Run Volatility Research Articles

Volatility Spill-Over and Financial Contagion Effect of Conventional Stock on Islamic Equity in Nigeria: Evidence from Covid-19

This study empirically investigated volatility spill-over and financial contagion effect between conventional stocks and shariah compliant equities before and during covid-19 pandemic in Nigeria. Banking and insurance sectoral stocks indices were selected to represent conventional equities while Nigerian stock exchange lotus islamic index represent islamic stocks. Daily closing stock price data from 02-01-2018 to 26-02-2020 for pre-covid and 27-02-2020 to 31-12-2021 for pre-covid and during covid were considered. DCC-GARCH model (Dynamic conditional correlation- Generalized Autoregressive Conditional Heteroskedasticity Model) was deployed to examine the spill-over effect while t-test was applied to check the consistency of the DCC coefficient before and during the pandemic. The result of the multivariate GARCH show that both banking and insurance stocks have long run volatility spillover effect on lotus islamic index, the result also revealed no significant increase in conditional correlation during covid-19 pandemic which indicate absence of financial contagion from the conventional to islamic stocks. The results provide important information to researchers, investors, and policymakers

Deterministic Effects of Volatility on Mixed Frequency GARCH in Means MIDAS Model: Evidence from Turkey

Volatility is a key concept for understanding the dual relationships between the economic variables since it is inversely related to the stability of economies. Many models such as GARCH models have been constructed through time to understand which determinants and conditions can affect the volatility. These models mostly show the significant relationships between the volatilities generated by the low frequency macroeconomic activities and the high frequency financial variables in a stochastic way. However, it is required to check whether there exist deterministic effects of volatilities on high frequency economic variables. In order to reveal these deterministic effects, we developed a new component-wise model, namely GARCH-M MIDAS model. We formulate this model on stock prices and exchange rates, in which long run volatility is driven by consumer price and industrial production indexes in a separate way. Hence, our empirical analysis supports that both types of the volatilities have statistically significant deterministic effects on the asset pricing of high frequency financial variables. We also find that macroeconomic activities have a significant role on the asset pricing in long horizons.

Contagion effects in ASEAN-5 exchange rates during the Covid-19 pandemic

The aim of this study is to examine the pure and fundamentals-based contagion effects in ASEAN-5 exchange rates during Covid-19 period using daily exchange rates from June 2019 to December 2020. We adopt VECM within the structural VAR framework and higher time–frequency wavelet analysis. The VECM findings show that ASEAN-5 exchange rates are cointegrated during this pandemic and should there be any disequilibrium, daily rate of adjustments in the Indonesian rupiah, Malaysian ringgit and Singapore dollar are 6.58%, 1.47% and 2.45% respectively. The wavelet power spectrum implies that Indonesia, Malaysia and Singapore experience prolonged high degree of exchange rates volatility, Thailand experiences mild volatility in the short run and high volatility in the long run and only Philippines experiences mild volatility in the short run and no heightened long run volatility. The wavelet coherence shows Indonesian rupiah reacts first to the Covid-19 shock leading to fundamentals- based contagion to Malaysia and Thailand, and temporary pure contagion based on sentimental to Philippines and Singapore. Only the Philippine peso that insulates itself from the long run shocks. These findings are important as it gives insights into the nature of contagion among ASEAN-5 exchange rates due to global shock of Covid-19 and the need for timely intervention to prevent the short run contagion turning into the long run.

Investigating Short and Long Run Volatility Movements in the Context of COVID-19 Pandemic: A Case Study for Norwegian Stock Market

Investigating Short and Long Run Volatility Movements in the Context of COVID-19 Pandemic: A Case Study for Norwegian Stock Market

The Impact of Interest Rate Volatility on Stock Returns Volatility: Empirical Evidence from Pakistan Stock Exchange

Apprehension pertaining to Stock return volatility always has been producing the appreciable significance in the various current research works and it has been lucrative to many researchers for forecasting stock market volatility. This study is about the forecasting of stock returns volatility on the basis of interest rate volatility in the well established Pakistan Stock Exchange (PSX). The stock returns are calculated on the basis of KSE 100 index and interest rate volatility is calculated on the basis of monthly treasury bills rate during a period of 1994 to 2016. Various volatility models like Auto Regressive Conditional Heteroscedasticity (ARCH) and Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) were used to predict stock return volatility on the basis of interest rate volatility in Pakistan. ARCH model is one of the well known methods to forecast the error term in the data and which will certain our forecast regarding stock prices. In the Pakistan Stock Exchange the ARCH (1, 1) has been statistically significantly proved. The GARCH (1, 1) model is also used to estimate the stock volatility. This model shows the short run volatility affect the lagged stock returns and is contributing to the overall volatility. The sum of α and β is less than 1 so the short run volatility is positively related to the overall stock volatility. The GARCH (1, 1) model has outperformed the other volatility models in the case of Pakistan Stock Exchange.

Nexus between financial innovations, remittances and credit performance: Evidence from augmented ARDL and nonlinear ARDL

The motivation for this study is to assess the impact of financial innovation and remittances on bank-based financial institutions’ credit performance in Bangladesh for the period 1981–2019. The study applies augmented ARDL (AARDL) and nonlinear ARDL (NARDL) to identify both long-run and short-run effects and directional causality by performing non-granger casualty tests. AARDL confirms the presence of a long-run association between financial innovation, remittance, trade openness, FDI, and credit performance, which is measured by non-performing loans. In the long run, financial innovation and FDI volatility expose a positive link with NPLs, but remittance inflows and trade openness establish a negative association. Asymmetry shocks in financial innovation reveal a positive relationship with credit performance. In contrast, the asymmetric shock of remittance and trade openness unveil a negative tie to credit performance, especially in the long run. Furthermore, directional causality provides evidence to support a feedback hypothesis explaining causality between financial innovation and credit performance, as well as remittance inflows and credit performance. These findings suggest that credit performance is guided by future development in remittances and financial innovation; thus, closer attention from policymakers and financial experts is persistent to capitalize or mitigate the impact of the financial system.

Mean-Reversion in Commodity Futures Volatility: An Analysis of Daily Range-Based Stochastic Volatility Models

We analyse the dynamic behavior of conditional volatility in commodity markets using a novel, manually collected dataset of daily price ranges over a time span of more than 140 years, which allows more precise daily volatility estimates than are otherwise prevalent in the commodity literature. We find that a one-factor range-based EGARCH-model (REGARCH) is not adequate to capture the very distinct long-run and short-run dynamic volatility components. While the long memory effect of volatility is numerically very small, it strongly affects the parameters of the short-run dynamics which become more stable and plausible in size. Moreover, long-run persistency in volatility shocks is practically unaffected after controlling for regimes which indicates that the stochastic movement of the long-run mean is not a statistical artefact. We also find that consistent with the theory of storage, long run volatility is positively related to lagged returns. Thus, asymmetry in volatility is not a short-run phenomenon.

Insurance against Long-Run Volatility Risk: Demand, Supply, and Pricing

Despite its importance implied in asset pricing and macroeconomic models, insurance against long-run volatility risk has received little empirical documentation regarding its demand, supply, or pricing. This paper bridges the gap. First, I show that households have directly purchased large quantities of insurance against long- run volatility risk through the minimum return guarantees available in variable annuities, a form of retail retirement and savings product offered by life insurance companies. Total net assets with such insurance grew from zero when the guarantees were first introduced in the early 2000s to close to $1 trillion in 2015. To supply the guarantees to households, life insurance companies hedged themselves with large quantities of long-maturity (> 5Y) options and variance swaps, which led to a sharp increase in the prices of these long-term volatility assets: the ten- year implied volatility increased from 20.0% before 2000 to 27.3% afterwards while the short-term counterpart (VIX) has remained unchanged (from 19.2% to 19.7%). Insurers’ hedging activities therefore explain the significant steepening of volatility term structure in the early 2000s. Relative to the price they paid on hedging, how- ever, the price that life insurance companies charged on the guarantees was much lower, at 15.2% implied volatility prior to the Great Recession. I show evidence of extensive product-cross subsidization – under-pricing of guarantees was used to induce sales and lock in customers that would be subject to over-priced base fees and mutual fund expenses.

U.S., European, Chinese economic policy uncertainty and Moroccan stock market volatility

We investigate the impact of economic policy uncertainty in the U.S., France, Spain, Germany, the U.K., Italy and China on the long run volatility in the Moroccan stock market. For this reason, we combine both daily returns and monthly uncertainty data in the GARCH-MIDAS model. We decompose total volatility into a long run persistent component and short run cyclical component. This study will contribute to stock market research and international economic policy uncertainty (EPU).Our findings show that, before the global financial crisis (GFC) of 2008, the link between the Moroccan stock market and the EPU is generally insignificant for the long run volatility component, namely for France and Spain. However, this effect was relatively significant with the U.S. and German economic policy uncertainty. This result means that the total variance was more explained by the short run volatility component generated by daily stock market returns. Nevertheless, during the post-crisis period we compare our results with benchmark GARCH models by using the AIC criterion and variance ratios values. They display that almost all GARCH-MIDAS models with economic policy uncertainty perform significantly in explaining the long run volatility in the Moroccan stock market, particularly, the EPU of France, Spain and the US.Our paper findings could be very helpful for policy makers and portfolio managers. Understanding the long-term relationship between the Moroccan stock market volatility and international economic policy uncertainty can be crucial in terms of adopting efficient decisions. They can also improve the efficiency of asset allocation for investors.

Long Run and Short Run Risk Premium in Currency Market

In this paper, I investigate risk premium of long run and short run volatility component of exchange rate returns in currency market. I find that high interest rate currencies of carry trade strategy load negatively on long run volatility innovation, while low interest rate currencies load positively. Risk price of long run volatility innovation is negative which implies that high carry trade returns are considered as compensation for time varying long run volatility risk. In contrast, risk price of short run volatility innovation is positive. Low interest currencies deliver low returns and high interest rate currencies yield high returns under times of high short run volatility. In terms of momentum strategy, risk price of short run volatility innovation is negative and statistically significant, while risk price of long run component is insignificant. Therefore, long run volatility does not provide any explanation for high returns of currency momentum strategy. High momentum returns, on the other hand are reward for investors to bear short run volatility risk.

Os Efeitos Alavancagem e Feedback na Volatilidade do Mercado Acionário Brasileiro

O objetivo deste estudo foi realizar uma comparação das volatilidades entre o segmento tradicional e o Novo mercado da BOVESPA de janeiro de 2008 a dezembro de 2012. Além disso, investigou-se a relação retorno das ações e sua volatilidade por meio das teorias da Alavancagem e Feedback. Como método, estimaram-se modelos ARCH/GARCH e regressões por Mínimos Quadrados Ordinários. As evidências empíricas mostram que a volatilidade das ações que fazem parte do novo mercado, é menos reativa e mais persistente quando comparada ao segmento tradicional. Os resultados empíricos revelam também que a volatilidade de longo prazo e a velocidade de convergência para o nível de longo prazo, foi menor para as ações com melhores práticas de governança. Além disso, pode se argumentar que tanto o efeito Alavancagem quanto o efeito Feedback não são os principais fatores explicativos da relação entre o retorno das ações e sua volatilidade, corroborando a teoria comportamental.

A time-varying long run HEAVY model

We propose a scalar variation of the multivariate HEAVY model of Noureldin et al. (2012) featuring a time-varying long run (co)volatility component coupled with DCC dynamics. The new model outperforms the original HEAVY model by delivering more accurate multi-step-ahead predictions.

On the Long Run Volatility of Stocks

In this paper we investigate whether or not the conventional wisdom that the volatility per period of stocks is lower over longer horizons. Taking the perspective of an investor, we evaluate the predictive variance of k-period returns for different models and prior specifications. We adopt the state space modeling framework of Pastor and Stambaugh [2012] as we feel it is the best alternative for capturing all important expected returns dynamics and accounting for the associated uncertainties. Part of the development includes an extension of the modeling framework to incorporate time-varying volatilities and covariances in a constrained prior information set up. We conclude, that in the U.S. market, there are plausible prior specifications such that stocks are indeed less volatile in the long run. Our results are supported by model assessment exercises that provide evidence to our assumptions. To understand the generality of the results, we extend our analysis to a number of international equity indices.

A Likelihood-Based Comparison of Macro Asset Pricing Models

We develop a model in which asset prices depend on long run growth, long run volatility, habit, and a persistent residual. We estimate the model using Bayesian methods which account for the entire likelihood of the data on consumption growth, dividend growth, and the price-dividend ratio. The residual is dominant, accounting for 60% of the variance of the price-dividend ratio. Moreover, the filtered residual tracks most of the recognizable features of the U.S. stock market, such as the late 1990's boom and bust. Long run volatility also plays a significant role, accounting for 30% of the variance, but it contributes primarily in rare crises. Long run growth and habit contribute 15% and 1%. These results show that while long run risks play a non negligible role, something else is driving the bulk of stock market fluctuations. Estimations under alternative priors show that the low correlations between asset prices and conditional moments of consumption growth underlie the large role for the residual.

BSE SME Equity Financing Platform: A study of Index Risk-Return Paradox

The study attempts to introduce an innovative initiative of the BSE's SME equity financing segment and explore the time varying risk-return relationship of the BSE SME IPO index by employing GARCH-M, TGARCH-M, EGARCH-M and Asymmetric CGARCH models. The results spotlight the existence of a positive risk-return relationship between short run volatility component and the actual returns, whereas a negative relationship has been observed between the long run volatility and index returns. The results reported by the GARCH-M, EGARCH-M and TGARCH-M model in the context of the BSE SME IPO index shows insignificant, but a positive relationship between the risk and return. A positive shock has a more pronounced impact on volatility in case of the BSE SME IPO segment. A study relating to the relationship between the index risk and returns is an imperative task to be performed by the existing and prospective investors.

Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks

In this paper, we re-examine two important aspects of the dynamics of relative primary commodity prices, namely the secular trend and the short run volatility. To do so, we employ 25 series, some of them starting as far back as 1650 and powerful panel data stationarity tests that allow for endogenous multiple structural breaks. Results show that all the series are stationary after allowing for endogenous multiple breaks. Test results on the Prebisch–Singer hypothesis, which states that relative commodity prices follow a downward secular trend, are mixed but with a majority of series showing negative trends. We also make a first attempt at identifying the potential drivers of the structural breaks. We end by investigating the dynamics of the volatility of the 25 relative primary commodity prices also allowing for endogenous multiple breaks. We describe the often time-varying volatility in commodity prices and show that it has increased in recent years.

VPIN and the flash crash

The Volume-Synchronized Probability of Informed trading (VPIN) metric is introduced by Easley, López de Prado, and O'Hara (2011a) as a real-time indicator of order flow toxicity. They find the measure useful in monitoring order flow imbalances and conclude it may help signal impending market turmoil, exemplified by historical high readings of the metric prior to the flash crash. More generally, they show that VPIN is significantly correlated with future short-term return volatility. In contrast, our empirical investigation of VPIN documents that it is a poor predictor of short run volatility, that it did not reach an all-time high prior, but rather after, the flash crash, and that its predictive content is due primarily to a mechanical relation with the underlying trading intensity. We also investigate a later incarnation of VPIN, stemming from Easley, López de Prado, and O'Hara (2012a), and reach similar conclusions. In general, we stress that adoption of any specific metric for order flow toxicity should be contingent on satisfactory performance relative to suitable benchmarks, exemplified by the analysis we undertake here.

Robust Estimation of Semiparametric Multiplicative Volatility Models

We investigate a model in which we connect slowly time varying unconditional long-run volatility with short-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility is totally unspecified whereas the short-run conditional volatility is a parametric semi-strong GARCH (1,1) process. We propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory of the proposed estimators. Numerical results lend support to our theoretical results.

Testing the Prebisch-Singer Hypothesis Since 1650: Evidence from Panel Techniques that Allow for Multiple Breaks

In this paper, we re-examine two important aspects of the dynamics of relative primary commodity prices, namely the secular trend and the short run volatility. To do so, we employ 25 series, some of them starting as far back as 1650 and powerful panel data stationarity tests that allow for endogenous multiple structural breaks. Results show that all the series are stationary after allowing for endogeneous multiple breaks. Test results on the Prebisch-Singer hypothesis, which states that relative commodity prices follow a downward secular trend, are mixed but with a majority of series showing negative trends. We also make a rst attempt at identifying the potential drivers of the structural breaks. We end by investigating the dynamics of the volatility of the 25 relative primary commodity prices also allowing for endogenous multiple breaks. We describe the often time-varying volatility in commodity prices and show that it has increased in recent years.

Testing the Prebisch-Singer Hypothesis since 1650: Evidence from Panel Techniques that Allow for Multiple Breaks

In this paper, we re-examine two important aspects of the dynamics of relative primary commodity prices, namely the secular trend and the short run volatility. To do so, we employ 25 series, some of them starting as far back as 1650 and powerful panel data stationarity tests that allow for endogenous multiple structural breaks. Results show that all the series are stationary after allowing for endogeneous multiple breaks. Test results on the Prebisch-Singer hypothesis, which states that relative commodity prices follow a downward secular trend, are mixed but with a majority of series showing negative trends. We also make a first attempt at identifying the potential drivers of the structural breaks. We end by investigating the dynamics of the volatility of the 25 relative primary commodity prices also allowing for endogenous multiple breaks. We describe the often time-varying volatility in commodity prices and show that it has increased in recent years.