Crisis and arbitrage opportunities: The role of causation, effectuation and entrepreneurial learning

This article examines the process by which entrepreneurs identify and work with an arbitrage opportunity emerging from an episodic crisis. Although prior research has investigated the role of entrepreneurial characteristics and context on opportunity development, the specific manner in which these factors emerge in the course of opportunity development during a crisis remain underexplored. By adopting a qualitative approach grounded in case studies of eight entrepreneurs in the US distillery industry, this article addresses that gap by examining the process of arbitrage opportunity development during COVID-19. Our study reveals the primacy of both causation and effectuation-based entrepreneurial decision logics and the role of double-loop learning, as entrepreneurs interact with the time-compressed duration of the arbitrage opportunity. Implications and insights for entrepreneurs, researchers and policymakers are discussed.

European Option Pricing Formula in Risk-Aversive Markets

In this study, using the method of discounting the terminal expectation value into its initial value, the pricing formulas for European options are obtained under the assumptions that the financial market is risk-aversive, the risk measure is standard deviation, and the price process of underlying asset follows a geometric Brownian motion. In particular, assuming the option writer does not need the risk compensation in a risk-neutral market, then the obtained results are degenerated into the famous Black–Scholes model (1973); furthermore, the obtained results need much weaker conditions than those of the Black–Scholes model. As a by-product, the obtained results show that the value of European option depends on the drift coefficient μ of its underlying asset, which does not display in the Black–Scholes model only because μ = r in a risk-neutral market according to the no-arbitrage opportunity principle. At last, empirical analyses on Shanghai 50 ETF options and S&P 500 options show that the fitting effect of obtained pricing formulas is superior to that of the Black–Scholes model.

Circular Economy and Value Creation: Sustainable Finance with a Real Options Approach

This paper presents a methodological proposal that integrates the circular economy concept and financial valuation through real options analysis. The Value Hill model of a circular economy provides a representation of the course followed by the value of an asset. Specifically, after the primary use, the life of an asset may be extended by going through four phases: the 4R phases (Reuse, Refurbish, Remanufacture and Recycle). Financial valuation allows us to quantify value creation from firms’ asset circularity under uncertainty, modelled by binomial trees. Furthermore, the 4R phases are valued as real options by applying no-arbitrage opportunity arguments. The major contribution of this paper is to provide a quantitative approach to the value of circularity in a general context that is adaptable to firms’ specific situations. This approach is also useful for translating relevant information for stakeholders and policy makers into something with economic and financial value.

Detection of arbitrage opportunities in multi-asset derivatives markets

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.

Further evidence on efficiency of Bahrain Bourse: A high challenge for other industries

The purpose of the present study is to provide further evidence of the weak form efficiency of the Bahrain Bourse. The research methodology is based on daily closing index values of the Bahrain Bourse from 2011 to 2015 in order to test the efficiency of the stock market while runs test, Autocorrelation Function, and advance tools such as ARCH and GARCH models and Hurst Index to provide further evidence of the weak form efficiency of the Bahrain stock market. For instance, a volatile and inefficient stock market has a negative impact on textile and apparel industry in the Kingdom of Bahrain, which is one of the most prosperous and attractive industries in the country. The empirical results revealed that Bahrain stock market does not follow normal distribution and the successive price changes are not independent. Further, ARCH effect is significant and indicative of a time-varying conditional volatility. There is an arbitrage opportunity and extreme mispricing in the Bahrain stock market as indicated by the GARCH (1,1) model. The results of the Hurst exponent also confirm the inefficiency of the market. The results of these tests are consistent indicating that the Bahrain stock market is inefficient

No-Arbitrage Principle in Conic Finance

In a one price economy, the Fundamental Theorem of Asset Pricing (FTAP) establishes that no-arbitrage is equivalent to the existence of an equivalent martingale measure. Such an equivalent measure can be derived as the normal unit vector of the hyperplane that separates the attainable gain subspace and the convex cone representing arbitrage opportunities. However, in two-price financial models (where there is a bid–ask price spread), the set of attainable gains is not a subspace anymore. We use convex optimization, and the conic property of this region to characterize the “no-arbitrage” principle in financial models with the bid–ask price spread present. This characterization will lead us to the generation of a set of price factor random variables. Under such a set, we can find the lower and upper bounds (supper-hedging and sub-hedging bounds) for the price of any future cash flow. We will show that for any given cash flow, for which the price is outside the above range, we can build a trading strategy that provides one with an arbitrage opportunity. We will generalize this structure to any two-price finite-period financial model.

No-Arbitrage Principle in Conic Finance

In a one price economy, the Fundamental Theorem of Asset Pricing (FTAP) establishes that no-arbitrage is equivalent to the existence of an equivalent martingale measure. Such an equivalent measure can be derived as the normal unit vector of the hyperplane that separates the attainable gain subspace and the convex cone representing arbitrage opportunities. However, in two-price financial models (where there is a bid-ask price spread), the set of attainable gains is not a subspace anymore. We use convex optimization, and the conic property of this region to characterize the “No-Arbitrage” principle in financial models with the bid-ask price spread present. This characterization will lead us to the generation of a set of price factor random variables. Under such a set, we can find the lower and upper bounds (supper-hedging and sub-hedging bounds) for the price of any future cash flow. We will show that for any given cash flow, for which the price is outside the above range, we can build a trading strategy that provides one with an arbitrage opportunity. We will generalize this structure to any two-price finite-period financial model.