New York Institute of Finance
Public University • US
Showing 13 courses from New York Institute of Finance
Introduction to Supply Chain Finance & Blockchain Technology
New York Institute of Finance (via Coursera)
What is Supply Chain Finance? How does Blockchain apply? In this course, you’ll learn about an emerging set of solutions within trade finance implemented by financial institutions, leading corporate buyers and their trading partners all over the world known as Supply Chain Finance. You’ll learn about the key enablers in Supply Chain Finance and recognize the key challenges in the current market that are responsible for the growing interest in Supply Chain Finance. You’ll cover the concept, attributes, and metrics of working capital in great detail and review the four main products and solutions in Supply Chain Finance. The course will wrap up with a brief introduction to Blockchain and the basic concepts of Blockchain Technology. By the end of this course, you’ll have learned about the options to enter into the Supply Chain Finance market and how to identify the best solutions for your organization. There is no prerequisite knowledge required to participate in this course, but general business and financial acumen are helpful in understanding the full details of Supply Chain Finance solutions.
공급망금융의 주요 성공 요소
New York Institute of Finance (via Coursera)
공급망금융의 주요 성공 요소를 알아봄으로써 기업 구매 조직을 위한 성공적인 자금 조달 프로그램을 구현하고 관리합니다. 본 강좌에서는 공급망금융이 당면한 과제와 장애물이 무엇인지 알아보고, 이들이 공급망금융 프로그램에 미치는 영향을 알아봅니다. 본 강좌는 공급망금융 프로그램에 이상적인 고객이 누구인지 파악하고, 수익 창출 방법과 함께 공급망금융 프로그램의 가격 책정 방법을 이해하는 데 도움이 될 수 있도록 합니다. 강좌를 통해 공급자가 온보딩하여 거래할 수 있는 관련 요소를 알아보고 공급망금융와 관련된 주요 역할 및 책임을 파악할 수 있습니다. 또한 본 강좌에서는 지표 개발 방법을 설명하고 효과적인 자금 조달 프로그램을 개발함에 있어서 필요한 요소를 파악합니다. 본 강좌를 마치고 나면, 사전 영업 분석 및 세부 공급자 분석을 수행할 수 있으며, 이는 공급망금융 프로그램을 설정함에 있어서 중요한 역할을 합니다.
Market Risk Management: Frameworks & Strategies
New York Institute of Finance (via Coursera)
This course provides the foundation for understanding the frameworks used to develop market risk management strategies. You will identify the market risks associated with each type of financial instrument. You will be introduced to techniques for estimating the risk associated with each class of investments. By the end of the course, you will be able to select the most effective derivatives for managing risk of a single asset and a portfolio of assets, develop asset selection strategies for managing risk in a portfolio, and model risk associated with a single asset and a portfolio of assets. Learners will complete a project covering the estimation and analysis of risk in a globally diversified equity portfolio. The portfolio will include allocations of equity indexes from the U.S., Japan, Hong Kong, and Germany. Data for the two years prior to March 2020 will be used to convert daily returns in each indexes' currency into dollar returns. Value-at-Risk and Expected Shortfall for the portfolio will be calculated using an equal-weighted sample and an exponentially weighted sample. Learners will then be given a new 2-year data set that includes the market data through August of 2020. They will be asked to re-evaluate risk for the portfolio using Value-at-Risk and Expected Shortfall.
Using Machine Learning in Trading and Finance
New York Institute of Finance (via Coursera)
This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
Introduction to Risk Management
New York Institute of Finance (via Coursera)
What is risk? Why do firms manage risk? In this course, you will be introduced to the different types of business and financial risks, their sources, and best practice methods for measuring risk. This course will help you gauge different risk types and set risk limits, describe the key factors that drive each type of risk, and identify the steps needed to choose probability distributions to estimate risk. You will explore the history and development of risk management as a science, and financial and business trends that have shaped the practice of risk management. By the end of the course, you will have the essential knowledge to measure, assess, and manage risk in your organization. To be successful in this course, you should have a basic knowledge of statistics and probability and familiarity with financial instruments (stocks, bonds, foreign exchange, etc). Experience with MS Excel recommended.
Introduction to Trading, Machine Learning & GCP
Google Cloud
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. You will learn how to identify the profit source and structure of basic quantitative trading strategies. This course will help you gauge how well the model generalizes its learning, explain the differences between regression and forecasting, and identify the steps needed to create development and implementation backtesters. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
Reinforcement Learning for Trading Strategies
New York Institute of Finance (via Coursera)
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. You will learn how RL has been integrated with neural networks and review LSTMs and how they can be applied to time series data. By the end of the course, you will be able to build trading strategies using reinforcement learning, differentiate between actor-based policies and value-based policies, and incorporate RL into a momentum trading strategy. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
Supply Chain Finance Market and Fintech Ecosystem
New York Institute of Finance (via Coursera)
This course provides an in-depth understanding of the Supply Chain Finance market including insights on the potential and current market size, market penetration, growth, and distribution. You’ll be introduced to the four distinctive groups serving the Supply Chain Finance market and learn about the main stakeholders and market participants in a Supply Chain Finance program. By the end of the course, you’ll have reviewed the key trends and upcoming risks affecting Supply Chain Finance and gained a deeper understanding of the key challenges in the market amongst corporate clients, banks, non-bank financiers and technology service providers.
Key Success Factors in Supply Chain Finance
New York Institute of Finance (via Coursera)
Implement and manage a successful financing program for a corporate buying organization by learning about the key success factors in Supply Chain Finance. In this course, you'll learn about the challenges and bottlenecks in Supply Chain Finance and understand their impact on Supply Chain Finance programs. This course will help you understand who the ideal customer is for a Supply Chain Finance program and understand how revenue is generated and such programs are priced. You'll learn about the relevant factors for suppliers to come onboard and trade as well as identify the key roles and responsibilities involved in Supply Chain Finance. Additionally, this course will explain how to develop metrics and list the necessary elements for developing an effective financing program. By the end of this course, you’ll be able to perform a pre-sales analysis and a detailed supplier analysis, which are crucial for setting up a Supply Chain Finance program.
Operational Risk Management: Frameworks & Strategies
New York Institute of Finance (via Coursera)
In the final course from the Risk Management specialization, you will be introduced to the different roles in risk governance and the benefits of establishing an operational risk management program at your own workplace. This course will highlight key elements of an Operational Risk Management framework and help you identify the appropriate elements to incorporate in your own program. By the end of the course, you will be able to capture, report, and investigate operational risk events, produce meaningful key risk indicator (KRI) data and trend analysis, assess organizational risk appetite, and design an Operational Risk Control and Self-Assessment program. To be successful in this course, you should have a basic knowledge of statistics and probability and familiarity with business operations. Experience with MS Excel and Python recommended.
Future Development in Supply Chain Finance and Blockchain Technology
New York Institute of Finance (via Coursera)
This course focuses on future developments in Supply Chain Finance such as Artificial Intelligence (AI) and Application Programming Interfaces (APIs). This course covers the basic concepts of Distributed Ledger Technology (DLT), the key features as well as the benefits the solution represents for Supply Chain Finance. This course concludes with an understanding of the applicability of Blockchain Technologies and how they impact Supply Chain Finance.
Credit Risk Management: Frameworks and Strategies
New York Institute of Finance (via Coursera)
In this course, you will use business and industry analysis to understand companies, projects, business models, and financing proposals. You will then prepare qualitative risk analysis for specific companies to use as the basis for financial analysis, project analysis, and risk decisions. Lastly, you will understand how to use financial ratios and financial metrics to evaluate a company or project’s profitability, balance sheet, capital structure, and cash flow to assess overall financial performance and risk profile.
공급망금융 시장 및 핀테크 생태계
New York Institute of Finance (via Coursera)
이 강좌는 잠재 및 현재의 시장 규모, 시장 침투, 성장 및 분포에 대한 정보를 비롯해 공급망 금융 시장에 대해 자세히 설명합니다. 공급망 금융 시장에 서비스를 제공하는 각기 다른 4개 그룹을 알아보고 공급망 금융 프로그램의 주요 이해 관계자 및 시장 관계자에 대해 배웁니다. 강좌가 끝나면 공급망 금융에 영향을 미치는 주요 추세와 잠재 리스크를 검토하고 기업 고객, 은행, 비은행 금융업자 및 기술 서비스 제공자가 각각 겪는 주요 문제점을 자세히 설명합니다.