A huge and growing family tree of “Tiger cubs”, grand cubs and grand grand cubs, who trace their lineage to Tiger Management founder Julian Robertson, share a long-term approach to deep fundamental research. They focus on high growth, misunderstood value and are not afraid to be long-term holders amid short term challenges and volatility.
Triata’s key differentiator from the other Tiger funds is its alternative data DNA. Co-founder and CIO Sean Ho was previously at Tiger grand cub Tybourne, a fund spun out of Tiger cub Lone Pine, where he set up their alternative data team, and his clear vision when he launched Triata – an acronym of “triangulating data” – was for data to be the core DNA in the fundamental research process. “The vision of Triata is to be a disruptor in fundamental investing, taking advantage of the huge and growing volume of alternative data available in China. Data volumes are growing at an exponential rate as more and more data fields are becoming digitalized. We can capture these alternative data and leverage more automation to better understand the fundamentals of our target companies. A large part of our research information set is related to alternative data,” says Ho.
The investment process follows a traditional, deep fundamental approach based on the Tiger philosophy. Beyond the traditional information sources of reviewing public filings, meeting management, making site visits, and interviewing expert networks, Triata’s information set is a lot larger as it uses alternative and big data to corroborate, prove or disprove its investment theses. This especially exploits the huge digital footprint of businesses in China, which has very high penetration of smartphones and e-commerce.
The vision of Triata is to be a disruptor in fundamental investing, taking advantage of the huge and growing volume of alternative data available in China.
Sean Ho, Founder and CIO, Triata Capital
“Beyond common apps engagement and GMV data, we look closely at very targeted data specific to each company and sector and relevant to our investment theses at that point of time,” says Ho. “We think this is a lot more powerful than expert networks for channel checking. For instance, for the jewelry sector we can analyze the competitive landscape of various brands by tracking data such as number of stores by tier cities, social heatness on live streaming platforms, online sales, consumer reviews, etc. In the auto industry, historically you would channel check through 4S auto dealership stores. Now in China’s growing electric vehicle market including local manufacturers such as Nio and Xpeng, as well as Tesla, which are selling direct-to-consumer (D2C), there’s a lot of digital information that can be tracked automatically such as orders for different models, car delivery time, consumer’s sensitivity to price change due to inflation or supply chain issues, etc.,” says Ho.
The Triata process is also partly informed by Ho’s time at Susquehanna, which taught him about probability and game theory. “We use big data to probabilistically test investment theses, not in a binary way. In an imperfect information environment, we maximise our probabilistic expected value like a poker player. We review our right and wrong decisions, and upgrade target prices and conviction levels to the most relevant data, using real time data feedback loops, which could include China policies,” he explains.
Despite the firm’s strong alternative data DNA, Ho explains that, “It is important to make the distinction here that we are not a quant fund looking to collect a massive amount of data to generate buy or sell signals from a black box model. Ultimately, our investment philosophy is based on a deep fundamental mindset with the goal of buying great businesses at reasonable valuations and shorting companies that we believe are overvalued.” This is helped by Ho’s past 14 years of experience in fundamental investing.
Triata has integrated alternative data from day one, in terms of investment process, proprietary data platform and people. The data and analyst teams are highly integrated, use collaboration tools, and both teams’ incentives are tied to their portfolio P&L contribution.
This might be difficult to implement in some other traditional fundamental funds if their founders do not have the right blend of fundamental and quantitative background or if there is a large resistance to change internally. Other managers may struggle to holistically handle data for several reasons: “The data side can sometimes be more of a support function that creates conflict and does not tie in well with P&L generation. It needs to be systematically structured and be an integral part of the investment process. Some firms also do not have the right composition of talent and rely mostly on third party subscriptions. Hence, talent gatekeeping is key for us. For our data engineers, we hire top technology talent with experiences from big tech companies such as Google, Yahoo, Alibaba; our analysts are from top MBA schools with strong buyside experiences and they have quantitative backgrounds to be able to work with large datasets,” says Edmund Ang.
“The outcome of this setup is a fully integrated investment process incorporating deep fundamental research and systematic use of alternative data and a robust risk management framework to ensure our idea generation and capture are repeatable and effective,” says Ho
The importance of synergistic team skills is also seen in the two co-founders. Says Ang: “Sean and I have known each other for a long time now since our student days at Columbia University. We both studied masters in mathematics of finance but developed different career paths and have complementary skillsets. My previous experiences included risk management as a derivatives trader at a buyside firm and setting up a new office and executing the turnaround strategy for another financial firm. Sean came to me with a very clear vision of wanting to build a fundamental hedge fund with alternative data as its core DNA and he wanted me to help build the business, culture, people and processes while he focuses all his effort on the investment side of the business”. “Edmund has a strong international and financial background and real-world experiences in building an organization that is well suited for the COO role,” says Ho.
The team will challenge each other, and they should not take it personally. We offer a safe environment to express true and different thinking.
Edmund Ang, Founder and COO, Triata Capital
“We lifted an entire FinTech start up team of four people and relocated them to Shenzhen, China’s Silicon Valley, because we think that their skillsets are a perfect match for Triata’s vision,” says Ho. The China office, where the analyst and data teams are based, provides on the ground research though the firm is regulated in Hong Kong and has offshore investors.
Team hires boast a variety of tech talents and analysts with in-depth sector experiences. “The objective is to hire people with a diverse range of expertise, including big data, AI, machine learning and natural language processing (NLP). New hires need to be complementary and additive to the existing team skillsets,” says Ho. Triata reviewed about 200 CVs for each role and typically interviewed 10-20 people. “The process involved multiple interviews with many team members, with some research/programming projects, monitoring reactions to challenges in case studies, and testing spontaneous responses to market conditions. Personalities and cultural fit were analysed informally by asking questions from multiple angles,” says Ang.
There is also diversity in the team: “We welcome top talents with different background and experiences, and harness diverse thinking through our collaborative, transparent culture,” says Ang.
Triata’s corporate culture champions transparency, meritocracy and collaboration. Staff are incentivized through performance-driven upside participation. “We have a very flat structure, and we believe in decentralized thinking and idea generation,” says Ho. Recruits need to be comfortable with something called ‘constructive conflict’. “The team will challenge each other, and they should not take it personally. They should be creative and open to critical feedback. We offer a safe environment to express true and different thinking. Our hires appreciate having more transparency and influence than they had at their previous firms,” says Ang.
TriataAlpha is the firm’s in-house proprietary AI platform developed internally to supercharge research workflows and link alternative data with fundamental intelligence. The platform includes the latest news and public opinions on regulatory policy and ESG etc. combined with sentiment analysis to help flag information that could affect the fundamentals of target companies. It also has in-depth internal notes on earnings beats or misses as well as consensus and proprietary forecasts on key business drivers. Alternative data tracking categories include apps engagement, e-commerce sales, offline stores, advertising, gaming, jobs and video streaming, etc. which supports related fundamental investment theses.
Triata practices agile software development commonly applied in tech companies and some of its latest initiatives include speaker recognition and tone analysis to analyze earnings calls, management quality scoring and policy tracking. Multilingual speech understanding and text classification are used, based on state-of-the-art speech and NLP technology.
“We use AI expertise to help identify fraud risk factors, but we still need a human to analyse it. Long run, AI is becoming better trained and better at identifying information. The TriataAlpha platform acts like a GPS for our analysts, helping them to extract and focus on the right information. Triata is a data-driven, tech savvy hedge fund with a substantially automated big data process. Our technology is designed to save time, uncover new insights and boost transparency,” says Ho.
Prior to launching Triata, Ho spent 19 months running friends and family money in a strategy with similar risk parameters, but with more position concentration, which annualized at 70% CAGR. Triata’s target return on capital is not that aggressive but is still very high at 25% CAGR for both long and short books, including a mix of beta and alpha, though Ho expects that alpha should drive the majority of returns. The strategy invests throughout Greater China equities and Ho sees a lot of alpha potential in China ‘A’ shares on the long and short sides. “The market is more uncorrelated and driven by retail investors, which make up 80% of flows and can cause deviations from fair value beyond fundamentals,” says Ho.
Triata China Equity Master Fund has generated an estimated June 2022 YTD performance of +19.6% and outperformed MSCI China Index (YTD -11.3%) by +30.9% over the same period. Since launch, the fund has generated an Upside/Downside Capture ratio of 3.7x. During the up months of MSCI China, the fund has produced an Upside Capture ratio of 2.2x. More importantly, during the down-months of MSCI China, the fund has produced a Downside Capture ratio of 0.6x.
Triata’s proprietary database can process large amounts of data continuously generating real-time insights. Triata’s strength is in identifying investment opportunities driven by themes related to Greater China. For instance, Triata has been tracking closely the evolution of the e-commerce sector in China ranging from 3P model to 1P model, social elements, live streaming, increased penetration in tier 3 and 4 cities, community buying and online grocery and identifying winners and losers as new business models continue to develop. The average holding period on longs is two to three years, based on extensive due diligence. The edge comes from aggregating and interpreting data, and the goal is long-term investment performance. The strategy can invest across all cap sizes but is mainly focused on large to mega cap stocks; exclusions cover ESG negative screening. Triata has high conviction and can size longs up to 15% at market.
In May 2022, Ho is constructive on Chinese equities, given the backdrop of economic growth, low absolute and relative valuations, thematic sector growth stories and stimulative monetary policy. Yet his strategy also profited during the market setback in January 2022 (+8.4%) and April 2022 (+5.0%), where short positions made a strong contribution.
Triata only shorts single stocks from a bottom-up perspective and prefer not to use sector or factor baskets or indices. The potential universe of short names is growing thanks to financial deregulation. Shorts are motivated by the 3Fs, “fade, fad and fraud”, and they are more tactical and diversified to weather potential short squeezes. The average holding period on shorts is three to twelve months with a focus on near term catalysts. Triata has developed statistical indicators that help to identify potential fraud based on inputs including financial statements, etc. This AI algorithm picked up a celebrated case involving a retailer of hot beverages and several China A shares companies.
“The strategy was run with friends and family money at first because it took time to assemble the right talent and develop our in-house proprietary alternative data platform (TriataAlpha). Over time, investors will see that our alpha generation is very different from that of other fundamental funds, and our return profile is already uncorrelated. In the near term, Triata is very focused on delivering alpha through its flagship equity long/short fund. Our deep fundamental plus alternative data DNA process and the culture of the firm is our core edge that will continue to compound, and we have a long-term vision,” says Ho.