Arbitrage Model Research Articles

Is Managed Futures an Asset Class? The Search for the Beta of Commodity Futures

This paper investigates potential sources of return to speculators in the commodity futures market. Initially, we focus on the classic arbitrage model based on the theories of Keynes (1930), Kaldor (1939), Hicks (1939, 1946), Working (1948) and Brennan (1958). Next our study examines the simplified arbitrage model which references the term structure of the futures price curve and provides rationale for a structural risk premium known as the roll return. We then introduce our theory of roll yield permutations which is derived from integrating the futures price curve with the expected future spot price variable. Last, we investigate Spurgin's (2000) hedging response model from which asymmetric hedging response functions transfer risk premia to speculators. Our research indicates that these models have inherent shortcomings in being able to pinpoint a definitive source of structural risk premium within the complexity of the commodity futures markets. We hypothesize that the classic arbitrage pricing theory contains circular logic, and as a consequence, its natural state is disequilibrium, not equilibrium. We extend this hypothesis to suggest that the term structure of the futures price curve, while indicative of a potential roll return benefit, in fact implies a complex series of roll yield permutations. Similarly, the hedging response function elicits a behavioral risk management mechanisms, and therefore, corroborates social reflexivity. Such models are inter-related and each reflects certain qualities and dynamics within the overall futures market paradigm. With respect to managed futures, it is an observable materialization of behavioral finance, where risk, return, leverage and skill operate un-tethered from the anchor of an accurate representation of beta. In other words, it defies rational expectations equilibrium, the efficient market hypothesis and allied models - the CAPM, arbitrage pricing theory or otherwise - to single-handedly isolate a persistent source of return without that source eventually slipping away.

On the Extent of Arbitrage Constraints Within Transaction Algebras (A Non-Standard Approach)

Although the standard trading arbitrage model provides with simple settings and adjustment mechanisms so as to take profit whenever an arbitrage opportunity comes up, empirical evidence has been piling up showing that this point of view suffers from many downsides, leaving distinctive issues unresolved. By the same token, similar shortcoming prevent the standard financial arbitrage model from being functional to real markets environments. To overcome such drawbacks, this paper sets forth a new approach that is grounded on transactional algebras, which shapes the arbitrage gaps of return within institutional settings, to give account of market microstructure features and enlarged transaction costs.

Arbitrage Models and Mortgage Options Pricing

In this paper we examine the applicability of arbitrage theory to real estate. Arbitrage theory has been applied to the valuation of mortgages using partial differential equations, however the implicit assumptions made are problematic when applied to real estate. The latter is a very complex financial asset, and for instance, for the case of default options, one could produce very large errors (even up to 100%) by applying - unwisely - conventional arbitrage theory techniques. The consequences of real estate appraisal are in this paper studied in particular. Because one has encountered similar problems in real options theory as in real estate, the tools developed in that field could probably well adapt to real estate; we provide here an example. Finally the possibility of pricing contingent claims written on properties is discussed.

A Generalized Portfolio Approach to Limited Risk Arbitrage: Evidence from the MSCI Global Index Change

We develop a framework to explore the asset pricing implications of simultaneous supply shocks in multiple assets in a setting with limits-to-arbitrage. The portfolio approach in Greenwood (2005) is generalized to allow for asymmetric information and therefore net positions of arbitrageurs against uninformed liquidity providers. We predict that announcement returns are not only positively proportional to the asset premium change of each stock (like in Greenwood), but also negatively proportional to the risk contribution of the arbitrage position captured by the product of the squared return covariance matrix and the vector of supply changes. The redefinition of the MSCI international equity index in 2001 and 2002 provides a powerful event study to test these predictions. We find strong evidence in favor of our generalized model of limited arbitrage. Moreover, asset pricing effects of weight changes across stocks are quantitatively similar for domestic and foreign stocks. MSCI stocks are therefore priced globally and not locally.

VARIANCE TERM STRUCTURE AND VIX FUTURES PRICING

Using no arbitrage principle, we derive a relation between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.

Macro Factors and the Brazilian Yield Curve with no Arbitrage Models

We use no arbitrage models with macro variables to study the interaction between the macroeconomy and the yield curve. This interaction is a key element for monetary policy and for forecasting. The model was used to analyze the Brazilian domestic financial market using a daily dataset and two versions of the model, one in continuous-time and estimated by maximum likelihood, and the other in discrete time and estimated by Monte Carlo Markov Chain (MCMC). Our objective is threefold: 1) To analyze the determinants of the Brazilian domestic term structure considering nominal shocks; 2) To compare the results of the discrete and the continuous time versions considering adherence, forecasting performance and monetary policy analysis; and 3) To evaluate the effect of restrictions on the transition and pricing equations over the model properties. Our main results are: 1) results from continuous and discrete versions are qualitatively and in most cases quantitatively equivalent; 2) Monetary Authorities are conservative in Brazil, smoothing short rate fluctuations; 3) inflation shock, or slope shock, depending on the model selected, are the main sources of long run fluctuations of nominal variables; and finally, 4) no arbitrage models showed lower forecasting performance than an unrestricted factor model.

Analysis of an ϵ-arbitrage model for incomplete markets

The optimal replication strategy for incomplete markets is obtained by solving a system of partial differential equations. In this paper, we study existence and uniqueness of the solution of this system and propose a numerical method to compute this optimal strategy.

APPLYING THE GENETIC-BASED NEURAL NETWORKS TO VOLATILITY TRADING

The Black-Scholes options pricing model is widely applied in various options contracts, including contract design, trading, assets evaluation, and enterprise value estimation, etc. Unfortunately, this theoretical model limited by the influences of many unexpected real world phenomena due to six unreasonable assumptions. If we were to soundly take these phenomena into account, the opportunity to gain an excess return would be created. This research therefore combines both the remarkable effects caused by the implied volatility smile (or skew) and the tick-jump discrepancy between the underlying and derivative prices to establish a two-phase options arbitrage model using a genetic-based neural network (GNN). Using evidence from the warrant market in Taiwan, it is shown that the GNN model with arbitrage operations is superior in terms of performance to the original Black-Scholes-based arbitrage model. The GNN model is found to be suitable for application to various options markets as the valuation factors are modified. This paper helps to integrate the theoretical model with important practical considerations.

Arbitrage and Convergence: Evidence from Mexican ADRs

This paper investigates the convergence between the prices of ADRs and the prices of the Mexican traded shares using a sample of 21 dually listed shares (listed in Mexico and in the U.S.). Since both markets have similar trading hours in Mexico, standard arbitrage considerations should make persistent deviation from price parity rare. We estimate the convergence of the ADRs and the locally traded shares using non-linear models. We reject the linear adjustment model and, based on different tests, we select the ESTAR model. We find that price spreads tend to die out quickly; for 15 out of 21 pairs, it takes about 1 day for the ADR-underlying price spread to be reduced by half. Four firms, however, have high half-life estimates (seven days or more), and in general correspond to companies that display very low average daily volume, and thus, arbitrage might be difficult to execute. The results of Spearman correlation tests confirm this finding as most liquidity market indicators are positively correlated to the speed of convergence to parity. The average half-life is 3.1 business days. By allowing non-linear adjustments, the average half-life is reduced by more than 57% when compared to the standard linear arbitrage model.

Variance Term Structure and VIX Futures Pricing

Using no arbitrage principle, we derive a relationship between the drift term of risk-neutral dynamics for instantaneous variance and the term structure of forward variance curve. We show that the forward variance curve can be derived from options market. Based on the variance term structure, we derive a no arbitrage pricing model for VIX futures pricing. The model is the first no arbitrage model combining options market and VIX futures market. The model can be easily generalized to price other volatility derivatives.

Arbitrage in Foreign Exchange Markets Within the Context of a Transactional Algebra

This paper sets forth the foundations for a transactional approach for the performance of arbitrage in foreign exchange markets. Firstly, we review both the standard model of financial arbitrage and the so-called covered-interest arbitrage environment, and we also lay bare striking shortcomings in these points of view, mainly grounded on a wide- ranging empirical evidence. Next, we move on to what we have labeled in previous research working papers a transactional algebra, from which we expand on its main tools of analysis, namely differential rates, residual information sets, arbitrage gaps and transaction costs functions. Afterwards, we establish and prove the minimal conditions under which a successful arbitrage can be carried out within a transactional algebra.

A filtered no arbitrage model for term structures from noisy data

We consider an affine term structure model of interest rates, where the factors satisfy a linear diffusion equation. We assume that the information available to an agent comes from observing the yields of a finite number of traded bonds and that this information is not sufficient to reconstruct exactly the factors. We derive a method to obtain arbitrage-free prices of illiquid or non traded bonds that are compatible with the available incomplete information. The method is based on an application of the Kalman filter for linear Gaussian systems.

The Corn Laws and English wheat prices, 1815–1846

The British Corn Laws of the nineteenth century are the classic example of a trade barrier. This paper evaluates their importance to English society by analyzing the effects of the Corn Laws on wheat markets. Import supply elasticities are estimated for all of England's major grain supply markets, using data on prices, quantities, and freight costs from each country. A partial equilibrium trade arbitrage model is then constructed. In the absence of the Corn Laws, prices would have been 9 percent lower and consumption about 1.5 percent greater. The Corn Laws were, therefore, of great social and economic importance as England moved into the period of industrialization.

Mean Reversion Tests of Put-call Parity for Equity Index Options with Randomization and Bayesian Gibbs Sampling Viewpoint: S&P500 versus DAX

The put-call parity (PCP) is traditionally tested by examining whether arbitrage strategies earn ex post profits. These 'direct' tests of PCP caution that these violations of PCP suggest the arbitrage models are subject to significant risk due to market frictions. The previous empirical results also indicate that when market frictions are taken into account, the deviations form PCP can fluctuate within a bounded interval without giving rise to any arbitrage profit. In contrast with previous studies, we presents a model of the option price mean reverting to a function form of PCP. We employ variance ratio test to the deviations of PCP with randomization and Bayesian Gibbs sampling viewpoint in the context of a three-state Markov-switching model. The result shows that the PCP deviations from the electronic screen-traded DAX index option, which is calculated as if the dividends are reinvested in the index, displays mean reversion at long horizons. On the other hand, those deviations from the floor-traded S&P500 index option, which is not corrected for dividend payments, vary randomly.

Tort Liability, Insurance Rates, and the Insurance Cycle

Markets for many types of property and casualty insurance exhibit soft-market periods, where premium rates are stable or falling and coverage is readily available, and subsequent hard-market periods, where premium rates and insurers' reported profits significantly increase and less coverage is available. Conventional wisdom among practitioners and other observers is that soft and hard markets occur in a regular "underwriting cycle." Like price fluctuations in equity markets, fluctuations in insurance premium rates and coverage availability are difficult to explain fully by standard economic models that assume rational agents and few market frictions. The mid-1980s "liability insurance crisis" remains the most infamous hard market in the United States. The dramatic increases in commercial liability insurance premiums and reductions in coverage availability for some sectors received enormous attention, motivating extensive research on those specific problems and on fluctuations in insurance prices and coverage availability more generally. Large losses from natural catastrophes in the United States during the late 1980s and early 1990s spurred further interest in and research on the dynamics of pricing in reinsurance and primary insurance markets following large, industry-wide losses. The hard market for commercial property and casualty insurance that began in late 2000 and accelerated following the destruction of the World Trade Center in September 2001 focused renewed attention on markets for commercial [End Page 97] property, medical liability, general liability, and workers' compensation insurance. With respect to general liability and medical liability insurance, substantial debate has arisen concerning the causes of increases in rates and reductions in coverage availability and the attendant implications for policy, such as tort reform, to reduce the expected value and uncertain costs of liability insurance claims or additional regulation of insurers to control allegedly imprudent underwriting and investment. This paper provides an overview of volatility in premiums, coverage availability, and insurers' reported profits in U.S. commercial general liability insurance and examines its broad relation to the U.S. tort liability system.1 I begin with a synopsis of the perfect markets model of insurance prices (sometimes called the arbitrage model) and its implications for commercial liability insurance. I next describe fluctuations in U.S. general liability insurance premiums, coverage availability, and reported profits during the past two decades and examine whether the perfect markets model is consistent with that evidence. I then summarize other factors that may affect insurance market volatility and provide new evidence concerning one alternative: that aberrant pricing by some firms aggravates soft markets and, by implication, the severity of subsequent hard markets. I conclude with a brief summary of policy implications and areas for future research. Competitive Insurance Premiums with Frictionless Capital Markets With rational insurers and policyholders, competitive insurance markets, and frictionless capital markets, insurance premiums will equal the risk-adjusted discounted value of expected cash outflows for claims, sales expenses, income taxes, and any other costs, including the tax and agency costs of capital. The levels and changes in premium rates will coincide with the levels and changes in discounted expected costs. Because the timing of payouts for claims incurred in a given year, nonclaim expenses, and capital costs should be comparatively stable over time, rate changes will primarily reflect changes in expected (forecast) claim and claim settlement costs and changes in interest rates. [End Page 98] In this perfect markets framework, long-run levels and short-run changes in premium rates for general liability insurance will reflect levels and changes in the following: Expected claim costs (incurred losses) and claim settlement costs, The timing of future claim payments for incurred losses, Interest rates used to discount expected future claim and claim settlement costs, Underwriting expenses (commissions, wages to underwriters, policy issue costs, premium taxes, and so on), Uncertainty about the frequency and severity of claims, including uncertainty about the form and parameters of the relevant probability distributions, which in turn affects the amount of capital that insurers need to hold to protect themselves against...

What Drives the Persistent Competitiveness of Small Banks?

Several trends in the financial industry could have weakened the competitiveness of small banks in recent years. Despite those challenges, small banks have grown more rapidly than larger banks over the period from 1985 to 2001, and their profitability has been sustained at high levels. However, small banks have needed to increase the interest rates offered on deposit accounts in order to attract progressively more deposit funding. In this paper, we provide empirical evidence that this increased interest cost primarily reflects the high rate of return that small banks were able to earn on their assets. Moreover, we show with an arbitrage model that the decline in the real value of deposit insurance has only a small effect on deposit rates as long as bank failure rates are in the low range of recent years.

What Drives the Persistent Competitiveness of Small Banks?

Several trends in the financial industry could have weakened the competitiveness of small banks in recent years. Despite those challenges, small banks have grown more rapidly than larger banks over the period from 1985 to 2001, and their profitability has been sustained at high levels. However, small banks have needed to increase the interest rates offered on deposit accounts in order to attract progressively more deposit funding. In this paper, we provide empirical evidence that this increased interest cost primarily reflects the high rate of return that small banks were able to earn on their assets. Moreover, we show with an arbitrage model that the decline in the real value of deposit insurance has only a small effect on deposit rates as long as bank failure rates are in the low range of recent years.

Establishing an Index Arbitrage Model by Applying Neural Networks Method - A Case Study of Nikkei 225 Index

Establishing an Index Arbitrage Model by Applying Neural Networks Method - A Case Study of Nikkei 225 Index

Index arbitrage with heterogeneous investors: A smooth transition error correction analysis

The traditional index arbitrage model assumes a constant threshold mispricing between the futures and cash prices for all investors. Allowing for heterogeneity in investors' transaction costs, objectives, and capital constraints, we model the intraday mispricing of DJIA futures as a smooth transition autoregressive (STAR) process with the speed of adjustment toward equilibrium varying directly with the mispricing. We show that the observed mean reversion in mispricing changes is induced by heterogeneous arbitrageurs, instead of a statistical illusion-infrequent trading of index portfolio stocks. We further use a STAR error correction model to describe the nonlinear dynamics between the DJIA futures and index. This model describes not only which market is more informationally efficient than the other, but also the legging process – the nonsimultaneous establishing of cash and futures positions.

Dynamic Models of the Term Structure

In the past 25 years, tremendous progress has been made in modeling the dynamics of the term structure of interest rates, which play an instrumental role in determining prices and hedging portfolios of fixed-income derivative securities. This article reviews the theoretical development of the dynamic models of the default-free term structure and their applications in pricing interest rate options. Classic models, sometimes termed equilibrium models, and their multifactor extensions are outlined. These models provide clear economic intuitions connecting the term structure with economic fundamentals. They also lay a foundation for the framework of the arbitrage models that price interest rate derivatives on the basis of the market prices of bonds. This framework has been expanded and enriched by recent advances in directly modeling observable market rates through the market models and in incorporating an internally consistent correlation structure through the “infinite-dimensional” models.