Axioma Risk Model Handbook 44 [UPDATED]
In this paper, we explore the ex-post attributes of 120 simulated portfolios across the U.S., International, and Emerging Markets. We estimate expected returns using a given global stock selection model employing Global Equity Rating (GLER) and Consensus Temporary Earnings Forecasting (CTEF) signals. Our portfolios are constructed under the Markowitz optimization framework and constrained at various tracking error levels. Further, an alpha alignment factor is applied to aid in portfolio construction. As a result of our research, we present the reader with three key findings. First, GLER and CTEF signals employed as the primary inputs to security selection result in portfolios with superior risk adjusted returns relative to the Russell 3000, MSCI AC World ex. US, and MSCI Emerging Markets benchmarks which they are measured against. Second, expanding the investment universe outside the U.S. increases the opportunity set yielding higher risk adjusted performance. Third, the incorporation of an alpha alignment factor within the portfolio construction process improves risk forecasts resulting in ex-post tracking error aligning more closely to ex-ante, and ultimately improving information ratios.
axioma risk model handbook 44
The analytics platform is based on a full revaluation methodology, enabling it to accurately capture non-linear risk from derivatives and produce fixed income, equity and multi-asset analysis consistent with market-leading front-office systems. Axioma Risk has upwards of 120 different instrument pricing models, covering equities, fixed income, currencies and commodities, as well as vanilla and exotic derivatives and illiquid investment vehicles such as private equity, private real estate, infrastructure and hedge funds.
The Axioma Factor-based Fixed Income Risk Model is a cross-sectional factor model that provides risk and portfolio managers with insights into systematic macro and style factor exposures, and is able to capture a significant level of systematic risk.
From a fundamental model perspective, we have succeeded in reducing the systematic risk in the portfolio from a 66% factor contribution down to 57%. In addition, the sensitivities to key, relevant macroeconomic factors have also been largely hedged, particularly the sensitivity stemming from USD 10Y Real Rates, which was cut almost in half from -0.25 to -0.15.
Because of the electrophysiologic and structural remodeling caused by AF, many patients with paroxysmal AF will progress to persistent and long-standing persistent AF. The degree to which this reflects the continuing influence of underlying cardiovascular risk factors as opposed to a direct effect of AF is unknown. Regardless, clinicians need to reevaluate their management strategies frequently, as AF burden and comorbidities increase with time.
The Axioma US Fundamental Equity Risk Model MH 3 provides factor-based portfolio risk analysis and covers over 8,800 securities (over 18,700 historically) listed on various U.S. stock exchanges, including American Depository Receipts, as of 2013. The model also covers more than 250 Exchange Traded Funds and more than 300 Enhanced Index Fund contracts, including all assets covered by the AXUS3 Fundamental and Statistical models. Market-traded, equity, and sector returns are available on a daily basis and are computed directly from market prices or extracted from the AXUS3-MH fundamental model. Core macro factor returns are estimated by means of a Dynamic Factor Model with a small number of dynamic factors distilled from eight years of 31 traditional economic time series released monthly, as well as over 100 daily time series from market data. Factors are common equity attributes that can describe a portion of portfolio performance with statistical significance.
The solution: Enables the management of investment strategies and model portfoliosProvides access to investment stories, themes and ideasAllows generation of investment proposals, suitability checks and systematic monitoring of portfolio restrictionsProvides aggregated performance and risk reports across all clientsAssist with reconciliation tasksThe platform is web-based and is already connected to over 70......
Moody's Analytics Asset Scenarios depict the plausible future paths of variables that are related in economically coherent ways. The scenarios deliver the results of thousands of simulated future rates, yields, returns, and asset prices, plus other economic risk drivers produced by an arbitrage-free modeling framework....
Powered by proprietary methodologies for issuer classification and modeling issuer spread returns, the Axioma Factor-Based Fixed Income Risk Model enables portfolio and risk managers to construct investment portfolios with better control for tracking error and to rigorously manage exposure to investment style factorsKey BenefitsMeaningful risk factorsPortfolio risk and performance attribution......
BarraOne is a research-driven platform that helps asset managers identify and manage risk exposures to make more informed investment decisions. Powered by a long-horizon Barra factor model, BarraOne combines public, derivative and private asset classes under a unified analytical framework. Integrated performance analytics help managers match sources of risk with......
The AlgoDynamix software, architecture and quant development teams have decades of experience in all aspects of software development and deployment across most areas of financial risk analysis, modeling and forecasting.In addition to our existing suite of market risk forecasting and financial portfolio enhancing products, the company also provides customised solutions......
Multi-custodian aggregationCora LiveWealth automates all forms of data gathering, digitization, and normalization.Powerful analytics and reportingA portfolio analytics engine provides industry-standard performance reporting models.Multi-custodian aggregationCora LiveWealth automatically extracts data from most major international custodians, and creates a normalized view with 100% accuracy.Robust performance and risk analyticsThe system's analytics engine delivers customized......
Client riskGoal based profiling of client, comparing to existing or new portfolios.Asset allocationAccommodate different investment strategy, benchmark and model portfolio.Product universe / selectorAn investment process that can select from all asset classes.Portfolio construction and rebalancingAutomated portfolio construction and re-balancing based on financial modelling.Performance and risk analysisDashboard of intuitive and innovative......
Powerful portfolioMultiple custodian data aggregationData reconciliationProposal generation and modellingComprehensive CRMTag clients for marketing purposesDoc and communication repositoryCreate reminders and to-dosBuilt-in complianceCustomizable KYC and workflowMonitor mandates and riskDoc template generation...
Driven by regulators, rating agencies, or a demand for best practices in investment solution design, asset allocation, and risk management, asset managers and investment advisers are facing ever greater requirements for modeling capabilities. Built around our economic research and scenario modeling capabilities, our analytic solutions enable asset managers to build......
Client and model portfolio toolsOur advanced portfolio management tool is designed to manage all the data needs of your advisors and clients. Obtain interactive data analytics on asset allocation, risk factors and performance for your model and client portfolios. Be aware of any significant events by setting up alerts on......
AuthenticationSet single and multi-factor auth and client permissions.Onboarding and KYCEncrypted client onboarding, plus KYC/AML integrations.AccountsCreate and manage client accounts & held away accounts.Portfolio managementManage securities, investment models, portfolios and goals.PerformanceRun robust risk and performance reporting on any entity.OrdersCreate and track single and bulk orders for trade execution.QuestionnairesConfigure decision trees and......
Grow your clients wealth by providing them with access to direct commercial real estate investments on a risk first basis.Leverage the power of Allocation Intelligence and proprietary industry-first matching algorithms.How it works1. Individualized risk assessmentQuickly create customized risk-based allocation models for all of your clients with our simple, white-label assessment......
The STAR ESG models can be used for generating economic scenarios under either a real-world or risk-neutral measure. It can be used by clients for setting investment strategy benchmarks, portfolio construction, ALM, pricing, capital setting and the market consistent valuation of options and guarantees.Our philosophy is to transfer knowledge and......
Using the risk factors from a commercial risk model, we present the active exposures3 of four factors. The definitions of the four factors are in line with those used in the S&P 500 GARP Index. In comparison with the S&P 500, the GARP strategy has higher exposures to earnings, sales growth, earnings yield, and profitability,4 and lower exposures to leverage (see Exhibit 4). The factor exposure results align with the objective of the index design.
ORC faculty are also currently contributing to application domains as wide ranging as manufacturing, communications, transportation, public services, logistics, marketing, financial services, health care, and nuclear engineering. Current projects are addressing such topics as air traffic control, epidemiology, AIDS testing, life-cycle modeling of municipal solid waste, safety and risk analysis in air transportation, telecommunication network design, supply chain management, production scheduling, and transportation logistics.
Autocratic peace and the explanation based on political similarity is a relatively recent development, and opinions about its value are varied. Henderson builds a model considering political similarity, geographic distance and economic interdependence as its main variables, and concludes that democratic peace is a statistical artifact which disappears when the above variables are taken into account.[132] Werner finds a conflict reducing effect from political similarity in general, but with democratic dyads being particularly peaceful, and noting some differences in behavior between democratic and autocratic dyads with respect to alliances and power evaluation.[131] Beck, King, and Zeng use neural networks to show two distinct low probability zones, corresponding to high democracy and high autocracy.[133][e] Petersen uses a different statistical model and finds that autocratic peace is not statistically significant, and that the effect attributed to similarity is mostly driven by the pacifying effect of joint democracy.[134] Ray similarly disputes the weight of the argument on logical grounds, claiming that statistical analysis on "political similarity" uses a main variable which is an extension of "joint democracy" by linguistic redefinition, and so it is expected that the war reducing effects are carried on in the new analysis.[135] Bennett builds a direct statistical model based on a triadic classification of states into "democratic", "autocratic" and "mixed". He finds that autocratic dyads have a 35% reduced chance of going into any type of armed conflict with respect to a reference mixed dyad. Democratic dyads have a 55% reduced chance. This effect gets stronger when looking at more severe conflicts; for wars (more than 1000 battle deaths), he estimates democratic dyads to have an 82% lower risk than autocratic dyads. He concludes that autocratic peace exists, but democratic peace is clearly stronger. However, he finds no relevant pacifying effect of political similarity, except at the extremes of the scale.[136]