Research articles for the 2019-06-15
A 'Bad Beta, Good Beta' Anatomy of Currency Risk Premiums and Trading Strategies
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We test a two-beta currency pricing model that features betas with risk-premium news and real-rate news of the currency market. Unconditionally, beta with currency market risk-premium news is “bad†because of significantly positive price of risk (2.52% per year); beta with global real-rate news is “good†due to nearly zero or negative price of risk. The price of risk-premium beta risk is counter-cyclical, while the price of the real-rate beta risk is pro-cyclical. Most prevailing currency trading strategies either have excessive “bad beta†or too little “good beta,†failing to deliver abnormal performance. Our empirical results can be delivered by a no-arbitrage model with precautionary savings and a pricing kernel characterized by two separate global shocks.
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We test a two-beta currency pricing model that features betas with risk-premium news and real-rate news of the currency market. Unconditionally, beta with currency market risk-premium news is “bad†because of significantly positive price of risk (2.52% per year); beta with global real-rate news is “good†due to nearly zero or negative price of risk. The price of risk-premium beta risk is counter-cyclical, while the price of the real-rate beta risk is pro-cyclical. Most prevailing currency trading strategies either have excessive “bad beta†or too little “good beta,†failing to deliver abnormal performance. Our empirical results can be delivered by a no-arbitrage model with precautionary savings and a pricing kernel characterized by two separate global shocks.
A Simple Pricing Model for Plain-Vanilla Dividend Futures Options
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This technical note provides a detailed description of a simple but effective modeling solution to mark and risk manage plain-vanilla options on dividend futures. We focus on equity indices, as dividend products for single stocks are less liquid and observable and we derive a simple pricing formula for dividend futures options based on a dynamic replication argument. The simplicity of the derived pricing methodology makes it particularly relevant for marking-making purpose.
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This technical note provides a detailed description of a simple but effective modeling solution to mark and risk manage plain-vanilla options on dividend futures. We focus on equity indices, as dividend products for single stocks are less liquid and observable and we derive a simple pricing formula for dividend futures options based on a dynamic replication argument. The simplicity of the derived pricing methodology makes it particularly relevant for marking-making purpose.
Apports de la Théorie des Valeurs Extrêmes au calcul de la Value-at-Risk (Contributions of the Extreme Values Theory in the calculation of Value-at-Risk)
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French Abstract: Le papier met en évidence les apports de la théorie des valeurs extrêmes (TVE) et son application à la mesure de VaR, et examine son effet sur la prise en compte des risques extrêmes. A cet égard, le papier étudie empiriquement l’indice SX5E sur une période de 22 années, et estime la VaR par deux modèles sous-jacents de la TVE, ainsi que deux autres modèles : dynamique GARCH et historique. Le backtesting de ces méthodes est conduit par le test de couverture non conditionnelle et le test de l’hypothèse d’indépendance. Les résultats montrent la supériorité des performances des estimations du modèle dynamique GARCH, par rapport aux modèles fondés sur la TVE, surtout en périodes de fortes volatilités.English Abstract: This paper shows evidence of the extreme value theory (EVT) contributions on the VaR estimations, and its applications in risk management through an empirical study of the SX5E index. The paper examines extreme risk measures over 22 years and reviews the non-conditional (dynamic GARCH and historical simulation) versus EVT VaR estimation models. Kupiec test and Chrisstoffersen test were used as backtests programs. The results show that dynamic GARCH, and historical simulation, perform better the EVT models (GPD and dynamic EVT), especially in volatile market conditions.
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French Abstract: Le papier met en évidence les apports de la théorie des valeurs extrêmes (TVE) et son application à la mesure de VaR, et examine son effet sur la prise en compte des risques extrêmes. A cet égard, le papier étudie empiriquement l’indice SX5E sur une période de 22 années, et estime la VaR par deux modèles sous-jacents de la TVE, ainsi que deux autres modèles : dynamique GARCH et historique. Le backtesting de ces méthodes est conduit par le test de couverture non conditionnelle et le test de l’hypothèse d’indépendance. Les résultats montrent la supériorité des performances des estimations du modèle dynamique GARCH, par rapport aux modèles fondés sur la TVE, surtout en périodes de fortes volatilités.English Abstract: This paper shows evidence of the extreme value theory (EVT) contributions on the VaR estimations, and its applications in risk management through an empirical study of the SX5E index. The paper examines extreme risk measures over 22 years and reviews the non-conditional (dynamic GARCH and historical simulation) versus EVT VaR estimation models. Kupiec test and Chrisstoffersen test were used as backtests programs. The results show that dynamic GARCH, and historical simulation, perform better the EVT models (GPD and dynamic EVT), especially in volatile market conditions.
Bond Risk Premia with Machine Learning
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We propose, compare, and evaluate a variety of machine learning methods for bond return predictability in the context of regression-based forecasting and contribute to a growing literature that aims to understand the usefulness of machine learning in empirical asset pricing. The main results show that non-linear methods can be highly useful for the out-of-sample prediction of bond excess returns compared to benchmarking data compression techniques such as linear principal component regressions. Also, the empirical evidence show that macroeconomic information has substantial incremental out-of-sample forecasting power for bond excess returns across maturities, especially when complex non-linear features are introduced via ensembled deep neural networks.
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We propose, compare, and evaluate a variety of machine learning methods for bond return predictability in the context of regression-based forecasting and contribute to a growing literature that aims to understand the usefulness of machine learning in empirical asset pricing. The main results show that non-linear methods can be highly useful for the out-of-sample prediction of bond excess returns compared to benchmarking data compression techniques such as linear principal component regressions. Also, the empirical evidence show that macroeconomic information has substantial incremental out-of-sample forecasting power for bond excess returns across maturities, especially when complex non-linear features are introduced via ensembled deep neural networks.
Changes in Inflation Expectations, Stock Returns, and the Economic State: A Signaling Role for Inflation?
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We find striking differences across economic states in how monthly and quarterly stock returns are related to changes in inflation expectations. Over 1997:11 to 2017:12 when fears of a deflationary low-growth regime were presumably more prevalent, we find a positive relation between stock returns and changes in inflation expectations that was much stronger during weaker economic times. Conversely, over 1982:01-1997:10 when fears of a high-inflation low-growth regime were presumably more prevalent, we find a negative relation between stock returns and changes in inflation expectations that was marginally stronger during weaker economic times. Using survey data, we also find that the comovement between inflation expectations and expected future real economic growth depends upon the economic state in a manner fitting with our stock-inflation results. Our evidence fits well with the `signaling role of inflation', as proposed in David and Veronesi (2013).
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We find striking differences across economic states in how monthly and quarterly stock returns are related to changes in inflation expectations. Over 1997:11 to 2017:12 when fears of a deflationary low-growth regime were presumably more prevalent, we find a positive relation between stock returns and changes in inflation expectations that was much stronger during weaker economic times. Conversely, over 1982:01-1997:10 when fears of a high-inflation low-growth regime were presumably more prevalent, we find a negative relation between stock returns and changes in inflation expectations that was marginally stronger during weaker economic times. Using survey data, we also find that the comovement between inflation expectations and expected future real economic growth depends upon the economic state in a manner fitting with our stock-inflation results. Our evidence fits well with the `signaling role of inflation', as proposed in David and Veronesi (2013).
Compound Returns
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We provide a theoretical basis for understanding the properties of compound returns. At long horizons, multiplicative compounding induces extreme positive skewness into individual stock returns, an effect primarily driven by single-period volatility. As a consequence, most individual stocks perform very poorly. However, holding just a few stocks (instead of a single one) greatly improves the long-run prospects of an investment strategy, indicating that missing out on the "lucky few" winner stocks is not a great concern. We show analytically how this somewhat counterintuitive result arises from an interaction between compounding, diversification, and rebalancing that has seemingly not been previously noted.
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We provide a theoretical basis for understanding the properties of compound returns. At long horizons, multiplicative compounding induces extreme positive skewness into individual stock returns, an effect primarily driven by single-period volatility. As a consequence, most individual stocks perform very poorly. However, holding just a few stocks (instead of a single one) greatly improves the long-run prospects of an investment strategy, indicating that missing out on the "lucky few" winner stocks is not a great concern. We show analytically how this somewhat counterintuitive result arises from an interaction between compounding, diversification, and rebalancing that has seemingly not been previously noted.
Dynamics and Heterogeneity of Subjective Stock Market Expectations
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Between 2004 and 2016, we elicited individuals’ subjective expectations of stock market returns in a Dutch internet panel at bi-annual intervals. In this paper, we develop a panel data model with a finite mixture of expectation types who differ in how they use past stock market returns to form current stock market expectations. The model allows. For rounding in the probabilistic responses and for observed and unobserved heterogeneity at several levels. We estimate the type distribution in the population and find evidence for considerable heterogeneity in expectation types and meaningful variation over time, in particular during the financial crisis of 2008/09.
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Between 2004 and 2016, we elicited individuals’ subjective expectations of stock market returns in a Dutch internet panel at bi-annual intervals. In this paper, we develop a panel data model with a finite mixture of expectation types who differ in how they use past stock market returns to form current stock market expectations. The model allows. For rounding in the probabilistic responses and for observed and unobserved heterogeneity at several levels. We estimate the type distribution in the population and find evidence for considerable heterogeneity in expectation types and meaningful variation over time, in particular during the financial crisis of 2008/09.
Growth Surge: How Private Equity Can Scale Up Firms and the Economy
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May 30, 2019 â€" Private equity deals are key to fueling the growth of small firms, as well as the Canadian economy, according to a report from the C.D. Howe Institute. In “Growth Surge: How Private Equity Can Scale Up Firms and the Economy,†Daniel Schwanen, Jeremy Kronick and Farah Omran examine the role of private equity as a stepping stone for growth by home-grown firms and recommend governments implement measures that can help firms grow, or gain a more solid footing, beyond the initial venture stage.
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May 30, 2019 â€" Private equity deals are key to fueling the growth of small firms, as well as the Canadian economy, according to a report from the C.D. Howe Institute. In “Growth Surge: How Private Equity Can Scale Up Firms and the Economy,†Daniel Schwanen, Jeremy Kronick and Farah Omran examine the role of private equity as a stepping stone for growth by home-grown firms and recommend governments implement measures that can help firms grow, or gain a more solid footing, beyond the initial venture stage.
Investment Trend Analysis of Dhaka Stock Exchange: A Comparative Study
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Capital market is a crucial financial market place where companies and the government can raise long-term funds and, at the same time, investors get the opportunity to invest in the listed companies. Capital markets play a vital role not only in shifting the funds from surplus entity to deficit for investment but also in the overall economic development of any developing country like Bangladesh. Being the first and biggest capital market of Bangladesh, Dhaka Stock Exchange (DSE) is the prime bourse of the country. From the historical data of this stock market, differences in the investment preference â€" among three broad categories of investors in DSE including individual investor, institutional investors, and government â€" are easily observed. Thus, authors of this article have used five different categories of investors such as sponsors or directors of the company, institutional investors, foreign investors, government, and the general public to present a comparative analysis of their investment patterns. Obtaining data on the percentage of investment by these five types of investors in different sectors from the DSE website, this study aims to analyze the sector-wise investment preference of these investors using August 2018 data. The study has found that the sponsors or directors of the company have the highest percentage of investment in the textile industry which is close to 16%. The Bangladesh government, as an investor, has the highest percentage of investment in the fuel & power sector, about 32%. It has also found that the mutual funds' sector is mostly financed by institutional investors, nearly 28%. Foreign investors have their most investments in the banking sector, which is close to 22%. It has also revealed that the textile sector is mostly financed by the general public, close to 17%. Nevertheless, the general public, surprisingly, has the lowest percentage of investment in the telecommunication sector, which is 0.10%.
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Capital market is a crucial financial market place where companies and the government can raise long-term funds and, at the same time, investors get the opportunity to invest in the listed companies. Capital markets play a vital role not only in shifting the funds from surplus entity to deficit for investment but also in the overall economic development of any developing country like Bangladesh. Being the first and biggest capital market of Bangladesh, Dhaka Stock Exchange (DSE) is the prime bourse of the country. From the historical data of this stock market, differences in the investment preference â€" among three broad categories of investors in DSE including individual investor, institutional investors, and government â€" are easily observed. Thus, authors of this article have used five different categories of investors such as sponsors or directors of the company, institutional investors, foreign investors, government, and the general public to present a comparative analysis of their investment patterns. Obtaining data on the percentage of investment by these five types of investors in different sectors from the DSE website, this study aims to analyze the sector-wise investment preference of these investors using August 2018 data. The study has found that the sponsors or directors of the company have the highest percentage of investment in the textile industry which is close to 16%. The Bangladesh government, as an investor, has the highest percentage of investment in the fuel & power sector, about 32%. It has also found that the mutual funds' sector is mostly financed by institutional investors, nearly 28%. Foreign investors have their most investments in the banking sector, which is close to 22%. It has also revealed that the textile sector is mostly financed by the general public, close to 17%. Nevertheless, the general public, surprisingly, has the lowest percentage of investment in the telecommunication sector, which is 0.10%.
Pricing the American Options: A Closed-Form, Simple Formula
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We overcome a major obstacle in the literature. In doing, we introduce a simple, closed-form formula for pricing the American options. In particular, we simplify Alghalith's closed-form formula for pricing American options. In doing so, we introduce a formula that does not require the additional parameter Ï•. That is, similar to a European option, we only need to know the interest rate and volatility.
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We overcome a major obstacle in the literature. In doing, we introduce a simple, closed-form formula for pricing the American options. In particular, we simplify Alghalith's closed-form formula for pricing American options. In doing so, we introduce a formula that does not require the additional parameter Ï•. That is, similar to a European option, we only need to know the interest rate and volatility.
Redistributive Consequences of Abolishing Uniform Contribution Policies in Pension Funds
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In a pension system with uniform policies for contribution and accrual, each participant has the same contribution rate and accrual rate independent of the age at the time of payment. Although a common practice for public sector pension plans in many countries, this is not actuarially fair because the investment horizon of young participants is longer than the investment horizon of the elderly. We show the unintended redistributive intergenerational effects of a uniform contribution system and the consequences of switching from uniform policies to an actuarially fair system, first analytically in a stylized model with three overlapping generations. We then quantify these effects in a detailed model with multiple overlapping generations, realistic parameters and detailed information on the income distribution, calibrated on the Dutch funded pension system. The system implies a substantial transfer of income from poor to wealthy participants of about 10 billion euros. The gross aggregate transition effect of abolishing the uniform policy pension for an actuarially fair system is about 37 billion euros (5% of the Dutch GDP). For each cohort, the redistributive effects are less than 5% of their total pension.
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In a pension system with uniform policies for contribution and accrual, each participant has the same contribution rate and accrual rate independent of the age at the time of payment. Although a common practice for public sector pension plans in many countries, this is not actuarially fair because the investment horizon of young participants is longer than the investment horizon of the elderly. We show the unintended redistributive intergenerational effects of a uniform contribution system and the consequences of switching from uniform policies to an actuarially fair system, first analytically in a stylized model with three overlapping generations. We then quantify these effects in a detailed model with multiple overlapping generations, realistic parameters and detailed information on the income distribution, calibrated on the Dutch funded pension system. The system implies a substantial transfer of income from poor to wealthy participants of about 10 billion euros. The gross aggregate transition effect of abolishing the uniform policy pension for an actuarially fair system is about 37 billion euros (5% of the Dutch GDP). For each cohort, the redistributive effects are less than 5% of their total pension.
Simulating Stress in the UK Corporate Bond Market: Investor Behaviour and Asset Fire-Sales
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We build a framework to simulate stress dynamics in the UK corporate bond market. This quantifies how the behaviours and interactions of major market participants, including open-ended funds, dealers, and institutional investors, can amplify different types of shocks to corporate bond prices. We model market participants’ incentives to buy or sell corporate bonds in response to initial price falls, the constraints under which they operate (including those arising due to regulation), and how the resulting behaviour may amplify initial falls in price and impact market functioning. We find that the magnitude of amplification depends on the cause of the initial reduction in price and is larger in the case of shocks to credit risk or risk-free interest rates, than in the case of a perceived deterioration in corporate bond market liquidity. Amplification also depends on agents’ proximity to their regulatory constraints. We further find that long-term institutional investors (eg pension funds) only partially mitigate the amplification due to their slower-moving nature. Finally, we find that shocks to corporate bond spreads, similar in magnitude to the largest weekly moves observed in the past, could trigger asset sales that may test the capacity of dealers to absorb them.
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We build a framework to simulate stress dynamics in the UK corporate bond market. This quantifies how the behaviours and interactions of major market participants, including open-ended funds, dealers, and institutional investors, can amplify different types of shocks to corporate bond prices. We model market participants’ incentives to buy or sell corporate bonds in response to initial price falls, the constraints under which they operate (including those arising due to regulation), and how the resulting behaviour may amplify initial falls in price and impact market functioning. We find that the magnitude of amplification depends on the cause of the initial reduction in price and is larger in the case of shocks to credit risk or risk-free interest rates, than in the case of a perceived deterioration in corporate bond market liquidity. Amplification also depends on agents’ proximity to their regulatory constraints. We further find that long-term institutional investors (eg pension funds) only partially mitigate the amplification due to their slower-moving nature. Finally, we find that shocks to corporate bond spreads, similar in magnitude to the largest weekly moves observed in the past, could trigger asset sales that may test the capacity of dealers to absorb them.
Stock Performance Subsequent to Combinations in Quarterly Revenue Surprise, Earnings Surprise, Guidance, Valuation, and Report Time
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Finance literature highlights various reasons for stock performance subsequent to earnings announcements. However, other moving parts in these scenarios must also be simultaneously specified. While both revenue and earnings surprises are important for determining stock performance, forward-looking guidance and firm valuation prior to earnings should also be considered. Additionally, analyses that solely consider market-level data miss important subtleties evident in a sector-specific study, as “normal†growth and valuation metrics across sectors widely differ. We differentiate between firms that announce earnings during the evening hours (after the close) and firms that announce earnings during the morning hours (prior to the open).
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Finance literature highlights various reasons for stock performance subsequent to earnings announcements. However, other moving parts in these scenarios must also be simultaneously specified. While both revenue and earnings surprises are important for determining stock performance, forward-looking guidance and firm valuation prior to earnings should also be considered. Additionally, analyses that solely consider market-level data miss important subtleties evident in a sector-specific study, as “normal†growth and valuation metrics across sectors widely differ. We differentiate between firms that announce earnings during the evening hours (after the close) and firms that announce earnings during the morning hours (prior to the open).
Tracking Foreign Capital: The Effect of Capital Inflows on Bank Lending in the UK
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This paper examines how UK banks channel capital inflows to the individual sectors of the domestic economy and to overseas residents. Information on the source country of foreign capital deposited with UK banks allows us to construct a novel Bartik instrument for capital inflows. Our results suggest that foreign funds boost bank lending to the domestic economy. This result is due to the positive effect of capital inflows on bank lending to non-financial firms and to other domestic financial institutions. Banks do not channel capital inflows directly to households or the public sector. Much of the foreign capital is also channelled back abroad, reflecting the role of the UK as a global financial centre.
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This paper examines how UK banks channel capital inflows to the individual sectors of the domestic economy and to overseas residents. Information on the source country of foreign capital deposited with UK banks allows us to construct a novel Bartik instrument for capital inflows. Our results suggest that foreign funds boost bank lending to the domestic economy. This result is due to the positive effect of capital inflows on bank lending to non-financial firms and to other domestic financial institutions. Banks do not channel capital inflows directly to households or the public sector. Much of the foreign capital is also channelled back abroad, reflecting the role of the UK as a global financial centre.
What Makes Cryptocurrencies Special? Investor Sentiment and Return Predictability During the Bubble
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The 2017 bubble on the cryptocurrency market recalls our memory in the dot-com bubble, during which hard-to-measure fundamentals and investors' illusion for brand new technologies led to overvalued prices. Benefiting from the massive increase in the volume of messages published on social media and message boards, we examine the impact of investor sentiment, conditional on bubble regimes, on cryptocurrencies aggregate return prediction. Constructing a crypto-specific lexicon and using a local-momentum autoregression model, we find that the sentiment effect is prolonged and sustained during the bubble while it turns out a reversal effect once the bubble collapsed. The out-of-sample analysis along with portfolio analysis is conducted in this study. When measuring investor sentiment for a new type of asset such as cryptocurrencies, we highlight that the impact of investor sentiment on cryptocurrency returns is conditional on bubble regimes.
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The 2017 bubble on the cryptocurrency market recalls our memory in the dot-com bubble, during which hard-to-measure fundamentals and investors' illusion for brand new technologies led to overvalued prices. Benefiting from the massive increase in the volume of messages published on social media and message boards, we examine the impact of investor sentiment, conditional on bubble regimes, on cryptocurrencies aggregate return prediction. Constructing a crypto-specific lexicon and using a local-momentum autoregression model, we find that the sentiment effect is prolonged and sustained during the bubble while it turns out a reversal effect once the bubble collapsed. The out-of-sample analysis along with portfolio analysis is conducted in this study. When measuring investor sentiment for a new type of asset such as cryptocurrencies, we highlight that the impact of investor sentiment on cryptocurrency returns is conditional on bubble regimes.
