Hypotheses

Faithful port of Quantiacs' MIT-licensed 'strategy-futures-trend-following' (strategy.ipynb, multi-pass `strategy(data)` function); credit to Quantiacs. The source's universe is the Quantiacs futures set. Our platform cannot trade CME futures, so the basket is OKX USDT perpetual futures with daily history back to at least 2021-01-24: BTC, ETH, SOL, ADA, LINK, BCH and TRX. OKX is under-represented in the corpus at 2.7%. RULES, identical per asset, computed on each asset's own 1-DAY close: ma = WMA(close, 200), a TA-Lib linear-weighted moving average with weights 1..200, newest weight highest. roc = ROCP(ma, 20) = ma[t]/ma[t-20] - 1. sideways_threshold = 0.02. positive_trend = roc > 0.02; negative_trend = roc < -0.02; sideways = |roc| <= 0.02. side_positive_trend = the last non-sideways state was positive; side_negative_trend = the last non-sideways state was negative; both are False before any non-sideways bar. Position state machine per asset, a port of the xarray code: start at 0. On each bar, in this order: if positive_trend, raw = +1; if negative_trend, raw = -1; otherwise raw is unset. fp = the forward-filled previous position, taking raw into account. If side_negative_trend and fp > 0, raw = 0. If side_positive_trend and fp < 0, raw = 0. position = raw if set, else the previous position (ffill), initialised to 0. In effect the asset goes long when the WMA's 20-day change exceeds +2% and short when it is below -2%. While it is sideways the position is held. Note that a positive trend sets side_positive_trend, so a long can only be stopped by a negative regime, which already flips it short through sell_signal. The stop branches therefore rarely produce a flat state, and the developer must reproduce the source's ordering exactly rather than simplify it. WEIGHTS: output = position / sum(|position|) across the basket, so each non-flat asset gets ±1/N_active of the gross book and nothing is held when all are flat. PLATFORM ADAPTATIONS (not in the source): (1) Gross notional = account equity × leverage 1.0, so each active leg's notional = equity / N_active, signed. (2) Execution: Quantiacs applies day-t weights from the next day. On a 24/7 venue our `next_bar_open_fill` capability is `use_equivalent`, so orders are market orders at the signal bar's close, which equals the next daily bar's open. (3) The source rebalances to its target weights every day. To avoid paying taker fees on tiny drift trades, a leg is resized only when its target sign changes, N_active changes, or its notional drifts more than rebalance_tolerance (fixed at 20%) from target. This is the only rule added beyond the source. (4) The source has no stop-loss, and none is added; exits come only from the state machine. (5) OKX fees are 0.05% taker, about 0.10% round trip, and funding is applied through the ledger. WARM-UP: indicators need 200 + 20 bars. The registered warm-up is 360 daily bars, which also covers the tunable maximum of 300 + 40. This fixes the prior contract's 1825-bar warm-up, which was the source's 5-year `lookback_period` data window rather than an indicator requirement and exceeded the basket's joint history. The source's own performance claims are unverified; our backtest decides.

A cross-venue, market-neutral relative-value trade between the tokenised-gold perpetual PAXGUSDT on Binance USD-M and spot gold XAUUSD.SPOTMETAL (Dukascopy XAU/USD mid). One PAXG token is redeemable for one fine troy ounce of LBMA gold, so the ratio PAXG/XAU should stay close to its slow structural level: a small persistent premium or discount driven by mint/redeem friction and perp funding. Crypto order flow (leveraged longs and shorts in the perp, liquidations, risk-off flows from stablecoin holders) pushes the perp away from that level. The OTC gold market does not follow. Because mint/redeem and cross-venue arbitrageurs exist, these dislocations should mean-revert within hours to a day or two. The strategy measures dev = 100*(PAXG_close/XAU_close - 1) - rolling median of the same premium over the last `baseline_hours` aligned hours. It takes the hedged position only when the deviation is both statistically extreme (|z| >= z_entry versus the rolling std) AND economically large (|dev| >= min_dev_pct, which by construction exceeds the ~0.115% two-leg round trip). Short the rich leg, long the cheap leg, dollar-neutral. Diversity: this is cross-venue (BINANCE + SPOTMETAL; the portfolio is 7.9% cross-venue against a target of 15% or more), long+short (20.7% against 45% or more), and uses SPOTMETAL (3 of 4323 experiments) plus a PAXG perp that is barely in the corpus. It is not the failed 'PAXG Weekend Safe-Haven Carry'. That was a directional, long-only, calendar trade on PAXG spot. This is a hedged spread with no gold beta and no weekend holding. It is also not the failed BCH/LTC distance pair, whose hedge ratio left one leg at ~5% notional. Here both legs are sized to equal dollar notional, and the two assets are economically the same claim. Execution: Binance is 24/7, so a market order at the signal bar's close stands in for a next-bar-open fill (capability next_bar_open_fill = use_equivalent). On the SPOTMETAL session venue the platform fills a bar-close decision at the next bar's open (next_open_fill, supported). The developer must therefore treat the XAU leg's fill as the next open, and both legs are submitted on the same decision. Protective stops are platform-matched intrabar stops on the spread P&L, evaluated per bar. History: PAXGUSDT.BINANCE 1H bars start 2025-03-27 (~18 months). XAUUSD.SPOTMETAL 1H runs from 2003, so the binding history is the PAXG perp. Pre-study note: I tried to measure the premium's distribution and firing rate, but the catalog scan timed out. Firing frequency is therefore NOT measured. Expected firing comes from the threshold design below, and the min_dev_pct floor is tunable so the optimizer can find a region that both fires and clears costs.

Faithful port of Myquant's Apache-2.0 open-source strategy "KDJ_STOCK" (https://github.com/myquant/strategy/blob/17595e6bf4a118e1fa87c90bfb0fd78afa69a60b/KDJ-STOCK/python/kdj_stock.py). Credit goes to the author, Myquant. Default parameters come from the repository's companion config KDJ-STOCK/python/kdj_stock.ini at the same commit: bar_type=86400 (daily), fastk_period=5, slowk_period=3, slowk_matype=0 (SMA), slowd_period=3, slowd_matype=0 (SMA), slowk_bid=25, slowd_bid=25, slowk_sell=75, slowd_sell=75, is_fixation_stop=0, is_movement_stop=1, stop_fixation_profit=0.20, stop_fixation_loss=0.068, stop_movement_profit=0.068, open_max_days=22, hist_size=30, open_vol=2000 shares, commission 0.03%, benchmark SHSE.000903 (CSI 800). The source is a long-only, daily-bar strategy over a pool of China A-shares, so it is ported to its home market: venue CNEQ (China A-shares, CASH account, long-only, 1x, platform fee 0.05% per side, about 0.10% round trip), 1-DAY bars, with daily history from 2018. The source's stock pool (stock_pool.csv) is not in the repository. The Research Lead therefore chose a fixed pool of 10 liquid CSI-300 large caps whose 100-share lot fits the per-name allocation: 601318 (Ping An), 600036 (CMB), 601398 (ICBC), 600887 (Yili), 601166 (Industrial Bank), 600030 (CITIC Securities), 000333 (Midea), 000651 (Gree), 600276 (Hengrui), 600900 (Yangtze Power). Each name is traded independently with identical rules. Platform adaptations: (1) Sizing: the source buys a fixed 2,000 shares, or as many 100-share lots as available cash allows. Here that becomes position_fraction=0.10 of current account equity per name, capped by available cash and floored to whole 100-share board lots (the lot rounding is kept from the source). If that floors to zero lots the entry is skipped, as in the source, but the cooldown counter still starts. (2) Fills: the source orders at bar.close (or price 0, a market order) on the daily bar. CNEQ has no modeled order latency, so a market order submitted on the daily bar fills at that bar's close, which matches the source. (3) Fees: platform CNEQ fees replace the source's 0.03% commission. (4) The source's live-mode setup (rebuilding the entry high from open positions at restart) and its adj_factor re-scaling are not needed: our bars are already adjusted and the backtest starts flat. No intrabar stops are used: the source evaluates every exit on the completed daily bar's close, and the port keeps that. T+1 is respected by construction, because every decision is made once per daily bar and entry and exit never fall on the same bar. Any performance the source claims is treated as unverified.

Derived by the Research Lead from 小草, "资金费率策略近况和推荐操作" (FMZ digest, 2021-12-02, https://www.fmz.com/digest-topic/8469, building on the strategy described at https://www.fmz.com/digest-topic/6381). The article describes a hedged perpetual funding arbitrage but does not specify its rules: long spot and short perpetual on coins with high positive funding, opened when the perp trades at a premium to spot (开仓溢价) and closed when that premium turns negative (平仓溢价). It makes three recommendations: (1) concentrate in a FEW high-funding coins rather than spreading across many, (2) use more exchanges, (3) seize extreme-funding events. What the figures show: two position tables from the author's live robot (digests 8469 and 6381) list per coin the short perp quantity, the matching spot quantity, an open premium % (typically 0.03–0.3%), a close premium % (0.1–0.18%), target position, average funding % (about 0.03%/8h in Dec-2021, versus about 0.15–0.17%/8h earlier in the bull market), current funding and reference annualised yield. A cross-exchange funding table shows OMG at -2.4% (Binance) to -5.4% (FTX) during an airdrop. Two further images are banners with no data. The linked code (strategy 333315) is only a funding-rate dashboard across exchanges. The robot page could not be read (FAILED). No exact rules were available, so the rules below are mine. OPERATIONALIZATION: the universe is 8 alts that appear in the author's own position tables and are listed on both Binance Spot and Binance USD-M: SAND, ICP, VET, ATOM, ANKR, 1INCH, EGLD, IOTA. Each coin is a pair of legs of equal USDT notional: long <COIN>USDT.BINANCE_SPOT (cash) and short <COIN>USDT.BINANCE (perp). The book is therefore delta-neutral, and PnL is funding received plus basis change minus fees. All 16 instruments use 1-HOUR bars. Funding is read point-in-time with supp_as_of / supp_window on the perp, never by abs() timestamp matching. At each 8h funding settlement (00/08/16 UTC bar close), coins are ranked by trailing mean funding over the last `funding_lookback` settlements. Only the top `top_n` whose mean exceeds `entry_funding_min` are held (recommendation 1, concentration). Recommendation 2 (multiple exchanges) is deliberately left out of this test: keeping one exchange means both legs share a venue's funding and prices. Recommendation 3 (OMG-style extreme negative funding) would need borrowed spot to short, which a CASH account cannot do, so only the positive-funding side is tested. Execution: every order is a market order at the signal bar's close, which is the 24/7 equivalent of a next-bar-open fill. The spot leg is long-only and unleveraged; the perp short is at 1x notional matching the spot leg, with leverage fixed at 1.0. Cost arithmetic: a full pair round trip pays 2×0.10% spot + 2×0.05% perp = 0.30% of one leg's notional (0.15% of gross two-leg notional). The source's late-2021 average funding is about 0.03%/8h (0.09%/day). Over a minimum hold of 7 days (21 settlements), expected funding is about 0.63% per pair round trip before basis. Adding the entry premium of at least 0.05% as basis converges gives about 0.68% gross versus 0.30% cost per leg-notional, so about 0.38% net per pair, or about 0.19% of gross notional per leg-trade. In the higher-funding regimes the source shows (0.15%/8h), the capture is several times that. This is a cross-venue (BINANCE_SPOT + BINANCE), market-neutral, multi-instrument hypothesis. Those buckets are under-represented in the portfolio (cross-venue 7.9% versus the ≥15% target).

Derived by the Research Lead from "BreakdownLevelDay" by MQL5 Code Base (library) https://www.mql5.com/en/code/17058: From the source: previous-day high/low Buy/Sell Stop pair placed at TimeSet 00:00, OCO cancellation, fixed SL/TP, no breakeven or trailing, and defaults Delta 6 / SL 2000 / TP 2000 read from the author's screenshot. Research Lead choices: XAUUSD.SPOTMETAL 1h instead of the EURUSD-type chart, trading day = SPOTMETAL session, points converted to % of price (0.004% / 1.4% / 1.4%), equity-relative 1x sizing instead of a fixed lot, OpenStop=false under netting, daily cancel-and-replace of unfilled orders. Port of the MQL5 Code Base Expert Advisor 'BreakdownLevelDay' (idea by Vladimir Khlystov, MQL5 code by barabashkakvn, https://www.mql5.com/en/code/17058). The EA trades daily breakouts with pending orders. At TimeSet it places a Buy Stop at the day's high + Delta and a Sell Stop at the day's low - Delta, each with fixed SL and TP. When one fills, the other is deleted. With TimeSet = 00:00 it trades the breakout of the PREVIOUS day. The source figures (MT terminal screenshots, EURUSD-like 1.43-1.50 prices, H1 bars, 4-12 Feb 2009) show the tested settings: TimeSet 00:00, Delta 6, SL 2000, TP 2000, Lot 0.10, risk 0, NoLoss 0, trailing 0. The charts mark one buy-stop/sell-stop pair at each midnight (dashed day separators), fills at the prior day's extremes, and SL/TP exits about 200 pips (~1.4% of price) from entry. The third attachment is an MQL5 Freelance banner with no trading content. The source is an FX EA, and we have no FX majors. Spot gold XAU/USD (XAUUSD.SPOTMETAL) is the closest supported OTC/FX-style 24x5 market with a daily session, and it is almost unused in the corpus (1 of 4,319 experiments). Adaptations: (1) 'Day' = the SPOTMETAL trading day (18:00 to 17:00 New York; use session_date_of, never a calendar date). TimeSet 00:00 maps to the session open: on the first 1-HOUR bar of each new trading day, read the completed previous trading day's high and low from the 1h bars. (2) Point distances become percentages of price: Delta 6 points on a 5-digit ~1.45 quote = 0.004% and becomes delta_pct = 0.004%. SL/TP 2000 points = 0.0200 on ~1.45 = 1.38% and becomes sl_pct = tp_pct = 1.4% from the fill price. (3) Fixed lot (risk=0) becomes equity-relative sizing: notional = 100% of equity (leverage 1.0), so one SL hit costs ~1.4% of equity. (4) NoLoss and trailing stay disabled, matching the figure. (5) OpenStop is not shown in the figure, and the account is netting (hedge_mode unsupported), so OpenStop = false: no new pending pair is placed while a position is open. The screenshot shows overlapping hedged positions; those cannot be expressed here, and only one net position exists at a time. (6) Unfilled pending orders are cancelled and replaced at the next trading-day open (the EA re-places them every day at TimeSet). Execution: the entry stops are platform-matched intrabar stop_market orders (capability intrabar_stop: supported), not exchange-hosted. SL/TP are an intrabar reduce-only stop plus a take-profit limit (a bracket) attached on fill. When one entry stop fills, the opposite one is cancelled (OCO). If a single 1h bar touches both stops, the engine's adaptive OHLC ordering decides, and the second order is cancelled as soon as the first fills. Overnight financing on SPOTMETAL (long pays fed funds + 2.5%/yr, short receives fed funds - 2.5%/yr, Wednesday x3) is charged by the platform and is part of the test. Fee arithmetic: RT cost ~0.015% spread plus ~0.02% per night held. With symmetric 1.4% SL/TP, the break-even win rate is ~51.3% including costs. The edge needs only a slight continuation bias after a prior-day extreme breaks: a 53% hit rate gives ~+0.08% per trade gross of financing and ~+0.05-0.06% net, about 4x the round-trip cost.

Adapt Chaos's Apache-2.0 TqSdk distance_based.py to BCHUSD.HYPERLIQUID and LTCUSD.HYPERLIQUID, preserving WINDOW=30, K_THRESHOLD=2.0, CLOSE_THRESHOLD=0.5, MAX_HOLD_DAYS=10, STOP_LOSS_PCT=0.05 and POSITION_RATIO=1.0. The original SHFE.rb2305/hc2305 contracts and February–April 2023 test dates are replaced with supported perpetuals and their common available history. The original samples developing daily closes when a new daily bar appears, effectively opening quotes rather than finalized daily closes. This adaptation explicitly substitutes synchronized completed 1-DAY closes, submitting market orders at the signal close, the platform's continuous-market equivalent of next-bar-open execution. It therefore tests an adapted daily-close version rather than an exact reproduction of TqSdk update timing. Replace the original fixed 200 lots with equity-relative quantities; preserve its price-ratio direction, two-decimal rounding and daily recomputation of the exit-accounting quantity. Actual hedge quantity remains frozen during each trade. Source statistics are unverified and exclude platform execution costs.

Derived by the Research Lead from Myquant's Apache-2.0 BOLL_STOCK: preserve its long-only, three-band rising entry, band-decline exit, daily action lock, re-entry cooldown and optional close-evaluated protective exits. The supplied Python file reads all trading parameters from boll_stock.ini without assigning defaults; attempts to retrieve that configuration failed. Therefore this is a distilled specification with explicitly chosen provisional parameters, not a verified exact-default reproduction. Use CSCO.USEQ daily split-adjusted bars, 1x exposure and platform spread/impact costs. Chosen parameters are boll_period=20, nbdev_up=2.0, nbdev_down=2.0, ma_type=0 (SMA), hist_size=60, open_max_days=10, is_fixation_stop=1, is_movement_stop=1, stop_fixation_profit=0.10, stop_fixation_loss=0.05 and stop_movement_profit=0.03. Replace the source's configured share lot with equity-relative sizing. These values must not be attributed to Myquant. Source: [BOLL_STOCK by Myquant](https://github.com/myquant/strategy/blob/17595e6bf4a118e1fa87c90bfb0fd78afa69a60b/BOLL_STOCK/python/boll_stock.py).

Derived by the Research Lead from "Universal_Investor" by MQL5 Code Base (library) https://www.mql5.com/en/code/1076: Preserved the source's directional ordering, joint slopes, reversal exits and loss-dependent sizing; supplied the unavailable numerical defaults, close-based indexing, BCH 4H venue mapping and explicit equity-relative reduction formula. Derived from Olek's Universal Investor, as described in MQL5 Code Base: preserve its EMA-versus-LWMA ordering, agreement of both slopes, and opposite-ordering exits. Trade BCHUSD.HYPERLIQUID on 4-HOUR close-stamped bars, long and short. The downloadable code could not be retrieved, so numerical defaults, applied price, slope indexing and the loss-reduction formula are unverified; the choices below are explicitly platform completions, not claimed original defaults. Use closing prices, a shared 20-bar smoothing period, consecutive completed-bar slopes, equity-relative sizing and a specified loss-streak reduction. The inspected attachment is a MetaTrader 5 promotional image showing a code editor; it identifies no reliable instrument, timeframe, indicators, marked trades or performance evidence. No pre-study or performance screening was performed.

忠实移植发明者量化-小小梦《平衡挂单策略(教学策略)》的现金—币值平衡公式、双边限价单和成交后撤单重建机制，交易DOTUSDT.BINANCE_SPOT，不做空、不加杠杆。原文未给出可确认的BalanceDistance默认值，因此明确采用初始权益的5%作为固定报价币距离；这是资本相对化的研究选择，不是作者默认参数。启动时将50%权益买入DOT，另外50%保留USDT，随后只按原公式调整库存，不加趋势过滤、止盈、止损或周期性清仓。使用1-HOUR bars进行历史限价撮合，挂单仅在提交后的行情中有效，不能使用当前已完成bar的高低价追溯成交。四张附图均已查看：首图为教学封面；第二图显示OKEX BTC/USDT初始1 BTC与10000 USDT及账户状态；第三图为2020年收益和回撤展示；第四图显示双边挂单、买单成交后撤销另一单并重建的日志。附图没有技术指标或明确K线周期，其收益数字不作为有效证据。原文章页面已核对，策略独立页面完整源码仍受登录限制；实施依据是提交的完整代码及文章代码。平台支持现货净持仓与限价订单，本策略不需要独立多空持仓、指定同bar成交顺序或离线保护订单。

忠实移植善《“移动平均线”操作的简单演示（My语言版）》中“双移动平均线策略的小幅改善”：保留日线、SMA5/SMA10、连续两期同向斜率确认和反向交叉退出。作者明确允许迁移至数字货币；Research Lead 选择 BCHUSD.HYPERLIQUID，并补充资本相对仓位，未添加新闻、资金费率或价格过滤器。所有决策仅使用已完成日线，市价单在信号日线收盘提交并按平台规则成交，不要求下一交易时段开盘成交。六张附件均已查看：201为文章封面；202为螺纹钢指数 rb888 日线、MA5、成交量及密集买卖箭头；203为对应收益曲线；204为同一螺纹钢日线和较疏交易箭头；205为未确认双均线收益曲线；206为斜率确认版本收益曲线。图片展示的趋势与震荡、交易标记及收益均属于原文演示，不能证明 BCH 上有效。本文多个版本属于同一均线机制家族，本次只提交一个固定参数实验。[原文及代码](https://www.fmz.com/digest-topic/4001)

Derived by the Research Lead from MQL5 Code Base contributor flaab's The classic Turtle Trading Indicator: retain directional Donchian breakouts, shorter-channel exits and ATR protection, completing the indicator with explicit portfolio execution and sizing. Use independent daily-bar sleeves on BCH, ETC and FIL perpetuals. The attached EURUSD daily chart shows blue/red entry arrows and exit dots; the alert image mentions re-entry after a losing signal. Both attached backtest reports show TradePeriod=35, StopPeriod=20, ATRPeriod=30 and ATRNumber=2, with StrictEntry=false, StrictExit=true, StrictStop=true and Greedy=false. Their performance claims are unverified, and the reports themselves warn about crude modeling. Adopt those visible numeric settings as baselines: close-confirmed entries, intrabar shorter-channel exits and intrabar ATR stops. The downloadable indicator code could not be retrieved, so this is a distilled contract rather than a claim of byte-for-byte indicator reproduction. Research Lead additions are the three-asset universe, Wilder ATR definition, explicit stop ratchet, equity-relative risk, exposure caps, no pyramiding and the re-entry lifecycle below. All orders use the supported platform execution model; protective stops are matched intrabar by the platform, without requiring exchange-hosted protection. No source performance filter is imposed.

Derived by the Research Lead from MQL5 Code Base's Exp_2pbIdealMA_ReOpen by GODZILLA: test bar-close moving-average crossings and additions after favorable movement from the latest fill. The page describes these rules and reports tests without stop-loss or take-profit. The downloadable EA and custom-indicator files could not be retrieved, so their formulas, defaults and exact exit implementation remain unverified. This is a disclosed adaptation using standard EMAs, not a reproduction of 2pbIdeal1MA or 2pbIdeal3MA. Research Lead choices are BCH and ETC Hyperliquid perpetuals, 4-HOUR bars, EMA periods 20/60, percentage-based addition spacing, equal equity-relative tranches, bounded additions and opposite-cross exits. Orders execute at the signal bar's close. Source performance claims are unverified.

Derived by the Research Lead from 康德《通过合约对冲策略实现资产移动的思考》: 移植其价差扩大时增加对冲仓位、指定空腿发生亏损时同时平掉两腿的明确规则。原文目的是尝试把一家交易所的损失对应为另一家的收益，并未提出稳定盈利或真正提取被冻结资产的办法。本实验保留这一目的，不改写为价差收敛止盈策略。将原来的 OKCoin/Huobi BTC 币本位季度合约替换为平台支持的 OKX/Bybit BTC USDT 线性永续合约；这是市场与计价适配，不是对原季度合约的精确复现。保留加仓步长20美元及亏损阈值0.001 BTC，后者按判断时 BTC 价格折算为USDT。将每次10张合约改为权益比例、等BTC数量的双腿订单，并增加固定仓位上限和组合风险退出。使用真实报价事件，不从日线或分钟线推断可成交跨所价差。已查看全部三幅图：第一幅是主题封面；第二幅展示2020-09-30至2020-10-19的BTC/USD双平台模拟Tick配置、日线主周期和分钟基础周期；第三幅展示两个平台方向相反的账户盈亏，没有K线、指标或标注交易信号。图中结果未经本平台验证。

Derived by the Research Lead from 发明者量化-小小梦《手把手教你给策略增加多图表支持》: 将示例展示的15分钟EMA与日线MACD操作化为顺大周期方向的回撤再启动实验。原文明确只是绘图，没有交易规则；本策略的方向过滤、入场、退出及风险管理均由Research Lead补充，不是作者策略。保留示例EMA5/20、日线MACD12/26/9和1小时、15分钟、日线三个观察尺度。第一张配图是教程封面，无交易标记；第二张展示小时价格下跌后修复、15分钟双EMA上穿和日线MACD仍偏弱的不同周期冲突，无标注买卖点，图中代码对应BTC季度期货。研究选择BCHUSDT.OKX线性永续，避免复用BTC和不支持的OKX逆向合约 sizing；小时ATR用于风险尺度，15分钟用于触发，已完成日线用于方向。所有订单在信号收盘提交市价单；保护性止损由平台盘中匹配。

Derived by the Research Lead from Arturo López's Stretch Breakout Channel: implement the article's one-sided Opening Range Breakout Preference on ETCUSDT.OKX using 5-minute execution bars and completed UTC daily bars. Preserve the source's 10-day Stretch calculation, entry threshold and opposite-channel protective stop. Complete its unspecified trend preference with a daily SMA, sizing with an equity-relative risk budget, and holding period with a same-day exit. A UTC day is a research-defined session on this continuous market. Because its opening price becomes available when the first 5-minute bar closes, orders are armed then, prospectively; days whose first bar already touched the intended entry are skipped. Stops trigger intrabar in the platform; exchange-hosted protection is not required. The supplied figure shows NZD/USD during June–August 2013, retail buy/sell stop clusters and buying-volume annotations, with no identifiable candle interval or Stretch channel; it supplies no additional executable rules. Source performance claims remain unverified.

Faithful port of the explicit trading rules in MQL5 Code Base contributor flaab's The Turtle Trading Channel, applied independently to XLM and ETC perpetuals using 1-DAY bars. Preserve the source's close-confirmed 20/10 and 55/20 systems, previous-S1-loss filter, failsafe entry, four-unit pyramiding and drawdown-adjusted risk. Research Lead completions are Wilder ATR(20), shadow-trade bookkeeping, startup state and portfolio exposure caps. The supplied figure shows EURUSD SELL alerts, a stepped blue channel and a dotted line following a sharp rally and pullback; its timeframe is unreadable and it supplies no performance evidence. This ports the article's stated rules, rather than claiming a byte-for-byte reproduction of its indicator code. Orders execute at the signal close; protective stops trigger intrabar in the platform. No independent opposing positions or exchange-hosted protection are required.

Derived by the Research Lead from je-suis-tm's London Breakout backtest: test whether London opening participation extends a breakout of the preceding hour's range on spot gold. Source: https://github.com/je-suis-tm/quant-trading/blob/611b73f2c3f577ac5b28aaa19ac8c43d3236c7a5/London%20Breakout%20backtest.py. Use XAUUSD.SPOTMETAL 5-MINUTE bars and Europe/London local time, including DST. This is a research-only gold adaptation, not a reproduction of the source's GBPUSD results. Orders execute at completed signal-bar closes; protective stops trigger intrabar in the platform. No next-session-open fills or exchange-hosted protection are required.

Test whether asymmetric sensitivity to market declines predicts subsequent relative underperformance across BCH, LTC, ADA and DOT Hyperliquid perpetuals. Using synchronized 4-HOUR bars, buy the instrument with the lowest downside-minus-upside beta and short the highest, holding equal entry-dollar notionals for seven days. This tests persistent downside fragility rather than cumulative-return momentum, price-pattern reversal or funding carry. Market entries execute at the completed signal bar's close; protective stops trigger intrabar through platform matching. Request up to the available approximately 2.3 years of 4H history, using only dates when all four instruments exist. No current market-regime assertion or preliminary performance test is used.

Faithful rule port of Myquant's Apache-2.0 ma_multi_signals.py at commit 17595e6bf4a118e1fa87c90bfb0fd78afa69a60b, adapted to LTCUSDT.BYBIT. Preserve the Python fallback settings: window_size=200, timeperiod=20, source_bar_type=60 seconds, threshold=0.235, tick_size=0.2, half_tick_size=0.1, significant_diff=0.52, eps=0.000001 and trade_unit=[3,1,2,0]. Rename the source's bar_type parameter to source_bar_type; the platform's reserved bar_type remains the string LTCUSDT.BYBIT-1-MINUTE-LAST-EXTERNAL and is excluded from the optimization parameter plan. The source's ma.ini was not supplied, so these are Python fallback values, not verified INI settings. Preserve the two-bars-apart crossing test, latest-trade confirmation, staged additions and opposite-signal liquidation. Replace contract lots with equity-relative quantities while preserving the 3:1:2:0 schedule. Submit limit orders at the latest observed trade price, as the source's priced orders imply; fills are not guaranteed. The source contains an indexing defect: after four same-direction opportunities, its no-opposite-position condition still permits an out-of-range trade_unit access. Make this explicit: the translation must suppress further additions at trade_count>=4 until an opposite signal closes the position and resets the counter. This is a runtime safety adaptation, not an extra trading signal. Do not add a stop, target, trend filter or time exit.

Derived by the Research Lead from MQL5 Code Base's EMA-Crossover_Signal: test its EMA3/EMA7 directional crossover, minimum three-point separation, avoidance of narrow ranges, and opposite-signal exit. The page credits Jason Robinson (jnrtrading). This is a completed signal specification, not a reproduction of an inspected program: the downloadable MQ4 source could not be retrieved. Research choices are completed 4-hour bars on LINKUSD.HYPERLIQUID, a scale-normalized point equal to 0.10% of the preceding close, a seven-bar range filter, scheduled FOMC/CPI entry blackouts, capital-relative sizing, and an intrabar protective stop. Thus three normalized points mean 0.30% EMA separation and ten mean a 1.00% range; these are explicit crypto adaptations of the source's unspecified original point scale. Entries execute as market orders at the signal bar's close. News-event selection uses separate scalar flags, avoiding the invalid string sequence in fixed news_event_types.