Quantitative Investor Solutions

CitiFX Quantitative Investor Solutions

The Quantitative Investor Solutions (QIS) group is the FX industry leader for systematic modeling. The team develops and trades alpha-generating models, which are utilized by a wide variety of clients including real money managers, pension funds and leveraged investors. It also analyzes a wide variety of issues which impact this client base and their investments, such as risk management, regime shifts, and the flow of risk from one market to another. QIS is a pioneer in understanding market drivers and volatility. In addition to creating sophisticated trading models, QIS works with other teams to develop products to enable investors to access the model returns. The following is a selective list and brief description of articles produced by this team:

FX Trading Based on Commodity Market Signals (April, 2009)

• Commodity price fluctuations play an important role in the economies of countries that derive the majority of their export revenues from a few commodities.
• We introduce a new trading model which exploits the lead-lag relationship between commodities and exchange rates. We focus on the currencies of those countries that rely heavily on commodity exports and trade these currencies using the price trends of their major commodities.
• We show that it is possible to generate attractive returns with a relatively simple model.The model yields annual returns in the 8%-9% range with a sharp ratio of around 1.

The Maximum Drawdown-at-Risk (February, 2009)

• In volatile times it is critical to be able to identify those models which are not suited to the environment and are at risk of unacceptable losses. Traditional risk metrics, such as Value-at-Risk, and their parametric estimators are often ineffective for this purpose – it is difficult to distinguish between the natural response of a model to a volatile market, and a model which is unsuited to the environment and should be stopped out.
• This article introduces a risk measure called the Maximum Drawdown a-Risk (MDaR) that is designed to model extreme losses and can be used to identify stop out points for models in a probabilistic approach.
• Central to the MDaR is the non-parametric scenario generator that is used for its estimation. From our investigations, it is shown that our choice of scenario generator is able to effectively replicate the nontrivial properties of financial time series.

Short Term Macro Risk Index (January, 2009)

• The Macro Risk Index has been a useful indicator of market risk sentiment since its inception in April 07.
• Crisis periods in 07 and 08 have been well indicated by unusually high levels of the Index.
• The Index has two variants; a longer term and a recently developed shorter term version. The latter can be used to indicate more transient risk  events.

FX Trading Based on Daily Equity Market Signals (June, 2008)

• There is a strong relationship between the moves in US equities and the moves in G10 currencies vs the USD. This behavior is symptomatic of the flow of risk through the market; equities are perceived as the risk drivers and investors position themselves vs the USD accordingly. In general as equities trend down, the USD appreciates against G10 currencies and vice versa.
• This behavior has been consistent since the 1990’s and it is possible to exploit it with a simple trading strategy.

Macro Risk Index as a Trading Tool (December, 2007)

• Investors’ risk appetite plays an important role in their investment decisions and has been a key market driver in the past 4 months as the global financial markets moved from mild to high risk aversion caused by the deepening concerns over the US subprime markets.
• In this article, we analyze the impact of changing risk attitudes on the performance of the carry trade and investigate whether one could use our Macro Risk Index (MRI) systematically as a trading tool.
• We show that MRI can be successfully used as a filter on the G10 carry strategy to time carry unwinds and the performance can be  improved significantly.

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