Top 5 Hedge Fund Technology Challenges All Blown Away by the Cloud
The year 2011 proved to be yet another lackluster year for the hedge fund industry. There are any number of possible explanations for why the average hedge fund lost 4.8 per cent including increased volatility, lack of focus, crowded strategies, and regulation. Whatever the precise reason for this continued poor performance, it is likely that the hedge fund industry has only a limited amount of time to get back to the glory years of consistently providing absolute returns, before it risks a significant outflow of assets under management.
The adoption of an on-demand market data cloud instantly benefits the hedge fund industry because it allows firms to address the top 5 hedge fund technology challenges.
This post is the first in a multi-part series that describes the top 5 hedge fund technology challenges all blown away by the market data cloud. In subsequent posts we will examine each of the five hedge fund technology challenges in greater detail.
Hedge Fund Technology Challenge #1
Focusing on alpha generation, not market data management
Now more than ever hedge fund managers need to be laser-focused on their core responsibility of alpha generation. Distractions such as reporting, IT management, and just the general business of running a hedge fund all play a role in reducing the hedge fund industry’s focus on the investment management process. With an on-demand market data cloud all the headaches involved with building and maintaining a market data infrastructure are removed.
Hedge Fund Technology Challenge #2
Expanding the universe of alpha generation possibilities
Hedge funds compete in a world where alpha generation opportunities have become more fleeting and dispersed than ever before. In this new world firms require a market data solution that allows them to quickly analyze a broad set of opportunities wherever they may be. The market data cloud model expands the universe of alpha generation possibilities by putting vast arrays of global and multi-asset class market data right at the fingertips of hedge fund managers.
Hedge Fund Technology Challenge #3
Bringing instant transparency to regulatory and investor reporting
The job of a hedge fund manager has become infinitely more complex with demands for improved transparency coming from seemingly every direction. For many firms this has meant onerous reporting requirements, made even more difficult by inflexible systems, and an inability to quickly access accurate market data. An on-demand market data solution, that offers comprehensive coverage of real-time, historical, and reference data, allows firms to instantly enrich their regulatory and investor reporting.
Hedge Fund Technology Challenge #4
Getting new funds up and running in record time
The health of the industry depends on relatively low barriers to entry for new hedge fund entrants, because as we know, size kills alpha. A major barrier for new funds Read more
AlphaClone – Investment strategies that mirror the world’s top hedge funds
Our Customer Spotlight series showcases the innovative ways our clients are using Xignite’s Cloud APIs to power their applications.
AlphaClone is a San Francisco-based investment management firm that enables investors to “follow the smart money” with equity strategies that mirror the world’s top hedge funds. In addition to investment management services, AlphaClone also offers a powerful online research platform that investors can use to analyze stocks and to create and backtest their own cloning strategies.
Xignite sat down with Mazin Jadallah, Founder and Chief Executive Officer, to learn more about AlphaClone.
Q: Describe AlphaClone’s service offering.
Mazin Jadallah – AlphaClone is a SEC registered investment adviser and research firm. Our objective is to give investors actionable, cheaper, more liquid access to the investment ideas of the world’s top institutional investors. Our investment research approach, a process called “cloning”, utilizes top hedge fund public disclosures to construct and backtest equity investment strategies.
Q: Very interesting concept. . . does cloning actually work?
Mazin Jadallah – Yes, cloning the investment strategies of top money managers has been independently shown by academic and industry research to generate alpha returns. Read more
Trading on Volatility? Build an Option Greeks Calculator.
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
2012 Market Data Industry Outlook – 4 Major Trends all Leading to the Cloud
In 2011 the cloud finally went from an unproven curiosity to an accepted mainstream technology solution. In 2012 we will witness the deepening penetration of the cloud into the consciousness of multiple industries. The market data industry is an interesting case in point because the major industry trends are all pointing to the rapid adoption of an on-demand cloud-based market data solution.
Let’s review each of these trends individually to understand how important the cloud will be for the market data industry in 2012:
1. Market Data Supplier Economics
The suppliers of market data are in a state of flux. On one hand, the cost of business is soaring with the new technology resources required to support sky-rocketing message rates, microsecond execution, and new regulation. On the other hand, the exchanges are experiencing sluggish revenue growth. Traditionally exchanges had four distinct sources of revenue: 1.) execution; 2.) listings; 3.) clearing; and 4.) market data. Of these, only market data is growing, while the others have either completely dried up or are not likely to be a significant source of revenue in the future. The exchanges have responded to these unfavorable economics with a wave of consolidation in an attempt to reduce costs but the health of the industry depends on growing the revenue side of the equation. The exchanges understand that their best revenue strategy is to distribute their most valuable asset, market data, direct to consumers. This strategy has already seen success with the exchanges offering direct feeds, co-location, and other services to their low-latency clients.
In 2012 we will see more exchanges begin to focus on the largely untapped segment of consumers who need market data, such as historical trade and quote data, but are not latency sensitive. This is potentially a huge revenue source for the exchanges and is ideally suited to the on-demand market data cloud. Forward-thinking exchanges such as CME DataCloud, Direct Edge EdgeBook Cloud, and NASDAQ Data-On-Demand, have already moved in this direction, but 2012 will be the year that many more exchanges embrace the market data cloud to sell directly to consumers.
(Read more about how the exchanges are embracing the cloud in our recent blog post – Cloud Strategy for Exchanges and Financial Markets.)
2. Market Data Consumer Economics
As with the suppliers of market data, consumers are also facing an uncertain future. For many consumers, particularly in the financial services industry, the whole process of data management has become overwhelming. The old model of bringing all market data in-house, so that it can be accessed quickly, is under considerable pressure. There is now simply too much data to do this cost-effectively. Another related issue is time to implementation. With intense competition, many investment firms require immediate access to global and multi-asset class market data. Unfortunately, the traditional method of having a vendor add a feed can be a very slow process. Investment firms require a much more nimble solution that allows them to quickly access discrete data sets.
In 2012 we’ll see more firms conclude that not all data should be brought in-house. This change in mindset will lead firms to become much more discerning about what data should be stored locally, and what data should be retrieved on an ad-hoc basis from a market data cloud.
3. Proliferation of Mobile Devices
It is clear that we are in the midst of a technological sea change Read more
How to create an Excel based Multi-Asset Class P&L Tool in 5 Minutes
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
Monetizing Market Data in an Evolving Global Marketplace
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? Read more
Developer Focus – StockTouch – Getting to the top of the iTunes Store
The Developer Focus series profiles developers who have built applications using Xignite’s Cloud APIs, highlighting their experiences, observations, and advice.
John Morris is the lead developer and CTO for StockTouch, an innovative financial market data visualization app that is currently the #1 paid financial app in the iTunes Store (read more about StockTouch in our recent Customer Spotlight).
StockTouch’s groundbreaking data visualization interface has received widespread attention from the media and from Apple, who have selected StockTouch as one of the few apps to be loaded on all iPads and iPhones in their Apple Stores worldwide. We recently sat down with John to learn more about him and the development process behind StockTouch.
Q: Tell us a little bit about your background?
John Morris – I’ve been programming since 1981, mostly as a contractor. My primary focus has been the gaming industry, mainly for two reasons. First, I love games! But perhaps more importantly, game development requires optimizing code at all levels in order to ensure good performance. It’s a challenge I enjoy taking on.
Q: How did you get involved with StockTouch?
John Morris – I learned about the StockTouch project through a mutual friend. I joined the project initially as a consultant to build the prototype. As everything came together, I was offered and accepted a position as the co-founder and CTO of StockTouch.
Q: How is the development process for StockTouch structured?
John Morris – The StockTouch team is completely virtual with the core members in New York, Seattle and Los Angeles. There are actually only two of us who are involved on the coding side of StockTouch. I work on the client side, and we have a contractor who works on the server side. We also work very closely with the other members of the team that deal with the overall user experience and feature set.
To build StockTouch, I was initially given just six screenshots, but we always had a pretty clear vision of what we wanted to do. We wanted the app to have a very intuitive interface with a fluid user experience. As a game developer, I personally wanted the application to offer a superior and unique visual experience, backed by extremely powerful features. StockTouch performs its rendering via OpenGL, and we really push the graphical capabilities of the iPad to deliver a cutting-edge experience.
Q: How difficult was the transition to the iOS platform?
John Morris – I’ve been building iOS products since 2008, so it wasn’t an issue for me. For programmers unfamiliar with iOS, transitioning to the platform is not very easy—there’s a Read more