Stock Returns and Cash Flows: A New Asset Pricing Approach

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Sonia di Tomaso, Antonio Amendola & Dennis Montagna

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Abstract

On this purpose, this work is focused on a non-conventional profitability measure, at least in terms of assets pricing models, where dividends or profits are widely used. The attention is focused on a proxy measure of Operating Cash Flows: the “Ebitda after Capex”. The relationship returns – cash flows’ volatility has been examined through an empirical analysis conducted on the stocks of the S&P500 Index combining the main quantitative and statistical approach with a qualitative overview respect the macroeconomic background. Starting from a correlation rolling window approach, three different regressions techniques have been implemented; the simple Ordinary Least Squares regressions (OLS), the linear Quantile (LQR) regression and the Multiple regression model (MLR), all performed at different levels in terms of stocks (QoQ and YoY) and sectors (MoM, QoQ, YoY).

The cross-sectional and time-series results support the effects of cash flow’ volatility on the stocks’ performance and highlighted its sensitivity respect not only the different short-term and long-term horizons, but also in terms of sector’ exposure.

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Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3709525

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Valuation Measures: From Simple Ratios to Stock Market’s Predictors

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Benedetta Sorge, Antonio Amendola & Dennis Montagna

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Abstract

This research represents the union of two main studies: the first one focused on the analysis of the CAPE Ratio, also known as the Cyclically Adjusted Price-Earnings ratio, a valuation measure introduced by the Nobel Prize Robert Shiller, and the second one focused on the predictability of the US stock market. The aim was to answer the following question: can valuation measures be considered reliable as stock market predictors? The result of the study then found practical application in the creation of different portfolio strategies, aimed at demonstrating the significance of the correlation between the ratio under analysis and future returns of the stock market.

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Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3756547

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The Low-Risk Effect, from Betting Against Beta to Betting Against Correlation

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Tommaso Pasetti & Dennis Montagna

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Abstract

The aim of this work is to analyze the so-called "Low Risk Effect" and the evolution of the risk-reward relationship in time. Perhaps one of the milestones of the whole modern finance has been the investigation and the debate about the positive relationship between risk and reward in asset allocation, but are we sure that this theoretical paradigm is able to provide also empirical evidence? Starting form the “father” of Modern Portfolio Theory, passing through Sharpe’s CAPM and Black 1972, we analyzed in deep the so-called "Low Risk Effect" and the debate between leverage constraints and behavioural theories. We concluded our journey decomposing Betting Against Beta (Asness, Frazzini and Pedersen) and analysing their last contribution: Betting Against Correlation (BAC), a factor that goes long low correlation stocks and shorts high correlation ones. Starting from the BAC methodology framework, we decided to create some modifications in order to test the goodness of the model in terms of performance against the reference index. Finally we tried to implement a profitable strategy for S&P500 over the time interval 2003-2021, evidencing the phases of negative correlated stocks and arriving to define strategy’s sector composition. To conclude our work we performed a sectorial analysis in which we investigated the composition of Long/Short portfolios for our best strategy Correlation Weighted qBAC, trying to evidence the main drivers for strategy’s performance and critical issues in the last few years. To go further we built a "walking correlation analysis" that resulted useful to observe the dynamic evolution of stocks correlation in time both against the market and within the sector.

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Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3995496

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VIX Index Strategies: Shorting Volatility As a Portfolio Enhancing Strategy

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Alberto Dondoni, Dennis Montagna & Mario Maggi

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Abstract

In this paper we perform an empirical analysis on the VIX Index and we develop a series of portfolio strategies on implied volatility by using VIX Futures. First, we give a brief introduction to the VIX Index and what it represents. Then we focus on the VIX Futures, with an analysis of the VIX Futures curve and its relationship with the VIX Index. The last part will be dedicated to the presentation of the results of different portfolio strategies, extending a long /short position on VIX Futures.

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Available at SSRN: https://ssrn.com/abstract=3104407 or http://dx.doi.org/10.2139/ssrn.3104407

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Analysis of Equity β Principal Components in Low Risk Framework: New Results and Prospectives

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Antonio Amendola, Dennis Montagna & Mario Maggi

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Abstract

With our work we want to exploit the so called "Beta anomaly" regarding the risk-reward relationship. Starting from the some evidences that so called Low Beta strategies generate, we decompose the formula in principal factors in order to asses the different drivers and contributions. Identifying Correlation and Standard Deviation as principal components we run an extensive analysis focusing on S&P 500 Index and relative members, covering the last 10 years. Based on that we assess the impact on the overall beta with Ordinary Least Square regression, performing also some portfolios backtests. We play basically 2 Long/Short strategies, ranking the stocks with correlation and with standard deviation, facing the results with other based on ranking. We extend our research looking in the different Sectors and finally we develop a new ideas in order to show the beta evolution respect market and reference sector, "Walking Beta". In the second paper we will extend our research, including a new application of the options combined with the high/low beta intuition.

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Published and available in Journal of Economics and Financial Analysis, Vol 3, No 1 (2019)

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Link to article, https://ojs.tripaledu.com/index.php/jefa

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Spotlight on Biotechnology: valuation challenges of early-stage companies. A case study on CRISPR Therapeutics AG and Allakos, Inc.

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Emanuele Fino, Giovanni Nocera, Dennis Montagna & Antonio Amendola

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Abstract

High volatility, no predictable cash flows and technological uncertainties make Biotech-Healthcare companies’ valuation a challenging task for analysts and investors. Translating clinical promises into economic value represents a rough obstacle of this attractive business, especially in measuring the potential implications that scientific breakthroughs can bring to society and the size of the financial markets’ reaction to such events. The aim of this work is to provide a deeper understanding of the dynamics behind Biotech companies’ analysis, moving from the traditional valuation models to a risk-adjusted framework, including the technological and regulatory issues related to FDA (Food and Drug Administration) and EMA (European Medicine Agency) approval process. The efforts made have required a full immersion in a biological and clinical context that is far and beyond the common practice proper of the financial valuation field.

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Available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3755675

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OOBNs for Financial Markets Signals Detection

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Alessandro Greppi

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Abstract

Equity markets dynamics can be analyzed only by considering at the same time a large amount of information of different nature. We propose to adopt Object Oriented Bayesian Networks as a quantitative and analytical tool for detecting market signals. We include in the same model microeconomic, macroeconomic, technical analysis and market sentiment variables. We exploit this graphical representation to describe relationships among variables and to perform simulations in real time. This approach allows us to provide in a mouse-click time operative signals to investors. In this work, we present an application to S&P 500.

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Available at SSRN: https://ssrn.com/abstract=3096794