- Statistical Arbitrage Strategies
- Algorithmic Trading and Direct Market Access
- Structured Products. Strategies for Bad and Good Times
- Volatility Trading & Strategies
- Absolute Return Funds, Risk Aversion and the Cash Challenge
- Systematic Models in FX: Alpha & Beta
- The Importance of the Capital Structure in the Greek Banking System during a period of Market Turmoil.
- STP - Straight Through Processing
Statistical Arbitrage Strategies
Speaker:Catherine Vaughn, CFA.
Highbridge's approach to Statistical Arbitrage involves trying to identify and profit from sustainable sources of alpha through superior stock selection. Highbridge believes that portfolios driven primarily by stock-specific risk are more likely to produce returns largely independent of broad market moves. Highbridge's statistical arbitrage process seeks to maximise alpha and minimise systematic risk, as it does not attempt to profit from timing exposures to common sources of risk or attempt to predict which sectors will outperform or underperform. Decisions made in Highbridge's approach to Statistical Arbitrage are driven by common sense investment principles similar to those used by many qualitative investment managers. The process is quantitative, but the underlying concepts are grounded in ideas with solid, fundamental economic underpinnings.
Highbridge's statistical arbitrage strategies are based on the belief that a stock's price movement, and therefore return, can be attributed to and decomposed into two parts: common factor risk and idiosyncratic (or unique) risk. Part of a stock's price is driven by sources of risk common to groups of stocks, such as the return of the stock market as a whole or the return of a stock's sector. In addition, Highbridge believes stock prices are also driven by characteristics unique to individual stocks, such as the underlying stock's fundamentals or one-off events. Highbridge's statistical arbitrage strategy aims to exploit these stock-specific sources on a continuous basis, while "neutralising" or minimising the effect of market or common factor moves.
All of the equity portfolios managed by Highbridge's Statistical Arbitrage Group run off the same underlying investment process, with application differences in the definition of the investment universe and portfolio construction to accommodate the diverse mandates and risk profiles across our fund ranges.
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Algorithmic Trading and Direct Market Access
Speaker:Stavros Siokos, Ph.D.
The following issues will be analyzed:
- With algorithmic trading seemingly besieging stock markets on both sides of the Atlantic over the past year, the buy-side users still need (ongoing) education about algorithmic trading techniques in order to make the most appropriate use of algorithms and reduce the fear among some over the so-called 'black box' and even 'white box' applications. Clearly there are different tastes and reasons for using algorithms as an execution and trading tool.
- In terms of the perception (and reality) of algorithmic trading and DMA (Direct Market Access), how does it vary from institution to institution on the buy-side? Has this changed over the last six-12 months and in what ways are different providers been responding? Are algos being used for 'high' as well as 'low touch' trades?
- With algorithmic trading accounting for around 50 per cent of trading in large caps in the US, possibly 10 per cent to 20 per cent in Europe, and Asia coming from a lower base, what can we expect from these different regions over the next 12 months in terms of growth and adoption of algos?
- With so much talk about multi-asset trading and gaining arbitrage opportunities from trading across asset classes, how appropriate are algorithms for that and for trading mid- and small-cap equities, emerging market equities, FX and commodities? Is more development needed in terms of IT infrastructure and capacity of systems (connectivity, FIX) to allow this to really bloom going forward?
- Despite a plethora of algorithms and solutions being touted by various providers - from agency/brokers and sellside firms - how important is it for service providers and sellside firms to differentiate themselves in terms of product and service offering, connectivity and innovation?
- With such a focus on performance, trading costs really matter to investors and can make a significant difference in a portfolio's overall return. What are the key factors in a decision to deploy one algorithmic trading system over another - ease of use, connectivity (FIX), liquidity, best execution and transparency or a combination?
- 'Best execution' is a term that has many different definitions. Some say it means delivering the execution that best suits the client's needs. Clearly algos are not appropriate for every trade, but can help deal with the 'noise' on trading floors and simpler trades - freeing up traders to intellectualise over the more complex transactions. Can they help generate alpha too?
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Structured Products. Strategies for Bad and Good Times
Speaker:Dimitris Flamouris, Ph.D.
Structured products are used to different degrees by investors in various countries. Italian and Dutch retail investors are ready to buy complex structures while UK investors for example prefer more risk averse and simpler alternatives. The reason people choose these products as a regular means of investing is that they allow the individual to get exposure to markets otherwise not within reach, (e.g. foreign futures and options markets or emerging markets) offering very attractive alternatives from the standard opportunities of investing in the domestic markets. Investors can expand the range of products available to them and go beyond the traditional stocks or bonds or mutual funds (typically long-only institutions) and invest in a potentially leveraged fashion risking only part or even none of their capital.
We will examine which products are available in the equity derivatives world, and how one should choose to invest in these products in different market environments. Different products should be chosen during the bad times of high uncertainty and high volatility and different products during the good times when low a volatility environment is present. Highly risk-averse investors should opt for different structures than more risk-seeking individuals who would not object to risking part or all of their capital. There are products that can give a guaranteed stream of cashflows and others that can pay a big coupon only at the end subject to a specific event taking place. The aim of this course will be to offer a guide to investing in structured products, for all investors with different views, different risk-profiles, different liquidity constraints and different budgets.
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Volatility Trading & Strategies
Speaker:Goudinakos Stratos
Volatility in the context of thermodynamics is the measure of the state of instability, the tendency of a substance to vaporize; in the context of finance is a measure of the uncertainty of the return realized on an asset, annually, adjustment for differing time periods is required. Volatility mostly refers to the standard deviation of the change in value of a financial instrument for a known time period. Usually, quantifies the risk of that instrument over that time period. It is one of the most "favourite" subjects among academics, market participants and especially option market makers. There are different types and interpretations. Characteristically, traders will be talking of four different forms of volatility (historical, forecast, implied, and future) depending on their own expertise and point of view in the markets.
Black-Scholes, theoretical models vs the real world.
Term structure of volatility shows the relationship between the implied volatilities of the options and their maturities.
Skew is the non symmetrical variation of implied volatility with strike prices.
Volatility matrix is a table showing the variation of implied vols with time to maturity and strike prices.
Volatility trading is implemented by trading an option portfolio with a delta neutral position.
Goals and expectations determine the choice of strategies from an outright purchase or sell of an option to vertical spreads and even more exotic straddles and strangles.
Examples from real markets will be elaborated.
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Absolute Return Funds, Risk Aversion and the Cash Challenge
Speaker:Siokis Dimitris
Fund managers have been recently offering a series of client solutions that target higher returns than Money Markets by assuming risk across different asset classes and packaging the end product as a Cash-Plus solution. In order to achieve this, Fund Managers employ new asset allocation and risk management techniques. The technique of Risk Budgeting is core to the evolution of the Cash-Plus solution and is a an example of how Fund Managers and Risk Management can work together in order to package risk-disciplined products to their clients.
We will examine the performance of these products for the last, volatile, year and discuss the following topics:
- Correlation of the Funds' Returns
- Evolution of NAV's
- Which risk factors explain the returns of the funds
- Risk appetite of the funds under a volatile market environment - Risk De-leverage
- Money Market Returns: Can Absolute Return Funds beat cash under current market conditions?
The aim of this presentation is to guide investing in Absolute/Target Return Funds and to predict their behaviour under different market conditions.
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The Importance of the Capital Structure in the Greek Banking System during a period of Market Turmoil.
Speaker:Georgikopoulos Nikolaos, D.Phil.
The following issues will be analyzed:
- The composition of Greek banks own funds: Trends and developments from an overall financial stability viewpoint.
- Analysis of capital trends in the Greek banking system.
- The impact of Market Turmoil in the stability of the Greek financial system.
- The impact of Basel II on the capital structure of Greek Banks.
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