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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.

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.

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.

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.

This paper investigates the strategic behavior of algorithmic trading firms from an innovation economics perspective. The authors seek to uncover the sources of competitive advantage these firms develop to make markets inefficient for them and enable their survival.

First, the authors review expected capability, a quantitative behavioral model of the sustainable, or reliable, profits that lead to survival. Second, they present qualitative data gathered from semi-structured interviews with industry professionals as well as from the academic and industry literatures. They categorize this data into first-order concepts and themes of opportunity-, advantage- and meta-seeking behaviors. Associating the observed sources of competitive advantages with the components of the expected capability model allows us to describe the economic rationale these firms have for developing those sources and explain how they survive.

The data reveals ten sources of competitive advantages, which the authors label according to known ones in the strategic management literature. We find that, due to the dynamically complex environments and their bounded resources, these firms seek heuristic compromise among these ten, which leads to satisficing. Their application of innovation methodology that prescribes iterative ex post hypothesis testing appears to quell internal conflict among groups and promote organizational survival. The authors believe their results shed light on the behavior and motivations of algorithmic market actors, but also of innovative firms more generally.

Based upon their review of the literature, this is the first paper to provide such a complete explanation of the strategic behavior of algorithmic trading firms.

This article takes its point of departure from the intellectual milieu in the mid-1980s that gave rise to Luc Boltanski and Laurent Thévenot’s book, On Justification: Economies of Worth. It shows how exposure to ideas and concepts in that book came to take varied forms as they were elaborated and modified in the work of an American sociologist across several decades of research in diverse empirical settings.

The purpose of this paper is to examine the role of derivative securities in over‐pricing and market corrections.

Daily market data from major indices are used to determine if the market was over‐priced in 1987. Then, the literature is examined to show differences in research findings for what caused the bubble and its correction.

Evidence is found that there was a market bubble in 1987. Examples are provided of how portfolio insurance can lead to the aggregation of traders' idiosyncratic errors and to an increase in the use of leverage, both of which can cause over‐pricing.

Although the analysis is limited to equity markets, the findings should stimulate further research on the relationship between derivatives and asset pricing. Theoretically, derivative prices should be a function of asset prices, but it could be argued that the relationship is symbiotic.

The findings may impact policy makers in establishing regulations regarding the use of derivatives. Moreover, asset managers may be able to better detect conditions of over‐pricing.

The paper demonstrates the important role of derivative securities in market prices.

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.

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.