Enhancing and implementing a pairs trading strategy

This paper designs a pairs trading model with the intent to identify existing profitable market opportunities to invest, i.e. traditionally strong correlated stocks that have diverged from its historical norm. It comprises a broad literature review on this strategy whose relevant findings (strategy improvements) are contemplated in the model. The authors combine the statistical results of the model with a backtesting analysis in order to provide guidance on the best investment opportunities.

Credit default swap (CDS) prediction model & trading strategy

This project focuses on the study of different explanatory models for the behavior of CDS security, such as Fixed-Effect Model, GLS Random-Effect Model, Pooled OLS and Quantile Regression Model. After determining the best fitness model, trading strategies with long and short positions in CDS have been developed. Due to some specifications of CDS, I conclude that the quantile regression is the most efficient model to estimate the data. The P&L and Sharpe Ratio of the strategy are analyzed using a backtesting analogy, where I conclude that, mainly for non-financial companies, the model allows traders to take advantage of and profit from arbitrages.

Is it possible to utilize VIX for a profitable trading strategy of S&P 500 Index?

The goal of this research was to make an overall sight to VIX® and how it can be used as a stock market indicator. Volatility index often referred as the fear index, measures how much it costs for investor to protect his/her S&P 500 position from fluctuations with options. Over the relatively short history of VIX it has been a successful timing coordinator and it has given incremental information about the market state adding its own psychological view of the amount of fear and greed. Correctly utilized VIX information gives a considerable advantage in timing market actions. In this paper we test how VIX works as a leading indicator of broad stock market index such as S&P 500 (SPX). The purpose of this paper is to find a working way to interpret VIX. The various tests are made on time series data ranging from the year 1990 to the year 2010. The 10-day simple moving average strategy gave significant profits from the whole time when VIX data is available. Strategy was able to utilize the increases of SPX in example portfolio value and was able to step aside when SPX was declining. At the times when portfolio was aside of S it was on safety fund like on treasury bills getting an annual yield of 3 percent. On the other side just a static number’s of VIX did not work as indicators in a profit making way.

A trading strategy based on the lead–lag relationship between the spot index and futures contract for the FTSE 100

This paper examines the lead–lag relationship between the FTSE 100 index and index futures price employing a number of time series models. Using 10-min observations from June 1996–1997, it is found that lagged changes in the futures price can help to predict changes in the spot price. The best forecasting model is of the error correction type, allowing for the theoretical difference between spot and futures prices according to the cost of carry relationship. This predictive ability is in turn utilised to derive a trading strategy which is tested under real-world conditions to search for systematic profitable trading opportunities. It is revealed that although the model forecasts produce significantly higher returns than a passive benchmark, the model was unable to outperform the benchmark after allowing for transaction costs.

Spread trading strategy for intraday short term interest rate futures markets

Neste trabalho analisaram-se estratégias de spread calendário de contratos futuros de taxa de juros de curto prazo (STIR – Short Term Interest Rate) em operações de intraday trade. O spread calendário consiste na compra e venda simultânea de contratos de STIR com diferentes maturidades. Cada um dos contratos individualmente se comporta de forma aleatória e dificilmente previsível. No entanto, no longo prazo, pares de contratos podem apresentar um comportamento comum, com os desvios de curto prazo sendo corrigidos nos períodos seguintes. Se este comportamento comum for empiricamente confirmado, há a possibilidade de desenvolver uma estratégia rentável de trading. Para ser bem sucedida, esta estratégia depende da confirmação da existência de um equilíbrio de longo prazo entre os contratos e a definição do limite de spread mais adequado para a mudança de posições entre os contratos. Neste trabalho, foram estudadas amostras de 1304 observações de 5 diferentes séries de spread, coletadas a cada 10 minutos, durante um período de 1 mês. O equilíbrio de longo prazo entre os pares de contratos foi testado empiricamente por meio de modelos de cointegração. Quatro pares mostraram-se cointegrados. Para cada um destes, uma simulação permitiu a estimação de um limite que dispararia a troca de posições entre os contratos, maximizando os lucros. Uma simulação mostrou que a aplicação deste limite, levando em conta custos de comissão e risco de execução, permitiria obter um fluxo de caixa positivo e estável ao longo do tempo.

Trading the changes of stock market index composition: Evidence from European markets

This paper studies the changes in European stock market indexes composition from 1995 to 2015. It was found that there are mixed price effects producing abnormal returns around the effective replacement of added and deleted stocks. The price pressure hypothesis seems to hold for added stocks in some indexes but not for deleted stocks as there is not a clear inversion of behaviour after the replacement. Finally, the building and back testing of a trading strategy aiming to capture some of those abnormal returns shows it yields a Sharpe Ratio of 1.4 and generates an annualised alpha of 11%.

Ecologies of Value in a Wall Street Trading Room

Our task in this paper is to analyze the organization of trading in the era of quantitative finance. To do so, we conduct an ethnography of arbitrage, the trading strategy that best exemplifies finance in the wake of the quantitative revolution. In contrast to value and momentum investing, we argue, arbitrage involves an art of association-the construction of equivalence (comparability) of properties across different assets. In place of essential or relational characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else-associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

How to recognize opportunities: Heterarchical search in a Wall Street trading room

Our task in this paper is to analyze the organization of trading in the era of quantitativefinance. To do so, we conduct an ethnography of arbitrage, the trading strategy that bestexemplifies finance in the wake of the quantitative revolution. In contrast to value andmomentum investing, we argue, arbitrage involves an art of association - the constructionof equivalence (comparability) of properties across different assets. In place of essentialor relationa l characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else - associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

Pairs Trading -strategia Suomen osakemarkkinoilla

Tutkielman tavoitteena on selvittää soveltuvatko suomalaiset osakkeet parikaupankäyntiin ja voidaanko niillä luoda tuottavia kaupankäyntistrategioita. Tutkielmassa tarkastellaan pystytäänkö suomalaisista osakkeista muodostamaan parikaupankäynnin kannalta toimivia osakepareja. Aineisto koostuu kaikkiaan 53 tutkitusta yrityksestä, joiden joukosta valitaan paras osakepari kultakin viideltä toimialalta. Tutkimusperiodi käsittää vuodet 2004–2007, eli se sisältää noin 1000 kaupankäyntipäivää per osa-ke. Viittä valittua osakeparia tutkitaan tarkemmin tilastollisilla ja teknisillä analyysimenetelmillä. Empiiristen tulosten perusteella suomalaiset osakkeet soveltuvat hyvin parikaupankäyntiin. Jokaisella viidellä tutkitulla osakeparilla ilmeni selvää hintojen erkaantumista ja konvergoitumista, joten niillä olisi tutkimuspe-riodin aikana pystynyt käymään menestyksekästä parikauppaa.

Pairs trading profitability in the Finnish stock market: A comparison between three methods

Pairs trading is an algorithmic trading strategy that is based on the historical co-movement of two separate assets and trades are executed on the basis of degree of relative mispricing. The purpose of this study is to explore one new and alternative copula-based method for pairs trading. The objective is to find out whether the copula method generates more trading opportunities and higher profits than the more traditional distance and cointegration methods applied extensively in previous empirical studies. Methods are compared by selecting top five pairs from stocks of the large and medium-sized companies in the Finnish stock market. The research period includes years 2006-2015. All the methods are proven to be profitable and the Finnish stock market suitable for pairs trading. However, copula method doesn’t generate more trading opportunities or higher profits than the other methods. It seems that the limitations of the more traditional methods are not too restrictive for this particular sample data.

Modelación estocástica y trading algorítmico del spread entre acciones mediante procesos de reversión a la media

Las estrategias de inversión pairs trading se basan en desviaciones del precio entre pares de acciones correlacionadas y han sido ampliamente implementadas por fondos de inversión tomando posiciones largas y cortas en las acciones seleccionadas cuando surgen divergencias y obteniendo utilidad cerrando la posición al converger. Se describe un modelo de reversión a la media para analizar la dinámica que sigue el diferencial del precio entre acciones ordinarias y preferenciales de una misma empresa en el mismo mercado. La media de convergencia en el largo plazo es obtenida con un filtro de media móvil, posteriormente, los parámetros del modelo de reversión a la media se estiman mediante un filtro de Kalman bajo una formulación de estado espacio sobre las series históricas. Se realiza un backtesting a la estrategia de pairs trading algorítmico sobre el modelo propuesto indicando potenciales utilidades en mercados financieros que se observan por fuera del equilibrio. Aplicaciones de los resultados podrían mostrar oportunidades para mejorar el rendimiento de portafolios, corregir errores de valoración y sobrellevar mejor periodos de bajos retornos.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.

An implementation of genetic algorithms as a basis for a trading system on the foreign exchange market

Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process is very helpful. In this paper, we try to create such a system with a genetic algorithm engine to emulate trader behaviour on the foreign exchange market and to find the most profitable trading strategy.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

Pairs trading in the UK equity market: risk and return

In this paper, we provide the first comprehensive UK evidence on the profitability of the pairs trading strategy. Evidence suggests that the strategy performs well in crisis periods, so we control for both risk and liquidity to assess performance. To evaluate the effect of market frictions on the strategy, we use several estimates of transaction costs. We also present evidence on the performance of the strategy in different economic and market states. Our results show that pairs trading portfolios typically have little exposure to known equity risk factors such as market, size, value, momentum and reversal. However, a model controlling for risk and liquidity explains a far larger proportion of returns. Incorporating different assumptions about bid-ask spreads leads to reductions in performance estimates. When we allow for time-varying risk exposures, conditioned on the contemporaneous equity market return, risk-adjusted returns are generally not significantly different from zero.