Research articles for the 2019-06-01
A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index
SSRN
The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from FRED, commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.
SSRN
The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from FRED, commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.
Corporate Transparency in the Technological Frontier
SSRN
After a review of the traditional disclosure justifications, this paper examines the dangers that new technologies are creating in finance, such as flash crashes and the hack of the DAO. Whereas the dangers do require and have received regulatory responses, the environment that is forming does not appear to be one requiring a systematically different regulatory approach to transparency or disclosure.
SSRN
After a review of the traditional disclosure justifications, this paper examines the dangers that new technologies are creating in finance, such as flash crashes and the hack of the DAO. Whereas the dangers do require and have received regulatory responses, the environment that is forming does not appear to be one requiring a systematically different regulatory approach to transparency or disclosure.
Cracking the Preemption Code: The New Model for OTC Derivatives
SSRN
Following the 2008 financial crisis, Title VII of the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank) established a comprehensive regulatory regime in 2010 for over-the-counter (OTC) derivatives. From a state law perspective, Congress could have chosen to put more cops on the beat by repealing preemption that was added to the Commodity Exchange Act (CEA) in 2000 by the Commodity Futures Modernization Act (CFMA). Instead, Congress embraced preemption, extending it beyond gaming and bucket shop laws that were previously preempted by the CFMA. Given the size and complexity of the OTC derivatives markets, together with new required market structure changes, Congress chose to carry out OTC derivatives regulation exclusively through federal agencies with the requisite expertise.Aside from those at the CFTC who were close to Title VII when it was drafted, it was not immediately apparent in 2010 what Congress had done for the OTC derivatives markets by resetting the preemption clock back to 1974, which was when Congress conferred exclusive jurisdiction on the CFTC for commodity futures. The concern was that Congress had gone the other way and repealed preemption for swaps, based on changes to CEA §12(e)(2), which provided (and continues to provide) preemption of state gaming and bucket shop laws solely for contracts that are excluded or exempt under the CEA. In 2000, the CFMA added §12(e)(2) to the CEA at the same time that the CFMA excluded swaps from the CEA. Because Dodd-Frank repealed this exclusion in 2010 and brought swaps back into the CEA under the new Title VII regulatory regime, Congress moved swaps out of §12(e)(2) and into §2(a)(1)(A), the exclusive jurisdiction clause, using the same approach it had in 1974 for futures.Unfortunately, the change to CEA §12(e)(2) could leave the impression that preemption had been repealed. Even were someone to shift their attention to the CEA’s exclusive jurisdiction clause, this was not enough, since to achieve preemption for swaps it also took excluding them from CEA §12(e)(1). This is the CEA’s concurrent jurisdiction clause, which Congress added in 1982 for off-exchange contracts. This exclusion from §12(e)(1) is provided in amended CEA §2(d) through a long list of enumerated section references, making preemption for swaps more difficult to decipher.This article examines these changes and the coherent and well-designed preemption model that Congress adopted in 2010 for CFTC-regulated swaps and SEC-regulated security-based swaps.
SSRN
Following the 2008 financial crisis, Title VII of the Dodd-Frank Wall Street Reform and Consumer Protection Act (Dodd-Frank) established a comprehensive regulatory regime in 2010 for over-the-counter (OTC) derivatives. From a state law perspective, Congress could have chosen to put more cops on the beat by repealing preemption that was added to the Commodity Exchange Act (CEA) in 2000 by the Commodity Futures Modernization Act (CFMA). Instead, Congress embraced preemption, extending it beyond gaming and bucket shop laws that were previously preempted by the CFMA. Given the size and complexity of the OTC derivatives markets, together with new required market structure changes, Congress chose to carry out OTC derivatives regulation exclusively through federal agencies with the requisite expertise.Aside from those at the CFTC who were close to Title VII when it was drafted, it was not immediately apparent in 2010 what Congress had done for the OTC derivatives markets by resetting the preemption clock back to 1974, which was when Congress conferred exclusive jurisdiction on the CFTC for commodity futures. The concern was that Congress had gone the other way and repealed preemption for swaps, based on changes to CEA §12(e)(2), which provided (and continues to provide) preemption of state gaming and bucket shop laws solely for contracts that are excluded or exempt under the CEA. In 2000, the CFMA added §12(e)(2) to the CEA at the same time that the CFMA excluded swaps from the CEA. Because Dodd-Frank repealed this exclusion in 2010 and brought swaps back into the CEA under the new Title VII regulatory regime, Congress moved swaps out of §12(e)(2) and into §2(a)(1)(A), the exclusive jurisdiction clause, using the same approach it had in 1974 for futures.Unfortunately, the change to CEA §12(e)(2) could leave the impression that preemption had been repealed. Even were someone to shift their attention to the CEA’s exclusive jurisdiction clause, this was not enough, since to achieve preemption for swaps it also took excluding them from CEA §12(e)(1). This is the CEA’s concurrent jurisdiction clause, which Congress added in 1982 for off-exchange contracts. This exclusion from §12(e)(1) is provided in amended CEA §2(d) through a long list of enumerated section references, making preemption for swaps more difficult to decipher.This article examines these changes and the coherent and well-designed preemption model that Congress adopted in 2010 for CFTC-regulated swaps and SEC-regulated security-based swaps.
Financial Transaction Taxes in Theory and Practice
SSRN
We explore issues related to a financial transaction tax (FTT) in the United States. We trace the history and current practice of the tax in the United States and other countries, review evidence of its impact on financial markets, and explore the key design issues any such tax must address. We present new revenue and distributional effects of a hypothetical relatively broad-based FTT in the United States, finding that, at a base rate of 0.34 percent, it could raise a maximum of about 0.4 percent of GDP ($75 billion in 2017) in a highly progressive manner.
SSRN
We explore issues related to a financial transaction tax (FTT) in the United States. We trace the history and current practice of the tax in the United States and other countries, review evidence of its impact on financial markets, and explore the key design issues any such tax must address. We present new revenue and distributional effects of a hypothetical relatively broad-based FTT in the United States, finding that, at a base rate of 0.34 percent, it could raise a maximum of about 0.4 percent of GDP ($75 billion in 2017) in a highly progressive manner.
Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model
SSRN
We analyse the consequences of predicting and exploiting financial bubbles in an agent-based model, with a risky and a risk-free asset and three different trader types: fundamentalists, noise traders and "dragon riders" (DR). The DR exploit their ability to diagnose financial bubbles from the endogenous price history to determine optimal entry and exit trading times. We study the DR market impact as a function of their wealth fraction. With a proportion of up to 10%, DR are found to have a beneficial effect, reducing the volatility, value-at-risk and average bubble peak amplitudes. They thus reduce inefficiencies and stabilise the market by arbitraging the bubbles. At larger proportions, DR tend to destabilise prices, as their diagnostics of bubbles become increasingly self-referencing, leading to volatility amplification by the noise traders, which destroys the bubble characteristics that would have allowed them to predict bubbles at lower fraction of wealth. Concomitantly, bubble-based arbitrage opportunities disappear with large fraction of DR in the population of traders.
SSRN
We analyse the consequences of predicting and exploiting financial bubbles in an agent-based model, with a risky and a risk-free asset and three different trader types: fundamentalists, noise traders and "dragon riders" (DR). The DR exploit their ability to diagnose financial bubbles from the endogenous price history to determine optimal entry and exit trading times. We study the DR market impact as a function of their wealth fraction. With a proportion of up to 10%, DR are found to have a beneficial effect, reducing the volatility, value-at-risk and average bubble peak amplitudes. They thus reduce inefficiencies and stabilise the market by arbitraging the bubbles. At larger proportions, DR tend to destabilise prices, as their diagnostics of bubbles become increasingly self-referencing, leading to volatility amplification by the noise traders, which destroys the bubble characteristics that would have allowed them to predict bubbles at lower fraction of wealth. Concomitantly, bubble-based arbitrage opportunities disappear with large fraction of DR in the population of traders.
NFL Betting Market Efficiency, Divisional Rivals, and Profitable Strategies
SSRN
In this paper, I examine market inefficiencies in the NFL betting market from the 2003 season through the 2016 season. I examine the impact that division rivals and previously known determinants of inefficiencies have on the current NFL gambling market. The results show that games against division rivals have a lower chance of the home team covering the spread and the chance the game will result in an over. This result demonstrates that the sportsbooks underestimate the familiarity that teams have with each other’s players, coaches, and tendencies from playing each other twice per year. Moreover, using this result in conjunction with previously known inefficiencies, I put forth a model to test out of sample predictions. The results from these tests show profitable strategies in the point spread and totals market with a win rate of nearly 57%. Overall, this paper demonstrates inefficiencies in the NFL betting market that future bettors may be able to take advantage of.
SSRN
In this paper, I examine market inefficiencies in the NFL betting market from the 2003 season through the 2016 season. I examine the impact that division rivals and previously known determinants of inefficiencies have on the current NFL gambling market. The results show that games against division rivals have a lower chance of the home team covering the spread and the chance the game will result in an over. This result demonstrates that the sportsbooks underestimate the familiarity that teams have with each other’s players, coaches, and tendencies from playing each other twice per year. Moreover, using this result in conjunction with previously known inefficiencies, I put forth a model to test out of sample predictions. The results from these tests show profitable strategies in the point spread and totals market with a win rate of nearly 57%. Overall, this paper demonstrates inefficiencies in the NFL betting market that future bettors may be able to take advantage of.
Ramadan Effect on Stock Market Return and Trade Volume: Evidence from Dhaka Stock Exchange (DSE)
SSRN
A predictable pattern of stock market return is the violation of the efficient market hypothesis (EMH). It is well studied and evident in financial literature that stock markets around the world have predictable patterns e.g. calendar effect, behavioural effect, and Religious festival effect. Analysing market return and trading volume data of Dhaka Stock Exchange (DSE) over the period of 1st January 2002 to 30th August 2018, this study attempts to investigate the association of Ramadan, the holy month for the Muslims, with the market return, volatility and trade volume in the of DSE. Applying GJR-GARCH (p,q) model on the market return of DSE, this study concludes that Ramadan month has no significant relationship with stock market return and volatility. However, Ramadan has a significant negative impact on the daily trade volume of DSE. This is might be the outcome of decreased trading and banking hour and religious perception of investors.
SSRN
A predictable pattern of stock market return is the violation of the efficient market hypothesis (EMH). It is well studied and evident in financial literature that stock markets around the world have predictable patterns e.g. calendar effect, behavioural effect, and Religious festival effect. Analysing market return and trading volume data of Dhaka Stock Exchange (DSE) over the period of 1st January 2002 to 30th August 2018, this study attempts to investigate the association of Ramadan, the holy month for the Muslims, with the market return, volatility and trade volume in the of DSE. Applying GJR-GARCH (p,q) model on the market return of DSE, this study concludes that Ramadan month has no significant relationship with stock market return and volatility. However, Ramadan has a significant negative impact on the daily trade volume of DSE. This is might be the outcome of decreased trading and banking hour and religious perception of investors.
Regulatory Effects on Short-Term Interest Rates
SSRN
We analyse the effects of EMIR and Basel III regulations on short-term interest rates. EMIR requires central clearing houses (CCP) to continually acquire safe assets, thus expanding the lending supply of repurchase agreements (repo). Basel III, in contrast, disincentivises the borrowing demand by tightening banks’ balance sheet constraints. Using unique datasets of repo transactions and CCP activity, we find compelling evidence for both supply and demand channels. The overall effects are decreasing short-term rates and increasing market imbalances in various forms, all of which entail unintended consequences originated from the new regulatory framework.
SSRN
We analyse the effects of EMIR and Basel III regulations on short-term interest rates. EMIR requires central clearing houses (CCP) to continually acquire safe assets, thus expanding the lending supply of repurchase agreements (repo). Basel III, in contrast, disincentivises the borrowing demand by tightening banks’ balance sheet constraints. Using unique datasets of repo transactions and CCP activity, we find compelling evidence for both supply and demand channels. The overall effects are decreasing short-term rates and increasing market imbalances in various forms, all of which entail unintended consequences originated from the new regulatory framework.
Robot arithmetic: new technology and wages
RePEC
Existing economic models show how new technology can cause large changes in relative wages and inequality. But there are also claims, based largely on verbal expositions, that new technology can harm workers on average or even all workers. This paper shows – under plausible assumptions - that new technology is unlikely to cause wages for all workers to fall and will cause average wages to rise if the prices of investment goods fall relative to consumer goods (a condition supported by the data). We outline how results may change with different assumptions.
RePEC
Existing economic models show how new technology can cause large changes in relative wages and inequality. But there are also claims, based largely on verbal expositions, that new technology can harm workers on average or even all workers. This paper shows – under plausible assumptions - that new technology is unlikely to cause wages for all workers to fall and will cause average wages to rise if the prices of investment goods fall relative to consumer goods (a condition supported by the data). We outline how results may change with different assumptions.
The Cost of Clearing Fragmentation
SSRN
Fragmenting clearing across multiple central counter-parties (CCPs) is costly. This is because dealers providing liquidity globally, cannot net trades cleared in different CCPs and this increases their collateral costs. These costs are then passed on to their clients through price distortions which take the form of a price differential (basis) when the same products are cleared in different CCPs. Using proprietary data, we document an economically significant CCP basis for dollar swap contracts cleared both at the Chicago Mercantile Exchange (CME) and the London Clearing House (LCH) and provide empirical evidence consistent with a collateral cost explanation of this basis.
SSRN
Fragmenting clearing across multiple central counter-parties (CCPs) is costly. This is because dealers providing liquidity globally, cannot net trades cleared in different CCPs and this increases their collateral costs. These costs are then passed on to their clients through price distortions which take the form of a price differential (basis) when the same products are cleared in different CCPs. Using proprietary data, we document an economically significant CCP basis for dollar swap contracts cleared both at the Chicago Mercantile Exchange (CME) and the London Clearing House (LCH) and provide empirical evidence consistent with a collateral cost explanation of this basis.
The Power of (Non-)Linear Shrinking: A Review and Guide to Covariance Matrix Estimation
SSRN
Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance matrix certainly will not do. In this paper, we review our work in this area going back 15+ years. We have promoted various shrinkage estimators, which can be classified into linear and nonlinear. Linear shrinkage is simpler to understand, to derive, and to implement. But nonlinear shrinkage can deliver another level of performance improvement, especially if overlaid with stylized facts such as time-varying co-volatility or factor models.
SSRN
Many econometric and data-science applications require a reliable estimate of the covariance matrix, such as Markowitz portfolio selection. When the number of variables is of the same magnitude as the number of observations, this constitutes a difficult estimation problem; the sample covariance matrix certainly will not do. In this paper, we review our work in this area going back 15+ years. We have promoted various shrinkage estimators, which can be classified into linear and nonlinear. Linear shrinkage is simpler to understand, to derive, and to implement. But nonlinear shrinkage can deliver another level of performance improvement, especially if overlaid with stylized facts such as time-varying co-volatility or factor models.
