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In a continuation of our volatility series (last we looked at the trading halts, specifically around August 24th), this week we take an in-depth look into volume profiles. Given the high volatility period of August and September 2015, many questions were raised about how price volatility affects the markets. One of the most interesting is whether high volatility days have a dramatic effect on when trading takes place. Said differently, how do these days change the typical VWAP “smile” curve? Most traders assume that the volume profile differs on days of high volatility, and that is a hypothesis which we want to test.
This article summarizes results of our extensive empirical study motivated by the intuitively appealing statement that institutional clients’ average transaction costs are sensitive to market conditions. Using a comprehensive sample of client execution data covering two years of trading, we confirm that average cost of institutional trades varies considerably and systematically with volatility, volume, and trade imbalance surprises. For the overwhelming majority of buy-side institutions, implementation shortfall is higher than normal when volatility and volume exceed their historical average values. However, the deviations of trading volume in excess of the values typically observed in high volatility conditions dampen the effect of high volatility environment on execution costs of institutional orders. We document a strong dependence of transaction costs on contemporaneous trade imbalances, which is amplified by higher than normal contemporaneous volatility. We observe that cost curves are more sensitive to order size at the times of less favorable buy-sell trade imbalances, reflecting the role played by directional market pressure indicators. In summary, buy-side institutions should not neglect market conditions monitoring, as failure to adjust promptly to market conditions may result in deteriorated performance and missed cost savings opportunities.
When balancing the trade off between finding liquidity and avoiding volatility around Asian open auctions, applying careful analysis to the specifics of the order generates more benefits than applying a standard approach or relying on ‘gut feel’.
Dark trading in Europe is expected to be fundamentally altered by the implementation of MiFID II/ MiFIR. The proposed cap on dark pool volumes will require all institutional investors to reevaluate how they interact with dark liquidity, but for some the impact of the changes will be greater than for others. This research examines the potential impact on a variety of algorithmic strategies. In particular we focus on the varying degrees to which different strategies participate in dark trading and how much of that volume is traded in sizes which qualify for the Large In Scale (LIS) waiver and so are exempt from the cap.
While Best Execution and Transaction Cost Analysis (TCA) are well-established in equity trading, other asset classes have been slower to adopt such techniques due to limitations in market data and market structure characteristics. In Over-thecounter (OTC) markets there has typically been no requirement for central reporting, making it difficult to demonstrate best execution in the same way as for equities. This is beginning to change due to pressure from regulators and end investors who require higher standards of information. Market structure changes, with more electronic platforms taking increasing shares of trading, are also enabling more precise analysis. Over the last three or four years, Foreign Exchange (FX) TCA has become increasingly mainstream for asset managers, while one recent survey shows that in the past year, Fixed Income TCA has become the fastest growing category of analysis1. These trends are expected to continue, not least in the light of MiFID II regulations.
The goal of this research was to study methods of altering the standard approach to VWAP such that it respects stock-specific volume volatility. The early returns are promising, and we think this concept can be applied to other algorithms where inappropriately tight constraints create excess cost. In this paper, we review the state of the art for volume forecasting and how these efforts are rewarded. We show the results of a random trial of orders that use a static tolerance around the target schedule vs. orders that use a tolerance that is set by the volume volatility of the stock. The results show less aggressive trading. We also argue that traders shouldn’t choose algorithms based on stock characteristics. Instead, algorithm choice should focus on the tradeoff between cost and timing risk.
As the next advance in FX TCA reporting, our clients in the investment community have requested size-adjusted spread (SAS) benchmarks that account for risk and liquidity on a pre-trade and a post-trade basis. However, one of the more frustrating aspects of over-the-counter trading is the lack of transparency around these spreads. An accurate size-adjusted spread based on aggregated electronic foreign exchange quotes would replace the old method of supplying expected spreads: manually-filled matrices for each trading region with spreads for given currency pairs and sizes. Buy-side traders depended on this information to both hold banks accountable for their agreed spreads as well as manage their own expectations for costs. Now that buy-side firms are more responsible for currency risk, they need a system that will digitally re-create those matrices and give them a benchmark that will show that they add value to the investment process.
- Single-stock circuit breakers occurred almost 1300 times on 8/24/15
- ETFs represent 79% of halts
- Halts are imprecise but a net benefit
Equity market volatility has come roaring back over the past month. As the VIX flirts with levels unseen since the financial crisis and 2% index moves represent a regular occurrence, the typically sleepy months of August and September have been anything but for equity traders. The past month has put global market structure through an unexpected stress test, and we have been reviewing the data for observations. In this note we will focus on trading halts (single-stock trading halts). In the coming weeks, we will look at additional important issues, including some of the effects of volatility on volume curves, spreads, and liquidity.
On September 8, 2015 the TMX Group published the much anticipated fee schedule for the revamped Alpha Exchange (subject to regulatory approval). Coupled with the recently published minimum size thresholds for “Post Only” orders, we now have near perfect information around how the market will operate and can opine intelligently on the expected impact the new model is likely to have on equity trading in Canada.
Chief Financial Officers at hedge funds, both established and emerging, have a lot on their minds these days: intense competition for assets, increased regulatory and compliance burdens and changes in market structure are among the many things which keep these financial professionals up at night.