity index daily returns. The parameters of the model are estimated recursively with the Kalman lter. We demonstrate our model and parameter estimation technique are effective by demonstrating improvements in model t compared to alternate models. Information from our model is used to build a Finite State Machine trading system with back-tested performance in excess of 15,000% above a buy and hold strategy for the DOW Jones Industrial average from 1928-2012. Similar results are found for both the S&P 500 index and the NASDAQ Composite index over a long period. Our model succeeds at identifying pro table investment opportunities and improving model t with a minimum of parameters.

Regime-Switching Behaviour In US Equity Indices: Two State Model With Kalman Filter Tracking And Finite State Machine Trading System

This thesis presents a time varying regime-switching model for US equity index daily returns. The parameters of the model are estimated recursively with the Kalman lter. We demonstrate our model and parameter estimation technique are effective by demonstrating improvements in model t compared to alternate models. Information from our model is used to build a Finite State Machine trading system with back-tested performance in excess of 15,000% above a buy and hold strategy for the DOW Jones Industrial average from 1928-2012. Similar results are found for both the S&P 500 index and the NASDAQ Composite index over a long period. Our model succeeds at identifying pro table investment opportunities and improving model t with a minimum of parameters.