The morale of this anecdote is that it is easy for philosophers to be rich if they choose; the famous Milesian went ahead and proved it. We, the Thalesians , admire him for that.
This wiki was created to serve as a source of information on quantitative finance, to collate references to various related resources, and to serve as a convergence point for the Thalesians , our colleagues and collaborators. It grew out of Paul Bilokon's finance wiki, which he started in February, We believe that secrecy and fidelity are important in the world of finance. But we also acknowledge the power of information sharing in open societies. Let your business logic remain a closely guarded secret. But release everything else into the public domain. What goes around, comes around; this will ultimately spare you reinventing the wheel.
Review of the Binomial Model for Option Pricing
You can register for this event and pay online on Meetup. We pose the problem of fitting a time series over a finite period of time as a dynamic stochastic optimization problem, in which the underlying cost functions depend on a measure of model approximation and variation in the selected parameters. We take advantage of the underlying Markov decision process to obtain a model that at optimality considers historical data as well as forecasts of future outcomes. By leveraging the theory of approximate dynamic programming we are able to obtain efficient methods that effectively react to changes in the data and consider the stream of future outcomes obtained from our past model decisions.
This give rise to models calibrated to historical data which at any point in time would be optimally positioned to react to possible future data stream. We conduct a broad set of numerical experiments to test our methods on energy-related time series data. Our numerical results show our methods performing strongly against traditional time series forecast methods. Ricardo A. His research focus on the science of decision-making in the presence of risk and utilizes dynamic stochastic optimization as its main tool.
This line of research impacts areas such as finance, management science, competitive energy markets, auction theory, and homeland security. Special thanks to the Fordham University Gabelli School of Business for hosting and sponsoring the seminar. Python is a great language for data science. When working with large datasets which don't fit entirely in memory, we may need to use some different approaches. In this talk we will discuss various Python libraries which are ideal for working with large time series datasets in a pandas-like way, including dask and vaex.
We shall also explore how to make computation parallel in Python, talking about the differences between threading and multiprocessing, and wrappers like concurrent.
- Francis Longstaff?
- Multi-grid methods and applications!
- The Construction of New Mathematical Knowledge in Classroom Interaction: An Epistemological Perspective (Mathematics Education Library).
- The Logical Structure of Philosophy, Psychology, Mind and Language in Wittgenstein and Searle?
- Oop - Learn Object Oriented Thinking and Programming.
We shall also talk about using the very powerful celery to distribute tasks. We shall illustrate the talk with a Jupyter notebook, including examples from finance such as using FX tick datasets. Saeed Amen is the founder of Cuemacro. Over the past fifteen years, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today Palgrave Macmillan and is the coauthor of The Book of Alternative Data Wiley , due in Through Cuemacro, he now consults and publishes research for clients in the area of systematic trading.
He has developed many Python libraries including finmarketpy and tcapy for transaction cost analysis. His clients have included major quant funds and data companies such as Bloomberg. He is also a co-founder of the Thalesians. In the face of the seemingly intractable existential problems and challenges the human race currently encounters, we actually need to systematically develop protocols to enhance emotional and social intelligence and creativity in the human individual.
These non-invasive protocols would be based on neuroplasticity and long term potentiation, and aim at neural retraining for optimal redevelopment and affect self-regulation in the individual regarded as a biological cybernetic system. In simple terms, to solve our existential problems, it is time to think about protocols for human development rather than just focus on AI and making machines more computationally intelligent.
Algorithmic Human Development seeks to aid individual human beings to trade their instinctual or learned traits of destructive aggression for individual and social creativity. Inspired partly by John Bowlby's Attachment Theory and supported by several computational models, our Self-Attachment protocol has parallels with Machine Learning as it employs the three basic paradigms of "substitution", "iteration" and "prior updating" in the human individual. Edalat will give the results of a long-term pilot project on the subject and describe two Bayesian brain models for Self-Attachment: one based on Hebbian artificial neural networks and one on the Free Energy Principle.
He will then describe a laughter protocol which directly counters old and entrenched beliefs of the Bayesian brain about past misfortunes and tragedies. It is designed to reduce negative emotions and boost positive affects and creativity. Last but not least, Edalat will also finally explain how, during his detention and confinement for eight months last year, he was able to successfully extend the domain of this laughter protocol to "existing conditions" and turn a very difficult situation into a highly productive opportunity.
He first took up a lectureship in Mathematics at Sharif University of Technology in Tehran and then joined the Computing Department at Imperial College London where he has been a professor of Computer Science and Mathematics since Edalat has also been a Social and Political activist and researcher. In early, 's he formulated the Mongol Trauma hypothesis to explain the relative demise of Islamic Societies in the Middle East as aconsequence of the enduring trans-generation of trauma caused by the Mongol invasions of the region in the 's.
It was partly in response to this hypothesis that in he started to work on Algorithmic Human Development. The scarcity of historical financial data has been a huge hindrance for the development algorithmic trading models ever since the first models were devised. In the ever-changing economic reality we live in, countless models are tried and evaluated. Most of these models seek extracting information from the market by measuring a set of reasonable variables.
Applications emphasize the use of derivative securities for managing financial risk. FIN - Financial Institutions and Markets 3 hours Operation of financial institutions and interrelationships between their operations and economic activity; credit flow and money movements, in the context of financial institutions' operations.
Structure and organization of the financial system; emphasis on markets and intermediaries.
FIN - Commercial Bank Management 3 hours The role of commercial banks in the capital markets; introduction and application of financial management concepts, tools, and techniques to the fundamental financial decisions that managers of commercial banks make. Focus is on the dynamic banking environment, regulations, nature of risks, asset and liability management, investment and credit decisions, and financing decision of commercial banks. FIN - Financial Services Marketing 3 hours Examination of the increasing use of marketing techniques in the financial services industry and the changing environment of financial services.
STEM-designated Full-Time Major - D'Amore-McKim School of Business at Northeastern University
Course is structured around the core marketing principles of buyer behavior, segmentation, product development, distribution, pricing and promotion, as well as topics such as relationship marketing, customer loyalty, and technological developments. Designed for students with an interest in banking, insurance, securities, and other financial services industries.
Cross listed with MTG FIN - Entrepreneurial Finance 3 hours Planning and strategies involved in starting or expanding a business. Emphasis on capitalization, record keeping, liquidity management, fixed asset management, financial analysis, expansion strategies, establishing firm value, and exiting the firm. Cross-listed with ENT FIN - Liquidity Management 3 hours Managing firms' liquidity position; emphasis on use of positive and normative models dealing with short term assets and liabilities; ensuring liquidity while enhancing firm value.
WI Interpretation and analysis of corporate financial statements. Current annual and interim reports as a source of data for management, stockholders, and creditors. Emphasis on modern finance tools in managerial decision making.
Recent literature of corporate finance. Strategic wealth creation, general valuation principles, evaluation of net present value rule, alternative capital budgeting methods, ranking projects, taxation, marginal cash flows, and the impact of inflation. Single-investment risk analysis, risk analysis for top management and fully diversified investors, cost of capital, capital structure, dividend policy, interactions between investment and financing decisions, leasing, and capital rationing.
Market-oriented capital asset pricing model, options pricing model, and arbitage pricing theory. Market efficiency. Relationship of portfolio theory to fundamental and technical analyses. Portfolio management and evaluation techniques. Econometric, distribution-based, Markov and Stochastic Process concepts are employed.
FIN - Topics in Finance 3 hours Topics of special interest which may vary each time course is offered.
Topic and prerequisite stated in current Schedule of Classes. May be repeated under different topics for a maximum of nine hours credit. FIN - Financial Strategy 3 hours Contemporary review of theory and practice of financial risk management. Principles for managing financial risk are applied to interest rates, exchange rates, and commodity prices.
Financial engineering is incorporated into unified ethical and sustainable managerial problem solving and policy decisions designed to achieve successful operations.