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WorldQuant University professor launches systematic hedge fund with “all-weather” trading approach

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Los Angeles-based TrueRisk Capital is a newly-established fully-systematic CTA manager which trades a range of algorithm-based options and futures strategies developed by co-founder and chief quant Rito Bhattacharyya over the course of almost nine years.

Los Angeles-based TrueRisk Capital is a newly-established fully-systematic CTA manager which trades a range of algorithm-based options and futures strategies developed by co-founder and chief quant Rito Bhattacharyya over the course of almost nine years.

Having launched a separately managed account managing internal money in July, the firm is preparing to roll out its first strategy, the TrueRisk Market Volatility Fund, later this month.

TrueRisk represents the start of founder Bhattacharyya’s own direct management of client assets and application of his models, having earlier worked as a consultant for several hedge funds, either as a chief quant or head of quantitative research, as well as licensing models to more than a dozen asset managers globally.

In 2015, Bhattacharyya set up TrueRisk Labs, a data and machine learning signals vendor for investment managers. He is also a faculty member of WorldQuant University, the financial engineering educational programme established by former Millennium Management statistical arbitrage portfolio manager Igor Tulchinsky.

TrueRisk was launched in May with USD4 million of internal capital, around USD1 million of which is already up and running in a separately managed account that began trading in July.

Now, the firm is preparing to launch its main strategy, the TrueRisk Market Volatility Fund, later this month, with an initial USD2.5 million in assets. The volatility income strategy focuses predominantly on equities markets, though the model can also adapt to broader institutional investor interest through a fixed income version.

Meanwhile, the remaining USD500,000 of assets will be used to launch a separate managed account for a systematic US equity long/short strategy, to be rolled out before the end of the year. That strategy will focus on US publicly traded equities with a market cap of USD1 billion or more, using machine-learning algorithms that take company information and market sentiment information, social signals.

All-weather approach

The firm’s main TrueRisk Market Volatility Fund is built around three algorithm systems, and offers what CEO, CIO and co-founder Kaushik Saha describes as an “all-weather return stream” that trades across “more scenarios more robustly” than typical managed futures strategies.

Saha, who has more than 25 years’ investment experience, met Bhattacharyya at Hercules Investments, where he had led the design, implementation and positioning of the firm’s liquid alternatives strategies.

Having started his career in 1997 within Freddie Mac’s portfolio group, building stochastic valuation models for the internal pricing valuation of mortgage purchases, Saha later held quant management roles at Barclays Global Investors, NewFleet Asset Management, and Black King Capital, where he had been co-founder and CIO.

“What’s unique about this strategy is that it is made up of three separate algo systems,” Saha tells Hedgeweek.

Dubbed ‘Differential Evolution Optimisation’, the complex three-system algorithm combines to configure the option strikes and entry and exit parameters for the investment portfolio.

“Our strategies are quantitative, systematic, fully-automated, including trade strategy generation, allocation, risk management, even trade execution – we have both manual and automated options to implement trade executions,” he explains.

If there is a sharp move in the index, coupled with a spike or rise in volatility, system three will kick in and help counterbalance systems one and two.

A viable alternative

Saha and TrueRisk’s chief operation officer Vishal Olson also discuss on some of the challenges and opportunities of launching a new strategy in the midst of the coronavirus pandemic, and reflect on the evolving investor sentiment towards quantitative funds.

Olson recalls how many fully-systematic so-called “black box” strategies had traditionally been frowned upon by institutional investors some 15 years back. But that cautious stance has shifted in recent years as managed futures strategies gathered momentum, he observes.

“Over the last decade, it has become obvious that the strategies that are more quantitative, or 100 per cent quantitative, and which remove the human element, or the discretionary element, from decision-making are much more viable than discretionary volatility strategies, especially during crisis moments or fat-tail events,” Olson tells Hedgeweek.

Prior to TrueRisk, Olson – who has some 15 years’ market experience – co-founded Holson Alternatives, a third-party marketer aimed at servicing, institutional investors and funds of funds, having earlier held a number of consultancy roles performing due diligence on CTAs, hedge funds, and funds of funds.

Red flags

He notes that certain discretionary short volatility strategies were rocked by the VIX “explosion” in February 2018, as well as the March 2020 market maelstrom at the outset of the Covid crisis, which saw US equities tumble some 35 per cent in a far shorter timeframe than ever before, later rebounding at equally-rapid speed.

“The strategies that have tended to survive and make it through those fat-tail risk events were either a hundred per cent quantitative or mostly quantitative,” Olson adds, while Saha suggests, that in his view, trend-following or equity volatility-based strategies with discretionary elements herald “all sorts of red flags”. 

Noting how automated trading has made markets move faster than ever before, with assets and sectors snapping increasingly-closer to the edge, Saha draws an analogy between sharp pencils and broad brushes when discussing the relative merits of systematic versus discretionary investing. 

“If you’re using a sharp pencil, you’re recomputing minute-by-minute, second-by-second, and arriving at precise numbers to make decisions on. But once you introduce a discretionary element, you’re talking more in terms of views and opinions, and you’re using a broad brush, instead of the sharp pencil,” he explains.

“Once that happens, you’re missing, say, two of the four decisions that you could have taken, because you’re happy with the two you have made, and you decide to forego the other two. Or two haven’t gone in your favour, and so the loss from those two trades is influencing your view on the next two trades and so you step away.”

The model is run at a leverage ratio that institutions are comfortable with, Saha says, adding that such institutionally-guided leverage allows the strategy to target returns averaging in the low-20s. The separately managed account – which has been in operation for just over a month – is already generating positive returns, largely due to volatility remaining range-bound, he adds.

“Some managers may often try and use up as much margin available to pump their returns while the going is good. Our systems are well-designed to extract the max out of these options,” he continues.

“Rising markets are a like a rubber band which can snap back, so similarly, when volatility gets too low, one has to be mindful that sudden shocks can cause volatility spikes that are higher since they are starting from a lower level.

“We haven’t seen that in any appreciable way. We have our three systems, with the third system that will counterbalance those potential vol spikes, so we can breathe a bit easier. It’s been so far, so good.”

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