Research articles for the 2019-09-13
151 Trading Strategies
SSRN
We provide detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscellany (such as weather, energy, inflation), global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms (such as artificial neural networks, Bayes, k-nearest neighbors). We also give: source code for illustrating out-of-sample backtesting with explanatory notes; around 2,000 bibliographic references; and over 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical. This is the complete version of the book.
SSRN
We provide detailed descriptions, including over 550 mathematical formulas, for over 150 trading strategies across a host of asset classes (and trading styles). This includes stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility (as an asset class), real estate, distressed assets, cash, cryptocurrencies, miscellany (such as weather, energy, inflation), global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms (such as artificial neural networks, Bayes, k-nearest neighbors). We also give: source code for illustrating out-of-sample backtesting with explanatory notes; around 2,000 bibliographic references; and over 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical. This is the complete version of the book.
Asset Pricing With Data Revisions
SSRN
This paper documents the asset pricing implications of the data release process of National Income and Product Accounts (NIPA) consumption expenditure. We consider a new consumption-based model, the Revised CCAPM, which incorporates this release process using NIPA vintage data. It explains a striking 75% of the cross-sectional variation in average returns on the 25 size-value portfolios when featuring the first data release and its state-dependent uncertainty coming from first data revisions. This is due to first revisions capturing genuinely novel information, whereas the remaining revisions serve to mitigate measurement error and functions as a filtering process. Our analysis implies that early consumption data releases are more suitable for asset pricing than final releases. We show that revision uncertainty is strongly linked to investors' ambiguity about consumption growth and is priced in the financial market as such. As as result, the strong performance of our Revised CCAPM is explained by state-dependent ambiguity attitudes.
SSRN
This paper documents the asset pricing implications of the data release process of National Income and Product Accounts (NIPA) consumption expenditure. We consider a new consumption-based model, the Revised CCAPM, which incorporates this release process using NIPA vintage data. It explains a striking 75% of the cross-sectional variation in average returns on the 25 size-value portfolios when featuring the first data release and its state-dependent uncertainty coming from first data revisions. This is due to first revisions capturing genuinely novel information, whereas the remaining revisions serve to mitigate measurement error and functions as a filtering process. Our analysis implies that early consumption data releases are more suitable for asset pricing than final releases. We show that revision uncertainty is strongly linked to investors' ambiguity about consumption growth and is priced in the financial market as such. As as result, the strong performance of our Revised CCAPM is explained by state-dependent ambiguity attitudes.
Capital Lock-in, Liquidity, and the Separation of Ownership and Control
SSRN
Who should own firm assets, the collection of investors or a distinct legal entity? In a partnership, individual investors own firm assets and retain the right to unilaterally withdraw their capital at wilL If, instead, firm assets are owned by a distinct legal entity (the corporation), investors implicitly waive this right, locking capital in the firm. Capital lock-in facilitates long-term investments but carries a risk of inefficient continuation of unprofitable projects. Withdrawal at will can lead to the inefficient liquidation of profitable projects. In this paper I provide a theory of the capital lock-in and the choice of organizational form.
SSRN
Who should own firm assets, the collection of investors or a distinct legal entity? In a partnership, individual investors own firm assets and retain the right to unilaterally withdraw their capital at wilL If, instead, firm assets are owned by a distinct legal entity (the corporation), investors implicitly waive this right, locking capital in the firm. Capital lock-in facilitates long-term investments but carries a risk of inefficient continuation of unprofitable projects. Withdrawal at will can lead to the inefficient liquidation of profitable projects. In this paper I provide a theory of the capital lock-in and the choice of organizational form.
Deposit Insurance and Banks’ Deposit Rates: Evidence from the 2009 EU Policy Change
SSRN
Deposit insurance is one of the main pillars of banking regulation meant to safeguard financial stability. In early 2009, the EU increased the minimum deposit insurance limit from e20, 000 to e100, 000 per bank account with the goal of achieving greater stability in the financial markets. Italy had already set a limit of e103, 291 in 1994. We evaluate the impact of the new directive on the banks’ average interest rate on customer deposits by comparing banks in the Eurozone countries to those in Italy, before and after the policy change. The comparability between the two groups of banks is improved by means of a propensity score matching. We find that the increase in the deposit insurance limit led to a significant decrease in the cost of funding per unit of customer deposit and that the effect is stronger for riskier banks, suggesting that the policy reduced the risk premium demanded by depositors.
SSRN
Deposit insurance is one of the main pillars of banking regulation meant to safeguard financial stability. In early 2009, the EU increased the minimum deposit insurance limit from e20, 000 to e100, 000 per bank account with the goal of achieving greater stability in the financial markets. Italy had already set a limit of e103, 291 in 1994. We evaluate the impact of the new directive on the banks’ average interest rate on customer deposits by comparing banks in the Eurozone countries to those in Italy, before and after the policy change. The comparability between the two groups of banks is improved by means of a propensity score matching. We find that the increase in the deposit insurance limit led to a significant decrease in the cost of funding per unit of customer deposit and that the effect is stronger for riskier banks, suggesting that the policy reduced the risk premium demanded by depositors.
ECB Corporate QE and the Loan Supply to Bank-Dependent Firms
SSRN
Using a representative sample of businesses in the euro area, we show that Eurosystempurchases of corporate bonds under the Corporate Sector Purchase programme (CSPP)increased the net issuance of debt securities, triggering a shift in bank loan supply infavour of firms that do not have access to bond-based financing. Identification comes frommatching bank-dependent firms to their lenders and accounting for the effect of CSPPon banks’ activity in the syndicated loan market. In a difference-in-differences setting,we show that credit access improved relatively more for firms borrowing from banksrelatively more exposed to CSPP-eligible firms. Unlike in previous studies, this resultapplies regardless of bank balance sheet quality as measured by Tier 1 and NPL ratios.
SSRN
Using a representative sample of businesses in the euro area, we show that Eurosystempurchases of corporate bonds under the Corporate Sector Purchase programme (CSPP)increased the net issuance of debt securities, triggering a shift in bank loan supply infavour of firms that do not have access to bond-based financing. Identification comes frommatching bank-dependent firms to their lenders and accounting for the effect of CSPPon banks’ activity in the syndicated loan market. In a difference-in-differences setting,we show that credit access improved relatively more for firms borrowing from banksrelatively more exposed to CSPP-eligible firms. Unlike in previous studies, this resultapplies regardless of bank balance sheet quality as measured by Tier 1 and NPL ratios.
Genetic Algorithms: A Heuristic Approach to Multi-Dimensional Problems
SSRN
Evolutionary algorithms are not new and have been developed, both their concepts and framework, since around the 1950’s based on the idea that the evolutionary process could be used as a general-purpose optimization tool. The goal of this paper is to propose an alternative to classical optimization techniques that can handle systems of a very high dimension. With the rapid rise of computing power, as well as the augmentation of alternative sources of data, quantitative analysts are confronted by numerical challenges that didn’t exist a decade ago. In this paper, we show that a Genetic Algorithm (GAs) is a simple process based on the evolution paradigm that is well adapted to very large portfolios, increasing the execution speed; an optimization of a portfolio of more than 100’000 times series of 5’000 daily returns takes less than 5 minutes. Finally, we illustrate that, although GAs are a random process that generates a different solution every time it is run on the same data, it is remarkably stable.
SSRN
Evolutionary algorithms are not new and have been developed, both their concepts and framework, since around the 1950’s based on the idea that the evolutionary process could be used as a general-purpose optimization tool. The goal of this paper is to propose an alternative to classical optimization techniques that can handle systems of a very high dimension. With the rapid rise of computing power, as well as the augmentation of alternative sources of data, quantitative analysts are confronted by numerical challenges that didn’t exist a decade ago. In this paper, we show that a Genetic Algorithm (GAs) is a simple process based on the evolution paradigm that is well adapted to very large portfolios, increasing the execution speed; an optimization of a portfolio of more than 100’000 times series of 5’000 daily returns takes less than 5 minutes. Finally, we illustrate that, although GAs are a random process that generates a different solution every time it is run on the same data, it is remarkably stable.
Jumps and the Correlation Risk Premium: Evidence from Equity Options
SSRN
This paper breaks the correlation risk premium down into two components: a premium related to the correlation of continuous stock price movements and a premium for bearing the risk of co-jumps. We propose a novel way to identify both premiums based on dispersion trading strategies that go long an index option portfolio and short a basket of option portfolios on the constituents. The option portfolios are constructed to only load on either diffusive volatility or jump risk. We document that both risk premiums are economically and statistically significant for the S&P 100 index. In particular, selling insurance against co-jumps generates a sizable annualized Sharpe ratio of 0.85.
SSRN
This paper breaks the correlation risk premium down into two components: a premium related to the correlation of continuous stock price movements and a premium for bearing the risk of co-jumps. We propose a novel way to identify both premiums based on dispersion trading strategies that go long an index option portfolio and short a basket of option portfolios on the constituents. The option portfolios are constructed to only load on either diffusive volatility or jump risk. We document that both risk premiums are economically and statistically significant for the S&P 100 index. In particular, selling insurance against co-jumps generates a sizable annualized Sharpe ratio of 0.85.
On Sources of Risk Premia in Representative Agent Models
SSRN
We use options data and realized returns to decompose unconditional risk premia into different parts of the return state space. Our decomposition shows that states associated with stock market crashes account for most of the equity premium in the data, but for nearly none of it in leading asset pricing theories based on habits, long run risks, and rare disasters. Calibrations with alternative shock specifications suggest that standard risk preferences make it challenging to account for sources of risk premia in a full information representative agent setting. A model with Generalized Disappointment Aversion preferences fits the data well.
SSRN
We use options data and realized returns to decompose unconditional risk premia into different parts of the return state space. Our decomposition shows that states associated with stock market crashes account for most of the equity premium in the data, but for nearly none of it in leading asset pricing theories based on habits, long run risks, and rare disasters. Calibrations with alternative shock specifications suggest that standard risk preferences make it challenging to account for sources of risk premia in a full information representative agent setting. A model with Generalized Disappointment Aversion preferences fits the data well.
Regulating the Doom Loop
SSRN
Euro area governments have committed to break the doom loop between banks and sovereigns.But policymakers disagree on how to treat sovereign exposures in bank regulation. Our contributionis to model endogenous sovereign portfolio reallocation by banks in response toregulatory reform. Simulations highlight a tension between concentration and credit risk inportfolio reallocation. Resolving this tension requires regulatory reform to be complementedby an expansion in the portfolio opportunity set to include an area-wide low-risk asset. Byreinvesting into such an asset, banks would reduce both their concentration and credit riskexposure.
SSRN
Euro area governments have committed to break the doom loop between banks and sovereigns.But policymakers disagree on how to treat sovereign exposures in bank regulation. Our contributionis to model endogenous sovereign portfolio reallocation by banks in response toregulatory reform. Simulations highlight a tension between concentration and credit risk inportfolio reallocation. Resolving this tension requires regulatory reform to be complementedby an expansion in the portfolio opportunity set to include an area-wide low-risk asset. Byreinvesting into such an asset, banks would reduce both their concentration and credit riskexposure.
The Greenium Matters: Evidence on the Pricing of Climate Risk
SSRN
This study provides evidence on the existence of a negative Greenium, i.e. a green risk premium, based on European individual stock returns and portfolios. By defining a green factor which is priced by the market, we offer a tool to assess a portfolio exposure to climate risk and hedge against it. We estimate that even in a rather benign scenario, there would be losses at the global level, including for European large banks, should they fail to price the Greenium. By halving the exposure to carbon-intensive sectors, losses would be reduced by 30%. These results call for the introduction of carbon stress tests for systemically important institutions.
SSRN
This study provides evidence on the existence of a negative Greenium, i.e. a green risk premium, based on European individual stock returns and portfolios. By defining a green factor which is priced by the market, we offer a tool to assess a portfolio exposure to climate risk and hedge against it. We estimate that even in a rather benign scenario, there would be losses at the global level, including for European large banks, should they fail to price the Greenium. By halving the exposure to carbon-intensive sectors, losses would be reduced by 30%. These results call for the introduction of carbon stress tests for systemically important institutions.
