Working Papers

Jaap W.B. Bos, Christopher F. Parmeter, Paulo Rodrigues, (2021) "Fixing or Funding: How Private Equity Firms Choose Their LBO Targets"

Abstract: We investigate whether private equity (PE) firms' claim that their main goal is to create value by increasing the operational performance of their targets is reflected in their choice of targets. To do so, we predict the acquisitions of public companies through leveraged buyouts using both financial and operational engineering variables. We find that the former is by far the most important in explaining PEs' decision to acquire, with the largest impact coming from the marginal effective tax rate: an increase of 1% increases the takeover probability by 1.7%, which is a large effect given the unconditional takeover probability of becoming a target of 1.02\%. Only in the case of what we refer to as a coin-flip decision, do we find evidence that operational engineering becomes the most important predictor of a leveraged buyout.

Piet Eichholtz, Rogier Holtermans, Paulo Rodrigues, (2021) " Intermediaries and the Pricing of Indivisible Assets"

Abstract: Intermediaries in financial markets are ubiquitous, but their role has hardly been studied in the markets for alternative assets. We study the pricing of commercial real estate transactions and the role of brokers therein. We analyze 104,998 transactions of U.S. office buildings and employ a hedonic model to generate predicted prices for each transaction. We investigate how the presence of sell-side brokers affects over- and underpricing relative to these predictions for different types of clients, and we study the pricing process from the initial asking price to the final transaction price.
We find no association with broker presence and higher sales prices, even in cases when the seller and the broker are from the same parent company. When we compare broker-added value for experienced and inexperienced clients, we find that brokers add significantly more value for the former, especially when they face competition.
For a subset of the transaction sample, we observe that broker presence is associated with more underpricing in the asking price compared to deals without one. The subsequent price revision during the negotiation and sale process does not fully compensate for this. When a broker represents a seller from his own firm, we find stronger underpricing in the ask, but a price revision that is so large that the final deal price is above the predicted price.  This markedly contradicts the findings from the IPO literature, where more initial underpricing is found to coincide with higher underpricing in the final listing price.

Paulo Rodrigues, Peter Schotman, Hugo Schyns (2024) "Conditional Betas: A Non-Standard Approach"

Abstract: The exposure of stock returns to risk factors has been shown to be varying over time. To capture this variation, classical methods, such as rolling windows, have been used extensively. However, they are highly dependent on the choice of the window length and are not necessarily able to capture the nonlinearities of the data. We propose a novel method that uses a neural network to deduce the stock exposure to market risk, on a time-varying basis. We show that this estimator has superior out-of-sample predictive performance when compared to regression-based estimators. In addition, the proposed estimator shows no systematic bias pattern across model-implied expected beta quintile portfolios.

 Yixuan Ma, Paulo Rodrigues, Peter Schotman (2024) "Solving Dynamic Portfolio and Consumption Problems by Going Forward in Time"

Abstract: The standard approach to solving dynamic portfolio and consumption problems numerically uses backward induction, which complicates the solution if decisions at time t depend on past decisions. In contrast, our solution algorithm goes forward in time. We use the insight that the main task in solving dynamic optimization problems consists of finding policy functions that use the current value of state variables as inputs and give the optimal decisions as outputs. Instead of assuming a functional form for these policy functions, we use a neural network for the estimation of the functions. 

Nicole Branger, Paulo Rodrigues, Peter Schotman (2024) "Optimal inflation risk sharing among pension fund participants"

Abstract: We study inflation hedging from the perspective of a pension fund. Retired participants in the fund have a demand for inflation protection but face a thin market for inflation-linked bonds. Young participants in the fund have their human capital as a natural inflation hedge. The young may be willing to offer some protection to the old, and thus contribute to complete the market, depending on the price at which the inflation risk is internally traded. Our analysis shows conditions such that a mutually beneficial internal trade exists. The price of the internal transfer will, however, generally deviate from the market price of the inflation-linked bond. Using data calibrated to a long history of inflation, interest rates and stock returns, we find that the internal real interest rate is likely to deviate from the market real interest rate.