Execution Analytics

About Time

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Stand-up comedy and trading have a surprising amount in common. Both rely on strong communication but can have unpredictable results depending on your audience. Most important though is the secret of comedy… timing.
Timing is arguably the most important part of any trading decision; it can often take days between a PM making a trading decision and it being implemented in the market. In fast moving markets a delay of even an hour or so can wipe out any improvements made through trading.
On the sell-side timing is equally important, even if a broker doesn’t have a say over when an order is placed, they often control how quickly it is executed and whether to front- or rear-weight the trading.
In this paper we look at how we can break down common performance metrics to show the benefits (or cost) of timing. This can help clients understand whether it is the algo itself that’s performing well or simply their choice of strategy.

Execution Analytics

Introducing… Continuously Variable Liquidity

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How many gears does your car have? 5, maybe 6? For casual driving that’s plenty, but as the complexity of driving goes up so does your need for control. F1 drivers currently have 8, and back in my farming days 24 was pretty standard on a tractor. Nowadays many vehicles are now doing away with traditional gears all together. Continuously Variable Transmission gives you infinite control over the gear ratio.

Now, how many liquidity seeking strategies do you have access to? 5, maybe 6? You see where this is going…

In this paper we introduce a new approach to defining a liquidity strategy and show how a thoughtful approach to venue access can provide a vastly better experience to the trader.

Execution Analytics

Buyback to the Drawing Board

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Over recent years we have seen a surge in corporate buybacks as the preferred way to deliver value to shareholders.

As someone who has spent years studying institutional trading and market structure, a buyback sounds like the perfect order; they are long running, passive trades with huge broker discretion. Yet for some reason, they often appear to be traded in a very clumsy fashion.

In this paper we review some recent buybacks and see how much a poorly executed buyback can really cost the corporate issuer and their shareholders.

Execution Analytics

The Problems with Performance

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Transaction Cost Analysis is a well-established part of the trading process. But with a growing number of buy-sides relying on algo wheels to ensure they are getting the best out of their brokers we decided to look at the common pitfalls with performance monitoring and ways to improve the measurement and evaluation of algos.

Redburn has been measuring both its own, and external brokers for many years. We have also spoken to a wider range of buy-side firms, some using an algo wheel with great success, others just starting out. Here we share our experience of the common mistakes and provide a guide for those who are just beginning.

Execution Analytics

Under the Hammer

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Here at Redburn labs, we were fascinated to read the LSE’s paper “Lifting the Lid on the Close” which provided some interesting insights into auction behaviour. Since then, we have seen the importance of auctions continue to grow. Despite a lot of existing literature around Auctions, when a single liquidity event accounts for nearly a third of the day’s trading there is always more to be understood.

Execution Analytics

Blurred Lines

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Are tomatoes fruit or vegetable? Is a Jaffa Cake a cake or a biscuit? In 1991, the latter question was finally settled through a court-case; after considering eight different attributes of the snack, it was agreed that Jaffa Cakes are legally cakes, not biscuits. Unfortunately, not all debates end with such a definitive resolution.

In this paper we explore how the role of Electronic Liquidity Providers (ELPs) has changed over time and how the lines between ‘lit’ and ‘dark’, ‘toxic’ and ‘non-toxic’ liquidity are not as clear as they seem.

We show that by carefully managing our interaction with liquidity sources at all levels we can provide high-quality, low-impact liquidity from sources previously perceived as toxic.

Execution Analytics

Superficial Intelligence

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There is no doubt that technology is taking over our lives. We allow machine learning algorithms to select the news that we read, to recommend the TV that we watch, to drive cars, and (unwittingly) to decide the outcome of elections. As coined by Klaus Schwab in 2015, we are in the midst of the ‘Fourth Industrial Revolution’ and the pervasion of technology is only going to increase.

Execution Analytics

Prickly Pairs

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Originally pioneered in the ‘80s, pairs trading has become a staple amongst a wide range of investors – from day traders to tier-one asset managers. Despite its ubiquity, the approach to executing pairs has changed very little over time. While algo providers have put huge effort into developing liquidity-seeking algorithms and improving benchmark performance; until recently, very little has changed for pairs.

Execution Analytics

Order Entry Requirement

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Last year, Redburn introduced the world to the concept of the ‘Order Entry Requirement’, or OER. The idea is that for orders below a particular size it is not worth interacting with certain venues. Although this seems intuitive – there’s no point sending a small order to a block venue – quantifying the value is far more difficult.