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:

Clicking on the “Calculate Option Greeks” button takes the inputs from the excel sheet, plugs it into the Black-Scholes formula, and returns all the option Greeks in the format as shown below.

As you saw in this post, using the Splice platform gives you the ability to create custom web service APIs that match your unique option trading strategies. Coupling these customized web service APIs with Excel gives you ability to quickly create a real-time options data Greeks calculator so that you can trade on volatility with all the important option indicators at your fingertips.  Give it a try and let me know what think…..

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, go to the Data tab and select From Web, then paste the URL.  At the end of the URL append the following; replacing the email address with the one you used to sign up for your Xignite account:  &header_username=yourauthenticationtoken

Note : The free trial does not grant you access to the Xignite’s real-time services. You can use the following web service APIs instead:

• Xignite BatsRealTime for stock quotes
• Xignite GetEquityOption for options data
• Xignite GetBondTradedPrice for bond data
• Xignite GetDelayedFuture for futures data

You should end up with a table that looks like this:

Now follow the same process for options, bonds, and futures, which will result in new tables for each asset class. If after the import your data does not have headings, right click anywhere on the data, select XML > XML Source, then right click on the folder icon, remove the element and right click again and remap it. The paste option at the end of the data now has the option to include XML headings.

Implementing a Macro for Real-Time P&L

Now that the data has been imported, a simple macro enables us to monitor price movements in real-time by automatically refreshing the data.

To implement this, simply go to the Developer tab in Excel, select Macros, and then create a new macro called RefreshTime and select This Workbook in the Macros dropdown.

Next, paste the following macro script in the VBA window:

Sub RefreshTime()

Application.ScreenUpdating = False
ActiveWorkbook.RefreshAll
Application.OnTime Now + TimeValue("00:00:01"), "RefreshTime"
Range("D1").Value = "Last:"
Range("E1").Value = Format(Now, "hh:mm:ss AM/PM")
Application.ScreenUpdating = True

End Sub

This macro refreshes all the Web Query connections set up in the worksheet every second. It also prints the last update time on the worksheet, so that you can be sure you’re getting real-time data.

Now that you have the proper data imported and the refresh macro set up, you can input your buy prices and set up the P&L calculations in Excel. To make the tool more visually intuitive, you can add conditional formatting to the data based on parameters like real-time price or volume movements.

Here’s a link to the multi-asset class P&L Tool that I built in Excel using this example. It refreshes the data every second and reflects changes in security prices and ITD (Inception-to-Date P&L), YTD (Year-to-Date P&L) & MTM (Mark-to-Market-P&L) by changing colors.

As seen in this example, combining Excel’s highly flexible and customizable tools with Xignite’s on-demand financial data enables you to quickly build powerful financial applications.  This real-time multi-asset class P&L tool is just a springboard – building upon this, you can create even more complex Excel financial models and presentation spreadsheets to suit your needs.

In our next post , we will explore how we can build a real-time greek calculator using Xignite’s web service APIs.

Technology has led a dynamic transformation of the exchange industry, and cloud strategies are an important factor in unlocking the revenue potential of exchange data.  The following article about how to monetize exchange data via the cloud was recently published in “How To Build An Exchange,” a fascinating must-read collection from our friends at Mondo Visione.  Request access to the full collection from Mondo Visione here. 

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Monetizing Market Data in an Evolving Global Marketplace

The global environment for exchanges and data originators is rapidly evolving with exploding data volumes, increasing and unpredictable regulation, expanding variety of financial instruments, fragmenting market, competitive encroachment and the need for new sources of revenue. Beyond these challenges, the race to microsecond latency will stretch the infrastructure capacities and budgets at major financial services firms.

Exchanges and data originators are struggling to service the opportunities of the future with the products and solutions of the past. A paradigm shift is rapidly approaching as old monolithic systems designed for universal applicability are being replaced by new custom tailored micro and mobile apps designed to satisfy the needs of a specific knowledge worker or user type.

The emergence of new mobile technologies and use-specific applications is altering the usage patterns of market data and changing the ways market data is purchased and consumed. If an emerging exchange is to succeed, it must tackle these issues in new ways.

A few years from now the market data application mix will boil down to two distinct flavors: low latency and everything else. How will exchanges capture new market data revenue profitably and manage the delivery of these two distinct flavors when their target applications, usage patterns and infrastructure requirements are so dramatically different?

Given its mission-critical impact on trading efficiency, low latency infrastructure has historically received the bulk of attention and investment. Meanwhile, legacy data distribution systems are crumbling under the weight of the increasing volumes of data produced by low-latency trading. The cost and complexity of servicing everything else is skyrocketing. Enter cloud computing. Once thought to be the domain of small and medium-sized businesses, cloud strategies are now seeing investment from exchanges and data originators to gain economies-of-scale, simplify the access and delivery of market data, decrease time-to-market for new products and add new revenue streams from new and underserviced segments.

In August of 2011, The Melbourne Group laid out the following cloud action plan for existing and emerging exchanges:

Make Core Market Data Assets Available from the Cloud

By creating an Internet-based cloud offering using standard cloud APIs, exchanges can offer both institutional and retail customers a means to access their core market data assets on-demand while driving down both the costs of access for the customer and the costs of service and maintenance for all.

Create Cross-Selling Opportunities with Direct Feed Customers

Direct feeds designed to service automated trading applications are poor vehicles for usercentric and mobile applications. A cloud offering coupled with an exchange’s direct feeds allows buy and sell-side firms to synchronize front and back-office operations seamlessly.

Monetize Exchange Data Assets by Targeting Unmet Business Needs

Without the cloud, the sheer volume of stale data sets make broad delivery cost-prohibitive to anyone but the largest clients. With the cloud, exchanges can move away from the one-size-fits-all approach and offer custom tailored products that allow customers to select and consume only the data required for their specific applications, modeling or back-testing.

Expand and Simplify Global Access and Delivery

Cloud-based delivery can be complemented with an e-commerce purchase and provisioning system to access new geographic regions and new customers through a 24×7 web presence which allows customers to select, purchase and use an exchange’s data products without a local sales organization, or any sales department intervention at all.

Increase Revenue by Expanding Retail Channels

A scalable, low-cost cloud platform allows exchanges to distribute exchange data directly to retail websites and investors. By accessing these channels directly, exchanges open revenue streams currently outside their reach and strengthen their brand within new and existing markets.

Deliver New Products Faster to Meet Emerging Customer Needs

New trading products create new information needs for financial services firms and market participants. The cloud allows exchanges to provide immediate global access to new market data products, removing constraints imposed by traditional market data vendors and eliminating infrastructure investments by customers.

Increase Market Transparency for OTC Derivatives and Complex Products

New exchange-traded products and new reporting requirements brought forth by Dodd-Frank, RegNMS and MiFid create new information needs for financial services firms and market participants. A cloud solution can provide both market participants and regulators easy global access to activity in these markets, providing accurate and auditable information that helps financial institutions manage risk and meet regulatory and internal compliance requirements.

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 that have allowed the fixed income trading world to creep towards a more electronic and transparent marketplace:

1998 – Tradeweb introduces an electronic request-for-quote-driven multi-dealer platform focused on U.S. treasury bonds.

2000 – MarketAxcess introduces an electronic request-for-quote-driven multi-dealer platform focused on corporate bonds.

2000 – FIX, the widely-used equity-focused electronic trading protocol, is expanded to include fixed income features.

2002 – NASD introduces TRACE (Trade Reporting and Compliance Engine) which captures and disseminates consolidated fixed income transactions from the secondary bond market.

On the retail side we’ve also seen some innovation with more fixed income market data becoming available on websites like “Investinginbonds.com” and “Yahoo! Bond Center”.

The Credit-Crisis and the Regulatory Response

The credit crisis and the yet-to-be-fully understood regulatory response has upset the status quo of the fixed income trading world and will result in the demands of the buy-side finally overwhelming the interests of the sell-side dealers.

The sell-side lost billions during the crisis and is already accepting that the writing is on the wall. In some cases they are not waiting for regulation and are in the process of downsizing their fixed income trading businesses. We are also seeing them less willing to risk their own capital in fixed income trading.

On the regulation front there have been a number of major initiatives including the Dodd-Frank Wall Street Reform and Consumer Protection Act and Europe’s MiFID II, both of which force transparency by mandating that swaps and other derivatives be traded on exchanges and Swap Execution Facilities (SEFs). The Volcker Rule will further strike at dealers by outlawing proprietary trading and tactics such as the highly profitable ‘flow trading’.

The Electronic and Transparent Future

Perhaps the biggest advantage of this new fixed income electronic trading world will be the broad availability of fixed income market data. As we’ve seen with other asset classes that have gone through this electronic transition the availability of accurate market data will result in the buy-side becoming much more focused on cost and efficiency. There will be increased interest in best-execution and over time we will see a more efficient marketplace.

Another key trend that we can expect is the ‘retailization’ of fixed income trading. As fixed income market data becomes ubiquitous we will see the retail investor want greater direct involvement in electronic fixed income trading. This will result in more services, websites, and even mobile apps aimed exclusively at the retail bond investor.

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 trading, workflow, integration, and Software-as-a-Service, but the components that make up the software infrastructure of the buy-side have essentially remained the same.

We believe that the arrival of mobile apps to the buy-side will have a profound  impact on the buy-side’s technology, employees, and ultimately the way clients are serviced. This revolution is different than other over-hyped technology fads because it is being driven by the end-user rather than by some easily-ignored top-down management dictum. Buy-side employees have already experienced the power of mobile apps as consumers and will begin using them at work, whether they are approved by their IT department or not.

We see the impact of buy-side mobile apps evolving in three distinct phases:

Phase 1 – View-Only Buy-Side Mobile Apps

Most of today’s buy-side mobile apps build on the anywhere capability of mobile devices and are strictly view-only type offerings, that display the same data that users see on their trading, order management, and portfolio management systems. These research, P&L, and client information apps augment the existing monolithic management systems and are many times used by employees outside of work during commutes or client visits.  The apps are  frequently designed to look like dashboards with the ability to drill-down to more detailed information. There are many examples out there but some of the most widely used are Bloomberg Anywhere for iPad, Merlin’s Compass for iPad, and Fidelity’s WealthCentral  Android/iPhone Mobile Apps.

Phase 2 – Action-Oriented Buy-Side Mobile Apps

This phase goes beyond the view-only capabilities of Phase 1 and allows the user to act on the information presented by their mobile app. Users for example may be alerted to a trading opportunity or a back-office reconciliation issue that they can then immediately act-on, just as if they were sitting in front of their office PC. Again this phase really just serves to augment or duplicate the existing monolithic management system functionality.  Many of the above-named firms are now in the process of releasing these newer more action-oriented Phase 2 buy-side mobile apps.

Phase 3 – Proliferation of Buy-side Mobile Apps/Decomposition of Monolithic Management Systems

The final phase is when mobile apps will really come into their own and we will see them begin to replace rather than just augment pieces of monolithic management systems.  This phase will produce buy-side mobile apps that combine the anywhere/view-only nature of Phase 1, the action-oriented ability of Phase 2, with other unique qualities that only mobile apps can offer. A hint of this future is the StockTouch app (www.stocktouch.com), that is powered by Xignite market data. StockTouch uses the touchscreen interface of the iPhone and iPad to bring to life a visualization of the stock market. Their mobile app offers functionality that no traditional buy-side application can emulate.

Over time we will see a proliferation of these smaller buy-side mobile apps that focus in on specific functionality.  This will lead to a fragmented app market just like in the consumer world. As users spend more and more of their time using these mobile buy-side apps we will see the monolithic management systems become less relevant, ultimately leading to the their decomposition.

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 firms to focus on alpha generation by moving all non-core infrastructure to the cloud. The Hedge Fund Cloud is made up of the fast-maturing ecosystem of cloud-based hedge fund service providers who have now begun to offer institutional-grade infrastructure.

The three main components of the Hedge Fund Cloud are as follows:

1 – Hedge Fund Cloud – Software-as-a-Service (SaaS)

SaaS means that software can now be accessed through a thin client or browser, from anywhere, as a service. SaaS includes upgrades, disaster recovery, and is paid for on a subscription model. Many of the important hedge fund systems including execution management, order management, risk management, portfolio management are now available from the leading providers on a Software-as-a-Service basis.

2 – Hedge Fund Cloud – Data-as-a-Service (DaaS)

DaaS delivers financial market and reference data via web services or API’s rather than the traditional data feeds and flat files.  This approach allows firms the ability to query and use just specific subsets of data rather than downloading and storing masses of data. It also means that firms do not have to build out data management infrastructures.

3 – Hedge Fund Cloud – Infrastructure-as-a-Service (IaaS)

IaaS involves the outsourcing of physical hardware such as telephony, storage, servers, and networking components.

To take advantage of this new model, managers must now take an impartial eye to their existing hedge fund infrastructures and ask themselves what really is vital to alpha generation. Everything else should be stripped away, moved to the cloud, and essentially turned into a utility. This return to basics offers the industry the best chance to get back to the pre-crisis glory days and to restore its mojo.

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)

Looking forward, Xignite has plans to put the vast majority its data onto the Azure DataMarket. “We have started with our most popular data sets, but will continue to add data until the market is satisfied with what Xignite is offering” said Chas Cooper, VP of Product management at Xignite.

Microsoft brings a very horizontal market to Xignite, with DataMarket providing broad coverage across different verticals. When Microsoft looked for companies to work with on Data Market, two things attracted Microsoft to Xignite; 1) the fact that Xignite understands how to deliver on-demand market data and financial web services” and 2) out of all the financial data providers evaluated for Azure Datamarket, Xignite has the most reasonable, rational terms of use across its data sets. Xignite also uses standards such as SOAP, REST & JSON to make integrate with Xignite’s web services simple and straight forward.

Developers should visit http://datamarket.azure.com, where they can type Xignite into the search bar there and see all of the services available. More information is available at www.xignite.com.

New to Xignite?  Curious about what we do and what were all about?  This interview with Xignite’s Joel York may provide the answers your looking for.  Visit TMCnet.com to view other videos from leading Silicon Valley companies.

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 import the XML output from a representative Web service request that you will use in the analysis. For example, if the analysis is driven by the current stock price of a range of equities, then you might want to use the XigniteQuotes Web service which provides delayed stock quotes for US Equities. This process was covered in the last post in this series and produces a table such as the one below.

Which for reference was created using the Excel Web XML import of the following Xignite Web service URL.

http://www.xignite.com/xquotes.asmx/GetQuotes?Symbol=MSFT%2CGOOG%2CAMZN&Header_Username=yourxigniteemail@yourcompany.com

Where the authentication token at the end of the URL “yourxigniteemail@yourcompany.com” is simply the email address used to log into your Xignite account. If you don’t have an Xignite account, you can sign up for the free trial. (Note: To create more secure authentication, you can also use your IP address or any random string instead of your Xignite email, simply by adding a new token to your Xignite account.)

If you right click anywhere on the table, you can bring up the options for handling XML. In particular, take a look at what happens when you select “XML Source.”

Excel will open up the details of what it calls the “XML Map” for the table.

So, what exactly is going on here??? If you have ever used Excel pivot tables, the leap to how Excel handles XML is not that big. What is happening is this:

1. Excel links to the XML output at the Web service URL. Excel calls this the “Data Binding“
2. Excel maps the XML output to a range of cells. Excel calls this the “XML Map“
3. Excel adds formatting, sorting, filtering to the output to make it dynamic. Excel calls this type of table a “list”

We’re going to continue by changing the name of the XML Map from the cryptic “ArrayOfQuote_Map” to simply “Quotes” by clicking XML Maps… and Rename… from the XML source dialog. You can also add and remove items from the table (Excel list) by dragging and dropping from the XML Map or simply cutting and pasting within the spreadsheet. For this example, we’re going to remove everything except for symbol, name, date, time, high, low, last and volume by directly deleting the irrelevant columns in the spreadsheet. Notice that the remaining columns are bold on the XML Map whereas the removed columns are not, i.e., the bold shows which columns have been mapped from the XML page on the Web to the Excel list in your spreadsheet. So, now our XML map looks like this.

Now the fun begins! From the last post we know that we can update the data in our Excel table in real-time simply by clicking the Refresh All button. But, we can’t change the parameters (e.g., stock symbols, currency pairs, etc.) that drive the output. We can only update it. What is really happening when we click Refresh All is that Excel goes back out to the “Data Binding” that points to the Web service URL and refreshes the XML output, then it uses the XML map to reload the table. To alter the output, we need to alter the input, i.e., the Web service URL in the Excel data binding. This can be done by creating an Excel Macro that automates the series of steps we used to create the table. The Excel VB Macro below does exactly this.

Private Sub CommandButton1_Click()

Dim Symbol_List As String
Dim Quote_Url As String

Symbol_List = ActiveWorkbook.ActiveSheet.Range(“$J$1″).Value
Quote_Url = “http://www.xignite.com/xquotes.asmx/GetQuotes?
          Symbol=” & Symbol_List & “
          &Header_Username=yourxigniteemail@xignite.com”

ActiveWorkbook.XmlMaps(“Quotes”).DataBinding.LoadSettings (Quote_Url)
ActiveWorkbook.XmlMaps(“Quotes”).DataBinding.Refresh

End Sub

The simple Excel macro links to a button in our spreadsheet above and automates the following tasks when the button is clicked:

1. Grabs a new set of symbols from the spreadsheet
2. Creates the proper URL for the Web service request using the new symbols
3. Loads the new URL into the Excel XML Map Data Binding
4. Refreshes the Excel XML Map Data Binding
5. Upon Refresh, the Web Service is called and the table reloads via the XML Map

The spreadsheet looks something like the image below.

This exact same procedure can be used with any Xignite Web service. Here is a sample of what a currency cross rate table might look like using the GetRealTimeCrossRateTable operation of the XigniteCurrencies Web service that was explored in the previous post in this series.

Finally, any service that returns a time series or similar data like the GetTicks operation of XigniteQuotes can be combined with Excel charts to create graphs that you can interactively update in real-time.

These three examples above use virtually the same Excel macro, the only difference is the Xignite Web service URL and the XML Map in Excel. They are available for download in this example spreadsheet, however, to make it work YOU MUST REPLACE THE GENERIC AUTHENTICATION STRING WITH YOUR OWN XIGNITE ACCOUNT in the VB Editor and YOU MUST ENABLE THE SECURITY SETTINGS IN EXCEL TO ALLOW MACROS as in the picture below.

If you’ve ever written an Excel macro in the past, this should be straightforward. These examples are just a springboard for automating Excel financial models with live market data. They show the basics of how to get live market data into your Excel financial model and update it dynamically. Building upon this foundation, you have the combined power of market data from every Xignite Web service and all Excel functions, charts and macros at your fingertips to create complex Excel financial models and presentation spreadsheets.

The beauty of Xignite on-demand market data is that it can power any application from spreadsheets to major financial websites, anywhere, anytime, because it uses industry standard Web service APIs and XML data exchange formats. This is great news for Excel users, because Excel has fantastic XML support.

This is the second post in a series for Xignite customer’s using Excel that explores how to import market data into Excel using XML. The previous post in this series showed how you can import market data into Excel using a CSV file (comma separated values), the most common data exchange format for spreadsheets. As the native data format of Xignite Web services, XML allows you to go beyond the simple file import available with CSV to create direct links to Xignite Web services that allow you to update real-time market data from within Excel.

Importing Market Data into Excel from an XML File

The simplest way to get market data into Excel using XML is to import an XML file just as you would import a CSV file.  Simply go to the Web page on Xignite’s website for any Web service operation, type in the relevant input parameters, and click the “View in XML” button.  This will open a new browser tab with the Web service output in XML.  Let’s try it now on the Web page for the GetLastSales operation in XigniteBATSLastSale, an Xignite Web service providing real-time stock quotes.  Keep in mind you must be logged in to your Xignite Web services account in order to receive data.  If you don’t have an account, just sign up for a free trial.

The output should look something like the image above. The next step is to save the Web page as an XML file (usually File>Save As and choosing XML or .xml as the file type). Here is the sample XML file from the GetLastSales example above. After saving the XML file, open it in Excel (usually File>Open and choosing XML or .xml as the file type)

You’ll see a quick import dialog box like the one above asking if you want to import the XML file as an Excel table. You do, so just click OK.

When Excel is done importing the XML file, you should see a nicely formatted Excel table like the one above.

Creating and Refreshing an Excel Table from the Web

Importing your market data into Excel as an XML file as described in the previous section works great for a one-off analysis, but it doesn’t really take advantage of the power of on-demand. If you plan to reuse your analysis and need to update the market data in any way, e.g., same analysis, different symbol, daily end-of-day calculations, or even live real-time calculations, then you are better off creating a direct Internet connection between the Xignite Web service and your Excel spreadsheet that you can refresh at will. This section will describe how you can create an Excel table that pulls market data directly into Excel over the Web with a simple mouse click.

First, navigate to the Web page for the Xignite Web service operation of interest. Then, type in the relevant input parameters, and click the “View in XML” button just like before. In this example, we’re going to use the GetCrossRatesTable operation of the XigniteCurrencies Web service to create a cross rate table in Excel that we can automatically refresh with real-time currency exchange rates. The relevant XML output should appear in your browser as in the image below.

The next step is to copy the Web address (URL) of the XML Web page from your browser. This URL is highlighted in the image above and has the following value for this example.

http://www.xignite.com/xcurrencies.asmx/GetRealTimeCrossRateTable?Symbols=USD%2CJPY%2CGBP%2CDKK

Next, add the following authentication text to the end of the URL “&Header_Username=yourxigniteaccountemail@yourcompany.com”, replacing the sample email address with your own email address used to log into your Xignite account. This will allow Excel to access Xignite market data using your account without having to log in through the Xignite Website. When you are done, the complete URL should look like this.

http://www.xignite.com/xcurrencies.asmx/GetRealTimeCrossRateTable?Symbols=USD%2CJPY%2CGBP%2CDKK&Header_Username=yourxigniteaccountemail@yourcompany.com

Let’s get some market data! Open a new Excel spreadheet and select the “Data” ribbon at the top. Then press the “From Web” icon (highlighted below). A dialog box like the one in the image below will appear. Paste the complete Web service URL, including your authentication email address, into the “Address” bar and click “Go”.

If all has gone well, you should see the XML output in the dialog box Web page region just like in the image above. When you do, press the “Import” button. This will set off the same process as in the previous section for importing the XML file and should result in a cross rate table similar to the one below.

However, there is the one BIG difference from the simple XML file import approach used in the previous section. The Excel table is now linked directly to the Xignite Web service via the Internet.

The market data in your Excel spreadsheet is LIVE! Simply click the “Refresh All” button on the “Data” ribbon above and the table will automatically update.

You may receive a warning dialog box like the one above on the first refresh. Since you hopefully trust the source of the file, Xignite, us, just click “OK” and all the exchange rates in the table will update to the most current values. XigniteCurrencies provides real-time exchange rates that update every ten seconds, so you can repeat the refresh every ten seconds to get the latest exchange rates.

How simple was that!

Well, the truth is that Excel did a lot of work behind the scenes to link the XML output directly to the table in your Excel spreadsheet, including mapping each data element to a particular row and column. This behind the scenes work sets up some very cool options for power Excel users that we’ll describe in the next post in this series, such as modifying the symbols to get different currency rates. In the next post, we’ll explore how you can create interactive Excel spreadsheets that pull live market data over the Web using XML and completely automate your analysis with Excel macros.