Summarise and explain the following transcript like I am a high school student: Interviewer: What is your Asset management's process for managed futures trend replication? Asset Manager: Well, the good news is we didn't have to reinvent the wheel there's some really good academic precedent for replication going all the way back to F and French with the returns-based style analysis there's a really great paper by aqr called Buffett's Alpha where they illustrate how you can replicate the outperformance of Warren Buffett relative to the US cap weed Equity indices by allocating to a combination of equities with certain types of characteristics quality for example and then adding some inexpensive leverage on top so we just stood on the shoulders of giants there and attempted to track the uh the sock gen Trend index using both a top down approach which is analogous to that return-based style analysis and a bottomup approach which is more analogous to the method that aqr used in their buffets Alpha paper so just starting with the top down approach the idea was can we assemble a portfolio of assets that are likely to be held or to be a representative sample of the markets that are held within the funds that are included in the sock gen Trend index and assemble that portfolio at each point in time so that that portfolio would have best tracked the actual return trajectory of the index over say the past 10 20 30 40 days and in fact we can do that and the advantage to replicating The Benchmark in this way is that we're able to take advantage of any potential changes or innovation in the underlying process that the managers within the index are changing over time as they're innovating and making impr improvements to their own strategies the downside is that because we need to look back 20 to 40 days to be able to model a portfolio that best tracks the returns of the Benchmark sometimes when the underlying funds are trading rapidly in or out of positions there's a lag in the underlying ability to track that portfolio and there's also extra noise for statistical reasons in trying to track that portfolio through time again the pros are that were able to actually x-ray into the underlying portfolios of the fund managers and try and see what they're actually holding from day to day and week to week the drawback is that there's sometimes a lag on the flip side another way to think about replicating is a bottomup approach which is more analogous to the method that aqr used in their buffets Alpha paper and and it also is a nice segue into the other way of thinking about it which is what if we sort of understood Buffett's process we know that Buffett likes to buy companies with um strong balance sheets and strong strategic Moes right High margins that have been high for a long time and where the company is not really directly under threat because they have for example a strong brand or strong intellectual property rights that make them sort of a a fortress they can't be easily overcome by competition well in the same way managed Futures there's a huge amount of literature many books have been published on this strategy because it has been so successful so for so many decades and so there's actually a decent General understanding of the processes that that most Trend following managed Futures managers use in their funds in order to decide whether to belong a market Market short a market or flat a market right so we can actually apply these relatively well-known processes to all of the different individual markets that form a representative Universe of what these funds might trade and then use a a regression analysis or some sort of model to determine what specific processes the funds in the sock gen Trend index are using in order to decide from dayto day whether they want to be long short or flat the individual markets right so it turns out that the Benchmark is very readily modelable by a fairly parsimonious Suite of um relatively simple methods of identifying Trends and that when you impl lement the weights to each of those methods that are suggested by the modeling process what comes out is a return profile that tracks the trend index very closely the benefit of this is that first of all the turnover is a lot more close to what you might um experience within the underlying man Futures funds especially after accounting for the fact that each of the individual funds employe their own unique process but when you blend all of the funds together into the index if you were to able to look through those funds own all of the individual positions within those funds because some funds might be buying while other funds are selling you actually get some trade netting so there's actually more stability in the Holdings of the replication strategy uh than we would expect there to be within each of the individual funds that are the constituents of the index so you have lower turnover which means lower transaction costs and you're also able to respond more quickly in the way that the actual underlying funds would to Major overnight or very short-term shifts in Trend profiles across the different markets that are traded in a way that you can't do using the the top down approach because of the lag that we've already mentioned so the great thing is that each of these different approaches the top down and the bottom up has advantages and disadvantages but they complement one another one of them's disadvantage is the other's advantage and vice versa and they're not perfectly correlated and when you put them together in a portfolio they both track The Benchmark relatively closely surprisingly closely actually and deliver performance that you might expect to get from a combination of all the underlying funds if you didn't have to also pay the 2 and 20 fees that typically a company anal application to manage Futures managers so there's an opportunity to ACR some fee Alpha by just not having to pay those steeper fees in aggregate the managed Futures industry Can Only Hold markets in proportion to the total open interest of each of the different Futures markets in other words the total liquidity or number of contracts that are open in aggregate across each of the different markets right it turns out that call it 80 to 90% of the total open interest within Futures markets is captured by between 25 and 30 of the major Futures markets right we're talking about the major Equity indices the S&P futures the the Dax Futures the footsie Futures in the UK that sort of thing some of the major Bond benchmarks like obviously the treasury complex the bond the the guilts in the UK that sort of thing and then a smattering of different energy markets which tend to be very highly liquid and have a lot of open interest and some other for example some of the metals that sort of thing and if you allocate to um a representative basket of kind of 25 to 30 of these markets you actually cover the vast majority of the major directions of risk that are taken with in the um underlying manag fatures funds right and the other benefit of allocating to this representative Universe of very highly liquid markets is that the the product can scale to hundreds of millions and billions of dollars in allocation without expecting a major increase in Market impact or slippage or transaction costs uh or potentially running into regulatory limits that um you might otherwise run into if you trade less liquid markets where the cftc says we don't want any single manager controlling Beyond a certain fraction of the total amount of contracts outstanding because they can monopolize that market and Corner that market and and there there may be some other adverse effects there so it was really striking a balance between spanning all of the relevant major bets or directions of risk or markets that the underlying ctas are probably Trading but doing so with a maximum amount of liquidity yeah it's a great case study recall that coming into the week of March 67 Jerome Powell was testifying before Congress about the reasons for their current policy stance and trying to provide some guidance on the potential policy trajectory for interest rates and quantitative tightening and when he spoke he reinforced a message that he has been very consistent about over the last 12 to 15 months and that is inflation has been higher than expected it has sustained a higher rate for longer than both the FED expected and the market expected the fed reconfirmed their commitment to bring inflation down to their target of 2% and stated that they're willing to move to a higher terminal interest rate and keep rates higher for longer if necessary in order to achieve that Target now keep in mind that they have been communicating this exact message for 12 to 15 months and the markets have for the most part especially the bond and rates markets have been taking very seriously so there had been a very strong and persistent negative Trend in rate Futures a strong and negative Trend in bond Futures there was also very strong negative carry and there were other reasons why CTA managers might want to be short very aggressively about the bonds and the rate complex and that had been a very profitable trade being short bonds and short rates were two of the largest contributors to Trend CT performance in 2022 and they'd also been a positive contributor to ca performance in 2023 on March 9th and 10th obviously there was rumors of a major Bank Run I think it was the 18th largest bank in the US which prompted the market to anticipate a major um run into other cash instruments and also anticipate a shift in the feds fed's reaction function that might result in them pivoting to more a more dobish orientation to cut interest rates in subsequent needings in the very near future and the market went from pricing in an increased likelihood of a higher rate trajectory to pretty well overnight pricing in a major shift lower in the rate trajectory and what that did is it caused a major rally in bonds and an even more substantial rally in rate instruments that resulted in in some cases a 10 or 12 standard deviation move in especially some of the the major rates what was interesting to to observe was how the different Trend replication methods responded to this major shift and Trend in rates and bonds the top- down approach for reasons that we've already discussed requires us to look back at the implied positions of the trend following managed Futures managers over the past 20 to 40 days this is the kind of move that happened almost overnight right in a span of 2 or 3 days so it took the top down method many days in order to lower its short allocation to rates in bonds at the same time the bottom up out methodology because it understands the underlying mechanics of the process that the managers are using in order to decide whether they want to be long or short every single day actually manage to flip to a very neutral position I in rates and bonds and so it was very neat to see how those different methodologies adapted so we're using about 70% of the bottom up and 30% of the top down and it really just came down to the relative advantages of the two different approaches and how well the bottom up actually replicates the SG Trend index and how stable the understanding of the of the underlying Machinery within the SG Trend index has been in its operation over time there there just doesn't seem to be much change in aggregate in the mechanical signals that the trend managers are using to inform portfolios so it made sense from a turnover standpoint on a return relative to transaction costs on a replication standpoint but the 30% allocation to the top down acknowledges that there are ongoing Innovations within the manage Futures space it's a lot of really smart creative resourced people working at these firms who are constantly trying to improve their competitive positioning and and deliver better performance and so the top down is an acknowledgement of that and and an attempt at carry through into what they hold which obviously is going to be a reflection of all of the different innovation that they've introduced over time so we thought that was the right balance.