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The purpose of this paper is to empirically analyze the “market-neutral” characteristics of the market-neutral strategy hedge funds in Chinese A-share market.

The analyses in the paper are conducted to study the market-neutral characteristics by means of index analysis, correlation analysis, β-neutral analysis and the three-factor model analysis.

The results show that the performance advantage of the market-neutral strategy hedge funds is obvious. Most market-neutral strategy funds are exposed to market risks and the α strategy funds also have obvious style factor exposure; strictly speaking, all of the market-neutral strategies have not reached the “market-neutral” requirements. This paper also finds that Chinese trading restrictions on stock index futures in September 2015 have a significant impact on Chinese market-neutral strategy hedge funds.

The conclusion of this paper has a certain reference value for understanding the risk characteristics and possible problems of hedge funds in emerging markets, and also has important reference value for investors.

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 present an alternative approach to equity trading that is based on cointegration. If there are long-run equilibria among financial assets, a cointegration-based trading strategy can exploit profitable opportunities by capturing mean-reverting short-run deviations.

First, the author introduces an equity indexing technique to form cointegration tracking portfolios that are able to replicate an index effectively. The author later enhances this tracking methodology in order to construct more complex portfolio-trading strategies that can be approximately market neutral. The author monitors the performance of a wide range of trading strategies under different specifications, and conducts an in-depth sensitivity analysis of the factors that affect the optimal portfolio construction. Several statistical-arbitrage tests are also carried out in order to examine whether the profitability of the cointegration-based trading strategies could indicate a market inefficiency.

The author shows that under certain parameter specifications, an efficient tracking portfolio is able to produce similar patterns in terms of returns and volatility with the market. The author also finds that a successful long-short strategy of two cointegration portfolios can yield an annualized return of more than 8 percent, outperforming the benchmark and also demonstrating insignificant correlation with the market. Even though some cointegration-based pairs-trading strategies can consistently generate significant cumulative profits, yet they do not seem to converge to risk-less arbitrages, and thus the hypothesis of market efficiency cannot be rejected.

The primary contribution of the research lies within the detailed analysis of the factors that affect the tracking-portfolio performance, thus revealing the optimal conditions that can lead to enhanced returns. Results indicate that cointegration can provide the means to successfully reproducing the risk-return profile of a benchmark and to implementing market-neutral strategies with consistent profitability. By testing for statistical arbitrage, the author also provides new evidence regarding the connection between the profit accumulation of cointegration-based pairs-trading strategies and market efficiency.

This paper aims to demonstrate a dynamic cointegration-based pairs trading strategy, including an optimal look-back window framework in the cryptocurrency market and evaluate its return and risk by applying three different scenarios.

This study uses the Engle-Granger methodology, the Kapetanios-Snell-Shin test and the Johansen test as cointegration tests in different scenarios. This study calibrates the mean-reversion speed of the Ornstein-Uhlenbeck process to obtain the half-life used for the asset selection phase and look-back window estimation.

By considering the main limitations in the market microstructure, the strategy of this paper exceeds the naive buy-and-hold approach in the Bitmex exchange. Another significant finding is that this study implements a numerous collection of cryptocurrency coins to formulate the model’s spread, which improves the risk-adjusted profitability of the pairs trading strategy. Besides, the strategy’s maximum drawdown level is reasonably low, which makes it useful to be deployed. The results also indicate that a class of coins has better potential arbitrage opportunities than others.

This research has some noticeable advantages, making it stand out from similar studies in the cryptocurrency market. First is the accuracy of data in which minute-binned data create the signals in the formation period. Besides, to backtest the strategy during the trading period, this study simulates the trading signals using best bid/ask quotes and market trades. This study exclusively takes the order execution into account when the asset size is already available at its quoted price (with one or more period gaps after signal generation). This action makes the backtesting much more realistic.

Purpose – This research pinpoints the limitations of conventional models for evaluating the performance of hedge funds and attempts to provide a new framework for modeling the dynamics of risk structures of hedge funds.

Methodology/approach – This chapter aims to explore how the systematic risk exposures of hedge funds vary over time and depend on exogenous variables that managers are supposed to use in their dynamic investment strategies. To achieve this, we used a Bayesian time-varying CAPM-based beta model within a state space technology.

Findings – The results showed that the volatility, term spread rate, and shocks in liquidity influence significantly on the time variation of hedge funds. Besides, the dynamics of beta indicates that the transmission channels of systematic risk are mainly the leverage levels of hedge funds and liquidity shocks.

Originality/value of chapter – These results are original because they help to explain how expected and unexpected hedge fund returns are correlated with the systematic risk factors via the beta dynamics.

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.

Purpose – After tracing the development of the global value chains (GVC) approach, the chapter argues that by refocusing on the international strategies of lead firms it is possible to bring location specificity issues into play and contribute to retrieve a distinctive international content to the GVC governance theory.

Design/methodology/approach – The chapter discusses the GVC governance theory, drawing from recent contributions in the field of international business (IB).

Findings – Although designed to account for the rise of new inter-firm networks controlled by international lead firms, the new GVC theory of governance somehow lacks a distinct international content and, privileging transactional constraints, falls short of explicitly considering variations in lead firm structural characteristics and strategies. An alternative governance schema is then proposed, taking explicitly into account the strategic evaluations that lead firms carry out with regard to their internal resources compared to suppliers’.

Research limitations/implications (if applicable) – The chapter provides the outlines of a new promising international research agenda for GVC researchers. Additional research is needed to further investigate the relation between location specificity, the strategic motives to go global and the international organisation of the value chain.

Practical implications (if applicable) – The alternative governance schema proposed in the chapter aspires to represent a simple tool aimed at supporting managers in the establishment of the appropriate boundaries of the firm.

Originality/value – The chapter shows that both IB research and GVC analysis could greatly benefit from reasoned cross-fertilisation.

Purpose – This chapter aimed to investigate hedge funds market risk. One aims to go further the traditional measures of risk that underestimates it by introducing a more appropriate method to hedge funds. One demonstrates that daily hedge fund return distributions are asymmetric and leptokurtic. Furthermore, volatility clustering phenomenon and the existence of ARCH effects demonstrate that hedge funds volatility varies through time. These features suggest the modelisation of their volatility using symmetric (GARCH) and asymmetric (EGARCH and TGARCH) models used to evaluate a 1-day-ahead value at risk (VaR).

Methodology/Approach – The conditional variances were estimated under the assumption that residuals t follow the normal and the student law. The knowledge of the conditional variance was used to forecast 1-day-ahead VaR. The estimations are compared with the Gaussian, the student and the modified VaR. To sum up, 12 VaRs are computed; those based on standard deviation and computed with normal, student and cornish fisher quantile and those based on conditional volatility models (GARCH, TGARCH and EGARCH) computed with the same quantiles.

Findings – The results demonstrate that VaR models based on normal quantile underestimate risk while those based on student and cornish fisher quantiles seem to be more relevant measurements. GARCH-type VaRs are very sensitive to changes in the return process. Back-testing results show that the choice of the model used to forecast volatility has an importance. Indeed, the VaR based on standard deviation is not relevant to measure hedge funds risks as it fails the appropriate tests. On the opposite side, GARCH-, TGARCH- and EGARCH-type VaRs are accurate as they pass most of the time successfully the back-testing tests. But, the quantile used has a more significant impact on the relevance of the VaR models considered. GARCH-type VaR computed with the student and especially cornish fisher quantiles lead to better results, which is consistent with Monteiro (2004) and Pochon and Teïletche (2006).

Originality/Value of chapter – A large set of GARCH-type models are considered to estimate hedge funds volatility leading to numerous evaluation of VaRs. These estimations are very helpful. Indeed, public savings under institutional investors management then delegate to hedge funds are concerned. Therefore, an adequate risk management is required. Another contribution of this chapter is the use of daily data to measure all hedge fund strategies risks.