Meaning of Market Event
A Market Event is anything significant that can affect the markets in terms of price movement, volume or market microstructure, like referendums or surprise regulatory decisions. The market events are classified in three types:
- Unplanned event or Black Swan – Price volatility is extremely high, profit potential is more (for ’always’ prepared firms) and disruption is high.
- Planned event with unknown outcome or Grey Swan – Post event price volatility is high, profit potential extremely high and disruption is limited
- Planned event with known outcome or White Swan – Price volatility post event is low, profit making opportunities and disruption in the market are limited.
On 15th Jan 2015, the Swiss National Bank (SNB) suddenly announced that it would no longer hold the Swiss franc at a fixed exchange rate with Euro. This was a totally unplanned event, and the markets were not ready for the outcome. Following the announcement, currency markets crashed with nearly 17% drop intraday, which is huge, considering typical movements are in the range of 0.5% for the daily transactions.
Fig1: Chart of EUR/CHF in the aftermath of the SNB announcement Source: ZeroHedge
Disruption and volatility in the market was exceptional. Big FX brokers were crippled, as FXCM, a major US retail foreign-exchange broker emerged as one of the biggest victim amongst the leading firms, only to be rescued later by a bailout from Leucadia. UK’s Alpari, however, did not have a favourable outcome as FXCM, as it became insolvent. However, due to the immense volatility In the market, HFT firms generated positive returns. Brokers like Oanda and Direct FX came out of it unscathed.
After UK’s decision to exit from the European Union following the results of a national referendum, currency markets globally saw a bloodbath. Nearly, $2 trillion was wiped out from global equity markets. Pound crashed 10% intraday and margin requirement across various asset classes related to GBP & Britain shot up. This was a case of planned event with unknown outcome.
Yet, as per media reports, computer-driven hedge funds generated positive returns. High Frequency Trading (HFT) firms profited from the changes in currency correlations with zillions of transactions throughout the day.
Securities transaction tax in India increased on options from 0.017% to 0.05% from June 1, 2016. Daily traders felt the heat, as volumes dropped. Everything was on expected lines, which limited the disruption. The HFT firms got impacted by this not much by the increase in STT directly, but from the fall in volume that limited the profit making opportunities for HFT as well as for most other firms in the market. In the below chart, the decrease in volume of Nifty Options for the first five days in June 2016 is plotted against the corresponding period of the previous month.
Data Source: nseindia.com
What helps HFT make money
Volumes and volatility contribute most to the success of trading strategies.
- High volatility – Ensures there are opportunities for the traders
- High volumes – Ensures that the opportunities are frequent and sizable
Profitable Strategies during high volatility events
The prime objective here is to capture the bid ask spread during the low volatility events. People buy at the ask price and sell at the bid price. Most traders have access to multiple exchanges or trade in multiple asset classes. Therefore, there is also a need to identify the leads and lags of different exchanges, which is embedded in most of the trading strategies.
Volatility results in disparity at different destinations. Classical arbitrage is a speed game – if you are not the fastest or among them, then there is not point using such a strategy. Of course, speed comes with its associated cost. However, if there is volume, there is an opportunity to scale up.
Machine learning/Directional strategy
Many High Frequency Trading firms employ directional strategies and Machine Learning that take full use of the short-term price deviations. At least 1000 orders in a minute’s time can be placed. Traders do not take market risk or hold position for more than a millisecond. Tick based decisions are taken to execute profitable roundtrips trade.
Sentiment Analysis & Machine Readable News based strategies
Sentiment Analysis is gaining popularity with a lot of HFT firms, however, they are more applicable for the events that are certain. People look at the data and react to it. HFT reacts to news much faster than the manual ones. Twitter feeds are used to design trading strategies. The downside is that a lot of processing has to be done to create a quantitative sentiment index and design a strategy around it.
Different kind of market events require relevant market strategies to remain profitable. To understand more on these market events, watch the webinar.
If you’re a retail trader or a tech professional looking to start your own automated trading desk, start learning algo trading today! Begin with basic concepts like automated trading architecture, market microstructure, strategy backtesting system and order management system.