Financial Market Data Web Services – Xignite Blog

If stock market pundits like Franklin Templeton’s Mark Mobius are to be believed, markets are going to be just as volatile as they were in 2011. The VIX index, a popular measure of implied volatility, made multiple excursions into the 40s last year, finally ending 2011 at 23.8, up almost 32% from 2010.

Options trading strategies cater well to volatility, offering the opportunity to capitalize on market volatility as a source of investment.  That being said, most option traders typically focus on one option Greek – Delta. While Delta certainly helps in mitigating the risk of an open position, it’s important to trade Delta in conjunction with the other option Greeks – Vega, Theta, and Gamma. Each option Greek measures a different dimension of the risk in an option position.  The aim of an options trader is to manage the option Greeks so that all risks are acceptable.

In this post, I’ll provide step-by-step instructions on how to create your own real-time Excel-based option Greeks calculator with on-demand options data from Xignite’s market data cloud. This will facilitate your option trading process, by allowing you to look at all the option Greeks, side by side. Although, this is our fifth post in the series on combining the power of Xignite and Excel, it’s our first one where we describe our powerful API mash-up platform, Splice, which provides you with the flexibility to get all the data you need in a single web service call.

Creating a Composite Black-Scholes Web Service API

Options are never traded by examining the option Greeks or the underlying stock in isolation. Traders need to look at the complete picture before making a decision. The composite web service API, we will create, addresses this need. It also provides the Black-Scholes option value, which can be used as a benchmark, for your own option Greek calculations. In this example, we will mash-up the following web service operations:

• GetLastSale for the latest stock quotes
• GetEquityOption for option quotes
• GetBlackScholesOptionValue for the Black-Scholes Value

A composite web service can be created by combining any of Xignite’s web service APIs. Keep in mind; you must be logged into Splice to do the same. If you don’t have an account yet, you can just sign up for a free trial.

After you login, click on create Splice, at the top of the page.

Clicking on the create Splice feature, will take you to the Splice editor, which offers a simple drag and drop UI.

The left pane lists all the web service APIs that Xignite offers. The right pane acts as a whiteboard where the web service APIs can be mashed-up.

The next step just involves dragging any web service from the left pane to the white board and linking the inputs and outputs you require for your web service call.

In this example, we used the GetLastSale, GetEquityOption and GetBlackScholesOptionValue web service APIs.  The mash-up I created is called BS. You can access it on the Splice Studio community. You can also clone it and make modifications.

Note: For a more detailed explanation on how to create a Splice, watch this 5 minute intro video.

Importing Option Data into Excel

We covered how to import data into Excel, using web services in a previous post.  The only difference in this post is that, you are now using a composite web service API that has been created by you (Isn’t that exciting!!!).

After you have imported data from the customized Black-Scholes API, there is another piece of data you need to import to complete the option Greek calculations. One of the most important inputs in option Greeks calculations is the volatility. In this example, I calculated historical volatility based on Google’s (GOOG) one year price movements. The historical data can be accessed using Xignite’s GetHistoricalQuotesAsof web service API. It lets you specify the period type (daily, weekly, monthly, quarterly or annually) and period, so that you can set up volatility calculations based on your volatility strategies. The GetHistoricQuotesAsof web service API produces a table as shown below:

Setting up an Option Greeks Calculator

All you need to do now is, provide the inputs and set up the calculations. The formula for all the option Greeks is present in the attached Excel spreadsheet.

To the make the process more intuitive, the attached spreadsheet contains a button that updates the stock quotes and also calculates the latest option Greeks. The macro that does this is given below: Read more

Tracking multi-asset class portfolios in real-time is critical to active investors. Since many investors, particularly portfolio managers and analysts, typically spend a good part of their day in Microsoft Excel, having the capability to track multi-asset class portfolios within Excel would be a tremendous benefit.

Getting real-time pricing on multi-asset class portfolios within Excel has historically been a tedious (and often expensive) chore, requiring multiple vendors and technologies.  But with Xignite’s on-demand cloud APIs, it’s now simple and straightforward.  Even those without a programming background can be up and running in just a few minutes.

In this article, I’ll provide step by step instructions on how to create your own multi-asset class P&L tool in Excel with real-time pricing data from Xignite. All the examples in this post are available for download in this Excel spreadsheet.

This is the fourth post in our series on combining the power of Excel and Xignite.  For more info on this topic, be sure to review our posts on automating financial models, importing market data using XML and importing data using CSV.

Importing Multi-Asset Class Data into Excel

In this example, let’s suppose we hold a multi-asset class portfolio with a few stocks (ORCL, AA & T), an ORCL call option, an ORCL bond, and crude oil futures. To create a real-time multi-asset P&L tool,  we need live financial data. We’ll use the following web services APIs from Xignite to import them into Excel via XML:

• Xignite ExtendedRealQuotes for stock quotes
• Xignite RealTimeOptions for options data
• Xignite Bonds for bond data
• Xignite Futures for futures data

We covered how to import XML in a previous post, but let’s quickly review the process by pulling the stock data as an example.  We’ll start on the Web page for the GetExtendedRealQuotes operation, a Xignite Web service providing real-time stock quotes.

Once you are on the webpage, update the symbols (ORCL, AA, T) in the prompt at the top of the page, click on view in XML, and copy the URL that gets generated.  Next, open a new Excel worksheet, Read more

The Last Hold-Out

The fixed income trading world has been the last hold-out in the broad shift towards electronic trading and more transparent centralized trading venues. We’ve already witnessed the other popular financial instruments including equities, options, futures, and currencies, succumb to the inevitable, but fixed income is still dominated by the murky business of OTC trading. There are signs, however, that even this asset class has finally reached a tipping-point, and that we are now on the verge of a new world where the buy-side’s demands for transparency will finally be realized.

To understand what this future may look like we must first understand how fixed income trading got to where it is today.

When Two Sides Collide

The fixed income trading world has always been defined by the opposing interests of the buy-side and the sell-side.

The buy-side has almost uniformly expressed dissatisfaction at the whole fixed income trading process. Complaints include a complete lack of transparency, an inability to obtain reliable price discovery and market data, the high-cost, and the general inefficiency when compared to the electronic trading of other asset classes. More recently there has been intense pressure to include fixed income in electronic multi-asset trading class strategies.

The sell-side on the other-hand has been highly motivated to keep things status quo. Over the years fixed income trading has been a cash cow business for the large Wall Street dealers. For example, fully 52% of Goldman Sachs’ $45 billion revenue in 2009 came from their fixed income trading division. The sell-side understands that moving fixed income trading away from the OTC model to more exchange-like platforms and Alternative Trading Systems (ATS’s) will almost certainly result in greatly reduced profits. The sell-side in their defense has argued that the sheer volume (3 million fixed-income securities and counting) and the inherent complexity of fixed income products does not lend itself to a more standardized and centralized market.

Innovation around the Edges

That is not to say that there has not been innovation or change. Over the years there have been some key developments Read more

There is little doubt that we are in the midst of a technological sea change as the world moves from an Internet that was tethered to PCs, to a world where the Internet can be accessed from anywhere, through a wide array of always-on smartphones and tablets. We’ve all heard the impressive statistics that support this trend with just over 400 million smartphones expected to be sold globally in 2011, and Gartner forecasting that the mobile web will grow to 1 billion smartphones and 320 million tablets sold in 2015.

A Consumer-Driven Revolution

To date this has been very much a consumer-driven revolution with the vast majority of Apple’s 1 billion monthly app downloads being aimed at the consumer. This, however, is beginning to change with more and more consumers demanding the convenience of mobile devices and mobile apps inside the enterprise. We are now seeing growing enterprise adoption with Apple reporting just this week that 92% of Fortune 500 companies are either testing or deploying the iPad. This is an astounding number especially since the iPad product itself did not exist 2 years ago. Closer to home, according to Good Technology, a firm that manages mobile devices for large companies, financial services firms accounted for almost half of all new iPad activations in the second quarter of 2011.

So as this mobile app revolution inexorably makes its way to the buy-side there are a number of questions to be answered:  How will buy-side mobile apps affect the technology landscape? How will buy-side mobile apps change the way people do their jobs? How will buy-side mobile apps allow firms to better serve their clients?

Monolithic Management Systems Meet Buy-Side Mobile Apps

Today, when we look at the applications used by the buy-side we can see that it is still dominated by the same trading, order management, and portfolio management systems, that have been around for the last 20 years. It could be argued that not much has changed. Buy-side employees are still spending most of their day working with these large monolithic management systems. Of course, there have been advances particularly in the areas of Read more

The last few years have been undeniably tough for the once brash hedge fund industry. Recent headlines do not suggest any improvement with August being the worst month for hedge funds since October 2008, and marquee firms like Paulson & Company firm down 34% year-to-date.  Prior to the crisis of 2008, the industry appeared to be on a steady upward trajectory, evolving from a small, scrappy upstart, that catered to high net worth investors, to a more formalized $2 trillion industry, that serviced the largest pension funds in the world. Since the crisis, however, the industry seems to have lost its way. What exactly happened and how can what we term the “Hedge Fund Cloud” return the industry to its former glory?

Institutionalize or Die

Pre-crisis, managers believed that the measure of success was not only returns but assets under management. In their race to acquire new assets, managers were motivated to “institutionalize” their infrastructure so that they could go after the really big allocations from large pension funds and endowments. For many firms this institutionalization meant leaving the relative simplicity of their single prime relationship to the much more complex world of building out their own multi-prime infrastructure. Almost overnight managers found themselves running complex and unwieldy businesses. Seemingly simple operations like adding a strategy, that required a new asset-class, or producing a new report, became long and involved IT projects.  Any thought of outsourcing any of this burden was dismissed because of perceived privacy and control concerns.

Prisoners of their own Hedge fund Infrastructure

The actual crisis further exposed the inflexibility of hedge funds’ infrastructures. Managers struggled to view their true exposure across asset classes and multi-prime relationships. Just when managers most needed their former agility they discovered that they had become prisoners of their own expensive infrastructures.

Fast forward to today. We are still experiencing the after effects of the crisis. A strong regulatory backlash response has been unavoidable. There is still tremendous uncertainly about the true impact of these new regulations, but what is certain, is that the business of running a hedge fund will become even more complex and costly.

How can the industry remove itself from this funk and prepare itself for the next crisis? The answer is that the industry needs to return to basics by once again making alpha generation its sole focus. The industry needs to regain its former investment agility. In short, managers need to get out of the running-a-hedge-fund business and get back to the investment business.

The Hedge Fund Cloud to the Rescue

Fortunately, the Hedge Fund Cloud offers managers the opportunity to get back to basics.  The Hedge Fund Cloud allows Read more

Like many of us, you may have run into challenges when importing real-time market data in Excel, Visual Studio & SQL Server. With the recent addition of Xignite Financial Market Data to the Microsoft Azure Marketplace Datamarket, users can now pull live stock quotes directly into Microsoft Excel 2010, develop data rich applications using Visual Studio 2010 and seamlessly populate backend database with SQL Server 2010.

In late 2010, Xignite and Microsoft teamed up to make XigniteBATSLastSale, a real-time stock quote data service, available through the Azure Marketplace Datamarket, with the addition of other datasets scheduled to rollout in the months ahead. With this, Microsoft users can obtain instant online access to real-time stock quotes from the BATS Exchange. Now everyone from hardcore mobile app developers to garage based startups can obtain access to the same professional grade APIs to power their applications.

New to Xignite is the addition of OData, or Open Data Protocol, a method of querying and updating data which unlocks the data from the silos that exist in legacy applications. Today, OData is being used to expose and access information from a variety of sources including, but not limited to, relational databases, file systems, content management systems and traditional Web sites.

Wes Yanaga with Microsoft’s Channel 9 sat down with Shoshanna Budzianowski (SQL Azure) and Chas Cooper (Xignite) to get the low down on what this partnership is all about, and how it will benefit end user around the globe.

After the Channel 9 video was completed, Shoshanna Budzianowski sat down with Marc Bollinger, Web Service Engineer at Xignite, for some one-on-one developer talk and a bit of programming fun (CLICK MORE to see developer video)

Read more

Ad hoc Excel financial models are employed across a wide range of applications from stock portfolio management, currency trading, loan processing, etc., but they all have one thing in common: they all need ad-hoc financial market data as the input to the analysis.

This is the third post in a series that describes how to use Xignite on-demand financial market data with Excel. The last post in the series described how to import live market data into Excel using Xignite Web Service XML output. This post will take it to the next level and explore how to create Excel financial models that not only bring in live market data over the Internet, but allow you to modify the market data requested using Excel macros to create dynamic Excel financial models. All the examples in this post are available for download in this Excel spreadsheet.

The first step is to Read more