Intraday Price Formation in U.S. Equity Index Markets

El proposito de esta investigacion es evaluar el efecto de la negociacion del mercado de futuros del indice COLCAP en la volatilidad del mercado accionario colombiano en los anos 2009 al 2018. Se identifica que el modelo AR(1)-TARCH(1,1) es el que mejor se ajusta a los datos, por lo cual se utiliza para explicar el comportamiento de la volatilidad. Los resultados indican que la negociacion del mercado de futuro del indice COLCAP no presento efecto alguno en la volatilidad del mercado accionario colombiano, y el efecto transitorio que se observo se puede asociar a los acontecimientos externos que ocurrieron en el 2011, ano que se caracterizo por su alta volatilidad en el segundo semestre del ano. Tambien, se encontro que la volatilidad del mercado de valores es mas sensible a las noticias malas que a las buenas, es afectado por choques del mercado estadounidense, y el escandalo de Interbolsa no influyo en la volatilidad, pero si en los volumenes de negociacion y liquidez. Teniendo en cuenta el efecto que tiene los choques externos en el mercado se recomienda impulsar el mercado de derivados en Colombia para protegerse frente a estas fluctuaciones.

Efecto del mercado de futuros en la volatilidad del mercado SPOT: caso aplicado al mercado accionario colombiano

Price discovery and spillover effect are prominent indicators in the commodity futures market to protect the interest of consumers, farmers and to hedge sharp price fluctuations. The purpose of this paper is to investigate empirically the price discovery and volatility spillover in Indian agriculture spot and futures commodity markets.,This study uses Granger causality, vector error correction model (VECM) and exponential generalized autoregressive conditional heteroskedasticity (EGARCH) to examines the price discovery and spillover effects for nine most liquid agricultural commodities in spot and futures markets traded on National Commodity and Derivatives Exchange (NCDEX).,The VECM results show that price discovery exists in all the nine commodities with futures market leading the spot in case of six commodities, namely soybean seed, coriander, turmeric, castor seed, guar seed and chana. Whereas in case of three commodities (cotton seed, rape mustard seed and jeera), price discovery takes place in the spot market. The Granger causality tests indicate that futures markets have stronger ability to predict spot prices. Supporting these, the results from EGARCH volatility test reveal that there exist mutual spillover effects on futures and spot markets. Thus, it could be inferred that futures market is more efficient in price discovery of agricultural commodities in India.,These results can help the market participants to benefit by hedging out the uncertainty and the policymakers to design futures contracts to improve the efficiency of the agricultural commodity derivatives market.,The findings provide fresh view on lead–lag relationship between future and spot prices using the latest data confirming that futures market indeed is dominant in price discovery.,There are very few studies that have explored the efficiency of the agricultural commodity spot and futures markets in India using both price discovery and volatility spillover in a detailed manner, especially at the individual agriculture commodity level.

Price discovery and volatility spillover: an empirical evidence from spot and futures agricultural commodity markets in India

The price discovery and spillover effect are significant indicators in futures markets. This study examines the price discovery and spillover effects using vector error correction model and general...

Price discovery and volatility spillover in spot and futures markets: evidences from steel-related commodities in China

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed ...

The linkages, persistence, asymmetry in the volatility, the price discovery and efficiency, and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This paper studies the volatility implications of the introduction of derivatives on stock market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for non-constant error variance in the return series, a GARCH model is fitted by incorporating futures and options dummy variables in the conditional variance equation. We find clustering and persistence of volatility before and after derivatives, while listing seems to have no stabilisation or destabilisation effects on market volatility. The postderivatives period shows that the sensitivity of the index returns to market returns and any day-of-the-week effects have disappeared. That is, the nature of the volatility patterns has altered during the post-derivatives period.

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The impact of derivatives on stock market volatility: a study of the nifty index

This paper analyses information-based superiority of markets mainly with an objective of exploring arbitrage opportunities. It attempts to determine the lead-lag relationship between spot and futures markets in the Indian context by using high frequency price data of twelve individual stocks, observed at one-minute interval. The study applies the concept of co-integration and establishes the spot-futures relationship using Vector Error Correction Mechanism (VECM) represented by EGARCH framework. To study the price discovery process in the two markets, five lags each of one-minute resolution for nine individual stocks and four lags for the remaining three stocks are chosen. The key results of the study are given below: There is a contemporaneous and bi-directional lead-lag relationship between the spot and futures markets. A feedback mechanism of short life is functional between the two markets. Price discovery occurs in both the markets simultaneously. There exists short-term disequilibrium that could be corrected in the next period. Volatility spillover from spot market to futures market is present in such a way that a decrease in spot volatility leads to a decrease in futures volatility. Volatility shocks are asymmetric and persistent in both the markets. Spillover from futures market to spot market is not significant. Neither spot nor futures assume a considerable leading role and neither of the markets is supreme in price discovery. In the case of 33.33 per cent of spot values and 33.33 per cent of futures values, there exists short-term disequilibrium that could be corrected in the next period by decreasing the prices. Spot market volatility spills over to futures market in most of the cases (66.66 %) and a decrease in spot volatility brings about a decrease in futures volatility in 50 per cent of the cases. Spillover effect from futures to spot market is present and significant in 91.66 per cent of stocks and is more than the spillover effect from spot to futures (50% valid cases). The markets are highly integrated. Asymmetric behaviour of volatility shocks is mixed in both the markets. Asymmetric volatility is detected in 50 per cent of the cases of spot market and 58.33 per cent cases of futures market. Stocks exhibiting asymmetric volatility show more sensitivity to negative shocks. There are no cases of market becoming more volatile in response to good news.

E M Afsal

Papers

The impact of derivatives on stock market volatility: a study of the nifty index

Price Discovery Process and Volatility Spillover in Spot and Futures Markets: Evidences of Individual Stocks