Tolga Cenesizoglu

Forecasting (aggregate) demand for US commercial air travel

We analyze whether it is better to forecast air travel demand using aggregate data at (say) a national level, or to aggregate the forecasts derived for individual airports using airport-specific data. We compare the US Federal Aviation Administration’s (FAA) practice of predicting the total number of passengers using macroeconomic variables with an equivalently specified AIM (aggregating individual markets) approach. The AIM approach outperforms the aggregate forecasting approach in terms of its out-of-sample air travel demand predictions for different forecast horizons. Variants of AIM, where we restrict the coefficient estimates of some explanatory variables to be the same across individual airports, generally dominate both the aggregate and AIM approaches. The superior out-of-sample performances of these so-called quasi-AIM approaches depend on the trade-off between heterogeneity and estimation uncertainty. We argue that the quasi-AIM approaches exploit the heterogeneity across individual airports efficiently, without suffering from as much estimation uncertainty as the AIM approach.

Is the Distribution of Stock Returns Predictable

A large literature has considered predictability of the mean or volatility of stock returns but little is known about whether the distribution of stock returns more generally is predictable. We explore this issue in a quantile regression framework and consider whether a range of economic state variables are helpful in predicting different quantiles of stock returns representing left tails, right tails or shoulders of the return distribution. Many variables are found to have an asymmetric effect on the return distribution, affecting lower, central and upper quantiles very differently. Out-of-sample forecasts suggest that upper quantiles of the return distribution can be predicted by means of economic state variables although the center of the return distribution is more difficult to predict. Economic gains from utilizing information in time-varying quantile forecasts are demonstrated through portfolio selection and option trading experiments.

The Effect Of Monetary Policy On Credit Spreads

In this paper, we analyze the effect of monetary policy on yield spreads between corporate bonds with different credit ratings over changing conditions in the economy. Using futures data on the Fed funds rate, we distinguish between expected and unexpected changes in monetary policy. We find that unexpected changes in the Fed funds rate do not have a significant effect on changes in credit spreads when we do not control for different conditions in the economy. We then distinguish between three different cycles in the economy: business, credit and monetary policy cycles. In line with predictions of imperfect capital market theories, credit spreads widen (narrow) following an unexpected monetary policy tightening (easing) during periods of poor economic and credit market conditions. Several robustness tests suggest that our results are not due to possible endogeneity problems, lack of control variables or identification methodology or different cycles.

Conventional Monetary Policy and the Term Structure of Interest Rates during the Financial Crisis

This paper analyzes whether the Fed had the ability through its conventional monetary policy to affect key economic and financial variables, and, in particular, the term structure of interest rates, during the recent financial crisis. This departs from the empirical literature that focuses mainly on the effectiveness of unconventional monetary policies during this episode, although these policies are appropriate only to the extent that the conventional policy was ineffective in the first place. Our identification strategy based on the conditional heteroskedasticity of the structural innovations allows us to specify a flexible structural vector auto-regressive process that relaxes the identifying assumptions commonly used in earlier studies. Comparing our results obtained from samples excluding and including the financial crisis, we find that the conventional monetary policy has lost its effectiveness shortly after the beginning of the financial turmoil. This result suggests that the Feds use of unconventional policies was appropriate, at least, with the objective of changing the term structure of interest rates.

Monthly Beta Forecasting with Low, Medium and High Frequency Stock Returns

Generating one-month-ahead systematic (beta) risk forecasts is common place in financial management. This paper evaluates the accuracy of these beta forecasts in three return measurement settings; monthly, daily and 30 minutes. It is found that the popular Fama-MacBeth beta from 5 years of monthly returns generates the most accurate beta forecast among estimators based on monthly returns. A realized beta estimator from daily returns over the prior year, generates the most accurate beta forecast among estimators based on daily returns. A realized beta estimator from 30 minute returns over the prior 2 months, generates the most accurate beta forecast among estimators based on 30 minute returns. In environments where low, medium and high frequency returns are accurately available, beta forecasting with low frequency returns are the least accurate and beta forecasting with high frequency returns are the most accurate. The improvements in precision of the beta forecasts are demonstrated in portfolio optimization for a targeted beta exposure.

Effects of the Limit Order Book on Price Dynamics

In this paper, we analyze whether the state of the limit order book affects future price movements in line with what recent theoretical models predict. We do this in a linear vector autoregressive system which includes midquote return, trade direction and variables that are theoretically motivated and capture different dimensions of the information embedded in the limit order book. We find that different measures of depth and slope of bid and ask sides as well as their ratios cause returns to change in the next transaction period in line with the predictions of Goettler, Parlour, and Rajan (2009) and Kalay and Wohl (2009). Limit order book variables also have significant long term cumulative effects on midquote return, which is stronger and takes longer to be fully realized for variables based on higher levels of the book. In a simple high frequency trading exercise, we show that it is possible in some cases to obtain economic gains from the statistical relation between limit order book variables and midquote return.

An Analysis on the Predictability of CAPM Beta for Momentum Returns

This paper demonstrates that the forecasted CAPM beta of momentum portfolios explains a large portion of the return, ranging from 40% to 60% for stock level momentum, and 30% to 50% for industry level momentum. Beta forecasts are from a realized beta estimator using daily returns over the prior year. Periods such as 1969 to 1989 have been found in earlier studies to contain abnormal profits from momentum trading,however, we show that these were spuriously generated by measurement error in systematic risk. These results cast further doubt on the ability of standard momentum trading strategies to generate abnormal profits.

Time Variation in Cash Flows and Discount Rates

The relative contributions of cash flow and discount rate news to the conditional variance of market returns exhibit significant variation over time. We identify lagged changes in PPI inflation as the main macroeconomic determinant of this time variation. Cash flow betas of value stocks increase following an increase in inflation, suggesting that investors should either tilt their portfolios away from high cash-flow-risk stocks or hedge this risk after observing increasing inflation.

Asymmetric Effects of the Limit Order Book on Price Dynamics

We analyze whether the information in different parts of the limit order book affect prices differently. We distinguish between slopes of lower and higher levels of the bid and ask sides and include these four slope measures as well as midquote return and trade direction in a vector autoregressive model. Slope measures of the same side based on different levels affect both short- and long-run price dynamics quite differently, in line with the predictions based on recent theoretical models such as Foucault, Kadan, and Kandel (2005) and Rosu (2009). In a high frequency day trading exercise, we show that ignoring these asymmetries costs a trader approximately 25 basis points in daily profits, suggesting that the asymmetries are important not only statistically but also economically. Our statistical results are robust to using alternative definitions of slope measures and sample periods while our economic results are robust to trading under alternative assumptions such as trading slower speeds.

Return Decomposition Over the Business Cycle

To analyze the determinants of the observed variation in stock prices, Campbell and Shiller (1988) have suggested decomposing unexpected stock returns into unexpected changes in investors’ beliefs about future cash flows (cash flow news) and discount rates (discount rate news). Based on a generalization of this approach to a framework with regime-switching parameters and variances, we analyze the decomposition of the conditional variance of returns on the S&P 500 index over the business cycle. The cash flow news is relatively more important than discount rate news in determining the conditional variance of returns in expansions. The conditional variances of returns and its components increase in recessions. However, the conditional variance of discount rate news increases more than that of cash flow news and, thus, the discount rate news becomes relatively more important than cash flow news in determining the conditional variance of returns in recessions. In contrast to the standard Campbell and Shiller approach with constant parameters and variances, cash flow news becomes more important than discount rate news in determining the unconditional variance of returns when we allow parameters and variances to vary over the business cycle. We show that these results are broadly consistent with the implications of a stylized asset pricing model in which the growth rates of dividends and consumption take on different values depending on the underlying state of the economy.