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The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus improve market efficiency.

Using nonparametric fixed effect panel data model, the authors build pricing model of convertible bonds and obtain fitted value for them. Then the authors constructs simultaneous confidence band for the smooth function to identify mispricing and study the pricing efficiency and arbitrage opportunities of convertible bonds.

Result shows, convertible bonds’ prices largely depend on stock prices. Pricing efficiency does not improve during the past few years as there are quite a few trading opportunities. Arbitrage opportunities increase as the stock prices approach it maxima, and selling opportunities for convertible bonds surpass buying opportunities which indicates that investors use market neutral strategies to arbitrage. Pricing efficiencies varies a lot and it is affected by the features of the stocks and convertible bonds. Index stocks eligible for margin trading with high liquidity enjoy higher pricing efficiency.

The study does not take into account trading cost and risk management measures.

Arbitrage between the underlying and the convertible bonds is profitable and contributes to pricing efficiency therefore should be encouraged. The regulator should pay attention to the extreme mispricing of the underlying and convertible bonds which cannot be corrected by the market as there might be manipulation.

Since traditional pricing methods are based on the framework of non-arbitrage equilibrium with the assumption of balanced and perfect market, there are many restrictions in the pricing process and the practical utility is somewhat limited, and the impractical assumptions lead to model risk. This study uses nonparametric regression to study the pricing of convertible bonds thus circumvents the problem of model risk. Simultaneous confidence band for smooth function identifies mispricing and explicitly reflects the variation of pricing efficiency as well as signalizes trading opportunities. Application of nonparametric regression and simultaneous confidence band in derivative pricing is advantageous in accuracy and simplicity.

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.

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.

This study explores the arbitrage profitability of box spread strategies to test the KOSPI200 options market efficiency. using minute-by-minute data for the December 2003 - June 2004 period. The sample consists of 39.445 and 38.318 observations for small discrepancy and large discrepancy in exercise prices. respectively.

In the case of credit box spreads, there were 681 (2%) and 2.293 (6%) arbitrage observations for small and large discrepancies, while debit box spreads showed 831 (2%) and 3.098 (8%) observations for small and large discrepancies. In general, mean profit and median profit were different, and the arbitrage profit varied over time. The time to option expiration did not impact the arbitrage profit.

Also, the arbitrage profit of box spreads was significantly higher on Fridays for large discrepancy, and it varied across weekdays except the case of small-discrepancy debit box spread. Both arbitrage opportunities and profits substantially decreased as execution time increased. Our overall results suggest that the KOSPI200 options market has been efficient.

The paper's aim is to explore the impact of statistical arbitrage and high-frequency trading as hedge fund investment strategies that have a significant impact on the environment of corporations.

The paper is a meta-analysis of the role of investment strategies within complex systems.

The growth of hedge fund investment activity based on statistical arbitrage tends to produce a vulnerability; more funds using the strategy helps to create the profitable outcomes that the strategy relies upon. However, the growth also reduces the time lines of profitability and produces an underlying instability based on overlapping holdings and the use of leverage. The shortened timelines also create a further impetus towards technological competition and promotes high frequency trading, which then introduces further vulnerabilities based on “stop-loss cascades”.

Much of the trading creates a superficial form of liquidity, which gives a limited sense of market vulnerabilities. The basis of complex interactions between high frequency traders is also not clearly understood. Researchers and agents of policy ought to pay greater attention to the issues than is currently the case.

The area is one that is under-researched.

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 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.

The purpose of this paper is to examine whether investors’ sentiment affects accruals anomaly across European countries.

The authors estimate the model using Fama–MacBeth regressions. The sample includes 54,572 firm-year observations for 4,787 European firms during the period 1994–2014.

The authors find that investors’ sentiment influences accruals mispricing across European countries. The effect is pronounced for stocks whose valuations are highly subjective and difficult to arbitrage. The cross-country analysis provides evidence that sentiment influences accruals anomaly in countries with weaker outside shareholder rights, lower legal enforcement, lower equity market development, higher allowance of accrual accounting and in countries where herd-like behavior and overreaction behavior are strong.

The findings suggest the generalizability of the sentiment-accruals anomaly relation in European countries characterized by different cultural values, levels of economic development and legal tradition.

The findings suggest to caution individuals investors. These investors would be wise to take into account the impact of sentiment on the performance of their portfolio. They must keep in mind that periods of high optimism are accompanied by a high level of accruals and followed by low future stock returns.

The research supplements previous American studies by showing the significance of the level of sentiment in understanding the accruals anomaly in Europe. Hence, it is important for future studies to consider investor sentiment as an important time-series determinant of the accruals anomaly, particularly for stocks that are hard to value and difficult to arbitrage.

We examine the impact of the unique Japanese stock market microstructure on the pricing of stock index futures contracts. We use intraday transactions data for the Nikkei 225 Futures contracts in Osaka and the corresponding Nikkei 225 Index in Tokyo. Incorporating more realistic transaction-cost estimates and various institutional impediments in Japan, we find that the time-varying liquidity of some component shares of the index in Tokyo represents the most critical impediment to intraday arbitrage and often causes futures prices in Osaka to deviate significantly and persistently from their no-arbitrage boundary, especially for longer-lived contracts.

The purpose of this paper is to investigate the reasons that urge US banks to securitize.

The authors apply a logistic regression model to a sample of 5,394 observations. The dependent variable takes 1 if the bank securitizes and 0 if not. The authors use also, a Heckman selection model to account for the potential dependence between the decision to securitize and the decision of which assets to securitize.

The results indicate that liquidity, credit risk transfer, regulatory capital arbitrage and profitability are the most important factors that drive securitization in the USA. Moreover, the nature of the asset securitized appears to be dependent on the objective that the bank pursues. For funding and capital arbitrage objectives, the bank needs to securitize its mortgage loans. However, for credit risk transfer purposes, it has to opt for a non mortgage securitization. The nature of the asset securitized can thus, be used as a signal for bank’s intentions to securitize.

This study contributes to a better understanding of the reasons that urge banks to securitize. It also presents, using a Heckman selection procedure, a detailed analysis that discriminates between different types of securitization.