Risks of Counting on OHLC Costs – the Case of In a single day Drift in GDX ETF – QuantPedia

Risks of Counting on OHLC Costs – the Case of In a single day Drift in GDX ETF

Can we really depend on the opening worth in OHLC information for backtesting? Whereas the in a single day drift impact is well-documented in plenty of asset lessons, we investigated its presence in gold utilizing the GLD ETF after which prolonged our evaluation to the GDX – Gold Miners ETF, the place we noticed an unusually robust in a single day return exceeding 30% annualized. Nonetheless, after we examined execution at 9:31 AM utilizing 1-minute information, the anomaly diminished considerably, suggesting that the intense return was partially an information artifact. This discovering highlights the dangers of blindly trusting OHLC open costs and underscores the necessity for higher-frequency information to validate execution assumptions.

Background

The in a single day impact and drift in quantitative finance discuss with the phenomenon the place inventory returns throughout non-trading hours, notably in a single day, exhibit important patterns that differ from these noticed throughout buying and selling hours. The in a single day impact refers back to the tendency of inventory returns to exhibit substantial actions throughout the night time, usually influenced by market dynamics and investor sentiment.

One of many more moderen papers on this area is “The Cross-Part of Intraday and In a single day Returns” by Vincent Bogousslavsky (2021). This influential work investigates the patterns of intraday and in a single day returns and their implications for asset pricing fashions, offering invaluable insights into the habits of economic markets throughout non-trading hours.

The paper “In a single day Drift” by Boyarchenko, Larsen, and Whelan (2023) additionally explores this attention-grabbing impact. The principle discovering is that U.S. fairness returns are notably constructive throughout the opening hours of European markets, pushed by order imbalances from the earlier buying and selling day. Market sell-offs result in robust in a single day reversals, whereas rallies lead to modest reversals, indicating an uneven response to demand shocks.

We at Quantpedia explored this impact considerably, too, and found an in a single day impact on Bitcoin returns and high-yield ETF returns. By constructing on this papers we goal to increase the understanding of in a single day methods and worth drifts, providing new views and leveraging the established SPY drift paradigm and increasing it to the commodities asset class that gold (and gold mining shares) ETFs signify.

Knowledge

Gold ETF

As talked about earlier, we analyzed GLD’s in a single day, intraday, and complete efficiency utilizing historic information from Yahoo Finance. Our evaluation reveals that a good portion of GLD’s efficiency happens in a single day. The GLD ETF’s intraday efficiency over the past 20 years is negligible. These findings are in keeping with the worth motion taking place within the different asset lessons we talked about earlier than (particular person shares, fairness indices, cryptocurrencies, or high-yield ETFs).

Nonetheless, as gold is a commodity, there exist corporations specializing within the strategy of extracting this gold from the Earth’s crust (sure, we’re talking about gold miners). Subsequently, we will bridge fairness and commodity markets, by shopping for ETFs which spend money on such shares, like GDX (VanEck Gold Miners ETF). In principle, this convergent asset ought to give us the potential for mixed in a single day drift results and better income, proper?

Let’s discover that.

Gold Miners ETF

Following the identical strategy, we carried out the identical process utilizing GDX OHLC (open, excessive, low, shut) information. Our evaluation reveals a big in a single day drift of roughly 30% each year (p.a.), contrasted by a considerable unfavorable intraday drift of about -25% each year. These findings immediate a logical buying and selling technique: iteratively buying at market open and shorting at market shut. Theoretically, this strategy might yield important returns over time.

Wow, we might get wealthy fast right here! Or not? Properly, really, from the expertise, this seems to good to be true. We have to examine the underlying downside.

From our expertise, the issue is normally hidden within the opening costs of the OHLC datasets. Notably, the opening worth is derived from the primary commerce slightly than the MOO (Market-on-Open) public sale outcomes, resulting in important discrepancies between anticipated and precise opening costs as one is unable to even intently strategy getting fills in that worth area, not talking about volumes traded at that costs which should be minuscule. That is frequent downside when utilizing the OHLC information. The shut costs are normally achievable in actuality by buying and selling (shopping for/promoting) near the top of the buying and selling session or collaborating within the closing public sale by way of MOC (Market-on-Shut) orders. Traditionally, closing costs on monetary platforms reminiscent of Yahoo Finance normally align with MOC public sale costs.

Whereas executing on the shut usually presents no points for opening costs, the fact is usually very totally different. Subsequently, our standard subsequent step is all the time to revert to testing anomalies and results with higher information granularity (minute-by-minute bars, second-by-second bars, or tick information). Subsequently, let’s attempt to modify the execution of the promote sign from 9:30 AM to 9:31 AM. One minute mustn’t make a distinction, proper? For that, we transitioned to the QuantConnect surroundings as intraday TOC (Time-of-Change) information are obligatory.

SPY and GDX In a single day Results Analysis

Let’s transfer to guage the efficiency of in a single day buying and selling methods utilizing

SPDR S&P 500 ETF (SPY) and
VanEck Vectors Gold Miners ETF (GDX).

It focuses on execution timing, specifically

Market-on-Open (MOO), vs.
a particular intraday execution at 9:31 AM.

Varied Situations

SPY Buying and selling Technique:

State of affairs 1: SPY, purchase MOC, promote MOO.

State of affairs 2: SPY, purchase MOC, promote 9:31.

GDX Buying and selling Technique:

State of affairs 1: GDX, purchase MOC, promote MOO.

State of affairs 2: GDX, purchase MOC, promote 9:31.

SPY

Our backtest outcomes present solely slight variations between executing on the open worth and the particular intraday time of 9:31 AM, with the latter exhibiting rather less revenue. The in a single day impact is effectively and alive. Sure, there’s a slight lower in efficiency in the event you execute a promote order at 9:31 AM (in comparison with the hypothetical execution at 9:30), however the lower is small, and the impact remains to be current as a big a part of the SPY complete return over the past years is registered over the night time session, and it doesn’t matter so much if that night time session ends at 9.30 or 9.31.

GDX

Backtest outcomes exhibit extremely unrealistic, excessive numbers.

Then again, our backtests on the GDX ETF can’t be extra totally different. The backtest utilizing the OHLC information additionally exhibits completely unrealistic efficiency, roughly 30% each year, for the in a single day drift technique. Then again, the second situation, by which the promote sign is executed at 9:31 AM, yields a considerably extra life like end result. The efficiency of the GDX in a single day technique (earlier than charges and slippage) is 8,58% each year, with a -40,7% most drawdown and 16.9% volatility. Sure, the in a single day drift in GDX costs is certainly there, too. Nonetheless, the magnitude of the impact will not be as excessive because the evaluation utilizing the OHLC information hinted.

Dialogue & Conclusion

The in a single day drift signifies a notable sample the place a lot of the asset’s efficiency is pushed by in a single day actions. This discovering aligns with our observations in different asset lessons, suggesting a broader applicability of in a single day drift phenomena. Along with elucidating the in a single day drift in conventional asset lessons reminiscent of equities, our investigation underscores the crucial significance of strong methodological scrutiny in backtesting buying and selling methods. Particularly, the pronounced discrepancies noticed between theoretically derived and virtually executable costs spotlight potential pitfalls within the naive utility of OHLC information.

The discrepancy in backtest efficiency for GDX is attributed to the methodology used to report open costs (open costs) in OHLC information. It’s impractical to anticipate execution on the reported open costs. Subsequently, rigorous consideration needs to be paid when growing methods that presume execution at open costs. It’s advisable to conduct robustness exams and confirm efficiency with intraday execution costs, reminiscent of these at 9:31 AM, to make sure extra dependable outcomes.

Creator: Cyril Dujava, Quant Analyst, Quantpedia

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