No trades in backtest, Mia Can't Find an Issue

Sure, I'd be happy to help. However, I'll need to see the code you're working with to provide specific guidance. Could you please share the code you're using for your algorithm?

from AlgorithmImports import * class MultiTimeframeTrendStrategy(QCAlgorithm):    def Initialize(self):        # Initialize algorithm parameters        self.SetStartDate(2010, 1, 1)        # self.SetEndDate(2015, 1, 1)        self.SetCash(100000)        # Add SPY Equity with hourly resolution        spy = self.AddEquity("SPY", Resolution.Hour)        spy.SetDataNormalizationMode(DataNormalizationMode.Raw)        self.spySymbol = spy.Symbol        # Set Benchmark        self.SetBenchmark("SPY")        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin)        # Initialize opening and previous bar prices for multiple time frames        self.weeklyOpenPrice = None        self.dailyOpenPrice = None        self.hourlyOpenPrice = None        self.lastDailyHigh = None        self.lastDailyLow = None        self.lastHourlyHigh = None        self.lastHourlyLow = None        # Schedule functions to update weekly, daily, and hourly opening prices        self.lastTradeWeek = -1  # Initialize to an invalid week number        self.Schedule.On(self.DateRules.EveryDay(self.spySymbol), self.TimeRules.AfterMarketOpen(self.spySymbol, 1), self.CheckIfNewWeek)        self.Schedule.On(self.DateRules.EveryDay(self.spySymbol), self.TimeRules.At(9, 30), self.DailyOpen)        # Initialize last hour        self.lastHour = self.Time.hour    def OnData(self, data):        # Ensure the algorithm isn't warming up and that SPY data is available.        if self.IsWarmingUp or self.spySymbol not in data or data[self.spySymbol] is None:            return        # Update hourly price data and track high/low for Inside Bar detection.        if self.Time.hour != self.lastHour:            if data.Bars.ContainsKey(self.spySymbol):                bar = data.Bars[self.spySymbol]                self.hourlyOpenPrice = bar.Open                self.lastHourlyHigh = bar.High                self.lastHourlyLow = bar.Low                self.lastHour = self.Time.hour                self.insideBarDetected = False  # Reset inside bar detection for the new hour        # Detect an Inside Bar based on the last hourly high and low.        if self.lastHourlyHigh is not None and self.lastHourlyLow is not None:            if self.hourlyOpenPrice < self.lastHourlyHigh and self.hourlyOpenPrice > self.lastHourlyLow:                self.Debug("Detected an Inside Bar at the hourly time frame")                self.insideBarDetected = True        # Ensure all necessary prices are set before proceeding.        if None in [self.weeklyOpenPrice, self.dailyOpenPrice, self.hourlyOpenPrice]:            return        # Current price from the data.        price = data[self.spySymbol].Price        # Execute trades based on Inside Bar breakout and trend continuity.        if self.insideBarDetected:            # Entry condition for a long position when current price breaks above the Inside Bar's high            if price > self.lastHourlyHigh and price > self.weeklyOpenPrice and price > self.dailyOpenPrice and price > self.hourlyOpenPrice:                if not self.Portfolio[self.spySymbol].Invested:                    self.Log("Inside Bar broken upwards, aligning with TFC for a long position")                    self.SetHoldings(self.spySymbol, 1)            # Exit condition if the price breaks below the Inside Bar's low            elif price < self.lastHourlyLow:                if self.Portfolio[self.spySymbol].Invested:                    self.Log("Inside Bar broken downwards, exiting position.")                    self.Liquidate(self.spySymbol)    def CheckIfNewWeek(self):        currentWeek = self.Time.isocalendar()[1]        if currentWeek != self.lastTradeWeek:            self.lastTradeWeek = currentWeek            self.WeeklyOpen()    def WeeklyOpen(self):        self.weeklyOpenPrice = self.Securities[self.spySymbol].Price        self.Log(f"Weekly open price updated on {self.Time.strftime('%Y-%m-%d')}: {self.weeklyOpenPrice}")    def DailyOpen(self):        bar = self.Securities[self.spySymbol]        self.dailyOpenPrice = bar.Price        self.lastDailyHigh = bar.High        self.lastDailyLow = bar.Low        self.Log(f"Daily open price updated on {self.Time.strftime('%Y-%m-%d')}: {self.dailyOpenPrice}")

Akira;

I found that Price > LastHigh never happens. Replacing it with Price >= LastHigh works.

if price >= self.lastHourlyHigh and price > self.weeklyOpenPrice and price > self.dailyOpenPrice and price > self.hourlyOpenPrice:

Here is the backtest - with some logging of various values (with formatting).

I appreciate your response Marc, thank you. I will review your recommendation.

You're welcome Akira.

Note that although your algo now buys, it never sells. 

The sell criteria requires the Price to fall BELOW the Last Low. Here again, the fix is  to use <=.

To better visualize the interactions of your algo's rules, I would recommend to use the Plot() feature. It helps especially when using various indicators like SMA, EMA, VWAP, etc.

Happy trails;

Marc