Relative-Value Funds.
DEFINITION of 'Relative-Value Funds'
A hedge fund that seeks to exploit differences in the price or rate of the same or similar securities. The relative value fund trades on gaps, rather than the price of a specific security alone. The relative value fund may take positions if the gap between prices or rates is considered to have reached its peak and is thus expected to shrink, or may take a position in a security if similar securities are experiencing price changes.
BREAKING DOWN 'Relative-Value Funds'
A relative fund manager will take long positions on securities considered undervalued, while taking short positions on securities considered overvalued. Fund managers determine what they consider normal differences in prices or rates by examining historical movements, and take positions that exploit gaps until the normal state is reached.
Relative value funds tend to be lower risk, and perform better in low volatility markets. If markets become volatile, it becomes more difficult to take advantage of relative changes in price, as investors become more willing to dump certain securities for safer havens.

Relative Value Trading-- Patent Awarded for the Unique Visualization of PAIR Orders.
Relative value trading is an investment strategy where one or more securities are traded in relation to another. Let’s assume that an investor likes a particular stock but is uncertain if the recent stock market rally will continue. To minimize volatility and benchmark risk, the investor could simultaneously buy the stock and sell a stock index future at a “spread.” A long only investor could achieve a similar strategy by simultaneously purchasing an inverse stock index ETF (whose value rises if the market declines). In these examples, the investor has changed the investment from having to be right both on the market and the stock to just being right that the stock’s performance will outperform the market.
Relative value trading strategies are growing in popularity. Over the past two years, Tradebook’s PAIR platform has experienced an 87% increase in the number of relative value strategy orders. The popularity is due, in part, because asset classes across geographies are becoming more electronically accessible. Investors can now algorithmically implement alpha capture strategies using multiple equities, options and futures that simply were not possible in manual markets.
Some strategies can be very complex, involving multiple instruments with each instrument having its own pricing – current bid, current ask, last price, etc. The multiplicity of instruments in a strategy (order) thus implies a multiplicity of values that might be relevant to trading decisions. Yurij Baransky and Vipul Nagrath have created innovative data visualization – a better presentation of data and market information to assist traders in immediately and intuitively understanding what is happening with the investment and execution implementation.
Yurij and Vipul have created a PAIR trader’s “cockpit.” Studies find that the human brain deciphers images and color simultaneously and more rapidly than the traditional grid of numbers. Images can elicit strong emotional responses. Their patented display uses color and icons to communicate for fast and immediately consumption the marketability of a strategy, its current state and the side (buy/sell) of the instrument in the strategy.
Relative value trades can be expressed with many spread types. For example, as a simple spread (e. g. A-B), a ratio (e. g. A/B), a % change (e. g. 100*(A∆% – B∆%)), merger arbitrage (xB + $ – A), etc. This novel visualization technique also provides investors with an easy comparison across different spread types. For instance, the trader can visualize whether a $0.10 simple spread for Strategy A is more marketable than a $2.00 simple spread in Strategy B or a ratio spread of $1.342 for Strategy C. Of course it all depends on the details of the strategy, but with the same brainpower, this technique enables traders and investors to visually compare different strategies to get a good “feel” for how “close” each strategy may be to getting done.
Congratulations to Yurij and Vipul on the patent. For more information on the “PAIR” front-end and the execution algorithm, contact a Tradebook Execution Consultant.
Yurij Baransky is the Global Head of Product Development where he oversees all aspects of building and maintaining Bloomberg Tradebook’s equity, derivatives, FX, fixed income and algorithmic trading functionality. Yurij joined Bloomberg L. P. in 2000, and has held various programming and management positions in Bloomberg R&D. He previously oversaw the US Listed Options trading platform and his team developed and launched the Tradebook PAIR trading platform.
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You are here: Global Markets Training В» Fixed Income Relative Value Trading.
Fixed Income Relative Value Trading.
This two-day course provides a comprehensive and concise overview of the models and tools required for relative value trading in the fixed income markets. The application of the relative value toolkit in an actual trading context is particularly emphasized with practical exercises and case studies enabling participants to translate theory into effective trading strategies. Familiarity with common fixed income instruments and Excel is assumed although in-depth mathematical knowledge is not required. Delegates are equipped with PCs.
DAY 1: Statistical Relative Value Models.
Introduction to Fixed Income Relative Value (RV) Analysis.
+ Concept of RV analysis.
+ Sources of RV opportunities.
+ The insights from RV analysis.
+ Applications of RV analysis: Trading, hedging, asset selection, creating alpha.
+ RV models: Statistical and financial models and their interaction.
Principal Component Analysis (PCA): Theory.
+ What is PCA and how does it help us?
+ PCA versus other factor models.
+ Mathematics of PCA.
+ Gaining insights into market mechanisms through interpretation of the PCA results.
+ Decomposing a market into directional (beta) and non-directional (alpha) factors.
+ Using PCA to screen the market for trading opportunities.
+ Using PCA for asset selection.
+ Combining all these elements into a step-by-step guide for PCA-based analysis and trading.
Principal Component Analysis: Practice.
+ Using PCA for yield curve analysis.
+ Using PCA for swaption analysis.
+ Using PCA for hedging and asset selection.
+ Using PCA in other markets: Stocks, FX, commodities.
Mean Reversion: Theory.
+ What is mean reversion and how does it help us?
+ Mathematics and model selection.
+ Calculating conditional expectations and probability densities.
+ Calculating Sharpe ratios.
+ Calculating first passage times.
Mean Reversion: Practice.
+ Which performance is likely over which horizon?
+ Setting performance targets.
+ Setting stop loss levels.
Practical case study: Applying statistical RV models in a trading context.
+ Perform a PCA on the yield curve and find trading opportunities.
+ Run a mean reversion model to assess the performance potential and speed of these trades.
DAY 2: Swaps, Options and their Combinations.
Asset swap spreads (ASW)
+ Model approach: Link between ASW and LIBOR-repo spreads + A model for pricing ASW.
+ Driving factors of ASW.
+ Making the pricing model for ASW work in practice.
Basis swaps (BSW)
+ Intra-currency basis swaps.
+ Cross-currency basis swaps.
+ Swapping bonds into a different currency.
+ Assessing the relative value between bonds in different currencies.
+ The mutual influences between ASW and BSW.
Credit default swaps (CDS) for government bonds.
+ FX component and other pricing issues.
+ The "arbitrage inequality" between ASW, BSW and CDS.
+ Trading this "arbitrage inequality" in practice.
Practical case study 1.
+ The mutual influences of ASW, BSW and CDS in the JGB market.
Swaption trading strategies.
+ Brief review of option pricing theory.
+ Classification of option trades.
+ Different exposures and goals of the different option trades.
Swaption trading strategy 1: Conditional curve trades.
+ Single underlying: Breakeven analysis, breakeven curves, link to macro models.
+ Multiple underlyings: Conditional steepeners and butterflies.
Swaption trading strategy 2: Implied versus realized volatility.
+ Single underlying: Delta hedging, calculation of realized volatility.
+ Multiple underlyings: Implied vol curve versus realized vol curve.
Swaption trading strategy 3: Implied versus implied volatility.
+ Factor model for the swaption vol surface.
Practical case study.
+ Finding, classifying and analysing swaption trades on the USD vol surface.

Fixed income relative value trading strategies

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Understanding Relative-Value Arbitrage.
Relative-value arbitrage is an investment strategy that seeks to take advantage of price differentials between related financial instruments, such as stocks and bonds, by simultaneously buying and selling the different securities—thereby allowing investors to potentially profit from the “relative value” of the two securities.
Before we explain that, let’s review the concept of arbitrage. Arbitrage, at its most simplest, involves buying securities on one market for immediate resale on another market in order to profit from a price discrepancy. But in the hedge fund world, arbitrage more commonly refers to the simultaneous purchase and sale of two similar securities whose prices, in the opinion of the trader, are not in sync with what the trader believes to be their “true value.” Acting on the assumption that prices will revert to true value over time, the trader will sell short the overpriced security and buy the underpriced security. Once prices revert to true value, the trade can be liquidated at a profit. (Remember, short selling is simply borrowing a security you don’t own, selling it, then hoping it declines in value, at which time you can buy it back at a lower price than you paid for it and return the borrowed securities.) Arbitrage can also be used to buy and sell two stocks, two commodities and many other securities.
Relative-value arbitrage is also referred to as “pairs” trading. That’s because with relative-value arbitrage, an investor invests in a pair of related securities. Ideally, these securities will have high correlations, meaning they will tend to move in the same direction at the same time.
Stocks in the same industry that have trading histories of similar lengths are often used in relative-value arbitrage. Automotive stocks GM and Ford are good examples, as are pharmaceutical stocks Wyeth and Pfizer. But indices, such as the S&P 500 Index and the Dow Jones Utilities Average, can also be used in relative-value arbitrage. So can index-tracking stocks, such as the QQQQ (which tracks the Nasdaq Composite Index) or the SPY (which tracks the S&P 500 Index). In fact, when it comes to choosing securities, the sky is the limit: Relative-value arbitrage works not only with stocks, but also with futures, options, currencies and commodities.
Whatever securities are used, when the prices of the two securities diverge—meaning one security rises in value and the other security falls in value—the relative-value arbitrageur buys one security and shorts the other. When the prices converge again, the relative-value arbitrageur closes the trade.
Because relative-value arbitrage requires securities to be correlated in price, it is typically used in a sideways market, which is a market that is neither rising nor falling, but trading within a specific range. Whether a market will continue to stay within a specific range can be difficult to evaluate, however, as markets can change direction quickly. So, relative-value arbitrage requires the knowledge and skill to evaluate not just individual securities, but the markets as well.
In summary, then, while relative-value arbitrage may help increase returns in difficult market environments, such as sideways markets, it requires significant expertise, and is best used by sophisticated investors who are willing to accept its risks.
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