Check your execution! – FinanceFeeds Interview
The data and information enlightenment age is here at last. We detail how brokers, traders and LPs can now measure the accuracy of every trade in real time
For those who have spent any length of their career within a retail FX brokerage, it is likely that when asked which particular position within a company is not only the most cognitively strenuous, but also which carries the most risk and responsibility, the heavily burdened team in the dealing room come to mind.
Ever since the dawn of MetaTrader 4 in 2004, the ease of access into a global electronic trading market by a vast array of companies whose executives do not necessarily hail from the vast, well backed safe havens of the institutional financial technology or interbank dealing sectors in London, New York or Chicago, operating a risk model and dealing desk has been a very difficult department to operate.
Indeed, maintaining a career as Chief Dealer is a commendable one indeed, as it can in many cases be akin to fighting several fires from several directions.
Having to manage the different relationships between the banks, non-bank liquidity providers, prime of primes, internal sales staff and of course the traders themselves is tricky enough, however there are continued requirements to analyze data and make sure all execution and risk management has been conducted not only in accordance with company requirements.
The fate of electronic trading companies lies almost completely in the hands of the dealers, but also in accordance with regulatory requirements.
As time has progressed, and the retail FX business has become somewhat mature, a necessity for extrapolating data from all areas of trade order flow has arisen, demanded by traders, brokers, liquidity partners and regulators alike.
By speaking to high net worth traders and hedge fund managers, and allowing them a platform to reach electronic brokerages, platform integrators and prime of prime liquidity companies, FinanceFeeds has had a clear view of what is being asked of brokers by the astute, among which all brokerages should be looking for market share.
Developments of this nature by executives with vast experience in our industry are therefore of great interest, and on that note, FinanceFeeds met with New York-based Pavel Khizhnyak, founder and CEO of Tradefora, to look at how his newly released set of analytics tools integrate into and refine the trading topography from Tier 1 bank to retail trader.
A global insight that led to development
“My background in the FX business may well be international, however I began to look closely at what the retail sector needed when I was at Forex Club, which was the first Russian company to go into the Chinese market. I joined Forex Club in 2005, and then two years later the company obtained its National Futures Association license to operate in North America, so I moved to develop partnership and institutional business in New York” said Mr. Khizhnyak.
“At the time, there was a lot of focus on heading into the mainland areas of China, and at that time I saw China as a country with great potential, but from a quality of life perspective, it is not the same as the Western markets, and that applies also the quality of the local business too. It is very frenetic, with very long working days, and highly competitive with very little transparency” said Mr. Khizhnyak, who as well as being fully conversant in English and Russian, speaks fluent Mandarin Chinese.
“When we into China and implemented our FX business back in 2005, it was a completely different market epoch with just a few international competitors, including brands like MAN Financial, REFCO, Forex.com, FXCM, CMC, CMS and KVB Kunlun. At that time, the market was wide open, Google and Baidu were fighting for FX business and the cost per lead that Baidu allowed for was several cents rather than 100+ dollars it can be today” he said.
“There used to be advertisements across newspapers, in the subway stations, on billboards and anywhere you looked, but times are very different now. Back then, the offline seminar model was booming with many FX companies used to invite over 50 running several large seminars per week and FX ads on radio, TV, newspapers, subways and even taxis” he said.
Nowadays, things are very different and Mr. Khizhnyak’s consultative expertise in structuring brokerage operations all the way from Shanghai to New York had led him to see the need to develop an enterprise level set of analytical tools for the purposes of sustaining and streamlining brokerage businesses, and ensuring a better relationship between regulators, clients and brokers.
When speaking about the original retail oriented version of Tradefora, Mr. Khizhnyak considers the product range to be very much trader-orientated. Traders can register online with Tradefora.com in just a few clicks with no KYC or AML documents required, as no funds are accepted from traders.
Upon registration, traders can download Tradefora EA for MT4, which will then automatically pull all the historical trade data from their accounts and starting from the activation moment will check all trades against the market average, issue trade score on the quality of execution and provider over 15 different TCA and execution quality metrics with millisecond precision and tick by tick accuracy.
Traders then have full access to the entire view of their transaction costs, both visible (e.g. spreads, commissions and swaps) and non-visible (e.g. slippage, rejected trades, requotes and also see the execution speed).
“Traders can automatically and manually verify where the execution price is in relation to the rest of the market, because we are pulling a full set of market data from 100+ brokers for Tradefora Composite Index, which is used as benchmark. This shows the trader where the trade was placed according to five distribution boxplots, those being Awesome, Above Average, Average, Poor and Outlier. Once in those categories, a trade can be further analyzed in great detail to be able to work out what created that result on both pre-trade and post-trade analytics basis and with powerful visual charts” explained Mr. Khizhnyak.
“From the onset we decided to make this product free of charge for traders, because we wanted to first and foremost empower the greater trading community by sharing the TCA tools that until that day would generally be only available to large hedge funds and prop trading houses” he explained.
“However, right after the initial launch we realized that what we have built in-fact perfectly fits the MIFID II best execution model. The vast majority of traders, brokers and regulators do not have access to aggregated feeds from other retail brokerage firms and therefore lack the tools required to store and process the reference execution data. Not only that, most brokers lack knowledge and infrastructure to even store their own market data with full market depth, required for their own in-depth price feed and execution quality analytics. For this reason, it became apparent to us that we can make a pivot to provide such best execution services to brokers as well” said Mr. Khizhnyak.
“When talking about best execution we need to measure it in 2 dimensions, the first being how good the broker’s execution is in relation to its own price feeds, and the second aspect is to look at how good is that execution in relation to the rest of the market” – Pavel Khiznyak, CEO, Tradefora
Stay ahead of the regulatory race
“This is exactly what RTS 27/28 Best Execution Reporting under MiFID II directive is trying to measure” said Mr. Khizhnyak. “This was our first commercial B2B product. The interesting point is that at the moment there is no clear definition of what best execution truly is due to the lack of measurement and benchmarking tools. Therefore, as it states in the regulatory directive brokers must “show best effort” to comply. As RTS 27 and RTS 28 are quarterly and annual reports, which must be publicly published, we took time to analyze on what has been published so far and found out that the overall reporting quality and accuracy leaves much to be desired” said Mr. Khizhnyak.
“A lot of columns in the RTS27 procedure report end up being filled out as NA by brokers, and quite often when generating a report about execution price vs reference price, the two are the same because many reporting officers within brokerages enter their own prices because they don’t access to quality reference pricing data. Some input reference feed from institutional vendors, which is again not correct, because we should not be comparing retail broker pricing to an institutional one. We should be comparing apples to apples” said Mr. Khizhnyak.
“There are a lot of obstacles if you want to make RTS27 properly as a broker” said Mr. Khizhnyak. “The whole thing makes no sense cost wise, as you would have to build infrastructure to collect, aggregate, store this market data, and then make it available for indexing and rendering. Besides, if you are storing data in-house in .csv format without any specialized compression algorithms, over time it will cost you much more than the report preparation itself” he said.
“If for example you carry about 600 instruments and want to store the entire tick-by-tick market depth data on them for the full year in AWS Cloud with real-time access, such IT infrastructure would cost you around 8,000 Euros for the 1st year, and then in the second year the storage cost would increase to around 22,000 Euros. But it doesn’t end there. Without proper compression and big data optimization tools, the data essentially becomes garbage, because it can’t be queried. So when a regulator or a client places an inquiry with the brokers to substantiate an execution at a particular price point for some period in the past, they often fail to provide such data as the vast majority of LPs themselves do not store it past 1 month” – Pavel Khizhnyak, CEO, Tradefora.
“All of this is how we came to realize that we needed to launch TickGuard – a highly optimized tool for market data storage and lookup. Our solution boasts 40x data compression factor while keeping the data hot and easily accessible via our TickGuard UI. In addition, we are able to store up to 25 levels of market depth, while currently regulators are only looking at top 3 levels, giving us more than enough cushion to meet and exceed our customer expectations,” he said. TickGuard is using fully GDPR compliant datacenters of Amazon with triple redundancy, which provides a comforting level of security and peace of mind for brokers” said Mr. Khizhnyak.
In terms of ease of integration into a brokerage’s topography, Mr. Khizhnyak explained that dealers do not like to have to wrestle with cumbersome software as this is not their core business. “We are connected to oneZero and PrimeXM, so it is plug and play if using those, and we are integrated with MT4. We can also integrate via other proprietary bridges when necessary. We plan to integrate with several other major bridge providers in near term and therefore, we are well positioned to serve the vast majority of brokerages” he said.
It could be considered as to what brokerages would think of this, as effectively such software metaphorically ‘lifts the Komono’ on dealing and execution practices.
On this basis, Mr. Khizhnyak said “We are open about how to do things, and our intention is not to present the broker in a bad light. We are here to spot issues with pricing and execution as they occur in real-time and be able to report these in detail to the broker. FeedGuard was developed as a result of brokers asking for help with identifying issues with their price feeds. Brokers often have so many price feeds from multiple providers and carry multiple trading platforms.”
“All brokers monitor their profitability on a per million traded, yet vast majority of brokers fail to explain the details in its fluctuation apart from attributing it to the market volatility or hedging practices. Therefore, very few brokers can actually provide detailed number of how much a bad feed could be costing them on a per million or annualized PL basis. Most spot bad price feed issues only post factum at the end of the day after they have been arbitraged when looking at the PL report” he said.
“As a result of us collecting 100+ price feeds in real time, and using our powerful aggregation engine we can analyze it in real time. We have developed three types of alerts for this, those being latency, stale pricing (if the price on a particular instrument stopped updating), and an alert on outlier trades (if the broker issuing prices that are outside of acceptable market range). On top of that we provide an in-depth analytics of the feed quality itself on the size of the top of the book, market depth, spreads and price feed refresh rates. This is a full set of diagnostics for the brokers to streamline their pricing” he said.
“This touches on one of the uses for our other product for brokers – TradeGuard. TradeGuard is a unique marketing tool, which allows brokers to showcase the true quality of their execution instead of blank statements on how tight their spreads are and high fast their execution is. We help brokers do the initial order book verification anywhere from 5,000 -to 100,000 order samples to identify any possible issues first on a very granular trade by trade basis” explained Mr. Khizhnyak.
“If no issues are found, we can then integrate our widget directly into the broker’s web platform or Member Area, which becomes super transparent to the end-clients, as the clients always hear the same things from brokers and it has been difficult to verify it until now. The time of transparency has come” he said.
FinanceFeeds asked if brokers check their liquidity providers with it, to which Mr. Khizhnyak replied “Yes. We are now integrated with Advanced Markets and working on adding more major LPs, so if a liquidity provider took this solution, they would be compared against other liquidity providers and be able to distinguish how similar services can be compared and their quality checked.”
How is it capitalized?
“Every single trade has to go through the back end, so TradeGuard pricing is based on a number of active clients, which allows us to build a flexible pricing model. This allows us to onboard clients both startup brokers and large well established brokers with tens of millions of transactions per month” he said.
“Among 15 key metrics that we display in the Execution Scorecard, we show positive and negative slippage across different order types, as sometimes traders don’t know how much they get on positive slippage as many set stop losses but not take profits” he explained. “If they could see the positive slippage then perhaps negative slippage wouldn’t be so much of an issue as it is today. A lot of big brokers are taking the right steps by publishing slippage data but still, this is the brokers talking about themselves, so it is not independently verified data and I think slippage should be reported impartially whether negative or positive” he said.
“There is a lot of data that has to be published, except it is not in a very user friendly format. If brokers want to take advantage of that it TickGuard allows it through storing underlying tick-by-tick market data. Recently we had a case in which a retail FX broker came to us and we found 13 outliers in their batch order check. We looked into it, found that the price that they were executing at was a very clear case of stale pricing, which they were unaware of. To remedy this we used FeedGuard to analyze the price, and could see that their price wasn’t updating and was static while the rest of the market was moving, and when the LP was asked to provide ticks, they couldn’t because they only store 1 month historic data” he explained.
“To sum up, in today’s world, everything revolves around best execution. Our product provides solutions for broker sales, marketing, compliance, dealing and IT needs when it comes to best execution.”
“We are now in the process of expanding our data scientists team to enhance our machine learning and neural network data processing, and it is the way forward in many industries. Elon Musk and other visionaries who are modernizing technologically advanced industries are doing this betting on big data usage as their key competitive driving force. With the right approach to working with big data, we hope that our products to some extent will help drive your broker on auto pilot” Mr. Khizhnyak concluded.