Arnav Sheth

Risk-Taking, Financial Distress and Innovation

We use our numerical technique to explore the optimality of risk-taking under financial distress. In our model, cash reserves are represented by a Brownian processes that includes an innovation parameter. When this innovation parameter goes to zero, our results show that risk-taking is optimal only when distress costs are extremely high. Thus, non-innovators need a hefty penalty to optimally take risks under financial distress. As the level of innovation increases however, it becomes optimal for innovators to undertake risky investments under financial distress without hefty penalties. The implications of our analysis might partially explain the financial crisis of 2007-2009.

Fama-French Factors and Business Cycles

We examine the behavior of Fama-French factors across business cycles measured in various ways. We first split up the business cycles into four stages and examine the cumulative returns of factors in each of those stages. We then look at the behavior of the factors after a yield curve inversion starts and ends, as the relationship between yield curve inversions and recessions has been well-explored. We finally run a logistic regression to test the predictive power of the term spread on the NBER recession indicator. Our results show that there is an effect on the factors of each of our four stages, and there is limited predictive power from the recession probabilities. We believe this is of practical importance to portfolio managers who are factor-oriented in their approach.

Power-Log Optimization and Positively Skewed Option Returns Reduce Risk and Raise Portfolio Performance

The current low-interest-rate, low-volatility environment demands a more innovative approach to investment management than the allocation to stocks and bonds that is practiced widely today. Options, with their significantly positively skewed returns, offer us the opportunity of boosting returns while controlling downside risk. Power-log optimization gives us the means to incorporate options into the asset allocation process effectively and requires only one input parameter, the downside power, to specify investor preferences. Using data for the last 20 years for a Treasury security, the S&P 500 Index, and a call option on the index, the authors find that optimal power-log portfolios reduce downside risk and the standard deviation of return for both conservative and risky portfolios, which results in positively skewed returns for the portfolios. The authors also deliver higher geometric average returns for riskier portfolios than matched mean–variance-efficient portfolios. In addition, they provide much better downside protection against unanticipated market shocks, such as the down markets in 2002 and 2008, and as a result deliver better performance for both conservative and risky portfolios in bad markets.

The Carrot: Executive Compensation, Risk-Taking and Innovation

Managers of firms with excess cash tend to misuse it. We extend the Radner-Shepp- Shiryaev framework, to create an incentive mechanism (the ‘carrot’) to motivate managers to pay out the cash instead. The problem cannot be solved in closed- form, and we devise a numerical technique to solve it. We find two main counter intuitive results: First, our mechanism results in higher firm value, and the greatest value goes to firms that are mid-level in their innovation. Second, we find that our mechanism increases risk-taking and interestingly, this is optimal to firm value maximization.