We build the network of the top 190 Italian quoted companies during the two financial crises of 2008-2009 (US credit crisis) and 2010-2011 (European sovereign debt crisis) and compare its structure to the pre-crises years, using both minimum spanning trees and the full network with thresholds. We also analyze the centrality and compactness of industry sectors. We find a general contraction of the network during the crises, both numerically due to stronger correlation as well as topologically, with the appearance of central dominant companies which attract the other ones into a very large cluster, dominated by financial institutions (commercial banks and insurance companies). In particular, we note the role of insurance behemoth Assicurazioni Generali, which rises from a pre-crises subordinate role to become the central company in the minimum spanning tree after the crises period. The few sectors which maintain compactness before and during the crises are utilities, publishing, and construction.
{"title":"The network of the Italian stock market during the 2008-2011 financial crises","authors":"Paolo Coletti, Maurizio Murgia","doi":"10.3233/AF-160177","DOIUrl":"https://doi.org/10.3233/AF-160177","url":null,"abstract":"We build the network of the top 190 Italian quoted companies during the two financial crises of 2008-2009 (US credit crisis) and 2010-2011 (European sovereign debt crisis) and compare its structure to the pre-crises years, using both minimum spanning trees and the full network with thresholds. We also analyze the centrality and compactness of industry sectors. We find a general contraction of the network during the crises, both numerically due to stronger correlation as well as topologically, with the appearance of central dominant companies which attract the other ones into a very large cluster, dominated by financial institutions (commercial banks and insurance companies). In particular, we note the role of insurance behemoth Assicurazioni Generali, which rises from a pre-crises subordinate role to become the central company in the minimum spanning tree after the crises period. The few sectors which maintain compactness before and during the crises are utilities, publishing, and construction.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"5 1","pages":"111-137"},"PeriodicalIF":0.5,"publicationDate":"2017-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-160177","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46703453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the effect of latency arbitrage on allocative efficiency and liquidity in fragmented financial markets. We employ a simple model of latency arbitrage in which a single security is traded on two exchanges, with price quotes available to regular traders only after some delay. An infinitely fast arbitrageur reaps profits when the two markets diverge due to this latency in cross-market communication. Using an agent-based approach, we simulate interactions between high-frequency and zero-intelligence trading agents. From simulation data over a large space of strategy combinations, we estimate game models and compute strategic equilibria in a variety of market environments. We then evaluate allocative efficiency and market liquidity in equilibrium, and we find that market fragmentation and the presence of a latency arbitrageur reduces total surplus and negatively impacts liquidity. By replacing continuous-time markets with periodic call markets, we eliminate latency arbitrage opportunities and achieve further efficiency gains through the aggregation of orders over short time periods.
{"title":"Latency arbitrage in fragmented markets: A strategic agent-based analysis","authors":"Elaine Wah, Michael P. Wellman","doi":"10.3233/AF-160060","DOIUrl":"https://doi.org/10.3233/AF-160060","url":null,"abstract":"We study the effect of latency arbitrage on allocative efficiency and liquidity in fragmented financial markets. We employ a simple model of latency arbitrage in which a single security is traded on two exchanges, with price quotes available to regular traders only after some delay. An infinitely fast arbitrageur reaps profits when the two markets diverge due to this latency in cross-market communication. Using an agent-based approach, we simulate interactions between high-frequency and zero-intelligence trading agents. From simulation data over a large space of strategy combinations, we estimate game models and compute strategic equilibria in a variety of market environments. We then evaluate allocative efficiency and market liquidity in equilibrium, and we find that market fragmentation and the presence of a latency arbitrageur reduces total surplus and negatively impacts liquidity. By replacing continuous-time markets with periodic call markets, we eliminate latency arbitrage opportunities and achieve further efficiency gains through the aggregation of orders over short time periods.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"5 1","pages":"69-93"},"PeriodicalIF":0.5,"publicationDate":"2017-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-160060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44435487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a computational economics model of the property-liability insurance underwriting cycle. This computer experiment is built on downward-sloping demand, a simplistic version of the capacity constraint model of insurance supply, and a simple pricing rule. The pricing rule has each experimental insurer determine its price from the expected losses per-policy (a constant), the previous year’s policyholders’ surplus and the previous year’s number of customers. Through the use of directional bit sequences a common structure is revealed between the simulated aggregate underwriting margin and the actual aggregate underwriting margin, 1930–2000. The common structure between these aggregate variables is evidence the property-liability underwriting cycle, in a consistent effort to reach equilibrium, follows an algorithmic process. Of more general inference; the pursuit of equilibrium, as an attractor, is the only consistent characteristic of the algorithmically generated process. This algorithmic process precludes the notion of a consistent continuous probability distribution being the basis of a data generating process (DGP). The times series behavior of the simulated underwriting margin, as it fluctuates around the equilibrium attractor, can assume a variety of shapes across many realizations of the algorithmic process. Finally, behavior of the simulated individual companies is not, for the most part, correlated with the aggregate behavior, and virtually all individual transactions are out-of-equilibrium transactions in the sense that they occur along the demand curve.
{"title":"Using directional bit sequences to reveal the property-liability underwriting cycle as an algorithmic process","authors":"Joseph D. Haley","doi":"10.3233/AF-170172","DOIUrl":"https://doi.org/10.3233/AF-170172","url":null,"abstract":"This paper presents a computational economics model of the property-liability insurance underwriting cycle. This computer experiment is built on downward-sloping demand, a simplistic version of the capacity constraint model of insurance supply, and a simple pricing rule. The pricing rule has each experimental insurer determine its price from the expected losses per-policy (a constant), the previous year’s policyholders’ surplus and the previous year’s number of customers. Through the use of directional bit sequences a common structure is revealed between the simulated aggregate underwriting margin and the actual aggregate underwriting margin, 1930–2000. The common structure between these aggregate variables is evidence the property-liability underwriting cycle, in a consistent effort to reach equilibrium, follows an algorithmic process. Of more general inference; the pursuit of equilibrium, as an attractor, is the only consistent characteristic of the algorithmically generated process. This algorithmic process precludes the notion of a consistent continuous probability distribution being the basis of a data generating process (DGP). The times series behavior of the simulated underwriting margin, as it fluctuates around the equilibrium attractor, can assume a variety of shapes across many realizations of the algorithmic process. Finally, behavior of the simulated individual companies is not, for the most part, correlated with the aggregate behavior, and virtually all individual transactions are out-of-equilibrium transactions in the sense that they occur along the demand curve.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"6 1","pages":"3-21"},"PeriodicalIF":0.5,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-170172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic. By selecting ten assets from those available in Yahoo Finance from S&P500, between 1985 and 2015, the performance of the new proposed model was measured and compared to the model of portfolio selection of Markowitz (1952). The results showed that the portfolios selected using the local Gaussian correlation model performed better than the traditional Markowitz (1952) method in 63% of the cases using block bootstrap and in 71% of the cases using the standard bootstrap. Comparing the calculated Sharpe ratios, the proposed model yielded a better adjusted risk-return in the majority of the cases studied. 5
{"title":"Wealth management: Modeling the nonlinear dependence","authors":"M. Montenegro, P. Albuquerque","doi":"10.3233/AF-170203","DOIUrl":"https://doi.org/10.3233/AF-170203","url":null,"abstract":"This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic. By selecting ten assets from those available in Yahoo Finance from S&P500, between 1985 and 2015, the performance of the new proposed model was measured and compared to the model of portfolio selection of Markowitz (1952). The results showed that the portfolios selected using the local Gaussian correlation model performed better than the traditional Markowitz (1952) method in 63% of the cases using block bootstrap and in 71% of the cases using the standard bootstrap. Comparing the calculated Sharpe ratios, the proposed model yielded a better adjusted risk-return in the majority of the cases studied. 5","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"6 1","pages":"51-65"},"PeriodicalIF":0.5,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-170203","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study was to detect latent periodicity in the presence of deletions or insertions in the analyzed data, when the points of deletions or insertions are unknown. A mathematical method was developed to search for periodicity in the numerical series, using dynamic programming and random matrices. The developed method was applied to search for periodicity in the Euro/Dollar (Eu/$) exchange rate. The presence of periodicity within the period length equal to 24 hours and 25 hours, in the analyzed financial series, was shown. Periodicity can be detected only with insertions and deletions. The results of this study show that periodicity phase shifts, depend on the observation time. A period of 24 hours is a common phenomenon for foreign exchange rates, indices and stocks of different companies. We show it for the Bank of America and Microsoft stocks, S&P500 and NASDAG indexes and for the gold and silver prices as examples. The reasons for the existence of the periodicity in the financial ranks are discussed. The results can find application in computer systems, for the purpose of forecasting exchange rates.
{"title":"Study of the periodicity in Euro-US Dollar exchange rates using local alignment and random matrices","authors":"E. Korotkov, M. Korotkova","doi":"10.3233/AF-170182","DOIUrl":"https://doi.org/10.3233/AF-170182","url":null,"abstract":"The purpose of this study was to detect latent periodicity in the presence of deletions or insertions in the analyzed data, when the points of deletions or insertions are unknown. A mathematical method was developed to search for periodicity in the numerical series, using dynamic programming and random matrices. The developed method was applied to search for periodicity in the Euro/Dollar (Eu/$) exchange rate. The presence of periodicity within the period length equal to 24 hours and 25 hours, in the analyzed financial series, was shown. Periodicity can be detected only with insertions and deletions. The results of this study show that periodicity phase shifts, depend on the observation time. A period of 24 hours is a common phenomenon for foreign exchange rates, indices and stocks of different companies. We show it for the Bank of America and Microsoft stocks, S&P500 and NASDAG indexes and for the gold and silver prices as examples. The reasons for the existence of the periodicity in the financial ranks are discussed. The results can find application in computer systems, for the purpose of forecasting exchange rates.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"6 1","pages":"23-33"},"PeriodicalIF":0.5,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-170182","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Financial markets are notoriously complex environments, presenting vast amounts of noisy, yet potentially informative data. We consider the problem of forecasting financial time series from a wide range of information sources using online Gaussian Processes with Automatic Relevance Determination (ARD) kernels. We measure the performance gain, quantified in terms of Normalised Root Mean Square Error (NRMSE), Median Absolute Deviation (MAD) and Pearson correlation, from fusing each of four separate data domains: time series technicals, sentiment analysis, options market data and broker recommendations. We show evidence that ARD kernels produce meaningful feature rankings that help retain salient inputs and reduce input dimensionality, providing a framework for sifting through financial complexity. We measure the performance gain from fusing each domain's heterogeneous data streams into a single probabilistic model. In particular our findings highlight the critical value of options data in mapping out the curvature of price space and inspire an intuitive, novel direction for research in financial prediction.
{"title":"Extracting predictive information from heterogeneous data streams using Gaussian Processes","authors":"Sid Ghoshal, Steve Roberts","doi":"10.3233/AF-160055","DOIUrl":"https://doi.org/10.3233/AF-160055","url":null,"abstract":"Financial markets are notoriously complex environments, presenting vast amounts of noisy, yet potentially informative data. We consider the problem of forecasting financial time series from a wide range of information sources using online Gaussian Processes with Automatic Relevance Determination (ARD) kernels. We measure the performance gain, quantified in terms of Normalised Root Mean Square Error (NRMSE), Median Absolute Deviation (MAD) and Pearson correlation, from fusing each of four separate data domains: time series technicals, sentiment analysis, options market data and broker recommendations. We show evidence that ARD kernels produce meaningful feature rankings that help retain salient inputs and reduce input dimensionality, providing a framework for sifting through financial complexity. We measure the performance gain from fusing each domain's heterogeneous data streams into a single probabilistic model. In particular our findings highlight the critical value of options data in mapping out the curvature of price space and inspire an intuitive, novel direction for research in financial prediction.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"5 1","pages":"21-30"},"PeriodicalIF":0.5,"publicationDate":"2016-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-160055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69723793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This contribution proposes a novel order placement strategy which can be used for simulating continuous double auction financial markets, within an agent-based model framework. The order placement decision is given by an optimization problem which minimizes the risk adjusted execution cost, taking into consideration relevant market microstructure factors and intrinsic agent characteristics. This order submission process is more realistic than has been done previously and contributes to a higher fidelity of the intraday market dynamics. The results show that, as opposed to random submission strategies, high-frequency stylized facts such as the concave shape of the market price impact function and the power-law decaying relative price distribution of off-spread limit orders are replicated. Therefore, the resulting model can be used as a realistic test environment for high-frequency trading strategies, in the context of the current, heated debate over the impact of high-frequency trading. Not only the impact of individual trading strategies can be analyzed, but also the interdependencies and the global emergent behavior of multiple coexistent strategies. Moreover, innovative regulatory policies, which have not been tested yet under real market conditions, could be inspected.Enhanced content available, see PDF for details.
{"title":"Microstructure-Based Order Placement in a Continuous Double Auction Agent Based Model","authors":"Alexandru Mandes","doi":"10.3233/AF-150049","DOIUrl":"https://doi.org/10.3233/AF-150049","url":null,"abstract":"This contribution proposes a novel order placement strategy which can be used for simulating continuous double auction financial markets, within an agent-based model framework. The order placement decision is given by an optimization problem which minimizes the risk adjusted execution cost, taking into consideration relevant market microstructure factors and intrinsic agent characteristics. This order submission process is more realistic than has been done previously and contributes to a higher fidelity of the intraday market dynamics. The results show that, as opposed to random submission strategies, high-frequency stylized facts such as the concave shape of the market price impact function and the power-law decaying relative price distribution of off-spread limit orders are replicated. Therefore, the resulting model can be used as a realistic test environment for high-frequency trading strategies, in the context of the current, heated debate over the impact of high-frequency trading. Not only the impact of individual trading strategies can be analyzed, but also the interdependencies and the global emergent behavior of multiple coexistent strategies. Moreover, innovative regulatory policies, which have not been tested yet under real market conditions, could be inspected.Enhanced content available, see PDF for details.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2016-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-150049","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we introduce natural time analysis in financial markets. Due to the remarkable results of this analysis on earthquake prediction and the similarities of earthquake data to financial time series, its application in price prediction and algorithmic trading seems to be a natural choice. This is tested through a trading strategy with very encouraging results.
{"title":"Natural time analysis in financial markets","authors":"A. Mintzelas, K. Kiriakopoulos","doi":"10.3233/AF-160057","DOIUrl":"https://doi.org/10.3233/AF-160057","url":null,"abstract":"In this paper we introduce natural time analysis in financial markets. Due to the remarkable results of this analysis on earthquake prediction and the similarities of earthquake data to financial time series, its application in price prediction and algorithmic trading seems to be a natural choice. This is tested through a trading strategy with very encouraging results.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"5 1","pages":"37-46"},"PeriodicalIF":0.5,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-160057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We develop a model to study the role of rationality in economics and biology. The model's agents differ continuously in their ability to make rational choices. The agents' objective is to ensure their individual survival over time or, equivalently, to maximize profits. In equilibrium, however, rational agents who maximize their objective survival probability are, individually and collectively, eliminated by the forces of competition. Instead of rationality, there emerges a unique distribution of irrational players who are individually not fit for the struggle of survival. The selection of irrational players over rational ones relies on the fact that all rational players coordinate on the same optimal action, which leaves them collectively undiversified and thus vulnerable to aggregate risks.
{"title":"Darwinian adverse selection","authors":"Wolfgang Kuhle","doi":"10.3233/AF-160056","DOIUrl":"https://doi.org/10.3233/AF-160056","url":null,"abstract":"We develop a model to study the role of rationality in economics and biology. The model's agents differ continuously in their ability to make rational choices. The agents' objective is to ensure their individual survival over time or, equivalently, to maximize profits. In equilibrium, however, rational agents who maximize their objective survival probability are, individually and collectively, eliminated by the forces of competition. Instead of rationality, there emerges a unique distribution of irrational players who are individually not fit for the struggle of survival. The selection of irrational players over rational ones relies on the fact that all rational players coordinate on the same optimal action, which leaves them collectively undiversified and thus vulnerable to aggregate risks.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"5 1","pages":"31-36"},"PeriodicalIF":0.5,"publicationDate":"2015-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-160056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69723809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Malihe Alikhani, B. Kjos-Hanssen, Amirarsalan Pakravan, Babak Saadat
We consider options that pay the complexity deficiency of a sequence of up and down ticks of a stock upon exercise. We study the price of European and American versions of this option numerically for automatic complexity, and theoretically for Kolmogorov complexity. We also consider run complexity, which is a restricted form of automatic complexity.
{"title":"Pricing Complexity Options","authors":"Malihe Alikhani, B. Kjos-Hanssen, Amirarsalan Pakravan, Babak Saadat","doi":"10.3233/AF-150050","DOIUrl":"https://doi.org/10.3233/AF-150050","url":null,"abstract":"We consider options that pay the complexity deficiency of a sequence of up and down ticks of a stock upon exercise. We study the price of European and American versions of this option numerically for automatic complexity, and theoretically for Kolmogorov complexity. We also consider run complexity, which is a restricted form of automatic complexity.","PeriodicalId":42207,"journal":{"name":"Algorithmic Finance","volume":"1 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3233/AF-150050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69724213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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