I currently work to build systems that generate fixed income analytics and I have no previous experience that relates to algo trading. I see that a lot of algo trading teams are coming up in fixed income space, esp for flow instruments (swaps, bonds, loans, cds contracts). I only know that algo trading for FX is on par with equities in terms of trading frequencies but trading in other FI assets is not primarily driven by low latency strategies, but please correct if I was wrong here. I mentioned it because for now I do not intend to develop low latency stuff as I believe it requires one to be an expert coder apart from a trading strategist. So can someone please point me to any literature that offers introduction/insight into this space. Also can someone mention about the level of Math and programming proficiency that is necessary to start with such algo teams.

If not from people who directly worked in systematic trading for Rates/Credit, can others who are knowledgeable about this area share information about any research/white papers that could be useful for those who wanted to pursue career in it? Thanks.

The well known researcher Robert F. Almgren is active in this area, especially concerning algo trading of fixed income futures (eurodollar and bond futures) but also other F.I. instruments. He has given a number of public presentations, for ex. this one in NY on June 7, 2011:QuoteAlgorithmic Trading for Interest Rate Futures. Interest rate futures markets present several novel microstructural features not found in equities and other futures markets. For effective trade execution, these features must be fully understood and properly exploited. Three features are the most important. First is pro rata order matching, which has strong effects on the optimal order placement strategy. Second is implied quoting via calendar spread and butterfly contracts, which presents opportunities to find hidden liquidity and better order fills. Third is the highly coupled nature of contracts at different points on the yield curve, requiring an inherently multidimensional analysis even to trade a single contract. We shall provide an overview of all these aspects, and the quantitative tools used to model them.

Thanks for the pointers acastaldo, that ppt was useful. Quantitative brokers also has some brief info about their algos on its website. From these 2 min videos it felt like the execution algos are similar to those used for Equities, which could be good when client order flow is passed through these algos. When used for proprietary purposes the bottleneck could be pricing these instruments if not at the order of milliseconds at least in the order of seconds.

The business press has recently noted increased algo trading in the commodity space. Little in the way of details, however, but if you think about it for a moment the commodity space has liquid exchange trading and some and very, very interesting quirks (locational, quality, timing etc. advantages) that are highly amenable to careful analysis.

They are just an exeution broker. Their algorithms are for seeking implied liquidity when clients place a trade. They are by no means a prop shop that might proactively trades for their own money.