Research articles for the 2019-03-13
Affine Multiple Yield Curve Models
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We provide a general and tractable framework under which all multiple yield curve modeling approaches based on affine processes, be it short rate, Libor market, or Heath–Jarrow–Morton modeling, can be consolidated. We model a numéraire process and multiplicative spreads between Libor rates and simply compounded overnight indexed swap rates as functions of an underlying affine process. Besides allowing for ordered spreads and an exact fit to the initially observed term structures, this general framework leads to tractable valuation formulas for caplets and swaptions and embeds all existing multicurve affine models. The proposed approach also gives rise to new developments, such as a short rate type model driven by a Wishart process, for which we derive a closed‐form pricing formula for caplets. The empirical performance of two specifications of our framework is illustrated by calibration to market data.
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We provide a general and tractable framework under which all multiple yield curve modeling approaches based on affine processes, be it short rate, Libor market, or Heath–Jarrow–Morton modeling, can be consolidated. We model a numéraire process and multiplicative spreads between Libor rates and simply compounded overnight indexed swap rates as functions of an underlying affine process. Besides allowing for ordered spreads and an exact fit to the initially observed term structures, this general framework leads to tractable valuation formulas for caplets and swaptions and embeds all existing multicurve affine models. The proposed approach also gives rise to new developments, such as a short rate type model driven by a Wishart process, for which we derive a closed‐form pricing formula for caplets. The empirical performance of two specifications of our framework is illustrated by calibration to market data.
Bayesian Nonparametric Learning of How Skill is Distributed Across the Mutual Fund Industry
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In this paper, we use Bayesian nonparametric learning to estimate the skill of actively managed mutual funds and also to estimate the population distribution for this skill. A nonparametric hierarchical prior, where the hyperprior distribution is unknown and modeled with a Dirichlet process prior, is used for the skill parameter, with its posterior predictive distribution being an estimate of the population distribution. Our nonparametric approach is equivalent to an infinitely ordered mixture of normals where we resolve the uncertainty in the mixture order by partitioning the funds into groups according to the group's average ability and variability. Applying our Bayesian nonparametric learning approach to a panel of actively managed, domestic equity funds, we find the population distribution of skill to be fat-tailed, skewed towards higher levels of performance. We also find that it has three distinct modes: a primary mode where the average ability covers the average fees charged by funds, a secondary mode at a performance level where a fund loses money for its investors, and lastly, a minor mode at an exceptionally high skill level.
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In this paper, we use Bayesian nonparametric learning to estimate the skill of actively managed mutual funds and also to estimate the population distribution for this skill. A nonparametric hierarchical prior, where the hyperprior distribution is unknown and modeled with a Dirichlet process prior, is used for the skill parameter, with its posterior predictive distribution being an estimate of the population distribution. Our nonparametric approach is equivalent to an infinitely ordered mixture of normals where we resolve the uncertainty in the mixture order by partitioning the funds into groups according to the group's average ability and variability. Applying our Bayesian nonparametric learning approach to a panel of actively managed, domestic equity funds, we find the population distribution of skill to be fat-tailed, skewed towards higher levels of performance. We also find that it has three distinct modes: a primary mode where the average ability covers the average fees charged by funds, a secondary mode at a performance level where a fund loses money for its investors, and lastly, a minor mode at an exceptionally high skill level.
Can Mutual Fund Managers Predict Security Prices to Beat the Market? The Case of Greece During the Debt Crisis
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The purpose of this paper is to examine the performance of Greek equity mutual funds, elaborating on stock selection in parallel with market timing measures, in comparison with the performance of ETFs and index funds for the period 01/24/2008-05/12/2017, and the short-term performance persistence of actively managed funds for the period 05/12/2015-05/12/2017. Using all domestic equity mutual funds at our disposal and daily data, the authors apply multi-factor models to estimate risk-adjusted returns and to evaluate the selectivity and market timing ability of fund managers. In order to investigate short-term performance persistence, the coexistence of stock selection and market timing strategy is allowed and a battery of parametric and nonparametric tests is implemented. Results show that actively managed mutual funds underperformed the market index, as well as passively managed ETFs and index funds, primarily due to the managers’ inability to time the market. Furthermore, a winner-picking strategy to outperform a-buy-the-market-and hold policy is questioned.
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The purpose of this paper is to examine the performance of Greek equity mutual funds, elaborating on stock selection in parallel with market timing measures, in comparison with the performance of ETFs and index funds for the period 01/24/2008-05/12/2017, and the short-term performance persistence of actively managed funds for the period 05/12/2015-05/12/2017. Using all domestic equity mutual funds at our disposal and daily data, the authors apply multi-factor models to estimate risk-adjusted returns and to evaluate the selectivity and market timing ability of fund managers. In order to investigate short-term performance persistence, the coexistence of stock selection and market timing strategy is allowed and a battery of parametric and nonparametric tests is implemented. Results show that actively managed mutual funds underperformed the market index, as well as passively managed ETFs and index funds, primarily due to the managers’ inability to time the market. Furthermore, a winner-picking strategy to outperform a-buy-the-market-and hold policy is questioned.
Do Financial Gurus Produce Reliable Forecasts?
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Many investors rely on market experts and forecasters when making investment decisions, such as when to buy or sell securities. Ranking and grading market forecasters provides investors with metrics on which they may choose forecasters with the best record of accuracy for their particular market exposure. This study develops a novel ranking methodology to rank the market forecaster. In particular, we distinguish forecasts by their specificity, rather than considering all predictions and forecasts equally important, and we also analyze the impact of the number of forecasts made by a particular forecaster. We have applied our methodology on a dataset including 6,627 forecasts made by 68 forecasters.
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Many investors rely on market experts and forecasters when making investment decisions, such as when to buy or sell securities. Ranking and grading market forecasters provides investors with metrics on which they may choose forecasters with the best record of accuracy for their particular market exposure. This study develops a novel ranking methodology to rank the market forecaster. In particular, we distinguish forecasts by their specificity, rather than considering all predictions and forecasts equally important, and we also analyze the impact of the number of forecasts made by a particular forecaster. We have applied our methodology on a dataset including 6,627 forecasts made by 68 forecasters.
Financial Attitudes, Behaviours, and the Disposition Effect
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It has been widely studied that investors suffer from the tendency to realize gains too quickly, while carrying losses too long --- also known as the disposition effect. Previous research on the phenomenon finds that there is a substantial heterogeneity with regards to the magnitude of investors' disposition effects. In this regard, we conduct an experiment in order to relate the disposition effect to subjects' self-stated financial attitudes and behaviours. We find that US investors' financial attitudes and behaviours can be captured by the following four dimensions: "financial planning," "anxiety," "interest in financial issues," and "impulsive financial decision-making." Furthermore, these dimensions reveal that investors who focus more on the long-term implications of their financial decisions exhibit lower disposition effects on average.
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It has been widely studied that investors suffer from the tendency to realize gains too quickly, while carrying losses too long --- also known as the disposition effect. Previous research on the phenomenon finds that there is a substantial heterogeneity with regards to the magnitude of investors' disposition effects. In this regard, we conduct an experiment in order to relate the disposition effect to subjects' self-stated financial attitudes and behaviours. We find that US investors' financial attitudes and behaviours can be captured by the following four dimensions: "financial planning," "anxiety," "interest in financial issues," and "impulsive financial decision-making." Furthermore, these dimensions reveal that investors who focus more on the long-term implications of their financial decisions exhibit lower disposition effects on average.
Financial Markets, Innovation and Regulation
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The papers included in this issue are selected from the 7th International Conference of the Financial Engineering and Banking Society (FEBS) organized by Strathclyde Business School during 1-3 June 2017. With circa 200 academics, practitioners and regulators participating as delegates from around the world more than 140 papers were presented at the conference. The conference covered a wide range of topics related to financial markets, innovation, banking, risk, alternative finance and financial technology. The three plenary sessions focused on how can regulation “make markets work well†by Dr Matteo Aquilina (Financial Conduct Authority (FCA), Manager - Chief Economist's Department), financial markets and risk by Professor Jonathan Crook (Professor of Business Economics, Deputy Dean and Director of Research at the University of Edinburgh Business School), and alternative finance and financial technology by Professor Raghavendra Rau (Sir Evelyn de Rothschild Professor of Finance at Cambridge Judge Business School). Hence, the three keynote speeches where perfectly suited to the theme of the conference: “Financial Markets, Innovation and Regulationâ€.
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The papers included in this issue are selected from the 7th International Conference of the Financial Engineering and Banking Society (FEBS) organized by Strathclyde Business School during 1-3 June 2017. With circa 200 academics, practitioners and regulators participating as delegates from around the world more than 140 papers were presented at the conference. The conference covered a wide range of topics related to financial markets, innovation, banking, risk, alternative finance and financial technology. The three plenary sessions focused on how can regulation “make markets work well†by Dr Matteo Aquilina (Financial Conduct Authority (FCA), Manager - Chief Economist's Department), financial markets and risk by Professor Jonathan Crook (Professor of Business Economics, Deputy Dean and Director of Research at the University of Edinburgh Business School), and alternative finance and financial technology by Professor Raghavendra Rau (Sir Evelyn de Rothschild Professor of Finance at Cambridge Judge Business School). Hence, the three keynote speeches where perfectly suited to the theme of the conference: “Financial Markets, Innovation and Regulationâ€.
Forecasting Individual Stock Returns Using Macroeconomic and Technical Variables
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We show that the previously documented predictability of macroeconomic and technical variables for market returns is also evident in individual stocks. Technical variables generate better predictability on firms with larger limits to arbitrage (smaller, illiquid, volatile firms), while macroeconomic variables better predict firms with lesser limits to arbitrage. Macro indicators perform well across the business cycle but comparatively stronger in recessions, while technical variables exhibit strong predictive power in recessions but somewhat weaker in expansions. Moreover, macroeconomic variables have better prediction performance on low arbitrage constraint firms in recession while technical indicators capture more forecast information for high arbitrage constraint firms in expansion.
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We show that the previously documented predictability of macroeconomic and technical variables for market returns is also evident in individual stocks. Technical variables generate better predictability on firms with larger limits to arbitrage (smaller, illiquid, volatile firms), while macroeconomic variables better predict firms with lesser limits to arbitrage. Macro indicators perform well across the business cycle but comparatively stronger in recessions, while technical variables exhibit strong predictive power in recessions but somewhat weaker in expansions. Moreover, macroeconomic variables have better prediction performance on low arbitrage constraint firms in recession while technical indicators capture more forecast information for high arbitrage constraint firms in expansion.
Genuine and Spurious Serial Correlations in Asset Returns â€" An Illustration: Real Estate versus Equity
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Asset returns in efficient markets should not display serial correlations. Otherwise, asset prices would be predictable to a certain extent and arbitrage opportunities would appear, contradicting the assumption of efficiency.Lack of serial correlation is considered to be true for most sufficiently traded financial assets. For other assets, such as real assets, and in particular for real estate, a substantial level of serial correlation is suspected, and, as will be seen, verified in practice. There are many factors that may contribute to a high level of serial correlation: high transaction costs, information imperfections, scarcity of transactions, and role of surveys instead of transactions in the process of price formation…This short paper focuses on one hidden factor: averaging. As transactions are scarce, and are related to heterogeneous assets, price indices must be built so as to encompass a minimal period of time : one month at least, generally a quarter, and the resulting index is computed as an average over that period.We show that averaging introduces a .25 serial correlation for basically non-serially correlated asset price moves. For genuinely serially correlated series, averaging increases the measured serial correlation. We check those findings on two large US asset classes: residential real estate and equity.
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Asset returns in efficient markets should not display serial correlations. Otherwise, asset prices would be predictable to a certain extent and arbitrage opportunities would appear, contradicting the assumption of efficiency.Lack of serial correlation is considered to be true for most sufficiently traded financial assets. For other assets, such as real assets, and in particular for real estate, a substantial level of serial correlation is suspected, and, as will be seen, verified in practice. There are many factors that may contribute to a high level of serial correlation: high transaction costs, information imperfections, scarcity of transactions, and role of surveys instead of transactions in the process of price formation…This short paper focuses on one hidden factor: averaging. As transactions are scarce, and are related to heterogeneous assets, price indices must be built so as to encompass a minimal period of time : one month at least, generally a quarter, and the resulting index is computed as an average over that period.We show that averaging introduces a .25 serial correlation for basically non-serially correlated asset price moves. For genuinely serially correlated series, averaging increases the measured serial correlation. We check those findings on two large US asset classes: residential real estate and equity.
How Do Anti-Discrimination Laws Affect Capital Structure Decisions? Evidence From the Post-World War II Period
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We exploit the staggered passage of state-level fair-employment laws in the post-World War II period to examine how stronger worker protection against racial discrimination impacts firm financing decisions. Race based anti-discrimination laws cause a reduction in firm debt ratios, especially for firms with high labor intensity, firms in states experiencing high African American influx, firms in states with high AFL union presence, and firms in concentrated industries. Operating leverage increases and profitability declines after the passage of these laws. Overall, we show that firms choose conservative financial policies when faced with more rigid labor markets due to stronger worker rights.
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We exploit the staggered passage of state-level fair-employment laws in the post-World War II period to examine how stronger worker protection against racial discrimination impacts firm financing decisions. Race based anti-discrimination laws cause a reduction in firm debt ratios, especially for firms with high labor intensity, firms in states experiencing high African American influx, firms in states with high AFL union presence, and firms in concentrated industries. Operating leverage increases and profitability declines after the passage of these laws. Overall, we show that firms choose conservative financial policies when faced with more rigid labor markets due to stronger worker rights.
Investment-Momentum: A Two-Dimensional Behavioral Strategy
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We propose an investment-momentum strategy of buying past winners with low investment and selling past losers with high investment, which exploits simultaneously two dimensions of market inefficiencies. The new strategy generates twice the monthly returns earned by either the price momentum or investment strategy (1.44% vs. 0.75% or 0.61%) for 1965-2015. Despite of the diminishing anomalies in recent decades, the investment-momentum stays persistent. The mispricing-based strategy performs better in periods of high investor sentiment or for stocks with high limits-to-arbitrage, which is consistent with our expectation. Overall, we show that, in addition to “fundamentals†enhanced momentum strategies, one can simultaneously condition on multi-dimension of inefficiencies to attain superior performance.
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We propose an investment-momentum strategy of buying past winners with low investment and selling past losers with high investment, which exploits simultaneously two dimensions of market inefficiencies. The new strategy generates twice the monthly returns earned by either the price momentum or investment strategy (1.44% vs. 0.75% or 0.61%) for 1965-2015. Despite of the diminishing anomalies in recent decades, the investment-momentum stays persistent. The mispricing-based strategy performs better in periods of high investor sentiment or for stocks with high limits-to-arbitrage, which is consistent with our expectation. Overall, we show that, in addition to “fundamentals†enhanced momentum strategies, one can simultaneously condition on multi-dimension of inefficiencies to attain superior performance.
Magnitude Effects in Lending and Borrowing: Empirical Evidence From a P2P Platform
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For varying borrowing and lending amounts, corresponding subjective discount rates will vary. A situation where high amounts correspond to lower discount rates is called a conventional magnitude effect, while the opposite is called a reverse magnitude effect. We present an overview of theoretical arguments for both kinds of magnitude effects. Against this background, we then offer the first comprehensive empirical analysis of this issue based on real-life transaction data. To do so, we rely on more than 9,000 credit applications from the formerly largest German P2P lending platform, Smava, between February 2007 and April 2013. We confirm that there is a conventional magnitude effect for lending money to others but a reverse magnitude effect for borrowing decisions. We suggest as an explanation for our findings the prevalence of cost-based determinants of magnitude effects for this special setting.
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For varying borrowing and lending amounts, corresponding subjective discount rates will vary. A situation where high amounts correspond to lower discount rates is called a conventional magnitude effect, while the opposite is called a reverse magnitude effect. We present an overview of theoretical arguments for both kinds of magnitude effects. Against this background, we then offer the first comprehensive empirical analysis of this issue based on real-life transaction data. To do so, we rely on more than 9,000 credit applications from the formerly largest German P2P lending platform, Smava, between February 2007 and April 2013. We confirm that there is a conventional magnitude effect for lending money to others but a reverse magnitude effect for borrowing decisions. We suggest as an explanation for our findings the prevalence of cost-based determinants of magnitude effects for this special setting.
Market-Making Costs and Liquidity: Evidence from CDS Markets
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In over-the-counter markets, dealers facilitate trading by becoming market makers. The costs dealers face, including the cost of holding inventory on balance sheet, and the ease, or difficulty, of reducing their positions, determine the degree of liquidity they provide. We provide a stylized model to examine the implications of these costs on dealer behavior and market liquidity. We use the model to guide an empirical study of the single-name credit default swap (CDS) market between 2010-2016. We find that transaction prices between dealers and clients have progressively become more dependent on the inventories of individual dealers rather than on the aggregate inventory across all dealers. We also find that the volume between clients and dealers decreases across all clients, with larger declines for clients that are depository institutions. At the same time, the volume of interdealer trades decreases, dealer inventories decline, and dealers with large inventories are more likely to trade with clients. Our results are consistent with the view that regulatory reforms implemented following the 2007-09 financial crisis increased the cost of holding inventory for dealers, and the cost of interdealer trading.
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In over-the-counter markets, dealers facilitate trading by becoming market makers. The costs dealers face, including the cost of holding inventory on balance sheet, and the ease, or difficulty, of reducing their positions, determine the degree of liquidity they provide. We provide a stylized model to examine the implications of these costs on dealer behavior and market liquidity. We use the model to guide an empirical study of the single-name credit default swap (CDS) market between 2010-2016. We find that transaction prices between dealers and clients have progressively become more dependent on the inventories of individual dealers rather than on the aggregate inventory across all dealers. We also find that the volume between clients and dealers decreases across all clients, with larger declines for clients that are depository institutions. At the same time, the volume of interdealer trades decreases, dealer inventories decline, and dealers with large inventories are more likely to trade with clients. Our results are consistent with the view that regulatory reforms implemented following the 2007-09 financial crisis increased the cost of holding inventory for dealers, and the cost of interdealer trading.
Maximize Market Timing Returns: Implementing Volatility-Weighted Bets
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Market timing is preferred path to alpha because it is very simple to implement even by individual investors. In this paper we apply the Hallerbach (2014) methodology to emerging markets from Asia and Eastern Europe. We find that by using volatility-weighted bets we improve significantly the ex-post Information ratio of the strategy. This approach is even more important in emerging markets, where volatility is much higher than on traditional stock exchanges.In our research we select 15 leading emerging markets around the world. Examining volatility-weighted bets on emerging markets is even more interesting, because of the significantly higher volatility in comparison to developed markets. We develop the strategy on monthly basis in the period January, 2005 â€" March, 2017.
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Market timing is preferred path to alpha because it is very simple to implement even by individual investors. In this paper we apply the Hallerbach (2014) methodology to emerging markets from Asia and Eastern Europe. We find that by using volatility-weighted bets we improve significantly the ex-post Information ratio of the strategy. This approach is even more important in emerging markets, where volatility is much higher than on traditional stock exchanges.In our research we select 15 leading emerging markets around the world. Examining volatility-weighted bets on emerging markets is even more interesting, because of the significantly higher volatility in comparison to developed markets. We develop the strategy on monthly basis in the period January, 2005 â€" March, 2017.
Microstructure of Foreign Exchange Markets
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This article presents an overview of research on the Microstructure of Foreign Exchange Markets. We begin by summarizing the institutional features of FX trading and describe how they have evolved since the 1980s. We then explain how these features are represented in microstructure models of FX trading. Next, we describe the links between microstructure and traditional macro exchange-rate models and summarize how these links have been explored in recent empirical research. Finally, we provide a microstructure perspective on two recent areas of interest in exchange-rate economics: the behavior of returns on currency portfolios, and questions of competition and regulation.
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This article presents an overview of research on the Microstructure of Foreign Exchange Markets. We begin by summarizing the institutional features of FX trading and describe how they have evolved since the 1980s. We then explain how these features are represented in microstructure models of FX trading. Next, we describe the links between microstructure and traditional macro exchange-rate models and summarize how these links have been explored in recent empirical research. Finally, we provide a microstructure perspective on two recent areas of interest in exchange-rate economics: the behavior of returns on currency portfolios, and questions of competition and regulation.
Outsourcing Property Management? An Evaluation of the Rationales and Motivations
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This paper investigates the operation of outsourced property management delivery. Drawing upon semi-structured interviews with senior professionals responsible for property management outsourcing in Finland, Netherlands and the UK, it is found that the perceived advantages and disadvantages of outsourcing property management are broadly consistent with existing work on broader business process outsourcing. In particular, the ability to transfer fixed into variable costs and, so, to externalize operational risks were perceived as key advantages. In addition, due to the size of third party providers, it was possible to benefit from their economies of scale and to gain access to expertise in specific real estate sectors and specialisms. Arms-length relationships with third party providers, relatively short contractual periods and service level agreements are perceived to facilitate more formal quality assurance and performance monitoring procedures. Cost savings did not emerge as a key issue in the property management context but a recurring theme was the trade-off between cost and service quality and the need to maintain the latter in the context of pressures to obtain operational efficiencies. Common outsourcing problems such as information leakage and loss of control of the customer relationship also emerged from the research.
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This paper investigates the operation of outsourced property management delivery. Drawing upon semi-structured interviews with senior professionals responsible for property management outsourcing in Finland, Netherlands and the UK, it is found that the perceived advantages and disadvantages of outsourcing property management are broadly consistent with existing work on broader business process outsourcing. In particular, the ability to transfer fixed into variable costs and, so, to externalize operational risks were perceived as key advantages. In addition, due to the size of third party providers, it was possible to benefit from their economies of scale and to gain access to expertise in specific real estate sectors and specialisms. Arms-length relationships with third party providers, relatively short contractual periods and service level agreements are perceived to facilitate more formal quality assurance and performance monitoring procedures. Cost savings did not emerge as a key issue in the property management context but a recurring theme was the trade-off between cost and service quality and the need to maintain the latter in the context of pressures to obtain operational efficiencies. Common outsourcing problems such as information leakage and loss of control of the customer relationship also emerged from the research.
Repo Rates and the Collateral Spread Puzzle
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Repo rates frequently exceed unsecured rates in practice. As an explanation, this paper derives a constrained-arbitrage relation between the unsecured rate, the repo rate, and the illiquidity adjusted expected rate of return of the underlying collateral. The theory is based on unsecured borrowing constraints in the market for liquidity. Repos and security cash-market trades are alternative means to get liquidity. Collateral spreads (unsecured less repo rate) can turn negative if borrowing constraints tighten, unsecured rates spike down, or from a depressed and illiquid security market. The constrained-arbitrage theory sheds light on the evolution of collateral spreads over time.
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Repo rates frequently exceed unsecured rates in practice. As an explanation, this paper derives a constrained-arbitrage relation between the unsecured rate, the repo rate, and the illiquidity adjusted expected rate of return of the underlying collateral. The theory is based on unsecured borrowing constraints in the market for liquidity. Repos and security cash-market trades are alternative means to get liquidity. Collateral spreads (unsecured less repo rate) can turn negative if borrowing constraints tighten, unsecured rates spike down, or from a depressed and illiquid security market. The constrained-arbitrage theory sheds light on the evolution of collateral spreads over time.
Repo Rates and the Collateral Spread: Evidence
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The spread between unsecured and repo rates (collateral spread) fluctuates substantially and is negative on a significant portion of days. Recent theoretical work argues that collateral spreads are determined by a constrained-arbitrage relation between the unsecured rate, the repo rates, and the expected rate of return of the underlying security. Negative collateral spreads arise in equilibrium if unsecured markets are sufficiently tight, unsecured rates spike down, or security markets are sufficiently depressed in terms of prices, liquidity, and volatility. The objective of this paper is to examine the determinants of collateral spreads by testing the constrained-arbitrage theory. The findings are supportive.
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The spread between unsecured and repo rates (collateral spread) fluctuates substantially and is negative on a significant portion of days. Recent theoretical work argues that collateral spreads are determined by a constrained-arbitrage relation between the unsecured rate, the repo rates, and the expected rate of return of the underlying security. Negative collateral spreads arise in equilibrium if unsecured markets are sufficiently tight, unsecured rates spike down, or security markets are sufficiently depressed in terms of prices, liquidity, and volatility. The objective of this paper is to examine the determinants of collateral spreads by testing the constrained-arbitrage theory. The findings are supportive.
Simple Valuation Methods: Franchise Value Approach
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Models based on economic profit divide the value of the company to “base value†and “added valueâ€. Best-known economic profit models are EVA and Residual income (RIM). Based on them a franchise value approach has been developed.The franchise value model makes two main adjustments: First is with the base value. For other models, the base value of the company is some balance sheet figure. Franchise value approach takes into account not the balance sheet, but rather the earning power of the company. Tangible value of the company is introduced and is equal to the present value of current EPS repeated in the future. It is more reasonable to see the base value as a function of the earnings rather some balance sheet figure. The second major innovation is the separation of the growth model from the performance evaluation. While in most valuation models for growth estimation is used GGM that is implemented in the terminal value, here growth separated in “Growth factorâ€. This creates interesting inter-model dynamics that will be discussed in detail.According to the approach, the firm value consist of two main elements:- Tangible value. It present the ability of the company to create earnings;- Franchise Value. It involves two parts. First, the Franchise factor. It gives information about the relative performance of company against the market expectations. Second, the Growth factor. It should be noted that this is the only model that separates the growth from the performance. There are two approaches to finding the necessary characteristics of the random process, one is to confine g to vary randomly in the borders of E(GDP growth) +/- Inflation). The other is to extract the characteristics from the historical observations.Biggest advantage of Franchise value approach are the required inputs. With the separation of the growth factor, rest of the model needs only current data without burdensome forecasting that usually brings heavy assumptions. This brings the valuation closer to the present state of the business. In our paper we demonstrate the application of the model to a real company - Delta Electronics, Inc.
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Models based on economic profit divide the value of the company to “base value†and “added valueâ€. Best-known economic profit models are EVA and Residual income (RIM). Based on them a franchise value approach has been developed.The franchise value model makes two main adjustments: First is with the base value. For other models, the base value of the company is some balance sheet figure. Franchise value approach takes into account not the balance sheet, but rather the earning power of the company. Tangible value of the company is introduced and is equal to the present value of current EPS repeated in the future. It is more reasonable to see the base value as a function of the earnings rather some balance sheet figure. The second major innovation is the separation of the growth model from the performance evaluation. While in most valuation models for growth estimation is used GGM that is implemented in the terminal value, here growth separated in “Growth factorâ€. This creates interesting inter-model dynamics that will be discussed in detail.According to the approach, the firm value consist of two main elements:- Tangible value. It present the ability of the company to create earnings;- Franchise Value. It involves two parts. First, the Franchise factor. It gives information about the relative performance of company against the market expectations. Second, the Growth factor. It should be noted that this is the only model that separates the growth from the performance. There are two approaches to finding the necessary characteristics of the random process, one is to confine g to vary randomly in the borders of E(GDP growth) +/- Inflation). The other is to extract the characteristics from the historical observations.Biggest advantage of Franchise value approach are the required inputs. With the separation of the growth factor, rest of the model needs only current data without burdensome forecasting that usually brings heavy assumptions. This brings the valuation closer to the present state of the business. In our paper we demonstrate the application of the model to a real company - Delta Electronics, Inc.
Stylized facts of the Indian Stock Market
arXiv
arXiv
Historical daily data for eleven years of the fifty constituent stocks of the NIFTY index traded on the National Stock Exchange have been analyzed to check for the stylized facts in the Indian market. It is observed that while some stylized facts of other markets are also observed in Indian market, there are significant deviations in three main aspects, namely leverage, asymmetry and autocorrelation. Leverage and asymmetry are both reversed making this a more promising market to invest in. While significant autocorrelation observed in the returns points towards market inefficiency, the increased predictive power is better for investors.
The Anatomy of Block Accumulations by Activist Shareholders
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We conduct a large-sample analysis of investor activism in the US based on all 13D filings from 2001 to 2016. While hedge funds represent the largest filer group, the sample contains a diverse set of other activist shareholders, ranging from corporate insiders to large corporations. This raises the question to what extent other investors perform a governance role similar to hedge funds. Based on target firms' outcome variables, like announcement returns of activist campaigns and changes in operating measures, we find relatively few differences. However, hedge funds play a special role when it comes towards takeovers. They also help to push activist monitoring into a set of larger firms and trade more systematically against negative market price signals.
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We conduct a large-sample analysis of investor activism in the US based on all 13D filings from 2001 to 2016. While hedge funds represent the largest filer group, the sample contains a diverse set of other activist shareholders, ranging from corporate insiders to large corporations. This raises the question to what extent other investors perform a governance role similar to hedge funds. Based on target firms' outcome variables, like announcement returns of activist campaigns and changes in operating measures, we find relatively few differences. However, hedge funds play a special role when it comes towards takeovers. They also help to push activist monitoring into a set of larger firms and trade more systematically against negative market price signals.
The Banking Sector in 2018: Key Trends
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In 2018, the number of banks whose banking licenses were withdrawn increased. The overall size of those banks’ assets as well as their average value decreased considerably, while the mechanism of financial rehabilitation was applied only once in 2018.
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In 2018, the number of banks whose banking licenses were withdrawn increased. The overall size of those banks’ assets as well as their average value decreased considerably, while the mechanism of financial rehabilitation was applied only once in 2018.
The Legacy of Stephen A. Ross
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Stephen A. Ross had an uncanny talent for translating economic theory into intuitive and rigorous concepts that were useful to researchers and practitioners alike. His most famous accomplishment, the arbitrage pricing theory, has inspired the ongoing search for factors that explain security returns. His work on agency theory is applied to portfolio performance evaluation and compensation. This introduction summarizes the contributions in this issue primarily from his former students and colleagues, who reflect on what they learned from Steve, how he influenced their work, and how his ideas continue to be adapted and refined.
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Stephen A. Ross had an uncanny talent for translating economic theory into intuitive and rigorous concepts that were useful to researchers and practitioners alike. His most famous accomplishment, the arbitrage pricing theory, has inspired the ongoing search for factors that explain security returns. His work on agency theory is applied to portfolio performance evaluation and compensation. This introduction summarizes the contributions in this issue primarily from his former students and colleagues, who reflect on what they learned from Steve, how he influenced their work, and how his ideas continue to be adapted and refined.
Variational inequality for perpetual American option price and convergence to the solution of the difference equation
arXiv
arXiv
A variational inequality for pricing the perpetual American option and the corresponding difference equation are considered. First, the maximum principle and uniqueness of the solution to variational inequality for pricing the perpetual American option are proved. Then the maximum principle, the existence and uniqueness of the solution to the difference equation corresponding to the variational inequality for pricing the perpetual American option and the solution representation are provided and the fact that the solution to the difference equation converges to the viscosity solution to the variational inequality is proved. It is shown that the limits of the prices of variational inequality and BTM models for American Option when the maturity goes to infinity do not depend on time and they become the prices of the perpetual American option.
What We Still Have to Learn from the Credit Collapse (and Other Market Crises)
SSRN
This editorial, which mirrors Bruce Jacobs’s book Too Smart for Our Own Good: Ingenious Investment Strategies, Illusions of Safety, and Market Crashes, finds that “free-lunch†strategies and products that promise to increase returns while reducing risk can attract substantial investments and encourage leverage, especially when complexity and lack of transparency obscure the true sources of risk. But they also have the potential to induce sharp price swings that can destabilize markets and lead to crashes. The structured securitization of subprime mortgage loans, which first helped to inflate the housing bubble before triggering the implosion of the U.S. credit market, shares some important characteristics with strategies and products at the heart of prior crises, beginning with the 1987 stock market crash.
SSRN
This editorial, which mirrors Bruce Jacobs’s book Too Smart for Our Own Good: Ingenious Investment Strategies, Illusions of Safety, and Market Crashes, finds that “free-lunch†strategies and products that promise to increase returns while reducing risk can attract substantial investments and encourage leverage, especially when complexity and lack of transparency obscure the true sources of risk. But they also have the potential to induce sharp price swings that can destabilize markets and lead to crashes. The structured securitization of subprime mortgage loans, which first helped to inflate the housing bubble before triggering the implosion of the U.S. credit market, shares some important characteristics with strategies and products at the heart of prior crises, beginning with the 1987 stock market crash.
Who Should Sell Stocks?
SSRN
Never selling stocks is optimal for investors with a long horizon and a realistic range of preference and market parameters, if relative risk aversion, investment opportunities, proportional transaction costs, and dividend yields are constant. Such investors should buy stocks when their portfolio weight is too low and otherwise hold them, letting dividends rebalance to cash over time rather than selling. With capital gains taxes, this policy outperforms both static buy‐and‐hold and dynamic rebalancing strategies that account for transaction costs. Selling stocks becomes optimal if either their target weight is low or intermediate consumption is substantial.
SSRN
Never selling stocks is optimal for investors with a long horizon and a realistic range of preference and market parameters, if relative risk aversion, investment opportunities, proportional transaction costs, and dividend yields are constant. Such investors should buy stocks when their portfolio weight is too low and otherwise hold them, letting dividends rebalance to cash over time rather than selling. With capital gains taxes, this policy outperforms both static buy‐and‐hold and dynamic rebalancing strategies that account for transaction costs. Selling stocks becomes optimal if either their target weight is low or intermediate consumption is substantial.
Who is Responsible for a Cryptocurrency?
SSRN
Cryptocurrencies have entered the economy as alternative money, speculation objects, and as utility tokens for digital platforms. Cryptocurrencies are based on cryptography-based asset disposals broadcasted peer-to-peer to be validated in a decentralized way according to consented protocols. The organization and governance of cryptocurrencies disrupts the way things have been done by centralized institutions. This has consequences for responsibility. A centralized institution can be held responsible for its actions; however, in a cryptocurrency scheme, those actions are taken by a crowd of distributed participants not individually necessary for the outcome. This paper explores the participants' causal links to harm produced by a cryptocurrency scheme, and discusses how these causal links translate into responsibility. It is found that despite the decentralized nature of cryptocurrencies, participants cannot conceptually, legally, or morally use lack of causal links as a justification to evade responsibility.
SSRN
Cryptocurrencies have entered the economy as alternative money, speculation objects, and as utility tokens for digital platforms. Cryptocurrencies are based on cryptography-based asset disposals broadcasted peer-to-peer to be validated in a decentralized way according to consented protocols. The organization and governance of cryptocurrencies disrupts the way things have been done by centralized institutions. This has consequences for responsibility. A centralized institution can be held responsible for its actions; however, in a cryptocurrency scheme, those actions are taken by a crowd of distributed participants not individually necessary for the outcome. This paper explores the participants' causal links to harm produced by a cryptocurrency scheme, and discusses how these causal links translate into responsibility. It is found that despite the decentralized nature of cryptocurrencies, participants cannot conceptually, legally, or morally use lack of causal links as a justification to evade responsibility.
