Capital Markets

Five House Rules for Managing Risky Behavior

How to analyze hedge fund risk with sparse data

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Larch Lane invests in early stage hedge funds, funds that are younger than three years old or that have assets of less than $400 million. Because of the limited (and infrequent) data provided by these funds, Larch Lane integrates other relevant data for its risk analysis.

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20/20 vision of risk

Social Media Crimes

Laura Hutton, Direct of Banking and Solutions at SAS, explains how technologies will improve visibility of operational risk.

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Demo: Real-time mortgage portfolio risk analysis

Senior Risk Consultant Srini Iyer

SAS can help you build an analytic platform for CCAR and stress testing. And the good news is that you can use the models you’ve already built. We plug your models into our solution to give you the scalability – and functionality – you need.

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Real-time risk aggregation demo

Risk aggregation demo

Obtaining consolidated risk results across asset classes, portfolios, and trading desks can be a daunting challenge. The amount of information to be aggregated is vast and can stress an organization’s systems. Worse, the results are often obtained using overnight batch processes. Doug Vestal shows how risk aggregation results can be delivered in real-time.

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Real-time transparency revolutionizes data management

catalog of risk_lrg

Firms stand to gain a lot from the data management revolution. By capturing opportunities and value that would otherwise be lost because the information came too late or didn’t account for late-breaking market conditions, you might be able to see threats ahead of time and capitalize on more agile planning.

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Six guidelines for constructing stress tests

Six guidelines for stress testing

The recent global financial crisis painfully revealed the need for better, more comprehensive stress testing in the financial industry. Keep these guidelines in mind when constructing stress tests and stress scenarios.

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Faster AND smarter: Supercharging capital markets with real-time data and visualization

data visualization

By performing deeper analyses on data captured in-stream, and then injecting the results back into the business in real time, firms can better manage market risk, liquidity and counterparty credit risk during the trading day.

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The high-velocity big data stream

Cyber-security

Organizations need to pull immediate insight from real-time, streaming data because traditional approaches, which apply analytics after data is stored, may provide insight too late to act.

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Six tips for managing risk data

data visualization

Combining these six tips will help the bank reduce operational costs, focus on more profitable trading operations, reduce RWA and thereby achieve a better return on capital deployed in its trading operations.

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Risk exposure in capital markets – real-time

big data

Event stream processing allows capital market firms to make complex business decisions on massive amounts of data in real-time. So, instead of waiting until the following day to get the latest reports, the risk management team can have an up-to-date view of their risk exposures on an intraday basis for more timely business decisions.

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Why banks struggle with counterparty risk management

large bank

To make an impact, counterparty exposures, risk sensitivities and trading events must be monitored intraday, and CVA must be allocated in near real time as trades are executed. The requirement to deal with counterparty risk in near real-time creates significant difficulties for many banks. Jeff Hasmann examines the difficulties and solution.

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