The era of 'active management' has arrived for bond investments. How can institutions gain the upper hand?

Through the Tianhong Five-Cycle Model, Tianhong's fixed income team has achieved deep integration of subjective and quantitative approaches, making bond investment more transparent rather than a black box.

Against the backdrop of cooling active equity investments and the rise of passive index investments, few have noticed that the long-bull bond market has entered an era of "active" investment where management capabilities are key.

For a long time, China's bond market had almost no credit risk or defaults. For bond fund managers, maintaining liquidity risk meant bond funds could remain relatively stable in both bull and bear markets, becoming a reliable profit tool.

However, in recent years, with frequent credit risks, narrowing credit spreads, and persistently low interest rates, uncovering bond yields has become more challenging. The business model of bond funds has also undergone significant changes: from early years when banks and other outsourced institutions had no clear preference for fund managers, to later when institutions began exploring fund managers with active management capabilities, and now clients prioritize fund managers' ability to generate capital gains and absolute returns.

As major investors in public bond funds, banks now place much higher demands on bond fund managers' active management capabilities, especially in timing trades. Take government bonds as an example: in a low-interest-rate environment, even 10-year government bonds yield only about 2.3%, very close to banks' FTP rates.

Currently, large banks' FTP rates hover around 2.1% to 2.2%, while most small and medium-sized banks' FTP rates range from 2.4% to 2.5%. This means most small and medium-sized banks already face an inverted yield curve between liabilities and assets. Without timing trades, these banks would struggle to meet profit targets by continuing to allocate such assets.

In fact, we can observe that in the current low-interest-rate environment, the volatility of government bonds is increasing as institutional investors also seek to boost returns through timing trades. Public bond fund managers now face a more competitive landscape.

Moreover, for individual investors, as real estate undergoes a mid-term adjustment, massive amounts of capital seeking stable wealth management are flowing into bond funds.

It's fair to say that amid an asset shortage, both institutional and individual investors are demanding higher returns from fund managers.

Where do higher absolute returns come from? Peng Wei, head of Tianhong Fund's interest rate and commercial bond management team, provided the answer: by studying market participants' expectations and pricing of the bond market, calculating the market's odds, and then adopting appropriate strategies in portfolio management based on win rates to generate capital gains.

This answer may seem like an idealized vision of bond market timing trades, but it is backed by Tianhong's systematic Five-Cycle bond investment framework and team-based execution. Formulating this answer was no overnight feat—this scientific investment research system was refined by Tianhong's fixed income team over three years in 2020 and has since been continuously improved through four more years of practice.

Can this give Tianhong a head start in the "active" era of bond investing?

01 Opening the Bond Market Black Box: Timing for Returns

With credit spreads narrowing, avoiding extreme risks by not diving into lower credit quality is particularly important, aligning with Tianhong's long-held conservative style. But where do excess returns come from? The answer lies in timing bond trades.

In stock investing, the difficulty increases from stock picking to sector selection and then to timing. Timing requires a comprehensive grasp of market information and precise identification of key market contradictions—sustained high-win-rate timing is no easy feat, given the market's unpredictability.

Tianhong's fixed income team didn't initially adopt timing trades to boost returns. They were simply trying to explain puzzling bond market phenomena: after 2016, bond market performance repeatedly diverged from economic fundamentals. For instance, in 2016, the economy stabilized, yet the bond bull market lasted three quarters. In 2018, a similar scenario unfolded—the economy was still declining, but bonds entered a bear market.

Facing these unresolved puzzles, Tianhong's fixed income team embarked on an exploratory journey in 2018 to make bond investing more scientific and traceable.

Initially, the team tried identifying patterns through indicators, even compiling high-frequency macroeconomic data, but none stood up to scrutiny.

Eventually, the team found a pattern by analyzing institutional behavior: bond market participants can be divided into trading desks and allocation desks, with trading desks further split into trend traders and high-frequency traders, and allocation desks into value allocators and residual liquidity allocators. These four investor types can be tracked through representative samples.

Zhao Dinglong, head of Tianhong's short-term bond management team and fund manager, gave an example: at market bottoms, value allocators typically enter first, followed by trend traders, and then residual liquidity allocators.

While studying institutional behavior, Tianhong's team found that institutions are primarily influenced by policies, which in turn are shaped by macroeconomic conditions. This led to the construction of the top three cycles in Tianhong's Five-Cycle model: macro, monetary policy, and behavioral cycles.

To stay more closely attuned to the market, the team further developed a positioning cycle to track the holdings of major bond market players like insurers, banks, and funds across different bond types, and a sentiment cycle to gauge market trading conditions.

Source: Tianhong Fund

After over two years of exploration and validation, Tianhong's fixed income team finally completed the Five-Cycle model in 2020, clarifying its internal relationships. This bond investment model merges the macro and trading schools of traditional bond investing, enabling more comprehensive scientific observation of the bond market and better solutions to timing challenges.

02 Tianhong Five-Cycle: From Theory to Practice

The Five-Cycle model can explain many bond market phenomena, decipher the market's odd moves, and debunk misleading common beliefs. For example, most believe credit spreads are mainly tied to DR007 or funding rates, dictated by the central bank—but sometimes that's not the case.

In reality, the recent compression of credit spreads stems from households shifting wealth into stable assets amid real estate's mid-term adjustment.

Theoretical explanations are one thing; the Five-Cycle model's true value lies in real-world testing. For instance, during the "sudden" bond market correction in Q4 2022, most fixed income products suffered sharp drawdowns, but Tianhong emerged largely unscathed.

Rewind to October 2022: in a Tianhong meeting room, the fixed income and sales teams sat together, tension in the air.

At the time, short-term bond funds were market darlings, but Tianhong's fixed income products ranked modestly in year-to-date performance.

Internally, this topic had been debated for rounds. Tianhong's fixed income team firmly believed short-term bonds carried significant risks and refused to chase returns at investors' expense.

Tianhong's analysis suggested that while macro conditions were favorable, monetary policy was constrained by exchange rates—a risk the market overlooked.

Behaviorally, as Ren Ming, head of Tianhong's credit research and deputy head of cash management, noted, the 2022 bond bull market had lured low-risk investors from money market funds into bank wealth products. However, these inflows were fragile short-term liabilities, while banks were extending asset durations—a mismatch.

Tianhong's experience showed redemptions correlate with asset performance. When bank products underperform money funds, inflows stall; after consecutive days of losses, redemptions snowball, amplifying market corrections. At the time, crowded positioning in bank and institutional portfolios heightened this feedback risk.

Thus, from August to October, Tianhong steadily reduced exposure, dodging the subsequent bond market turmoil and emerging as one of the few major fund houses with positive average returns.

iFinD data shows that in H2 2022, the average short-term bond fund returned 0.72% with a 0.61% max drawdown; Tianhong's averaged 1.02% with a 0.17% drawdown. The average medium/long-term bond fund returned 0.75% (1.26% drawdown); Tianhong's averaged 0.94% (1.04% drawdown).

If preemptively cutting positions before Q4 2022 showcased the Five-Cycle model's "risk avoidance," building positions ahead of insurers' 30-year bond binge in early 2023 demonstrated its "opportunity capture."

Peng Wei noted they positioned early in 30-year bonds before the market recognized their value—and held on during the subsequent rally, despite macro/policy puzzlement over the surge.

To Tianhong, 30-year bonds' rise reflected their rare dual appeal as tradeable and allocatable assets amid an asset shortage, driven by insurer and rural bank demand—not zero-rate narratives.

Many structural and spread puzzles invisible from a macro lens can be explained through institutional behavior—the Five-Cycle model's edge over traditional yield frameworks lies in combining institutional/retail behavior with macro/policy analysis for multi-cycle validation.

03 New Paradigm: Teamwork & Quant Augmentation

To keep the Five-Cycle model ahead of the curve, Tianhong mandates hands-on research by all managers—a stark contrast to peers.

At Tianhong, every manager is also a researcher, specializing in their domain to stay at the knowledge frontier. Weekly deep-dive sessions share insights, elevating the team's collective expertise beyond individual niches.

Managers then tailor strategies by product mandate and liability risk appetite, using macro/policy/behavior cycles to set portfolio baselines and trading for alpha.

Beyond teamwork, Tianhong's quant-aided decision-making adds further edge.

In 2022, pandemic shocks tested all investors. Yin Liyu, head of credit bond management, tracked urban traffic congestion—a proxy for economic recovery—compiling GDP-weighted data from 99 cities. Spotting a June uptick, he unwound long bond positions, anticipating peak disruption.

To parse bond market noise, Tianhong managers code analytical models, filtering redundancies and emotional biases.

Previously Excel-reliant, Tianhong fully transitioned to Python in late 2019 to handle Five-Cycle modeling's data demands.

Internally, all Python code is open-source, revealing each manager's logic for rapid team learning and iterative improvement—continuously evolving the Five-Cycle model.

In bond investing's "active" era, Tianhong has fused subjective and quant approaches, transitioning from solo acts to orchestrated teamwork—and bringing transparency to bond markets.

Risk Disclosure: Views are for reference only and do not constitute investment advice. The market carries risks; invest with caution.

Past fund performance does not predict future results. Other funds managed by the same manager do not guarantee this fund's performance. Investors should carefully review prospectuses and contracts, assess risk tolerance based on objectives, horizon, and experience, and make informed decisions. Funds investing overseas bear additional risks like currency and foreign market volatility.

Short/medium-long-term bond fund statistics cover iFinD-classified pure bond funds (excluding those unlaunched or lacking 2022 data).

Tianhong's short-term bond funds include Tianhong Hongze Short-Term Bond (A/C), Tianhong Zengli Short-Term Bond (A/C), Tianhong Anli Short-Term Bond (A/C), Tianhong Anyi 30-Day Rolling, Tianhong Anyue 90-Day Rolling Short-Term Bond, and Tianhong Youli Short-Term Bond (A/C). Medium/long-term funds include Tianhong Xinli Bond (A/C), Tianhong Youxuan Bond, Tianhong Zunxiang, Tianhong Yuexiang Fixed-Term Bond, Tianhong Anyi (A/C), Tianhong Huaxiang 3-Month Fixed-Term, Tianhong Xinyi (A/C), Tianhong Xinli 3-Year Fixed-Term, Tianhong Jijixing 3-Month Fixed-Term (A/C), Tianhong Hengxiang 1-Year Fixed-Term, Tianhong Chunxiang 1-Year Fixed-Term, Tianhong Xingxiang 1-Year Fixed-Term, Tianhong Xinyi 39-Month Fixed-Term Bond, Tianhong Heyi Bond (A/C/D), Tianhong Ruixuan Rate Bond (A/C), Tianhong Qixiang Bond (A/C), and Tianhong Fengyi Bond (A/C).

Average returns and max drawdowns are arithmetic-weighted for July 1–December 31, 2022, per fund reports.