Data Analytics has certainly created its mark in several diversified domains but its importance in Risk Analysis cannot be underestimated. With the sudden surge in the investment options, the probability of Portfolio Risk has also increased. In simple terms, Portfolio Risk can be explained as the unfavorable event attached with the combination of a variety of assets /units in the investment scope which fails to meet financial objectives. Thus, Portfolio Risk Analytics assists advisers and wealth managers to develop forward-looking risk analyses for supporting multi-asset investment portfolios.
What is Portfolio Risk Analytics?
It is a flexible cloud-based financial analysis and projection solution hosted by development companies to make the process of financial scenario modeling more refined, relevant, and reliable. The tool makes it convenient to design and delivers robust risk management support for the effective governance of retail investment portfolios or propositions. Moreover, this secure cloud-based AI solution carries out bespoke risk analyses and further facilitates data visualization and reporting with its modernized Machine Learning (ML) infrastructure.
Use Cases of Portfolio Risk Analytics
The use cases of Data Risk Analytics in Portfolio Risk Management have brought major delight to the complete investment ecosystem. The use of AI-driven prediction and projection has extended its application scope and made the portfolio management process extremely seamless.
|Facilitate Asset Allocation||Portfolio Risk Analytics serves as the perfect solution for financial planning and helps make appropriate planning decisions with the lower risk associated with the investment products. This technological solution proves efficient in testing ad running different asset allocations in the portfolio. These incorporated assets are identified and evaluated on the two major grounds – risk and return through the Portfolio Risk Analytics.|
|Designing Investment Product||The analytics tool delivers the solution in the form of a suitable framework for designing and developing the investment proposition which aligns best with the specific business needs of the individuals and business houses. Such a robust portfolio risk analysis tool enables objective risk–graded proposition and aligns with the standard regulation while addressing the specific needs of each client or investor.|
|Multi-Asset Portfolio Management||The scenario and asset-liability modeling of the Portfolio Risk Analytics help to offer well-researched investment product designs and risk-management solutions for the long–term benefit of the associated parties. Thus, returns are made to overpower investment, not the risks.|
|Tracking Portfolio Errors||While making investment decisions, the tracking error is extremely useful as it helps to define the standard deviation concerning the return. Thus, Portfolio Risk Analytics helps to provide a common benchmark for deriving true analysis and leading towards better strategy formulations|
Metrics used for Portfolio Risk Analytics
While planning an investment the quantification of the risk is the priority task and begins with a thorough analysis of standard deviation. As a result, to process the portfolio risk assessment and analysis the list of metrics has been classified into two main parts – Absolute and Relative Risk Metrics. Through each of these metrics, the uncertainty of the investment in a specified period can be derived.
These metrics are aimed at measuring the risk of financial assets in absolute terms i.e. avoiding any relation with market returns.
|Portfolio Standard Deviation||It is one of the widely used metrics used for evaluating risk and refers to the extension of dispersion for a complete population of observations. Thus, it helps to ascertain the investment return volatility.|
|Short Fall Risk||Using this data simulation, the risk of assets being exhausted at a given interval is determined. Hence, play a crucial role in assessing the true value of the overall investment portfolio.|
|Value – at–Risk (VAR)||With this metric, the potential of extreme loss in the given portfolio is determined. It is calculated based on a specified level of loss in a period covering risk assessment intervals.|
This form of metric measures the volatility and comparable risk associated with the potential investment in the broader market.
|Sharpe Ratio||The ratio represents the risk-adjusted return of the portfolio and helps in determining the risk level of the assets. The negative ratio indicates that the portfolio underperforms risk–free assets and vice –versa.|
|Information Ratio||The ratio is an additional portfolio risk metric that is broadly used by portfolio managers for analyzing the risk-adjusted return while defining the benchmark. It is calculated by dividing excess return on an asset with tracking error concerning the benchmark.|
|Treynor Ratio||The ratio also measures the risk-adjusted return of the portfolio with the overall market. Thus, provides a comparative study of the investment’s excess return to the risk–free asset.|
|Beta ( as a metric)||The Beta as a risk ratio measures the volatility of the investment for the market as a whole. Furthermore, it is expressed as the positive integer with 1 indicating the perfect match of the security and market performance.|
Examples of Portfolio Risk Analytics
The emerging Fintech and Investment Companies are making advantageous use of Portfolio Risk Analytics to manage risk and determine the value of the potential investment portfolio. The big industrial names are the early birds for adopting this profound Data Analytics technique in their ecosystem.
- CRISIL –Risk and Performance Analysis: Through its end–to–end risk management services this credit rating agency can help top assets management firms across the world, especially in the USA and Europe. With the integration of bespoke Portfolio risk analytics into its operations, the company has managed to stand invalidating and evaluating the market risk for its portfolio investors.
- Morgan Stanley – Productivity Portfolio: The company is known to create gains for its client companies by investing through technologies such as Portfolio Risk Analytics. After its fundamental and quantitative analysis, the company selects the portfolio for investment and helps deliver productivity.
Tools Used for Portfolio Risk Anlaytics
There are some of the tools and applications acting as the portfolio risk analyzer and help in planning portfolio and its attributes independently,
|Kubera– Net worth Tracking||It is the premium Net Worth tracking tool that is used for banking and investment (including cryptocurrency) purposes. With the help of this asset tracking platform (that can track DeFi assets too) the movement and risk in the portfolio can be easily detected without any compromise with the security. Based on this the size and the nature of the portfolio are determined and customization becomes the real-time game.|
|Personal Capital – High-Level Visualizations||It is a free portfolio analysis tool that visualizes the composition of a portfolio in the form of a “mosaic” plot chart by breaking it down into stocks, domestic and internal bonds, etc. It also helps to track cash flow, net worth and create healthy space for personalized investing with the help of relevant market insights which define the risk spectrum of the portfolio too.|
|Visualizer – Probability-based tool||This is the most robust portfolio analysis tool which specializes in Monte Carlo simulation giving the probability for the portfolio lasting for a specified period. Furthermore, it is suitable for backtesting and asset allocation analysis by providing insights into timing strategies. Thus portfolio risk analysis becomes highly reliable with this probability–driven tool.|
Portfolio Risk Analytics Companies
Portfolio Analytics solutions are widely adopted by several companies and investors to manage their portfolios effectively. Thus, the quantum of the companies providing these profound solutions has increased too. These Portfolio Risk Analytic companies analyze all the relevant current and historical exposures such as rating, valuation measures, weights, and other ratios to provide the best-suited analytics model.
|Trend Rating||The company uses the “trend capture” technology to add desired discipline in the portfolio for generating higher returns with lesser risks. With the use of Advanced Data Analytics capturing trends and identifying the stocks with high-risk probability becomes convenient. Its Performance Management Platform is a complete array of functionalities facilitating market screening, portfolio risk monitoring, and opportunity identification.|
|BondIT||Being founded merely a decade ago, this company offer Portfolio Risk Analytics solution for portfolio managers and investment advisers using its powerful Machine Learning algorithms. The super-intuitive user interface helps to implement fixed income strategies for increasing revenue, trade flow, asset acquisition, and reducing risk.|
The company founded in the year 1998 is known to provide a well-integrated suite with all forms of investment management solutions for global clients. The Portfolio Risk Analytics services provided by Axioma are suitable for asset managers, insurance companies, wealth managers, investment banks, etc. Its intelligent decision intelligence tool helps to create a competitive advantage by shifting the portfolio from risk to return category.
|FactSet||The company has been serving the market for almost 4 decades with its data integration services. The content fueled by the company is used for investment lifecycle from stock selection to researching to ordering to reporting. With its precise data analytics including Portfolio Risk Analytics the company has influenced 95% of the asset managers and helped in creating investment worth.|
Advanced Portfolio Risk Analytics is playing a crucial role in shaping the nature of the investment portfolio by assessing the risk level and increasing the gains. With the upward inclination of investors towards alternative investment products the probability of the arising risk can be well – predicted and analyzed with this AI-driven data analytics tool which is here to go the longest way,
Topics in Data Analytics
- Advanced Data Analytics
- Clinical Analytics
- Credit Risk Analytics
- Cyber Risk Analytics
- Data Analytics for Customer Behavior and Customer Experience
- Data Analytics for Customer Journey
- Data Analytics for Fraud Detection
- Data Analytics for Human Resources
- Data Analytics for Logistics and Supply Management
- Data Analytics for Risk Management
- Data Analytics for Talent Acquisition and Management
- Data Analytics in Asset Management
- Data Analytics in Digital Marketing
- Data Analytics in Healthcare – Use Cases, Metrics, Techniques, Companies and More
- Data Analytics in Manufacturing
- Data Analytics in Pharmaceutical Industry
- Descriptive Analytics – Definition, Types, Examples, and More
- Digital Analytics
- Financial Data Analytics
- Financial Risk Analytics
- HealthCare Claim Analytics
- Insurance Risk Analytics
- Insurance Risk Analytics
- Population Health Analytics
- Portfolio Risk Analytics
- Revenue Cycle Analytics
- Risk Assessment Analytics