FinTech, the wedding between finance and technology, is a hotbed of startups and innovation, especially in London. Now it’s lighting the fires of the investment community in Silicon Valley, so I prevailed on Ajo Fod, who knows the FinTech world well, first as a quant and now as an entrepreneur, to attend the Trading Show and share his observations with you.

I had the pleasure of attending Trading Show West Coast 2015: West Coast’s leading quant, automated trading and big data event last week. This is one of the most legitimate trading shows I’ve seen and truly geared to professionals.

The first thing that caught my eye, was the surprisingly large majority wearing business attire; I was expecting some confusion. Google tried to hold down the fort of casual-at-work and a few people were dressed in jeans, with long-sleeved shirts for good measure.

But finance won over West Coast causal even in San Francisco. My decision to dress in a brown suit and a tie was just the right measure down from full business dress.

I was impressed by the balance between different groups of professionals. Quants / traders / investors / hardware / risk management and students were all well represented.

Different scales of enterprise from startups to micro hedge funds to medium sized funds, such as AXA Rosenberg, to industry titans like BNY Mellon Financial and Blackrock were there, too.

The mix of speakers, from hardware tech providing fast access to markets to macro thoughts from Lex Huberts, was good, especially considering the audience.

Systematic trading and HFT is no longer about the fastest execution. The marginal advantage from trading faster needs to be weighed carefully against the cost of the infrastructure, while the ability to forecast farther into the future is significant.

Apparently, the fastest access to markets is provided by Algo Logic. They sell machines that race the path from tick data reception to placing trades in 1.2micro seconds!

They achieve this by storing the logic in hardware in FPGA (field-programmable gate array). They include trading logic and risk checks on the chip to achieve this kind of reaction time.

The speed is used to grab favorably priced orders before anyone else can. The winners at any speed tend to be the ones with higher algorithmic sophistication. The direction of development in this field tends to be about adding computing power to the FPGA.

The discussion on Co-location vs Cloud Servers focused on the tradeoff between speed and algorithmic sophistication.

Pravil Gupta of Quadeye Trading and Bert Shen from SuperMicro are both suppliers of HFT technology. The difference is that one is about more sophisticated but still very fast trading while the other is at the higher speed end of the spectrum.

Speed is not everything in the HFT world. The incremental speed edge costs significantly. While there will always be fast traders that grab obviously mispriced orders over a short time horizon, others will play the game of taking the not so short-term bet.

The roundtables covered a list of varied topics. As expected the round table audiences in the Bay Area were largely focused on state-of-the-art in Big Data and deep learning.

These technologies could be the future, but I don’t see as much profitable application of these technologies as there is hype.

FinTech startups seem to be numerous in data services for the finance industry. iSentium: works on estimating the sentiment of tweets. Another works on interpreting SEC filings. Strategies are being fed information faster to produce more efficient markets.

The past was a speed race. The future is going to be about more information used in smarter ways.

For example, Alpha Sangha, my startup, combines information from a variety of data-sources using complex models/algorithms that maximize profitability while filtering out noise.

Acronyms come and go, so here are three relatively new ones stay aware of.

BRIC : Brazil Russia India China
MINT : Mexico Indonesia Nigeria Turkey
ESG: refers to the three main areas of concern that have developed as central factors in measuring the sustainability and ethical impact of an investment in a company or business

Ajo Fod is the founder of Alpha Sangha, which helps companies optimize complex forecasting models or algorithms based on large quantities of past data while avoiding the common pitfall of noise. They can further increase profitability by mining for model/algorithm variants that are better fits based on historical data.

Ajo previously worked as a quant at BGI/Blackrock and Mellon. He has masters degrees in both Computer Science (AI) and Operations Research (optimization). He earned a BTech degree from the prestigious IIT-Madras.

This entry was posted on Thursday, March 12th, 2015 at 1:15 am and is filed under Entrepreneurs, Innovation. You can follow any responses to this entry through the RSS 2.0 feed.
Tags: Ajo Fod, big data, deep thinking, fintech
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