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The Power of Financial Innovations Petko S. Kalev Professor of Finance Director Centre for Applied Financial Studies University of South Australia Business School University of South Australia
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Recent Trends and Innovations in Capital Markets Introduction to the topic – A model of a financial system - market regulators’ major goals – A model of financial innovations’ evolution Exchanged Traded Funds (ETFs) Algo (‘robot’) trading including high frequency ('fast’) trading Summary Agenda
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A Simplified Model of a Financial System Market regulators’ major goals: 1. Market efficiency 2. Market fairness Capital Market Regulator Finance Industry Academia Stock Exchange Officials
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A Model of the Evolution of Financial Innovations Industry Academia/ Stock Exchanges Market Regulators
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The power of the Exchanged Traded Funds ETFs (or ETPs) are, in themselves, innovative products Growth of ETFs over the past two decades has been extensive The main drivers are the low cost of buying and selling ETFs and the ability to gain exposure to an index (market, country, sector, others) in a single transaction
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Growth of ETFs Source: BlackRock Advisors (UK), 2012
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ETF Asset Share Diverse range of ETFs tracking known indices with equity and fixed income ETFs sharing about 87% of total assets
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ETFs and Innovations Focus of attention will be on ETF categories: – Inverse/Leverage – Alternative – Actively Managed
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Inverse and Leveraged ETFs Provide multiples of a daily index return: +2, +3, -1, -2, -3 multiples of the expected index returns Extensive use of financial derivatives to achieve these returns Rebalance the portfolio daily Have become popular due to the exposure to the market at multiples – very attractive to speculators
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ProShares UltraPro Short Russell 2000 ETF (SRTY) Price Information as of 6/20/14 NAV $36.17 NAV Change -$0.41 Market Price Closing $36.18 Market Price Closing Change -$0.37 Daily Trading Volume 354,383 SRTY seeks daily investment results corresponding to 300% (triple) of the inverse of the daily performance of the Russell 2000 Index SRTY seeks a return of -300% of the return of an index for a single day Fund launched on Feb 9, 2010
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Spread ETFs Spread ETFs have a long position on an index ETF combined with a short position on another index ETF One of these two ETFs are leveraged Example: a fund launched on 24.02.11 – FactorShares 2X S&P 500 Bull/USD Bear ETF (FSU) – Long the S&P 500 index at a multiple of two and short the USD ETF
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Spread ETFs cont. These ETFs are structured such that for a given macroeconomic event, the returns of each of the ETF in the spread ETF have limited correlation Some diversification potential may be achieved rather than simply investing in a multi-asset universe (Roll, 2011)
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Actively Managed ETFs ETFs where the portfolio manager manipulates the ETF asset allocation more often May take advantage of analysts’ reports Enhances the ability of the manager to look for a nearer term of returns Allows for identification of hot sectors that may arrise due to sentiment rather than fundamentals
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Actively Managed ETFs cont. Measurement on performance is easily done though known techniques (alpha) Investors may gain benefit from investing in these ETFs as they aim to beat the benchmark ETFs provide a larger choice for investors when tracking a given index – passive vs active strategies The transparency of ETF holdings limits the expansion of actively managed ETFs
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Regulatory Issues Many of these new innovative ETFs have attracted some attention from regulators Much of these concerns result from: – Counterpart agreements – Volatility – Limited academic studies
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Regulators Issues cont. The growth of ETFs has caused providers to look at niche markets and exotic indices Exotic indices generally comprise of assets that are illiquid, hence difficult to purchase all of the necessary components ETF providers may need to enter into agreements with a counterparty to guarantee the return Generally the counterparty is a bank Exposure to the desired asset class can be structured as a swap
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Counterparty agreements Any ETF that replicates an index through derivatives will be subject to a counterparty agreement Commodity ETFs utilise derivatives (Corn, pork bellies, copper etc.) Exotic index tracking ETFs, Leveraged/Inverse ETFs and other alternative ETFs all utilise swaps
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Counterparty agreements cont. The Global Financial Crisis and Lehmann Brothers has raised concerns for counterparty agreements Of particular concern is: – What if the counterparty cannot pay its obligations? The provisions that are set aside for such situations may not cover the losses in these situations Disclosure to investors on the use of derivative products may not be sufficient Different jurisdictions have different policies regarding the amount and nature of the collateral put aside for counterparty default
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Limited academic studies Leveraged and Inverse ETFs (LETFs) rebalancing is done during the last hour of the trading (Cheng and Madhaven, 2009) – concern due to possible liquidity constraints Rebalancing of LETFs is similar to portfolio insurance strategies (Tuzan, 2013) – Tuzan (2013) shows a “1% increase in a broad stock index induces LETFs to initiate rebalancing flows equivalent to US$1.04 billion worth of stock” – Together with trading during the last hour results in excess volatility in the underlying stocks – Rebalancing may be predictable to opportunistic investors who may place orders anticipating LETF, rebalancing flows and resulting in a cascade effect
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Limited academic studies cont. Stock ownership within an ETF has recently been studied in two academic papers – Ben-David et al. (2013) investigate the primary question of whether ETFs increase volatility in underlying stocks – Da and Shive (2013) investigate the arbitrage activity between stocks and ETFs to document the transfer of non- fundamental shocks from ETFs to the stocks that they hold In both of these papers the results show that price shocks are transferred to the underlying constituents – Concerns here are that ETFs are moving constituent stock prices out of equilibrium having a direct impact on the market
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Algorithmic Trading Algorithmic trading (AT) began in late 80s Several hedge funds employed AT to efficiently pursue their quantitative trading strategies Technological developments over the past decade have substantially increased the use of computer algorithms by equity investors AT now accounts for the majority of the trading volume in developed countries
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Types of Algorithms Execution Algorithms Generally used by investors to execute existing trade intentions Volume-Weighted Average Price (VWAP) is commonly used Situational Algorithms Generally used by traders Profit by monitoring market data and news (no prior trading intentions) High-Frequency Trading (HFT) is a subset, which emphasizes trading speed
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Media Concerns Source: The Economist, 11 th Aug, 2012
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HFT - Stability and Integrity of the Equity Markets "HFT firms have a tremendous capacity to affect the stability and integrity of the equity markets. Currently, however, high frequency trading firms are subject to very little in the way of obligations either to protect that stability by promoting reasonable price continuity in tough times, or to refrain from exacerbating price volatility.“ (SEC Ex-Chairman Mary Schapiro Sep. 22, 2010)
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Another View on the HFT “There is also the misperception that high- frequency traders are speculators who move markets to extremes. In fact, the vast majority of HFT involves looking for very small arbitrage opportunities, as between futures and cash markets or between the prices of exchange traded funds and their net asset values. These actions do not create volatile markets, they close gaps across markets and increase market efficiency.” (Burton Malkiel, The Financial Times, Dec. 14, 2009)
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Another View on the HFT cont. “Technology has dramatically improved the efficiency of our trading markets. Rather than putting the individual investor at a disadvantage, HFT cuts costs significantly for everyone. Individual investors are the ultimate beneficiaries when their pension funds and mutual funds can transact large volumes of trades anonymously with great speed and at lower cost.” (Burton Malkiel, The Financial Times, Dec. 14, 2009)
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Intraday Effects Algorithmic Trading (AT) increases liquidity (Hendershott, Jones & Menkveld 2011) Algo trades have less price impact (Hendershott, Jones & Menkveld 2011) AT trades are more profitable (Frino, et al. 2013) Algo Traders (Aters) can better monitor the market (Hendershott & Riodan 2014) HFT decreases spreads, increases displayed depth and lowers short-term volatility (Hasbrouck & Saar 2013) ATers are more patient while their trades are more cost effective (Kalev, Lian & Zhou 2014)
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VWAP of AT and non-AT Traders VWAP, AT and nonAT traded prices - “PMV” on 4 th Aug 2009
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VWAP of AT and non-AT Traders VWAP, AT and nonAT traded prices - “PMV” on 4 th Aug 2009
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VWAP of AT and non-AT Traders VWAP, AT and nonAT traded prices - “PMV” on 4 th Aug 2009
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Conclusions With every new innovative product there are hurdles and challenges to ensure market efficiency and fairness ETFs provide a diverse range of investment opportunities for all types of investors Stocks with lower AT activity experience greater price swings in volatile markets However, with these new investment opportunities come significant regulatory challenges
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Thank you! Any questions?
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