“Central bankers will fight the next recession with their backs against the wall. Will the weapons of the last crisis work in the next one?” asked a 2018 article from The Economist. It’s a difficult question to answer. Monetary policy works by increasing borrowing and spending, but for it to be successful, there must be creditworthy borrowers. With corporate debt at near-record highs and banks unwilling to lend during a downturn, investors may shrink their balance sheets rather than expand them when the next market decline comes.
The current low-interest-rate environment has made it easy for companies to meet their debt service coverage requirements, and they can easily roll over debt to increase working capital. But with such high levels of debt needing to be refinanced, just one key default or failure to refinance could spook markets.
With high levels of debt needing to be refinanced, just one key default or failure to refinance could spook markets
If monetary policy fails, will governments turn to fiscal stimulus, even in the face of growing deficits? We have no way of knowing. This creates something of a dilemma for risk managers. To determine what they should do, they must understand how the dynamics of risk management have changed in recent times.
At Kamakura Corporation, we employ risk managers with a broad spectrum of knowledge. We are also keen to make use of the latest technology in order to supply our clients with the most accurate, research-driven advice possible. While this doesn’t mean we know what the future holds, it equips us with a full appreciation of the facts so we can advise our clients of where risks are likely to emerge.
The field of risk management has undergone enormous change in the last 50 years, with the pace of transformation accelerating in the aftermath of the financial crisis. However, many practitioners came into the business after the worst of the credit crisis had passed and may not recall those lessons, especially trading desk staffers and lenders at banks and investment funds.
At Kamakura, we define risk management as the forecasting and management of the relative risks and returns of different strategies, both at the portfolio level (from the perspective of the CEO) and at the transaction level (from the perspective of the trader, portfolio strategist or lending officer). The best-practice definition of risk management has been summarised by Donald R van Deventer, Kenji Imai and Mark Mesler in their book Advanced Financial Risk Management.
They explain: “Risk management is the discipline that clearly shows management the risks and returns of every major strategic decision at both the institutional level and the transaction level. Moreover, the risk management discipline shows how to change strategy in order to bring the risk-return trade-off into line with the best long and short-term interests of the institution’s shareholders (in the case of public firms) or taxpayers (in the case of government-related entities).”
Given today’s economic climate and our position in the credit cycle, companies should consider how well equipped they are to deal with risk
At Kamakura, we believe that risk management is not limited by organisational or political boundaries. It encompasses all the traditional siloes of credit risk, market risk, liquidity risk, capital allocation, performance measurement, transfer pricing and regulatory compliance. It is equally applicable to banks, insurers, pension funds, governmental treasuries and any other entities that experience counterparty risk.
One of the most significant risks the economy faces today is that, after a long period of complacency, a single event could trigger a flash crash, signalling a huge market shift. It is difficult to identify potential trigger events in advance, though many experts take credit for seeing them after the fact. The best defence against the risks posed by uncertainty is sound underwriting and portfolio management. This means using best-practice quantitative tools and working with companies that perform well, have liquidity that is driven by financial performance, and do not have excess leverage or significant refinancing risk.
In exuberant markets, it is easy for speculative businesses to achieve enthusiastic multiples without appearing to have significant refinancing risk. But to ground ourselves in reality, all we need to do is remember the case of WeWork, where even the best and brightest on Wall Street mistook a real estate firm for a technology unicorn. Quantitative analysis helps risk managers arrive at appropriate valuations in cases where emotions heavily influence investors’ thinking. Because it is objective, it avoids introducing the biases and irrational enthusiasm that lead to economic bubbles and crowd mania.
Negative rates pose risks on many fronts. For one thing, studies have shown that they fail to increase lending. In addition, many risk models cannot accurately account for negative rates. But they can have powerful effects, including possibly ending retail bank franchises or destroying the valuation of pension funds, which in many countries are already insufficient to deliver promised benefits. Negative rates encourage investors to stretch for yield, but if they overextend themselves on a massive scale, it could lead to sovereign default risk.
Risk managers often confuse compliance with sound capital management, but they cannot rely on regulators to ‘pull the punchbowl’ at the right moment. Instead, risk managers must be objective and quantitative. They must employ robust predictive tools utilising multi-factor models and Monte Carlo simulations to understand the risks to their portfolios and firms. Given today’s computational power, there is no excuse not to model as many simulations as possible to understand their implications in advance.
The tools for success
In the last year, we have seen a sharp increase in short-term default risks, while cumulative 10-year default expectations remain higher than they were prior to the recession (see Fig 1). Given today’s economic climate and our position in the credit cycle, companies should consider how well equipped they are to deal with risk.
Understanding the factors that drive movement in this relatively risk-free point in the cycle is an important start. The tools companies select will depend on the country. The yield curve for Japanese Government bonds, for example, can be analysed using a 10-factor Heath, Jarrow and Morton model. Kamakura has undertaken equivalent analyses for Australia, Canada, Germany, Singapore, Spain, Sweden, the UK and the US. In modelling interest rates, companies cannot be floored at zero, nor should they compromise by using workarounds for existing models, which can lead to misunderstandings and inaccuracy.
For default risk, the most useful measure is the Jarrow-Turnbill reduced-form model, which offers unrivalled accuracy. Incorporating years of research, it is one of the largest and most accurate default databases in the industry, combining financial, market and macroeconomic factors to generate a full-term structure of defaults.
From a simulation standpoint, businesses need a calculation engine that is fully integrated and allows an unlimited number of risk factors. A fully integrated solution supports business decisions, internal and external reporting, and regulatory reporting for credit risk, market risk, liquidity risk, interest risk, asset and liability management, performance measurement, portfolio risk, transfer pricing and risk-adjusted return on capital. Unlike black-box testing, an integrated solution allows for common assumptions across the firm and provides maximum transparency and flexibility. In the fund management and pension fund business, most portfolio managers are judged by comparing their risk-adjusted return with a predefined benchmark.
Equity markets tend to ignore bankruptcy risk when calculating indices, but the holder of a stock that defaults or is dropped from an index suffers a large loss. Therefore, even if you are not running a credit investment portfolio, you should have best-practice tools to manage credit risk.
Even the most astute risk managers don’t know what the future holds. To provide the guidance our clients need and expect, we must employ best-practice tools to evaluate risks and returns at both the portfolio and transaction level, and understand how to either hedge or avoid them. Using robust simulation models and having the discipline to avoid the large number of biases that traditional measures introduce are essential steps that today’s risk managers must take to succeed.