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In the following, we recall the notions of arbitrage, completeness and option pricing in quite general one-period (or multi-period) market models, but always based on a finite sample space.

This paper specifies a simulated convertible bond arbitrage portfolio to characterise the risks in convertible bond arbitrage. For comparison the risk profile of convertible bond arbitrage hedge fund indices at both monthly and daily frequencies is also examined. Results indicate that convertible bond arbitrage is positively related to default and term structure risk factors. These risk factors are augmented with the simulated convertible bond arbitrage portfolio, mimicking a passive investment in convertible bond arbitrage, to assess the risk and return of individual hedge funds. We provide estimates of the performance of two hedge fund indices (an equally weighted and value weighted index) and a sample of convertible bond arbitrage hedge funds using a factor model methodology. Lagged and contemporaneous observations of the risk factors are specified, controlling for illiquidity in the securities held by funds. Our results cover two time periods. Initially we find evidence of abnormal risk adjusted returns in the individual hedge fund data and the equally weighted hedge fund index and no evidence of abnormal risk adjusted returns in the value weighted hedge fund index. When we examine performance during the credit crisis of 2007 and 2008 we find evidence of negative abnormal returns amongst individual hedge funds and the hedge fund indices.

The returns to carry trades are controversially discussed. There seems to be no unifying risk-based explanation of currency returns and stock returns, while the countries’ interest rate differential plays a leading part in the carry-trade performance. Therefore, this paper addresses carry-trade returns from a risk-pricing perspective and examines if these returns can be connected to cross-country differences in risk pricing in the interest-rate market compared to the stock market. Data from Thomson Reuters Datastream and Federal Reserve Economic Data covering Australia, Japan, New Zealand, Switzerland and the United States were analyzed based on GMM estimation. The results indicate significant and persistent cross-country differences in risk aversion in the interest-rate market compared to the implied risk aversion in the stock market. This may offer opportunities for risk arbitrage and, therefore, a risk pricing-related explanation of carry-trade returns.

Research about equity index options has shown that option prices systematically violate rational pricing bounds for the risk-averse representative investor. These results raise the question of whether profitable trading possibilities exist in this market. Standard portfolio optimization does not apply because of the large bid-ask spreads and low quote sizes in this market. Motivated by these complications, a system of linear inequalities is developed that completely characterizes all risk arbitrage opportunities in the presence of transaction costs and portfolio restrictions. The practical use of this system is illustrated with an application to front-month S&P500 stock index options. Small-scale portfolios seem to produce surprisingly large abnormal returns out of sample; outperformance, however, seems elusive for institutional investors because of the limited quote size, possibly reflecting data limitations.

PurposeThis paper explores the effects of US President Donald Trump's Twitter messages (tweets) on the stock prices of media and non-media companies.Design/methodology/approachThe authors’ empirical analysis considers all Twitter messages posted by Donald Trump from May 26, 2016 (the date he passed the threshold of 1,237 delegates required to guarantee his presidential nomination) to August 30, 2018. The authors accessed President Trump's tweets through http://www.trumptwitterarchive.com, which provides links to all Twitter messages the President has ever posted. Of the 6,983 presidential tweets during our sample period, the authors select 513 messages that mention companies that are publicly traded in the United States for this study. The selected messages are then classified as having a positive, neutral or negative sentiment. The authors employ a series of univariate and multivariate tests as well as Heckman two-step regressions and partial least squares regressions to examine the effect of the President's tweets on the stock prices of the firms he tweets about.FindingsFor media firms, the authors find that positive tweets have a pronounced positive stock price impact, whereas negative and neutral tweets have little or no effect. For non-media firms, the authors observe the opposite: negative tweets tend to be associated with significant stock price declines, whereas neutral and positive tweets incur weakly positive stock price reactions. To a large extent, these stock price declines reverse on the following day. The authors further find that the President's reiteration of information that is already known by the market incurs an additional stock price reaction. The President's attitude towards the news appears to play a major role in this context.Originality/valueThe authors contribute to the literature by offering various new insights regarding the effect social media has on the stock markets. In addition, this paper expands the emerging strand of literature that explores how President Trump affects the stock prices of firms he tweets about. This paper differs from prior studies in this area by considering a broader range of tweets, by controlling for potential selection biases, by differentiating between Trump's tweets about media and non-media firms and by exploring the impact of “old” vs “new” news based on whether the President repeats information that is already known to the market. If social media posts by single influential people are found to affect markets, they may create trading opportunities for investors and financial managers and risk arbitrage opportunities for arbitrageurs. In the political science field, the findings of this research provide valuable insights into how politicians can employ social media platforms to affect the public, and the differential influence of nominees and politicians in office. Finally, our study gives corporations that wish to back a certain campaign or a candidate in an election a better idea of the possible risks and benefits of their actions, considering that candidates or politicians could post negative messages on social media platforms targeting companies that backed their opponents.

Using merger announcements and applying methods from computational linguistics we find strong evidence that stock prices underreact to information in financial media. A one standard deviation increase in the media-implied probability of merger completion increases the subsequent 12-day return of a long-short merger strategy by 1.2 percentage points. Filtering out the 28% of announced deals with the lowest media-implied completion probability increases the annualized alpha from merger arbitrage by 9.3 percentage points. Our results are particularly pronounced when high-yield spreads are large and on days when only few merger deals are announced. We also document that financial media information is orthogonal to announcement day returns.

We use relative value to measure limits to arbitrage in fixed-income markets. Relative value captures apparent deviations from no-arbitrage relationships. It is simple, intuitive and can be computed model-free for any bond. A pseudo-trading strategy based on relative value generates higher returns than one based on the well-known noise measure. The relative value is therefore a better proxy for limits to arbitrage. We construct relative value indices for the US, UK, Japan, Germany, Italy, France, Switzerland and Canada. Limits to arbitrage increase with the scarcity of capital: we find that each index is correlated with local volatility and funding costs. Limits to arbitrage also exhibit strong commonality across countries, consistent with the international mobility of capital. The relative value indices are updated regularly and available publicly.

In practice, price differences can occur at different markets, at least for a short time. By taking advantage of arbitrage, one may be able to benefit from this phenomenon.

The classical discrete time model of proportional transaction costs relies on the assumption that a feasible portfolio process has solvent increments at each step. We extend this setting in two directions, allowing for convex transaction costs and assuming that increments of the portfolio process belong to the sum of a solvency set and a family of multivariate acceptable positions, e.g. with respect to a dynamic risk measure. We describe the sets of superhedging prices, formulate several no (risk) arbitrage conditions and explore connections between them. In the special case when multivariate positions are converted into a single fixed asset, our framework turns into the no good deals setting. However, in general, the possibilities of assessing the risk with respect to any asset or a basket of the assets lead to a decrease of superhedging prices and the no arbitrage conditions become stronger. The mathematical technique relies on results for unbounded and possibly non-closed random sets in Euclidean space., 31 page. Accepted for publication in Finance and Stochastics

Tax-exempt municipal bonds (‘munis’) are usually held in taxable accounts. The objective of the manager of such accounts should be to maximize after-tax performance. The standard tool for this is the so-called tax-loss harvesting, i.e. selling a bond at a price below the investor’s tax basis and recognizing the resulting loss for tax purposes. Another, albeit less familiar tax-beneficial transaction, which will be discussed in detail below, is tax rate arbitrage. The economics of sale depend on both the tax associated with selling the bond, or holding it. In Section 2 we provide an overview of the tax treatment of munis. Selling a bond is tax-beneficial only if the after-tax proceeds from sale exceed the bond’s ‘hold’ value, i.e. the value of the bond to its current holder. As discussed in Kalotay [2016a, 2016b], in the case of munis hold value can substantially differ from the market price. Hold value is a critical input into after-tax analysis, and in Section 3 we illustrate the calculation of hold value in the case of tax-loss harvesting. In Section 4 we describe what we call the ‘tax rate arbitrage’ strategy and demonstrate how it is calculated. Tax rate arbitrage entails a tradeoff between paying tax earlier at a lower rate or later at a higher rate. The discount rate applicable to the tax at maturity is a critical input into this analysis. Any tax-beneficial sale is an exercise of the so-called tax option. The tax option is acquired automatically and at no cost when a taxable account invests in a security, such as a muni. As discussed in Kalotay [2016c], for investment-grade bonds the value of the tax option can be determined using standard analytical models, such as tax-neutral OAS analytics in the case of munis [Kalotay, 2014a]. Selling and reinvesting the proceeds entails swapping the associated tax options. If the sale is cashflow beneficial, by reinvesting in a like bond (i.e. one with similar interest rate and credit exposure) the investor can realize a riskless gain. The deterrent to transacting is the related transaction cost. The so-called tax efficiency measure, which compares the cashflow benefit to the net loss of option value, provides the signal for the optimal time to transact [Kalotay, 2014b]. These calculations are illustrated in Section 5.

In an age of accelerating wealth at the very top and accelerating risks at the bottom, there is a clear disjunction between the flow of social benefits and social damages produced by different actors and their share of these respective benefits and damages. Yet, the specific processes that generate the dualization of tracks of accumulation of rewards or accumulation of risks and precarity are still up for debate. In tackling this dual process in a way that is attuned to the critical contribution of contemporary forms of the law to this uneven accumulation of wealth and of risks, this paper focuses on organized irresponsibility—where individuals can cumulatively contribute to risks, but avoid individual culpability—and how relations of organized irresponsibility provide extensive opportunities for risk arbitrage. Risk arbitrage is correspondingly a process where actors, whether it be individuals or larger organizations, can produce social risk, appropriate benefit from these risks, and disproportionately avoid the consequences of the risks so as to benefit from the overall “cycle of reward and risk”—even if society as a whole is worse off. The paper identifies organized irresponsibility as fundamentally undergirded by mismatches between existing configurations of law and the existing complexity of the processes of the production of social goods and risks. This paper proceeds to show how gaps in the law enable the organized irresponsibility principle—that given a level of risk production, the greater the number of actors involved and the greater complexity between causes and the risk’s impacts, the less overall culpability that tends to be assigned. It then shows how the organized irresponsibility principle enables relationships of risk arbitrage that intensify contemporary risk and inequality.

In an “activist risk arbitrage,” a shareholder attempts to improve terms of an announced M&A through public campaigns. Activists target deals with low premiums and those susceptible to managerial conflicts of interest, including going‐private deals and deals in which CEOs receive outsized payments. Activist arbitrageurs are associated with a significant decrease in the probability that targets will be sold to the announced bidders, and an increase in the premium paid, both ex post among surviving deals and ex ante among all deals. Activist arbitrage serves as a governance mechanism in M&A and earns higher returns than passive arbitrage.

We examine net arbitrage trading (NAT) measured by the difference between quarterly abnormal hedge fund holdings and abnormal short interest. NAT strongly predicts stock returns in the cross-section. Across ten well-known stock anomalies, abnormal returns are realized only among stocks experiencing large NAT. Exploiting Regulation SHO, which facilitated short selling for a random group of stocks, we present causal evidence that NAT has stronger return predictability among stocks facing greater limits to arbitrage. We also find large returns for anomalies that arbitrageurs chose to exploit despite capital constraints during the 2007–09 financial crisis. We confirm our findings using daily data.Received September 1, 2016; editorial decision May 28, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We examine the interaction between funds implementing hedge and merger arbitrage strategies and a set of traditional assets comprising equities, bonds, gold, crude oil, currency, commodities and real estate, by applying a time-varying spillover approach for the period 1/1/2010-7/31/2020. Results indicate that the funds absorb the fewest shocks from equities, crude oil, gold and currency compared to commodities, bonds and real estate. Furthermore, we test the effective hedging ability of these funds by estimating hedge ratios and optimal portfolio weights. Taking a short position in the volatility of the funds provides impeccable hedging effectiveness for all asset classes, except currency.

This study offers insights into the profitability of convergence trading in European commodity markets, thereby shedding light on the compensation for enforcing the Law of One Price. We analyze profits of a cointegration-based statistical arbitrage strategy on a wide range of European energy sectors and indeed find economically and statistically significant risk-adjusted excess returns which are also different from simple contrarian and momentum-based strategies. More importantly, the magnitude of this intermediation fee seems to be linked to commodity specific frictions limiting arbitrage possibilities. Consistent to the limits to arbitrage literature (e.g. Shleifer and Vishny, 1997 or Xiong, 2001), we find that convergence traders in Europe's commodity markets tend to be non-diversified investors focusing on specific market niches.

This study examines how limits of arbitrage can affect the pricing of idiosyncratic volatility. Using both unique trading constraints in the Chinese stock market and other commonly-used limits-of-arbitrage measures, we construct a comprehensive limits-of-arbitrage index. Based on this index, we find that the negative idiosyncratic volatility return premium is much stronger and more persistent in stocks with high limits of arbitrage. Furthermore, the existing explanations about the idiosyncratic volatility return premium cannot fully explain what we find about the role of limits of arbitrage in the pricing of idiosyncratic volatility in the Chinese stock market. Our study suggests that the trading constraints introduced in the name of protecting individual investors can actually hurt them, since these additional limits of arbitrage will increase the inefficiency of the security market.

The yield curve of the Treasury bonds has important economic implications. Its shape can reflect the expectation of the economy, and the corresponding trading strategy can be formulated by ...

Classical economic theory suggests that excess returns should be competed away as new participants enter the market. This is especially true for the profits from riskless arbitrage. Yet, there is conflicting evidence in the financial economic literature over whether high frequency trading (HFT) profits, in general, (Baron et al [2012]) and arbitrage profits, in particular (Budish et al [2013] and Chaboud et al [2013]), decline as high frequency or other algorithmic trading increases. There are important public policy implications for market microstructure and the social value of investments by HFT firms in being faster if arbitrage profit opportunities persist (in the absence of limits to arbitrage). There are several different strategies that high frequency and other latency sensitive traders engage in. These include: index arbitrage; spread arbitrage/market making; and correlated arbitrage among others. This study focuses on only one - index arbitrage. Specifically, it examines whether the duration, frequency and profitability of potential arbitrage opportunities between the Australian Securities Exchange (ASX) Share Price Index (SPI) futures contract and the exchange traded fund (ETF), STW, have changed as the number of HFT firms (or intensity of HFT activity) has increased, since the ASX’s introduction of co-location services in February 2012. In addition, we use estimated potential arbitrage profits and compare them to the cost of being co-located to determine the value of minimum latency. Not surprisingly, we find the frequency and profitability of potential arbitrage opportunities are greater during volatile and high turnover periods - other things equal. We examine the increased competition in high frequency trading by identifying the number of ‘cabinets’ co-located in the ASX’s liquidity center. With increased HFT connections, we observe increasing value, frequency and duration of index arbitrage profit opportunities. Our results are robust to the inclusion of transaction costs. We conclude that the activity of disruptive HFT outweighs the activity of index arbitrage HFTs.

Bond ETFs trading at a premium (discount) to NAV experience more creations (redemptions) than those trading at parity. When these transactions occur, subsequent returns partially offset the premium or discount. These results suggest that arbitrage trading between the underlying bonds and the ETFs has a significant impact on market returns. However, in the absence of cash flow, premiums and discounts persist. The authors consider market factors that discourage arbitrage trading around premiums and discounts, and find these anomalies persist in part due to costs and uncertainty in the secondary market.

Purpose 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. Design/methodology/approach A number of hedging approaches proposed to improve the hedging results and final returns of Black-Scholes model are analyzed and compared. Findings 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. Practical implications This paper offers a new method for volatility arbitrage in Chinese financial market. Originality/value 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.

This study analyzes cross-listed Taiwanese firms from 1997 to 2015 to identify the rule of one price, market integration, and arbitrage opportunities. Results show cross-listing locations significant positively and negatively influence home and foreign market returns of firms. The exchange rates insignificantly influence cross-listed firms. Trading volume effect via locational arbitrage opportunities exist in firms with an average return of 10% under 30 days. The minimum and maximum arbitrage average returns are 2% and 18%, respectively. Cross-listed firms in the UK and Hong Kong represent the most liquid arbitrage locations for Evergreen Marine, Far Eastern New Century, and Neo-Neon.

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Despite extensive empirical evidence of the economic and financial benefits of green buildings, energy retrofit investments in existing buildings have not reached widespread adoption.This paper empirically estimate returns to energy retrofit investments for multifamily and commercial buildings in New York City, using a novel database of actual audit report recommendations and permitted renovation work extracted using natural language processing. By modeling the estimated rate of return for energy retrofit investments, we generate a more comprehensive understanding of the perceived risk of these investments and the market and regulatory mechanisms that can overcome financial and informational barriers to investment in energy conservation measures (ECMs). Based on auditor costs and savings estimates, the median internal rate of return (IRR) for adopted ECMs is found to be 21% for multifamily buildings and 25% for office properties. Adoption rates are higher for office buildings than multifamily, and in both cases adopter buildings tend to be larger, higher value, and less efficient at the time of implementation. The economically significant magnitudes of returns to adopted ECMs raise important questions about why many property owners choose not to adopt. As such, we discuss incentive and regulatory mechanisms that can overcome financial and informational barriers to the adoption of energy efficiency measures.

In order to take advantage of the “one true free lunch” in investing, namely the increase in compound return due to the reduction of volatility by regular re-balancing among uncorrelated assets, it is necessary to first establish what those uncorrelated asset classes are. In practice, many investors are disappointed to find their attempts at “style-box” diversification (e.g. large vs. small, and growth vs. value) failed to provide much overall portfolio benefit in terms of this re-balancing effect. Machine-learning algorithms such as cluster identification via hierarchical trees have seen some success in identifying truer sector and industry classifications among individual equities; can such algorithms provide any insights as to the diversification benefits of standard asset classes? We apply various clustering algorithms to asset classes and hedge fund strategies from 1990 to the present to investigate cluster stability and compute the returns of a risk-parity investing approach. Some surprising insights emerge with actionable implications for portfolio construction (a few examples: there are three types of bonds; TIPS are not different; High Yield is mostly Equity; MLPs and Precious Metals are interesting; and all hedge funds except Merger Arbitrage and certain sub-categories of Macro have morphed over time into Equity).

Considering the factors such as arbitrage lag, transaction cost and overall discount or premium, this paper constructs the split and merger arbitrage models to investigate the pairing arbitrage strategy of stock passive structured fund in China under extreme market conditions. The empirical results mainly show that: (i) the actual success times of merger arbitrage is significantly higher than that of split arbitrage, indicating that the former is more likely to succeed than the latter. (ii) the actual yield of split arbitrage is higher than that of merger arbitrage, and the former is far more at risk than the latter.

资本市场中，套利交易是一种规避风险的重要交易方式。统计套利在近几十年来在国外资本市场十分盛行。而国内资本市场由于缺乏做空机制，统计套利等量化投资策略很难得以实现。而近年来随着融资融券和股指期货的推出，这一局面有所缓解，放开做空机制已是大势所趋。本文尝试采用统计套利的思想，利用协整模型，先在机制成熟的外汇市场进行套利检验，选取相关度较高的欧元/美元(EUR/USD)和瑞郎/日元(CHR/JPY)两个货币对在2015年5月28日20时至5月29日20时每分钟收盘价的价差时间序列进行实证研究，发现日内存在大量的套利机会，从而为今后投资者提供了一种新颖的量化投资思路。 In capital market, arbitrage is an essential trading method to avoid risks. Statistical arbitrage, which is a genre of arbitrage, has been widely utilized by foreign financial institutions since several decades ago. Since lacking of Short Hedge Mechanism, statistical arbitrage can hardly be realized in domestic capital markets. However, the situation is being relieved with the introduction of margin trading and stock index futures. And the trend to set up Short Hedge Mechanism is overwhelming. In this dissertation, we tested the arbitrage chances in forex market by adopting the thought of statistical arbitrage, combining with cointegration modeling and every minute’s closing rate of EUR/USD and CHR/JPY, which are highly correlated with each other, within 24 hours. After studying in the time series of price difference, we found that there were abundant opportunities for arbitrage. Hence, we are able to give out a novel quantified path for investors in the future.

We find that the average holding period of newly issued convertible bonds by convertible arbitrage hedge funds is approximately 11.6 months, which on average represents only 14% of the bonds’ time to maturity. The relatively short holding periods highlight that hedge funds’ motivations for holding convertible bonds are distinct from firms’ traditional reasons for issuing them. The short holding periods are in line with convertible arbitrage hedge funds making convertible issues a low cost financing alternative for firms. We show that both issue and hedge fund characteristics affect holding periods.

Using an optimal changepoint approach, we find a structural change in the relation between hedge funds’ stock market exposure and aggregate stock market liquidity that takes place in the period 2000 to 2002. Before the structural break, market betas have no relation to liquidity and only a few style categories of hedge funds show increased market presence when liquidity is low. After the break, the relationship is inverted, pointing towards an increased liquidity timing ability of hedge funds, as users of liquidity. We relate our findings to best execution rules and decimalization in the US stock market that were introduced in that period and impacted aggregate liquidity conditions. Furthermore, the returns to a momentum strategy display a similar structural break and momentum-loading funds constitute a sizeable proportion of hedge funds that manifest a distinct beta-liquidity evolution with a structural break in that period.

This article presents a unique test of the effectiveness of technical analysis in different sentiment environments by focusing on its usage by perhaps the most sophisticated and astute investors, namely, hedge fund managers. We document that during high-sentiment periods, hedge funds using technical analysis exhibit higher performance, lower risk, and superior market-timing ability than nonusers. The advantages of using technical analysis disappear or even reverse in low-sentiment periods. Our findings are consistent with the view that technical analysis is relatively more useful in high-sentiment periods with larger mispricing, which cannot be fully exploited by arbitrage activities because of short-sale impediments.

We examine the elasticity of demand curves using a recent sample of 100% secondary equity offerings (i.e., a large block of shares held by current shareholders; the proceeds of the sale go to the selling shareholders, not the issuing company) and employ measures of arbitrage risk that allow us to control for variation in arbitrage risk. We find that demand curves are inelastic for firms with high levels of arbitrage risk and elastic for all others. We also document that during the second half of our sample period demand curves are elastic for all stocks regardless of the arbitrage risk.

Derivatives valuation has strong theoretical support because models are derived from the principle that arbitrage between the derivative and its underlying will eliminate riskless profits and drive the market price to the model value. “No-arbitrage” is invoked routinely whenever a new pricing model is developed. But real world market prices are determined by trades, not by theories. In this talk, I discuss how different the arbitrage trade is for different markets and different models and I review articles from the literature that illustrate how limits to the arbitrage trade have affected the way derivatives theory gets into prices in practice. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

Recent evidence (Stambaugh, Yu, and Yuan, 2015) indicates that the most promising explanation for the negative price of idiosyncratic volatility is from its function as a limit arbitrage. Our evidence incorporating firm specific news is inconsistent with the limited arbitrage explanation. Since mispricing is most likely to occur during news announcements, the pricing of news volatility (volatility contemporaneous to news announcements) should be stronger than that of non-news volatility (volatility without an identified news announcement). We find the opposite. Non-news volatility has robust negative price and lacks some of the key features expected from the limited arbitrage explanation. We conclude that the pricing of idiosyncratic volatility is beyond its function as a limit of arbitrage. In addition, we consider evidence at odds with explanations based on difference of investor opinion and investor sentiment. Hence the pricing of idiosyncratic volatility is a deeper puzzle.

The article provides an overview of the unfolding of the financialization of commodities in the 2000–2014 time frame. Different phases are described according to the positioning of the group of traders, their motivations, and the type of financial assets used to take a position in commodities. The main theme is the failure of arbitrage to level prices of similar financial assets traded in different markets. However, this failure does not depend on financing constraints suffered by arbitrageurs. Following Mirowski (2010) it is shown that arbitrage becomes a form of financial innovation rather than an equilibrating mechanism in contemporary financial markets. Historical accidents and changes in policy affect the positions of groups in the financial market game. The various strategies used are explained by creating a set of T-accounts for the various groups that highlight the winners and the losers in the various phases.