Conditional Volatility Measures Research Articles

Socially responsible investing: performance evaluation of BRICS nations

PurposeThe study aims to contribute towards the sustainable development of financial systems, by testing the performance of socially responsible investing alternatives in emerging BRICS countries. The study outcomes give us an insight into viability of responsible financial decisions in contrast with the conventional style of investing.Design/methodology/approachThe authors examine the performance of socially responsible indices of BRICS nations vis-à-vis respective conventional market indices using various risk-adjusted measures and conditional volatility measures. We further segregate the 12-year study period to crisis and non-crisis period particular to the respective country, as well as a common global financial crisis period to analyze the impact of market conditions in BRICS nations and observe the performance using dummy regression analysis. Conditional volatility of the stochastic index series is measured using ARCH-GARCH analysis. Fama Decomposition Model helps rank the index performance through the sub-periods.FindingsFama Decomposition Model helps us observe that while Brazil secures a position in top rankers consistently, it is India that ranks top during crisis period. With evidence of outperformance in terms of risk-return by SRI indices of BRICS countries through the overall period as well as through different market conditions, our study contributes to the positive literature on socially responsible investing.Research limitations/implicationsThe study explores performance of SRI in BRICS and finds evidence of the sustainable investment to be non-penalizing to the investor, even as the performance trend remain distinct in the countries with same level of development. It has implications for the investors and asset managers to include responsible stocks, while for the companies and regulatory bodies to unite for better reporting and disclosures. Given the broad implications, future research is required to link the impact of various cultural, legislative and demographic factors on the level and performance of the socially responsible investment in BRICS nations.Practical implicationsThe current study evaluating and comparing performances of the socially responsible investments in BRICS nations puts forth following implications for the different sectors of the society, especially in emerging countries: (1) BRICS organization – The association of five economic giants, having significant influence over global as well as regional affairs, can aim to orient the countries' efforts towards collective sustainable development by designing uniform SRI framework. (2) Investors – In the globalization era, the investor can gain from ethical cross border investments to diversification and country benefits. (3) Companies and regulatory bodies – Only voluntary or mandatory unified efforts, to provide accurate and consistent disclosures, can upscale the mediocre growth trends of sustainable investing in emerging economies. (4) Asset Managers – Call of greater role in educating, warding off inhibitions related to RI.Originality/valueThis is to certify that the research paper submitted by us is an outcome of our independent and original work. We have duly acknowledged all the sources from which the ideas and extracts have been taken. The project is free from any plagiarism and has not been submitted elsewhere for publication.

Long range dependence in the Bitcoin market: A study based on high-frequency data

Using the high-frequency data of Bitcoin, this paper investigates the long memory characteristics of the unconditional and conditional volatilities of Bitcoin at different time scales using the local Whittle (LW) estimator, the exact local Whittle (ELW) estimator and the ARMA–FIAPARCHmodel. The results show that the long memory parameter is significant and quite stable for both unconditional and conditional volatility measures across different time scales. This paper also examines the long memory characteristics of the unconditional and conditional “realized” volatilities of Bitcoin at different time scales using the local Whittle (LW) estimator, exact local Whittle (ELW) estimator and the ARFIMA model. Long memory is found to be significant and stable also in case of unconditional and conditional “realized” volatilities. The study also undertakes quarterly non-overlapping rolling window analysis to develop deeper insights into the evolution of long memory parameter, d, over the period. The results indicate high persistence in the Bitcoin market. This study has useful implications for different investors and market participants having varying exposures in the Bitcoin market depending on their trading horizons. The findings can help them in forecasting the expected volatility in the Bitcoin market and thereby in developing and implementing trading strategies.

Long Memory Volatility Persistence in High Frequency Precious Metals Returns

Using high frequency data, this paper examines the long memory property in the conditional volatility of the precious metals return series at different time frequencies using FIGARCH models. Very significant long memory characteristics have been detected in absolute returns by using Semiparametric local Whittle estimation of the long memory parameter. Estimation of the long memory parameter across many different data sampling frequencies gives consistent estimates of the long memory parameter, indicating that the series are exactly to show some degree of self-similarity. Results indicate that the long memory property remains quite consistent across different time frequencies for both unconditional and conditional volatility measures. This study is useful for investors and traders (with different trading horizons) and it can be used in predicting expected future volatility and in designing and implementing trading strategies at different time frequencies.

Long range dependence in the high frequency USD/INR exchange rate

Using high frequency data, this paper examines the long memory property in the unconditional and conditional volatility of the USD/INR exchange rate at different time scales using the Local Whittle (LW), the Exact Local Whittle (ELW) and the FIAPARCH models. Results indicate that the long memory property remains quite stable across different time scales for both unconditional and conditional volatility measures. Results from the non-overlapping moving window approach indicate that the extreme events (such as the subprime crisis and the European debt crisis) resulted in highly persistent behavior of the USD/INR exchange rate and thus lead to market inefficiency. This paper also examines the long memory property in the realized volatility based on different time scale data. Results indicate that the realized volatility measures based on different scales of the high frequency data exhibit a consistent and stable long memory property. However, the realized volatility measures based on daily data exhibit lower degree of long-range dependence. This study has implications for traders and investors (with different trading horizons) and can be helpful in predicting expected future volatility and in designing and implementing trading strategies at different time scales.

The information content in a volatility index for Spain

A model-free methodology is used for the first time to estimate a daily volatility index (VIBEX-NEW) for the Spanish financial market. We use a public data set of daily option prices to compute this index and show that daily changes in VIBEX-NEW display a negative, tight contemporaneous relationship with IBEX daily returns, contrary to other common volatility indicators, as an implied volatility indicator or a GARCH(1,1) conditional volatility model. This relationship is approximately symmetric to the sign on VIBEX-NEW changes and asymmetric to the IBEX-35 returns sign, which make it clearly a suitable volatility index for the Spanish stock market. We also examine the relationship between current VIBEX-NEW and future IBEX-35 volatility. Our results suggest that VIBEX-NEW can be used to produce IBEX-35 volatility forecasts at least as good as historical and conditional volatility measures. A feasible volatility correction methodology is proposed to achieve it.

The Information Content in a Volatility Index for Spain

A model-free methodology is for the first time used in this paper to estimate a daily volatility index (VIBEX-NEW) for the Spanish financial market. We show that daily changes in VIBEX-NEW display a negative, tight contemporaneous relationship with IBEX daily returns, contrary to other common volatility indicators based on implied volatility or historical volatility, which make it a suitable volatility index for the Spanish stock market. Finally, even though the VIBEX-NEW volatility index has not been constructed with a forecasting goal in mind, it can produce forecasts of IBEX-35 realized volatility at least as good as those emerging from historical and conditional volatility measures from a GARCH(1,1). A feasible volatility correction methodology is proposed to achieve it.

Non-linear dynamics in financial asset returns: the predictive power of the CBOE volatility index

In this paper we attempt to predict the direction of change of the S&P500 index over the period 8 April 1998 to 5 February 2002 by means of a recurrent neural network (RNN). We demonstrate that the incorporation in the trading rule of the Chicago Board Options Exchange (CBOE) volatility index changes strongly enhances its profitability during ‘bear’ market periods. This improvement is measured in comparison with a RNN including changes of estimated conditional volatility measures, a linear autoregressive model as well as to a buy-and-hold strategy. We suggest a number of theories that are consistent with our findings.

Persistence of volatility in futures markets

This article examines the characteristics of key measures of volatility for different types of futures contracts to provide a better foundation for modeling volatility behavior and derivative values. Particular attention is focused on analyzing how different measures of volatility affect volatility persistence relationships. Intraday realized measures of volatility are found to be more persistent than daily measures, the type of GARCH procedure used for conditional volatility analysis is critical, and realized volatility persistence is not coherent with conditional volatility persistence. Specifically, although there is a good fit between the realized and conditional volatilities, no coherence exists between their degrees of persistence, a counterintuitive finding that shows realized and conditional volatility measures are not a substitute for one another

Conditional variance tests of integration between direct and indirect real estate markets

This study tests the hypothesis of market integration between the securitised and the unsecuritised real estate market by examining the information contents of their respective ex‐post conditional volatility measures. The two markets are said to be integrated if the conditional volatility terms of one market do not contain incremental information for the ex‐post conditional volatility of another market. Our empirical results showed no evidence of the ex‐post returns of the direct real estate (PPI) market incorporating the market volatility of the securitized real estate asset. The ex‐post conditional volatility of the PPI market, which contains only information on the past shock and the past conditional volatility, is sufficient to statistically explain the variation in the log‐PPI price variations. However, there was significant evidence of incremental information flowing from conditional volatility of the unsecuritized property market to the securitized property market. Therefore, the securtized and unsecuritized real estate markets are integrated, but the integration is only uni‐directional. Some degree of segmentation is still observed as the information of property market (PPI) still has significant impacts on the returns of the property stock market.

Conditional Volatility Measures of Inflation Uncertainty: Evidence from the Greek Experience

This paper investigates the dynamics developed in the relationship between output and prices. It examines the case of Greece which is of particular interest since the Greek economy is currently characterized by surrounding inelasticities and rigidities in labour and goods markets. By using a model of conditional volatility the CPI-inflation is decomposed in two components, one expected and one unexpected. It is argued that there is a strong long-run relationship between the unpredicted inflation and total output for the period examined.

Conditional volatility and the production smoothing hypothesis of inventory investment

This paper introduces a conditional second moment approach to the production smoothing hypothesis of inventory investment. The multivariate ARCH technique makes it possible to calculate the time series of the relevant conditional variances and covariances. The importance of explaining the production and inventory decision rules in terms of the sales anticipation errors is emphasized. The time varying conditional volatility measures suggest that the factors affecting the production and inventory investment are changing over time. It is shown that the buffer stock motive can be the source of production smoothing when firms face unanticipated sales changes, but the stock adjustment behavior may cause production bunching through the intended change in production if the desired stock of inventories is proportional to anticipated sales, and demand shifts are considerably durable.