Memory in returns and volatilities of futures' contracts

Abstract

Various authors claim to have found evidence of stochastic long-memory behavior in futures' contract returns using the Hurst statistic. This paper reexamines futures' returns for evidence of persistent behavior using a biased-corrected version of the Hurst statistic, a nonparametric spectral test, and a spectral-regression estimate of the longmemory parameter. Results based on these new methods provide no evidence for persistent behavior in futures' returns. However, they provide overwhelming evidence of long-memory behavior for the volatility of futures' returns. This finding adds to the emerging literature on persistent volatility in financial markets and suggests the use of new methods of forecasting volatility, assessing risk, and optimizing portfolios in futures' markets.

Long Memory and Fractional Integration in High Frequency Data on the US Dollar/British Pound Spot Exchange Rate

“…On the other hand, Baum, Barkoulas and Caglayan (1999) estimated fractional ARIMA (ARFIMA) models for real exchange rates in the post-Bretton Woods era and found almost no evidence to support long run PPP. Additional studies on exchange rate dynamics using fractional integration are those by Crato and Ray (2000), Wang (2004), Dufrenot et al (2006Dufrenot et al ( , 2008 and Aloy et al (2011) among others. All these papers, however, focus on low frequency (mainly quarterly) data, and do not examine the case of high frequency (intraday) data.…”

Exploring frequency of price overreactions in the Ukrainian stock market

“…For example, the downward nature of the asset prices dynamics in the stock market signals about the accumulation of negative phenomena in financial and economic systems; a growing trend indicates a restoration of a favorable economic situation (Grech & Pamula, 2008). Sharp growth of volatility signals about increase of the panic moods in the stock market and allows to detect crisis phases (Crato & Ray, 2000;Kazemi, 2013). The growth of correlations between various assets in the stock market signals about the emergence of crisis phenomena in financial and economic systems (Sandoval & Franca, 2012), the same is true for the market persistence (Caporale et al, 2016).…”

Testing PPP for the South African Rand/US Dollar Real Exchange Rate at Different Data Frequencies

“…For instance, Booth et al (1982) found positive memory (d > 0) during the flexible exchange rate period (1973-79) but a negative one (d < 0, i.e., anti-persistence) during the fixed exchange rate period for the British pound, French franc and Deutsche mark; Cheung (1993) also found evidence of long memory behaviour during the managed floating regime. On the other hand, Baum et al (1999) estimated ARFIMA models and found no evidence of long-run PPP in the post-Bretton Woods era (see also Fang et al, 1994;Crato and Ray, 2000;and Wang, 2004). Caporale and Gil-Alana (2010) also provide some evidence for the Latin American countries.…”