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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.

The purpose of this paper is to empirically examine whether investor attention is a significant risk pricing factor.

Using investor attention data from Eastmoney.com, which provides for each stock the number of investors whose watch list includes that stock on a daily basis, this paper constructs a “heat” factor based on the change in investor attention and a “market exposure” factor based on the proportion of attention on a given stock over the attention to all stocks. Using the Fama−MacBeth two-step regression and a rolling analysis, this study examines the ability of the investor attention factor to explain market returns.

The empirical results show that there exists a risk premium for the “heat” factor and “market exposure” factor that is significantly different from zero. This finding shows that investor attention can systematically influence stock returns, making it a significant risk pricing factor.

This paper’s research on the risk pricing factors of investor attention can help investors to rationally build investment portfolios, avoid risks and form a sound investment concept, which will further reveal the information recognition mechanism of the capital market and standardize the information disclosure behavior of listed companies.

This paper provides evidence that investor attention is a risk pricing factor for the stock market. There are “heat” factors and “market exposure” factors in the Chinese stock market that significantly affect the purchasing behavior of individual investors.

In counterparty credit risk management for swaps, forwards, and other derivative contracts, it is recognized that most common applications of credit exposure measurement suffer from the bias that counterparty default is independent of the amount of exposure. Stress tests are often proposed to compensate for this bias, but these measures tend to be arbitrary and cannot be uniformly applied to setting prices and limits as readily as more standardized approaches. The author proposes a framework in which standard measures of counterparty exposure are conditioned on default probabilities. These conditional measures thus account for “rong way” exposures, but fit naturally into current applications.

In this study, we produce mean-variance efficient portfolios for various universes in the U.S. equity market, and show that the use of a composite of analyst earnings forecast, revisions, and breadth variable as a portfolio tilt variable and an R&D quadratic term enhances stockholder wealth. The use of the R&D screen creates portfolios in which total active return generally rise relative to the use of the analyst variable. Stock selection may not necessarily rise as risk index and sector index returns are affected by the use of the R&D quadratic term. R&D expenditures of corporations may be integrated into a mean-variance efficient portfolio creation system to enhance stockholder returns and wealth. The use of an R&D variable enhances stockholder wealth relative to the use of capital expenditures or dividends as the quadratic term. The stockholder return implications of the R&D quadratic variable are particularly interesting given that most corporations allocate more of their resources to capital expenditures than R&D.

This study aims to examine whether mutual funds can earn daily alpha and time daily market return.

Based on the Treynor and Mazuy (1966) model and the Henriksson and Merton (1981) model, the author tests the daily market-timing ability of actual mutual funds and bootstrapped mutual funds.

The author finds that daily alpha and daily market-timing ability can come from pure luck. In addition, the relation between fund alpha and market-timing ability is at best minimal.

Using bootstrapped funds as the benchmark, this study shows that daily fund market is overall efficient.

Hedge fund replication gained considerable attention during the period surrounding 2007 when it was anticipated to become for hedge fund investors what index funds are for equity investors. The hedge fund replication concept only lacked a track record. This paper aims to present an updated evaluation.

Performance is evaluated on both a raw‐return basis and a risk‐adjusted basis using Fung and Hsieh's 8‐factor model. Particular emphasis is given to analyzing the performance of these products during the financial crisis and to highlighting the specific characteristics that distinguished them from their hedge fund cousins during this period.

The results show that the hedge fund replication space is definitely proving its existence as a credible hedge fund investment alternative. Talented hedge fund managers will always be in high demand, but they may have to just prove their high compensation a bit harder.

Although this study is based on a short sample period, the results indicate that hedge fund replication products delivered returns that were at par with the returns of hedge funds. The replication products performed comparatively well during the crisis probably as a result of having less exposure to illiquid assets.

To the best of the authors' knowledge, this article uses the most extensive data set of 22 hedge fund replication products to analyze their performance.

A composite sentiment index (CSI) from quantitative proxy sentiment indicators is likely to be a lag sentiment measure as it reflects only the information absorbed in the market. Information theories and behavioral finance research suggest that market prices may not adjust to all the available information at a point in time. This study hypothesizes that the sentiment from the unincorporated information may provide possible market leads. Thus, this paper aims to discuss a method to identify the un-incorporated qualitative Sentiment from information unadjusted in the market price to test whether sentiment polarity from the information can impact stock returns. Factoring market sentiment extracted from unincorporated information (residual sentiment or sentiment backlog) in CSI is an essential step for developing an integrated sentiment index to explain deviation in asset prices from their intrinsic value. Identifying the unincorporated Sentiment also helps in text analytics to distinguish between current and future market sentiment.

Initially, this study collects the news from various textual sources and runs the NVivo tool to compute the corpus data’s sentiment polarity. Subsequently, using the predictability horizon technique, this paper mines the unincorporated component of the news’s sentiment polarity. This study regresses three months’ sentiment polarity (the current period and its lags for two months) on the NIFTY50 index of the National Stock Exchange of India. If the three-month lags are significant, it indicates that news sentiment from the three months is unabsorbed and is likely to impact the future NIFTY50 index. The sentiment is also conditionally tested for firm size, volatility and specific industry sector-dependence. This paper discusses the implications of the results.

Based on information theories and empirical findings, the paper demonstrates that it is possible to identify unincorporated information and extract the sentiment polarity to predict future market direction. The sentiment polarity variables are significant for the current period and two-month lags. The magnitude of the sentiment polarity coefficient has decreased from the current period to lag one and lag two. This study finds that the unabsorbed component or backlog of news consisted of mainly negative market news or unconfirmed news of the previous period, as illustrated in Tables 1 and 2 and Figure 2. The findings on unadjusted news effects vary with firm size, volatility and sectoral indices as depicted in Figures 3, 4, 5 and 6.

The related literature on sentiment index describes top-down/ bottom-up models using quantitative proxy sentiment indicators and natural language processing (NLP)/machine learning approaches to compute the sentiment from qualitative information to explain variance in market returns. NLP approaches use current period sentiment to understand market trends ignoring the unadjusted sentiment carried from the previous period. The underlying assumption here is that the market adjusts to all available information instantly, which is proved false in various empirical studies backed by information theories. The paper discusses a novel approach to identify and extract sentiment from unincorporated information, which is a critical sentiment measure for developing a holistic sentiment index, both in text analytics and in top-down quantitative models. Practitioners may use the methodology in the algorithmic trading models and conduct stock market research.

This paper reports on a study into the market for electronic publishing in the Welsh language which was undertaken for the Welsh Books Council. The scope of the potential market is estimated including both home computer users, educational institutes and libraries. The current Welsh multimedia industry is described and topics are considered that might be possible for electronic publication. Financial details are given of the amount of sponsorship needed.

The purpose of this paper is to examine the level of foreign exchange exposure of listed nonfinancial firms in South Africa. The study spans the period January 2002 and November 2015. Foreign exchange risk exposure is estimated in relation to the exchange rate of the South African Rand relative to the US$, the Euro, the British Pound and the trade-weighted exchange rate index.

The study is based on the augmented-market model of Jorion (1990). The Jorion (1990) is a capital asset pricing model-inspired framework which models share returns as a function of the return on the market index and changes in the exchange rate factor. The market risk factor is meant to discount the effect of macroeconomic factors on share returns, thus isolating the foreign exchange risk factor. In addition, the study further added the size, value, momentum, investment and profitability risk factors in line with the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model to account for the fact that equity capital markets in countries such as South Africa are known to be partially segmented.

Foreign exchange risk exposure levels were estimated at more than 40% for all the proxy currencies on the basis of the standard augmented market model. However, after controlling for idiosyncratic factors, through the application of the Fama–French three-factor model, the Carhart four-factor model and the Fama–French five-factor model, exposure levels were found to range between 6.5 and 12%.

These results indicate the importance of controlling for the effects of idiosyncratic facto0rs in the estimation of foreign exchange risk exposure in the context of emerging markets of Sub-Saharan Africa (SSA).

This is the first study to apply the Fama–French three-factor model, Carhart four-factor model and the Fama–French five-factor model in the estimation of foreign exchange exposure of nonfinancial firms in the context of a SSA country. These results indicate the importance of controlling for the effects of idiosyncratic factors in the estimation of foreign exchange risk exposure in the context of emerging markets.

The purpose of this paper is to assess how much difference it makes for US firms to use the two‐factor ICAPM to estimate their cost of equity instead of a single‐factor CAPM.

For a large sample of US companies, the authors compare the empirical cost of equity estimates of a two‐factor international CAPM with those of the single‐factor domestic CAPM and the single‐factor global CAPM.

The authors find that the cost of equity estimates of the two‐factor ICAPM are reasonably close to those of either single‐factor model for US firms with low‐to‐moderate foreign exchange exposure; and second, perhaps surprisingly, for US firms with extreme foreign exchange exposure, that the cost of equity estimates of the two‐factor ICAPM tend to be very close to those of the domestic CAPM, and even closer than to those of the single‐factor global CAPM.

The paper's findings might prove useful to academic researchers wanting to resolve the seemingly contradictory empirical results on the pricing of FX risk.

The findings will hopefully help managers decide whether they should go to the trouble of estimating a US firm's cost of equity with the two‐factor international CAPM instead of a traditional single‐factor CAPM.

The paper extends the existing literature by focusing on the two‐factor ICAPM, and finds some new and surprising empirical results.