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The empirical studies of the options market efficiency have reported contradictory results, which sometimes confuse practitioners and academicians. The aim of this study was to clarify several aspects of options market efficiency by exploring the answers to two main questions: Under what conditions is the options market more efficient? Are the discrepancies in the estimated efficiency due to the reality of efficiency or mismeasurement?

Using a meta-analysis approach, 54 studies have been analyzed, which included 1,315 tests. The sum of the observations for all of the tests is 3.7 m observation sets. The effect size (type r) has been used to compare the different statistics in different studies. The cumulative effect size and its diversification have been calculated by the random effects model and Q statistic, respectively.

The most interesting finding of the study was that the options market, in all circumstances, is significantly inefficient. Another important finding was that the heterogeneity of options market efficiency is due to the complexity of pricing relations, test time, violation index and price type. To overcome this heterogeneity and accuracy, future studies should test the no-arbitrage options pricing relations at different times and by different price types, using complex and simple pricing relations and either mean violation or violation ratio efficiency measures.

Public disagreement about the options market efficiency in past studies means that this variable is heterogeneous in different conditions. As a significant contribution, this study develops the literature by proposing the causes of options market efficiency heterogeneity.

The purpose of this paper is to investigate the strategy that a turnaround in the USA will portend a turnaround in the UK's economy and property market. For this strategy to operate, it is assumed that the capital and property markets in and between the two nations are highly integrated with endogenous pricing functions.

Given the endogenous assumptions of the conjectured research statement, tests of integration (or segmentation) between two capital and property markets are conducted. Correlation, tracking error analysis, and a multiple systematic risk factor model are used to test the pricing relationships. The methodological form employs variant macroeconomic variable pricing models (MVM) of alternative combinations of systematic affects operating across and between the national markets.

Pricing integration is noted between the UK and US capital markets, while the property markets are economically and statistically segmented. Opportunities for arbitrage based on different prices/returns for equivalent risk exposures are statistically observed between the UK and USA. The effect is that systematic pricing between the two markets cannot be addressed solely by diversification options. This infers a potential for arbitrage (statistically, strategically or in practice) is possible, given that systematic risk exposures between the two markets are not equivalently priced across cyclical phases. In this context it is inferred that the probable measure of pricing differences across the two markets is more than a cyclical lag effect.

The paper delineates the degrees of integration/segmentation in the UK and US property and capital markets as a function of systematic risks in changing economic conditions. These differences support the existence of statistical arbitrage and the specification of investment behaviour as a function of differencing pricing expectations. These findings can assist in the formulation of investment and hedging strategies to assist in managing international portfolios subject to cyclical market exposures. This paper contributes to an understanding of and foundation for testing the nature and impact of cycles on property investment performance as a function of pricing changes.

This study explores the arbitrage profitability of the KOSPI200 futures spread, using intraday data during 10 days prior to the expiration day of each contract for the 9/3/2001 ∼ 6/912005 period. The theoretical frameworks for arbitrage strategies were developed for the analysis. Our results show that 97.36% of the total 8.633 observations were fairly priced. 1.46% (126 observations) were underpriced, and 1.18% (102 observations) were overpriced, in the ex post arbitrage profitability analysis between the futures spread and the calendar spread. Also, in the arbitrage profitability analysis based on the mispricing of the KOSPI200 futures spread against the theoretical price. 90.39% of the total 10.054 observations were fairly priced and 9.61 % (966 observations) were underpriced. There was no overpriced observation. The ajority of those underpriced observations were concentrated in the 3rd Quarter of 2001 and the 1st quarter of 2003. Overall, there were very few arbitrage opportunities except for the introductory period and some contracts with high uncertainty, implying that the KOSPI200 futures spread market has been generally efficient.

Using volatility cones as the estimate of actual volatility instead of GARCH models, the purpose of this paper is to explore whether volatility arbitrage strategy can provide positive profits and how the transaction costs existed in the real market affect the effectiveness of volatility arbitrage strategy.

A number of hedging approaches proposed to improve the hedging results and final returns of Black-Scholes model are analyzed and compared.

The general finding is that volatility arbitrage strategy can provide satisfactory returns based on the samples in Chinese market. Regarding transaction costs, the variable bandwidth delta and delta tolerance approach showed better results. Besides, choosing futures together with ETFs as hedging underlying can increase the VaR for better risk management.

This paper offers a new method for volatility arbitrage in Chinese financial market.

This paper researches the profitability of the volatility arbitrage strategy on ETF 50 options using volatility cones method for the first time. This method has advantage over the point-wise estimation such as GARCH model and stochastic volatility model.

We investigate the frequency of arbitrage opportunities and the size of their profits in the options and futures markets of KOSPI200 index. A thread of existing studies shows that these opportunities arise frequently, albeit the frequency is decreasing as the market matures. These studies, however, use transaction data in their analysis. Using the transaction data tends to overestimate both the frequency and the size of arbitrage gains, since it ignores the transactions cost imbedded in the bid-ask spread. In this study, we use the quote data to correctly reflect the transactions cost in executing the trades to take advantage of an arbitrage opportunity. By using the data spanning the period from Sep. 3, 2001 to Mar. 29. 2002, we show that both the frequency and size of arbitrage gains are much smaller than those when transaction data are used instead of Quote data. We also find that the Individual traders are the primary source that provide the arbitrage opportunities.

This study investigates the impact of program trading on the market volatility by separating the volatility into long-run and short-run components using VA-CEGARCH model. This approach allows us to observe the two channels through which the program trading affects the market volatility. We have following results. Program trading and non-program trading both have no impact on the long-run component but do increase short-run component. In case of short-run component‘ program trading has a larger impact compared to non-program trading. Secondly, in both daily and intra-day analysis, arbitrage program trading is found to have a larger impact on short-run components than non-arbitrage program trading.

Thirdly, ARCH effects are found in short-run components of daily analysis and long-run components of intra-day analysis. And the volatility’s asymmetric responses to good or bad news are introduced through long-run components. What is noteworthy is the fact that non-arbitrage program trading is actually found to reduce short-run volatility in the intra-day analysis.

Which means that non-arbitrage program trading, such as hedging transactions, helps promote intra-day market stability. Our findings mean that the short-run component is the main channel by which program trading produce unnecessary market volatility.

The purpose of this paper is to examine the risk of inefficiency of China's stock index futures market by investigating the opportunity and profitability of exchange‐traded fund (ETF) arbitrage. The explanation of behavioral risk to market efficiency is examined.

Based on cost‐of‐carry model, some assumptions about market efficiency were examined, and statistical tests were implemented to support the findings.

In China, borrowing and lending interest rates are quite different; dividends are small and paid in an irregular manner; and short sale cannot be used in arbitrage by all investors. It is found that the Chinese index futures market is far from efficient.

With reference to the empirical study, this is believed to be the first application of behavioral study to the study of market efficiency. The analysis of the statistics about Chinese index futures market and the algorithm parameters are very valuable for in‐depth understanding of the emerging markets.

The research for this paper focuses on the implied expected exchange rates between the U.S. dollar and the Deutsche Mark. We use one year debt yield and one year inflation forecasts to derive expected exchange rates based on uncovered interest arbitrage and on the purchasing power parity relationship. We also explore the explanatory power of combinations of these two alternative expected exchange rates including what they might reveal regarding exchange rate premiums. Our results indicate that a combination of the two approaches which models a risk premium may be beneficial. We indicate some further work to be done along this line and provide a summary and conclusion based on the work reported here.

This study aims to examine the cross-market efficiency of the FTSE/MIB index options contracts traded on the Italian derivatives market (IDEM) during a period including the financial crisis between 1st October 2007 and 31st December 2012 using daily option prices.

Two fundamental no-arbitrage conditions were tested: the lower boundary condition (LBC) and the put–call parity (PCP) condition while taking into account the role of transaction costs in mitigating the number of violations reported. Ex post tests of LBC and PCP revealed a low incidence of mispricing in this market. Furthermore, to check the robustness of the results obtained by the ex post tests, ex ante tests were applied to PCP violations occurring within a one-day lag.

The results showed a significant drop in the number of profitable arbitrage strategies. The findings obtained from all these tests generally support the cross-market efficiency of the Italian index options market during the sample period, though some violations were occasionally reported. Overall, the number and monetary value of the violations reported declined during the post-financial crisis period compared to those during the financial crisis period.

This study can be extended to test the relationships between arbitrage profitability and other factors such as the moneyness (in the money, out of the money, at the money) of options and the maturity of options. Options market efficiency tests can be conducted such as call and put spreads, box spreads and put/call convexities (butterfly spreads).

There are several factors that influenced the decision to test the Italian index options market. First, the limited number of studies conducted on this market. Second, the fact that the two main studies on this market are relatively old, which makes it interesting to test the efficiency of this market with respect to a new set of data, taking into account the introduction of the Euro and the impact of the recent financial crisis on this market and whether the market efficiency hypothesis holds during the period of crisis. Third, it is important to consider the effect of the new rules applied to this market.

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange rate policy shocks as China introduces gradual reforms to make its exchange rate regime more flexible. The paper aims to discuss this issue.

The authors characterize the specification of the discrete-time AFNS model, prove the uniqueness of the solution for model identification, perform specification analysis on its canonical form and detail the MCMC estimation method with a fast and reliable prior extraction step.

Model decomposition reveals that in the US yield responses, changes in risk premia for medium- to long-term yields dominate changes in yield expectation for short- to medium-term yields, indicating that the portfolio rebalancing effect due to varying risk perception is stronger than the signaling effect due to policy rate expectation.

The results are helpful in diagnosing market sentiment and exchange rate risk pricing as China further internationalizes its currency.

The methodology can be easily extended to study yield curve responses to other scenarios of policy shocks or regime changes.