Annualized Sharpe Ratio Research Articles

What drives informed trading before public releases? Evidence from natural gas inventory announcements

This paper shows evidence of informed trading in the natural gas futures market before gas inventory announcements. We examine whether traders can predict the upcoming announcement by processing public information. The results show that the difference between the median forecast of analysts with high historical forecasting accuracy and the consensus forecast can be used to predict inventory surprises. This predictor explains some of the pre‐announcement price drift, suggesting that informed trading before the announcement is likely to be driven by superior forecasting rather than by information leakage. A simple trading strategy conditioned on the predictor would have generated an annualized Sharpe ratio of 1.26.

Pairs trading with a mean-reverting jump–diffusion model on high-frequency data

This paper develops a pairs trading framework based on a mean-reverting jump–diffusion model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to 2015. The established statistical arbitrage strategy enables us to perform intraday and overnight trading. Essentially, we conduct a three-step calibration procedure to the spreads of all pair combinations in a formation period. Top pairs are selected based on their spreads’ mean-reversion speed and jump behaviour. Afterwards, we trade the top pairs in an out-of-sample trading period with individualized entry and exit thresholds. In the back-testing study, the strategy produces statistically and economically significant returns of 60.61% p.a. and an annualized Sharpe ratio of 5.30, after transaction costs. We benchmark our pairs trading strategy against variants based on traditional distance and time-series approaches and find its performance to be superior relating to risk–return characteristics. The mean-reversion speed is a main driver of successful and fast termination of the pairs trading strategy.

Leveraging Herd Behavior in Foreign Exchange Markets

We examine the relationship between equity and foreign exchange markets at, and around, the WM/Reuters benchmark exchange rate known as the the 'Fix'. Execution at the Fix is a service offered by brokers provided they obtain the trade order before 4pm GMT. We have three main goals with this paper: (i) to show a connection between equities and foreign exchange markets via this window; (ii) to leverage this connection using an algorithmic trading strategy; and (iii) to rank various statistical techniques used to make predictions for trading. We are successful in all three endeavors with the best technique producing an out-of-sample annual cumulative return of 4.02% with an annualized Sharpe ratio of 3.43.

Non-linear dependence modelling with bivariate copulas: statistical arbitrage pairs trading on the S&P 100

ABSTRACTWe develop a copula-based pairs trading framework and apply it to the S&P 100 index constituents from 1990 to 2014. We propose an integrated approach, relying on copulas for pairs selection and trading. Essentially, we fit t-copulas to all possible combinations of pairs in a formation period. Next, we trade these pairs in-sample to assess the profitability of mispricing signals derived from t-copulas. The top pairs are transferred to an out-of-sample trading period, and traded with individualized exit thresholds. In particular, we differentiate between pairs exhibiting mean-reversion and momentum effects and apply idiosyncratic take-profit and stop-loss rules. For the top 5 mean-reversion pairs, we find out-of-sample returns of 7.98% per year; the top 5 momentum pairs yield 7.22% per year. Standard deviations are low, leading to annualized Sharpe ratios of 1.52 (top 5 mean-reversion) and 1.33 (top 5 momentum), respectively.

Bond Variance Risk Premiums*

This paper studies variance risk premiums in the Treasury market. We first develop a theory to price variance swaps and show that the realized variance can be perfectly replicated by a static position in Treasury futures options and a dynamic position in the underlying. Pricing and hedging is robust even in the underlying jumps. Using a large options panel data set on Treasury futures with different tenors, we report the following findings: First, the term structure of implied variances is downward sloping across maturities and increases in tenors. Moreover, the slope of the term structure is strongly linked to economic activity. Second, returns to the Treasury variance swap are negative and economically large. Shorting a variance swap produces an annualized Sharpe ratio of almost two and the associated returns cannot be explained by standard risk factors. Finally, the returns remain highly statistically significant even when accounting for transaction costs and margin requirements.

Investment performance of shorted leveraged ETF pairs

ABSTRACTWe analyze investment strategies involving triple-leveraged and inverse triple-leveraged ETF pairs by simulating daily returns over a 48-year period. Our results show that many such strategies significantly outperform the S&P 500 on a risk-adjusted basis. For example, when shorting the bear triple-leveraged ETF and the bull triple-leveraged ETF in a 2:1 proportion (while going long Treasuries), we find that the average annual Sharpe ratio is more than four times higher than for the S&P 500 and that the strategy outperforms the S&P 500 in 43 of the 48 years. Our results are robust to variations in bear/bull proportions, rebalance thresholds, and underlying parameters.

Partial Moment Momentum

Momentum profits benefit from persistent trends of the market, which can be predicted by market volatility. However, such strategies are unable to distinguish between upside and downside risk. We propose partial moments-based momentum trading strategies and find that they outperform plain momentum and volatility-scaled momentum strategies. Our best performing partial moments-based strategy shows an annualized Sharpe ratio of 1.62 during the period of 2000–2016 against a Sharpe ratio of 0.15 from a plain momentum strategy. We suggest that this greater profitability is due to the unexploited investment opportunities that arise from being able to distinguish between good and bad risk. We find strong outperformance for seven out of eight partial moments-based strategies during states of market downturn. The outperformance is robust across different time periods.

...And Nothing Else Matters? On the Dimensionality and Predictability of International Stock Returns

We use the information contained in 161 cross-sectional trade signals to explore the multidimensionality and predictability of individual stock returns in five international markets (North America, Europe, Pacific, Japan, and Emerging Markets). All markets are highly dimensional, but the most important return predictors differ across regions. Exploiting these characteristics, a single globally diversified high-dimensioned long/short return forecast strategy realizes a monthly equal-weighted (value-weighted) four-factor alpha of 4.1% (1.9%), and an annualized Sharpe ratio of 7.9 (3.4). Collectively, these results add to our understanding of market integration, data mining, and the degree of informational efficiency of global stock markets.

Variance Risk in Aggregate Stock Returns and the Return Predictability

This paper introduces a new out-of-sample forecasting methodology for asset returns using the variance risk premium (VRP). While Bollerslev, Tauchen, and Zhou (2009) demonstrate that the VRP predicts market returns up to six months, I show that the out-of-sample performance is comparably weak. In contrast, my new approach produces an out-of-sample forecast that is both highly statistically and economically significant. Specifically, I find a monthly out-of-sample R-squared of 8% and a trading strategy that produces a 0.1 gain in the annual Sharpe ratio. This new approach is motivated by the 'beta representation,' which implies that the market risk premium is related to the price of variance risk by the exposure to variance risk (beta). Hence, empirically, when the slope of the contemporaneous regression of market returns on variance innovation is larger, future returns are more sharply related to the current VRP. Also, when variance shocks explain a greater fraction of market returns, the predictions are more accurate. Furthermore, these results are extendable to the cross-section of exchange rates. The VRP of the S&P 500 Index only predicts returns of currencies that are highly correlated with changes in market variance. For those currencies, the new methodology offers considerable improvements in out-of-sample performance. These results suggest that the variance risk exposure is a key factor that determines whether and how returns are predictable by the VRP.

What Drives Informed Trading Before Public Releases? Evidence from Natural Gas Inventory Announcements

This paper shows evidence of informed trading in the natural gas futures market before gas inventory announcements. We examine whether traders can predict the upcoming announcement by processing public information. The results show that the difference between the median forecast of analysts with high historical forecasting accuracy and the consensus forecast can be used to predict inventory surprises. This predictor explains some of the pre-announcement price drift, suggesting that informed trading before the announcement is likely to be driven by superior forecasting rather than by information leakage. A simple trading strategy conditioned on the predictor would have generated an annualized Sharpe ratio of 1.26.

Related Securities and the Cross-Section of Stock Return Momentum: Evidence From Credit Default Swaps (CDS)

We document that related securities linked through firm fundamentals provide important cross-market return performance information. Using 1,074 firms during 2003-2014, we find stock return momentum for “joint” winners/losers whose past stock and CDS returns are in congruence, whereas return reversal for “disjoint” entities whose past stock returns disagree with their past CDS returns. Stock strategies combining momentum on joint winners/losers with contrarian on disjoint winners/losers outperform traditional stock momentum by 132 bps per month with an annualized Sharpe ratio of 1.11. Relative pricing of credit across related securities explains, in part, the cross-section of stock return momentum.

Relief Rallies after FOMC Announcements: How Much Do Investors Care About Uncertainty?

We find substantial positive average stock returns after FOMC announcements accompanied by the release of the Summary of Economic Projections (SEP) and press conference by the Fed Chair. A simple trading strategy of buying index futures contracts five minutes before the announcement and closing the position 55 minutes after the release would have generated an annualized Sharpe ratio of 2.10. We show that the market uncertainty, measured by the VIX index, declines significantly after FOMC meetings followed by SEP releases. After controlling for changes in the VIX, the positive post-announcement returns disappear, suggesting that these returns are related to the resolution of uncertainty after the announcement.

Intraday pairs trading strategies on high frequency data: the case of oil companies

This paper introduces novel ‘doubly mean-reverting’ processes based on conditional modelling of model spreads between pairs of stocks. Intraday trading strategies using high frequency data are proposed based on the model. This model framework and the strategies are designed to capture ‘local’ market inefficiencies that are elusive for traditional pairs trading strategies with daily data. Results from real data back-testing for two periods show remarkable returns, even accounting for transaction costs, with annualized Sharpe ratios of 3.9 and 7.2 over the periods June 2013–April 2015 and 2008, respectively. By choosing the particular sector of oil companies, we also confirm the observation that the commodity price is the main driver of the share prices of commodity-producing companies at times of spikes in the related commodity market.

Quantitative Style Investing

I introduce a systematic portfolio choice solution that significantly beats a benchmark market portfolio by an average of 34.2% per year after transaction costs. The corresponding annual Sharpe ratio is 1.97 per year compared to 0.42, over 4.7 times the size of the benchmark. A more conservative sample that excludes micro cap stocks yields an annual Sharpe ratio 2.18 times the benchmark. I construct my solution by applying multivariable cross-sectional regressions of six key stock characteristics, to aggregate forecasting signals from multiple sources. I apply simple filtering techniques to reduce estimation and sampling error, use only information known at time t, and predict expected returns. I validate the procedure by achieving commensurate results as prior studies when forming portfolios from decile sorts. However, by sorting stocks by expected returns into more extreme portfolios, i.e. 25 and 50 portfolios, I am able to further enhance performance gains over existing works.

Managing the Risk of the 'Betting-Against-Beta' Anomaly: Does It Pay to Bet Against Beta?

We study the risk dynamics of the betting-against-beta anomaly. The strategy shows strong and predictable time variation in risk and no risk-return trade-off. A risk-managed strategy exploiting this achieves an annualized Sharpe ratio of 1.28 with a very high information ratio of 0.94 with respect to the original strategy. Similar strategies for the market, size, value, profitability, and investment factors achieve a much smaller information ratio of 0.15 on average. The large economic benefits of risk-scaling are similar to those of momentum and set these two anomalies apart from other equity factors. Decomposing risk into a market and a specific component we find the specific component drives our results.

Show Me the Money: The Monetary Policy Risk Premium

Measuring the monetary policy exposure of an individual stock is challenging because the large idiosyncratic volatility of individual stock returns leads to imprecise estimates of the exposure. In this study, we generate a parsimonious monetary policy exposure (MPE) index based on observable firm characteristics that are likely to drive the exposure of firms to monetary policy. Using this index, we find that stocks whose prices react more positively to expansionary monetary policy shocks earn lower average returns, consistent with the intuition that monetary policy is expansionary in bad times when marginal value of wealth is high and thereby provides a hedge for the investors of high MPE stocks. A long-short trading strategy designed to exploit this effect achieves an annualized return of 10.56% (t-statistic of 6.19), an annualized Sharpe Ratio of 0.98, and a Fama-French-Carhart alpha of 7.56% (t-statistic 6.51) between 1975 and 2014. Our findings build a bridge between the literature that connects firm characteristics to expected returns and the literature that studies macroeconomic aggregates as predictors of asset returns.

Diffusing explosive portfolio performance evaluation of high frequency traders

Several analysts report explosive annualized Sharpe Ratios (ASRs) for investment portfolio performance evaluation of high frequency traders (HFTers) ranging from 4.3 to 5,000. This suggests that the profitability of HFT is much higher than that of other actively managed portfolios. In highly competitive financial markets where ASRs for experienced traders are often much less than 2, those numbers imply that the ASR for HFT is misspecified. Thus, HFT performance is incomparable to the performance of experienced traders, hedge funds, and other actively managed portfolios. This paper addresses the misspecification problem by introducing an efficient Sharpe Ratio (ESR) that diffuses explosive ASRs for HFT so that they are comparable to SRs for other actively managed funds. We derive a subordinate stochastic process for HFT strategy which jumps positively only when the trader executes a successful trade or stays flat otherwise. We apply the ESR formula to a sample of risk and return data on HFT strategy, and find that the ESR for aggressive HFT is 1.15, medium HFT is 2.88, and passive HFT is 1.43. For the HFT industry as a whole the ESR is between 1.07 and 1.87. Those ESRs for HFT are equivalent to SRs reported for experienced traders, hedge funds multistrategy, convertible option arbitrage, and fund of fund strategies. Thus, contrary to reports, the profitability of HFT is in line with industry norms for active portfolio management.

Evolution of high-frequency systematic trading: a performance-driven gradient boosting model

This paper proposes a performance-driven gradient boosting model (pdGBM) which predicts short-horizon price movements by combining nonlinear response functions of selected predictors. This model performs gradient descent in a constrained functional space by directly minimizing loss functions customized with different trading performance measurements. To demonstrate its practical applications, a simple trading system was designed with trading signals constructed from pdGBM predictions and fixed holding period in each trade. We tested this trading system on the high-frequency data of SPDR S&P 500 index ETF (SPY). In the out-of-sample period, it generated an average of 0.045% return per trade and an annualized Sharpe ratio close to 20 after transaction costs. Various empirical results also showed the model robustness to different parameters. These superior performances confirm the predictability of short-horizon price movements in the US equity market. We also compared the performance of this trading system with similar trading systems based on other predictive models like the gradient boosting model with L2 loss function and the penalized linear model. Results showed that pdGBM substantially outperformed all other models by higher returns in each month of the testing period. Additionally, pdGBM has many advantages including its capability of automatic predictor selection and nonlinear pattern recognition, as well as its simply structured and interpretable output function.

Diffusing Explosive Portfolio Performance Evaluation of High Frequency Traders

Several analysts report explosive annualized Sharpe Ratios (ASRs) for investment portfolio performance evaluation of high frequency traders (HFTers) ranging from 4.3 to 5,000. This suggests that the profitability of HFT is much higher than that of other actively managed portfolios. In highly competitive financial markets where ASRs for experienced traders are often much less than 2, those numbers imply that the ASR for HFT is misspecified. Thus, HFT performance is incomparable to the performance of experienced traders, hedge funds, and other actively managed portfolios. This paper addresses the misspecification problem by introducing an efficient Sharpe Ratio (ESR) that diffuses explosive ASRs for HFT so that they are comparable to SRs for other actively managed funds. We derive a subordinate stochastic process for HFT strategy which jumps positively only when the trader executes a successful trade or stays flat otherwise. We apply the ESR formula to a sample of risk and return data on HFT strategy, and find that the ESR for aggressive HFT is 1.15, medium HFT is 2.88, and passive HFT is 1.43. For the HFT industry as a whole the ESR is between 1.07 and 1.87. Those ESRs for HFT are equivalent to SRs reported for experienced traders, hedge funds multistrategy, convertible option arbitrage, and fund of fund strategies. Thus, contrary to reports, the profitability of HFT is in line with industry norms for active portfolio management.

Economic Momentum and Currency Returns

Past trends in a broad range of fundamental variables predict currency returns. We document that a trading strategy that goes long currencies in countries with strong economic momentum and short currencies in countries with weak economic momentum exhibits an annualized Sharpe ratio close to one and yields a significant alpha when controlling for standard carry, momentum, and value strategies. Moreover, the economic momentum strategy subsumes the alpha of carry trades, suggesting that cross-country differences in interest rate differentials are captured by differences in past economic trends. Finally, we study investors' expectations of fundamental variables and find the expectations to be uniformly extrapolative across countries and variables.