About

Dr. Alexander Becker recently completed his PhD in econophysics at Boston University. He is an expert in quantitative finance with very solid knowledge of applied finance, possessing both theoretical and hands-on experience in advanced finance tools and methods. Dr. Becker has a strong publishing record and has been involved in educational science and teaching research. He has served as a Scholar of Teaching and Learning at the BU Center for Teaching and Learning, and as a Teaching and Research Fellow at the BU Center for the Integration of Research, Teaching and Learning (CIRTL). In 2014, he was the recipient of the CAS Outstanding Teaching Fellow award at BU. Currently, as an Affiliate Faculty member (Assistant Professor – MET) at Boston University, Dr. Becker teaches courses in quantitative methods for finance, financial concepts, and investments. His office is located at MET 425, and his contact information includes email apbecker@bu.edu and phone 617-353-3016.

Research topics

• Computer Science
• Computer Security
• Economics
• Business
• Financial system
• Finance
• Artificial Intelligence
• Actuarial science
• Macroeconomics
• Microeconomics
• Monetary economics

Selected publications

• Market Instability from Option Flows

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Market Instability from Option Flows

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Market Instability from Option Flows

  SSRN Electronic Journal · 2024-01-01

  articleOpen access
  PublisherDOI

• Systemic stress test model for shared portfolio networks

  Scientific Reports · 2021 · 10 citations

  • Computer Science
  • Business
  • Artificial Intelligence

  We propose a dynamic model for systemic risk using a bipartite network of banks and assets in which the weight of links and node attributes vary over time. Using market data and bank asset holdings, we are able to estimate a single parameter as an indicator of the stability of the financial system. We apply the model to the European sovereign debt crisis and observe that the results closely match real-world events (e.g., the high risk of Greek sovereign bonds and the distress of Greek banks). Our model could become complementary to existing stress tests, incorporating the contribution of interconnectivity of the banks to systemic risk in time-dependent networks. Additionally, we propose an institutional systemic importance ranking, BankRank, for the financial institutions analyzed in this study to assess the contribution of individual banks to the overall systemic risk.

  PublisherOA PDFDOI

• From stress testing to systemic stress testing: The importance of macroprudential regulation

  Journal of Financial Stability · 2020 · 18 citations

  • Computer Science
  • Computer Security
  • Business

  Stability of the banking system and macroprudential regulation are essential for healthy economic growth. In this paper we study the European bank network and its vulnerability to stressing different bank assets. The importance of macroprudential policy is emphasized by the inherent vulnerability of the financial system, high level of leverage, interconnectivity of system's entities, similar risk exposure of financial institutions, and susceptibility for systemic crisis propagation through the system. Current stress tests conducted by the European Banking Authority do not take in consideration the connectivity of the banks and the potential of one bank vulnerability spilling over to the rest of the system. We create a bipartite network with bank nodes on one hand and asset nodes on the other with weighted links between the two layers based on the level of different countries’ sovereign debt holdings by each bank. We propose a model for systemic risk propagation based on common bank exposures to specific asset classes. We introduce the similarity in asset distribution among the banks as a measure of bank closeness. We link the closeness of asset distributions to the likelihood that banks will experience a similar level and type of distress in a given adverse scenario. We analyze the dynamics of tier 1 capital ratio after stressing the bank network and find that while the system is able to withstand shocks for a wide range of parameters, we identify a critical threshold for both asset risk and bank response to a shock beyond which the system transitions from stable to unstable.

  PublisherDOI

• Systemic Stress Test Model in Shared Portfolio Networks

  SSRN Electronic Journal · 2020 · 3 citations

  • Computer Science
  • Business
  • Financial system
  PublisherDOI

• Interdependence, Vulnerability and Contagion in Financial and Economic Networks

  New economic windows · 2019-01-01 · 7 citations

  book-chapterSenior authorCorresponding
  PublisherDOI

• Maximum entropy and network approaches to systemic risk and foreign exchange

  OpenBU/Boston University Institutional Repository (Boston University) · 2018-01-01 · 2 citations

  dissertationOpen access1st authorCorresponding

  The global financial system is an intricate network of networks, and recent financial crises have laid bare our insufficient understanding of its complexity. In response, within the five chapters of this thesis we study how interconnectedness, interdependency and mutual influence impact financial markets and systemic risk. 
\n In the first part, we investigate the community formation of global equity and currency markets. We find remarkable changes to correlation structure and lead-lag relationships in times of economic turmoil, implying significant risks to diversification based on historical data. 
\n The second part focuses on banks as creators of credit. Bank portfolios generally share some overlap, and this may introduce systemic risk. We model this using European stress test data, finding that the system is stable across a broad range of asset liquidity and risk tolerance. However, there exists a phase transition: If banks become sufficiently risk averse, even small shocks may inflict great losses. Failure to address portfolio overlap thus may leave the banking system ill-prepared. 
\n Complete knowledge of the financial network is prerequisite to such systemic risk analyses. When lacking this knowledge, maximum entropy methods allow a probabilistic reconstruction. In the third part of this thesis, we consider Japanese firm-bank data and find that reconstruction methods fail to generate a connected network. Deriving an analytical expression for connection probabilities, we show that this is a general problem of sparse graphs with inhomogeneous layers. Our results yield confidence intervals for the connectivity of a reconstruction.
\n The maximum entropy approach also proves useful for studying dependencies in financial markets: On its basis, we develop a new measure for the information content in foreign exchange rates in part four of this thesis and use it to study the impact of macroeconomic variables on the strength of currency co-movements.
\n While macroeconomic data and the law of supply and demand drive financial markets, foreign exchange rates are also subject to policy interventions. In part five, we classify the roles of currencies within the market with a clustering algorithm and study changes after political and monetary shocks. This methodology may further provide a quantitative underpinning to existing qualitative classifications.

  Publisher

• Economic and political effects on currency clustering dynamics

  Quantitative Finance · 2018-12-13 · 11 citations

  article

  The symbolic performance of a currency describes its position in the FX markets independent of a base currency and allows the study of central bank policy and the assessment of economic and political developments

  PublisherDOI

• Economic and Political Effects on Currency Clustering Dynamics

  SSRN Electronic Journal · 2017-01-01 · 1 citations

  articleOpen access
  PublisherDOI

Frequent coauthors

• Irena Vodenska

  Saints Cyril and Methodius University of Skopje

  14 shared

• Hideaki Aoyama

  RIKEN

  4 shared

• Amir Alamir

  Metropolitan University College

  3 shared

• Marcel Kremer

  3 shared

• H. Eugene Stanley

  Boston University

  3 shared

• Rudi Schäfer

  University of Duisburg-Essen

  2 shared

• Hiroshi Iyetomi

  Canon (Japan)

  2 shared

• Yoshi Fujiwara

  2 shared

Education

• Ph.D., Department of Physics

  Boston University

  2018

Awards & honors

• 2014 CAS Outstanding Teaching Fellow award at BU