Arbitrage Opportunities Research Articles

Optimal pricing in the online betting market

I find that the optimal price of a bet for a risk-averse bookmaker is a function of elasticity of demand and the number of outcomes of the betting event. In the presence of shocks to the order flow, however, the optimal price can change, and large adjustments can create arbitrage opportunities for informed investors. Using a large sample of online bookmakers and a unique data set of real-time betting odds, I find strong support for these predictions. Overall, the results shed new light on the efficiency of online betting prices.

Exact solutions and numerical simulation for Bakstein-Howison model

In this paper, European options with transaction cost under some Black-Scholes markets are priced. In fact stochastic analysis and Lie group analysis are applied to find exact solutions for European options pricing under considered markets. In the sequel, using the finite difference method, numerical solutions are presented as well. Finally European options pricing are presented in four maturity times under some Black-Scholes models equipped with the gold asset as underlying asset. For this, the daily gold world price has been followed from Jan 1, 2016 to Jan 1, 2019 and the results of the profit and loss of options under the considered models indicate that call options prices prevent arbitrage opportunity but put options create it.

Risk‐neutral pricing techniques and examples

AbstractTractability and flexibility are among the two most attractive features of models in mathematical finance. For the pricing of derivative products, to avoid arbitrage opportunities, the fundamental theorem of asset pricing requires the existence of an equivalent martingale measure under which the discounted price process is a (local) martingale. In the semimartingale setting, the traditional approach of risk‐neutral valuation uses a change of measure invoking Girsanov's theorem. This approach often destroys the tractability of the process which is undesirable for quantitative finance applications. To overcome these limitations, we employ a transformation based on the concept of intertwining relationships that allows us to convert Markovian semigroups into a pricing semigroup while keeping its tractability. In order to illustrate the usefulness of this approach, we apply it to exponential Lévy, positive self‐similar, and generalized CIR processes that all fall within the class of polynomial processes introduced by Cuchiero et al. (2012). Furthermore, for the jump CIR class, relying on recent work of Patie and Savov (2019), we provide an eigenvalues expansion of the pricing semigroup and carry out some numerical experiments.

Key Roles of Crypto-Exchanges in Generating Arbitrage Opportunities.

The evolving crypto-currency market is seen as dynamic, segmented, and inefficient, coupled with a lack of regulatory oversight, which together becomes conducive to observing the arbitrage. In this context, a crypto-network is designed using bid/ask data among 20 crypto-exchanges over a 2-year period. The graph theory technique is employed to describe the network and, more importantly, to determine the key roles of crypto-exchanges in generating arbitrage opportunities by estimating relevant network centrality measures. Based on the proposed arbitrage ratio, Gatecoin, Coinfloor, and Bitsane are estimated as the best exchanges to initiate arbitrage, while EXMO and DSX are the best places to close it. Furthermore, by means of canonical correlation analysis, we revealed that higher volatility and the decreasing price of dominating crypto-currencies and CRIX index signal bring about a more likely arbitrage appearance in the market. The findings of research include pre-tax and after-tax arbitrage opportunities.

Impact of Interest Rate Differential and Exchange Rate Movement on the Dynamics of Nigeria’s International Private Capital Flows

The study examines the impact of interest rate differential and exchange rate movement on the dynamics of Nigeria’s international private capital flows from 2010Q1 to 2019Q4. It uses the interest rate parity theory and the Markov Switching Time Varying Transition Probability Modelling approach. Findings show that interest rate differential does not explain the dynamics of aggregate capital and Foreign Direct Investment (FDI) flows, but significantly explains Foreign Portfolio Investment (FPI) flows. Also, Movement in real exchange rate is significant in explaining outflows and inflows in FPI, and inflows in FDI, but neutral to aggregate capital flows. The study concludes that deviations from interest rate parity provides opportunities for interest rate and currency arbitrage in Nigeria but using aggregate capital flows mask this evidence. The study therefore recommends that the CBN should focus on exchange rate stabilization policies, so as not only to discourage FPI reversal but to also enhance FDI inflow. This can be done by putting in place foreign reserve accretion measures to boost the ability of the CBN to defend the Naira. The new policy initiative on remittances is a right step in the right direction as it could boost external reserve.

The impact of RMB’s SDR inclusion on price discovery in onshore-offshore markets

In this study, we leverage various price discovery measurements to investigate whether and how the addition of the Chinese yuan in Special Drawing Right (SDR) affected price discovery in onshore (USD/CNY) and offshore (USD/CNH) markets. The results show that the less regulated offshore exchange rates contribute more to price discovery than the onshore rates do. Including the yuan in SDR does not change the relative price discovery contributions of the onshore and offshore markets, and more importantly, it enhances the overall price efficiency in both markets, due to lower autocorrelations in the error correction term and fewer arbitrage opportunities. In particular, the price spreads between the onshore and offshore markets decrease, implying that arbitrage opportunities have diminished, as market integration has increased, following the inclusion of the yuan in SDR.

Return Anomalies in the Kuwaiti Stock Market

This paper intends to investigate the existence of daily return anomalies and the weekend effect within Boursa Kuwait, Kuwait’s stock exchange. Kuwait as an economy has continued to be opened up to foreign investment and as foreign funds being to flood into the market; return anomalies akin to those within international markets begin to materialize, bringing new opportunities for abnormal returns and arbitrage. The premise of this paper is the existence of the January effect and the Weekend effect, and uses econometric methods in support of their existence, bringing into question the challenges to market efficiency and the changing landscape for investors and their strategies.

How does skewness perform in the Chinese commodity futures market?

AbstractThis paper investigates a negative relationship between skewness and expected returns in China's commodity futures market. Unlike the impact of skewness in the US commodity markets, the impact of skewness in Chinese commodity markets is completely monotonic and asymmetric, which indicates more potential arbitrage opportunities in China's commodity markets. Also, we demonstrate that skewness is an effective risk factor in China's commodity futures market that contains different information from traditional risk factors. Investors require positive risk compensation for lower skewness. Empirical findings are shown to be robust with alternative skewness measures in different business cycles.

Intraday indirect arbitrage between European index ETFs

We investigate intraday arbitrage between close substitute Exchange-traded Funds (ETFs) on two major European indices: FTSE100 and DAX30. Using intraday data, we establish arbitrage links between our ETFs through cointegration and error correction models. We then apply an arbitrage identification procedure on approximately 18 million intraday matched quotes, resulting in 1.95% and 0.2% of observations on the ETF pairs for FTSE100 and DAX30 as arbitrage opportunities. They occur on specific days in our sample, disappear relatively quickly, and result in economically insignificant profits from arbitrage trades within the mispricing window, indicating overall price efficiency.

Carry Trade Returns and Segmented Risk Pricing

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.

Statistical arbitrage in jump-diffusion models with compound Poisson processes

We prove the existence of statistical arbitrage opportunities for jump-diffusion models of stock prices when the jump-size distribution is assumed to have finite moments. We show that to obtain statistical arbitrage, the risky asset holding must go to zero in time. Existence of statistical arbitrage is demonstrated via ‘buy-and-hold until barrier’ and ‘short until barrier’ strategies with both single and double barrier. In order to exploit statistical arbitrage opportunities, the investor needs to have a good approximation of the physical probability measure and the drift of the stochastic process for a given asset.

Why Do Firms Fail to Engage Diversity? A Behavioral Strategy Perspective

The persistent failure of organizations to engage diversity—to employ a diverse workforce and fully realize its potential—is puzzling, as it creates labor-market inefficiencies and untapped opportunities. Addressing this puzzle from a behavioral strategy as arbitrage perspective, this paper argues that attractive opportunities tend to be protected by strong behavioral and social limits to arbitrage. I outline four limits—cognizing, searching, reconfiguring, and legitimizing (CSRL)—that deter firms from sensing, seizing, integrating, and justifying valuable diversity. The case of Moneyball is used to illustrate how these CSRL limits prevented mispriced human resources from being arbitraged away sooner, with implications for engaging cognitive diversity that go beyond sports. This perspective describes why behavioral failures as arbitrage opportunities can persist and prescribes strategists, as contrarian theorists, a framework for formulating relevant behavioral and social problems to solve in order to search for and exploit these untapped opportunities.

The Leverage Effect and Other Stylized Facts Displayed by Bitcoin Returns

In this paper, we explore some stylized facts of the Bitcoin market using the BTC-USD exchange rate time series of historical intraday data from 2013 to 2020. Despite Bitcoin presenting some very peculiar idiosyncrasies, like the absence of macroeconomic fundamentals or connections with underlying assets or benchmarks, an asymmetry between demand and supply and the presence of inefficiency in the form of strong arbitrage opportunity, all these elements seem to be marginal in the definition of the structural statistical properties of this virtual financial asset, which result to be analogous to general individual stocks or indices. In contrast, we find some clear differences, compared to fiat money exchange rates time series, in the values of the linear autocorrelation and, more surprisingly, in the presence of the leverage effect. We also explore the dynamics of correlations, monitoring the shifts in the evolution of the Bitcoin market. This analysis is able to distinguish between two different regimes: a stochastic process with weaker memory signatures and closer to Gaussianity between the Mt. Gox incident and the late 2015, and a dynamics with relevant correlations and strong deviations from Gaussianity before and after this interval.

Tracking performance of VIX futures ETPs

Abstract We find that, at the daily level, none of the VIX futures Exchange-Traded Products (ETPs) track their intrinsic values perfectly, although the tracking improves at the weekly and monthly frequency. We show that all products tracking deviations are driven by mainly driven by limits to arbitrage, measured by market conditions, liquidity and transaction costs. Exchange-Traded Funds’ (ETFs’) deviations are more significantly related to fund flows, which shows authorized participants taking advantage of arbitrage opportunities by creating/redeeming ETF units. The Exchange-Traded Notes (ETNs) do not have this mechanism, creation and redemption is reliant on the issuers and delayed, so their deviations are less related to flows.

Immediate sale or stock-up: value of rent-to-own contracts for experience goods

Many high-value experience goods, such as pianos and Chinese zithers, are usually characterized by uncertain future values. As such, a portion of customers (called ‘consumers’) may hesitate to buy the product because they are unsure of the product’s actual value and/or they may expect to buy the product at a lower price in the future. Moreover, the fluctuating future value creates arbitrage opportunities for another group of customers (called ‘speculators’) who may benefit from stocking up a product and reselling it at a higher price at a future time. Considering a firm that sells a limited number of high-value experience goods over two periods, this paper investigates the profitability of a rent-to-own (R2O) contract, under which a consumer can return the product in the future period (e.g. when it turns out to be inappropriate) or buy the product at the realised future price. We study the optimal pricing decisions involved in the R2O contract for two scenarios. In the base model, the uncertain future price is exogenously given, and in the extended model, the future price is endogenously determined by the firm and speculators. Numerical experiments are conducted to evaluate the value of R2O contracts.

Detection of arbitrage opportunities in multi-asset derivatives markets

Abstract We are interested in the existence of equivalent martingale measures and the detection of arbitrage opportunities in markets where several multi-asset derivatives are traded simultaneously. More specifically, we consider a financial market with multiple traded assets whose marginal risk-neutral distributions are known, and assume that several derivatives written on these assets are traded simultaneously. In this setting, there is a bijection between the existence of an equivalent martingale measure and the existence of a copula that couples these marginals. Using this bijection and recent results on improved Fréchet–Hoeffding bounds in the presence of additional information on functionals of a copula by [18], we can extend the results of [33] on the detection of arbitrage opportunities to the general multi-dimensional case. More specifically, we derive sufficient conditions for the absence of arbitrage and formulate an optimization problem for the detection of a possible arbitrage opportunity. This problem can be solved efficiently using numerical optimization routines. The most interesting practical outcome is the following: we can construct a financial market where each multi-asset derivative is traded within its own no-arbitrage interval, and yet when considered together an arbitrage opportunity may arise.

Identifying Arbitrage Opportunities in Retail Markets using Predictive Analytics

While the body of literature on arbitrage opportunity identification is well established in the financial, energy, and real-estate markets, research on arbitrage in the retail marketplace is relatively limited. As arbitrage opportunities in this context differ inherently from other markets, we propose a data analytics framework to identify such an arbitrage by leveraging a machine learning model to predict the optimal purchasing point from the price movement. Our predictive approach is enhanced by incorporating user-generated content which demonstrates its informative power. Overall, the enhanced model attains the precision rate of more than 90 percent while the recall rate is higher than 80 percent in a cross-validation test using the data collected from Amazon Marketplace. In addition, we conduct a field experiment to verify the external validity of the model in a real-life setting. The result shows that our model is capable of generating as much as a 113.31% profit margin.

Cyclic Arbitrage in Decentralized Exchange Markets

In May 2020, Uniswap V2 was officially launched on Ethereum. Uniswap V2 allows users to create trading pools between any pair of cryptocurrencies, without the need for ETH as an intermediary currency. Uniswap V2 introduces new arbitrage opportunities: Traders are now able to trade cryptocurrencies cyclically: A trader can exchange currency A for B, then B for C, and finally C for A again through different trading pools. Almost surely, the three floating exchange rates are not perfectly in sync, which opens up arbitrage possibilities for cyclic trading. In this paper, we study cyclic arbitrages in Decentralized Exchanges (DEXes) of cryptocurrencies with transaction-level data on Uniswap V2, observing 285,127 cyclic arbitrages over eight months. We conduct a theoretical analysis and an empirical evaluation to understand cyclic arbitrages systematically. We study the market size (the revenue and the cost) of cyclic arbitrages, how cyclic arbitrages change market prices, how cyclic arbitrageurs influence other participants, and the implementations of cyclic arbitrages. Beyond the understanding of cyclic arbitrages, this paper suggests that with the smart contract technology and the replicated state machine setting of Ethereum, arbitrage strategies are easier implemented in DEXes than in Centralized Exchanges (CEXes). We find that deploying private smart contracts to implement cyclic arbitrages is more resilient to front-running attacks than applying cyclic arbitrages through public (open-source) smart contracts.

Between Walras and Marshall: Menger's Third Way

Neoclassical economics is bifurcated between Marshall’s partial-equilibrium and Walras’s general-equilibrium analyses. Given the failure of neoclassical theory to explain the Great Depression, Keynes proposed an explanation of involuntary unemployment. Keynes’s contribution was later subsumed under the neoclassical synthesis of the Keynesian and Walrasian theories. Lacking microfoundations consistent with Walrasian theory, the neoclassical synthesis collapsed. But Walrasian GE theory provides no plausible account of how GE is achieved. Whatever plausibility is attributed to the assumption that price flexibility leads to equilibrium derives from Marshallian PE analysis, with prices equilibrating supply and demand. But Marshallian PE analysis presumes that all markets, but the small one being analyzed, are at equilibrium, so that price adjustments in the analyzed market neither affect nor are affected by other markets. The demand and cost (curves) of PE analysis are drawn on the assumption that all other prices reflect Walrasian GE values. While based on Walrasian assumptions, modern macroeconomics relies on the Marshallian intuition that agents know or anticipate the prices consistent with GE. Menger’s third way offers an alternative to this conceptual impasse by recognizing that nearly all economic activity is subjective and guided by expectations of the future. Current prices are set based on expectations of future prices, so equilibrium is possible only if agents share the same expectations of future prices. If current prices are set based on differing expectations, arbitrage opportunities are created, causing prices and expectations to change, leading to further arbitrage, expectational change, and so on, but not necessarily to equilibrium.

Exploring Spatial Price Relationships: The Case of African Swine Fever in China

We use a temporary ban on inter-province shipping of live hogs induced by the 2018 outbreak of African Swine Fever (ASF) in China as a natural experiment to study spatial mechanisms behind the dynamics of market integration. With a unique dataset of weekly provincial hog prices, we employ a novel spatial network model to estimate the strength of price co-movement across provinces pre and post the ban. Results indicate that, in the highly integrated national market prior to the ban, longer geographical distances between two provinces did not weaken the strength of their price linkage. The ban broken down spatial integration. Longer distances became a significant obstacle to spatial price linkage in the post-ban periods, implying faster re-integration of hog prices between proximate provinces than remote ones. The negative effect of distance can be rationalized by the interplay between arbitrage opportunities and imperfect information. Our findings highlight information transparency as a key to market integration post shipping bans used to curb animal pandemics like ASF. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.