diff --git a/__pycache__/view_trade_analysis.cpython-314.pyc b/__pycache__/view_trade_analysis.cpython-314.pyc
index 1bd2e85..bbb3962 100644
Binary files a/__pycache__/view_trade_analysis.cpython-314.pyc and b/__pycache__/view_trade_analysis.cpython-314.pyc differ
diff --git a/icmarkets_parser.py b/icmarkets_parser.py
new file mode 100644
index 0000000..af49cd2
--- /dev/null
+++ b/icmarkets_parser.py
@@ -0,0 +1,172 @@
+"""
+icmarkets_parser.py
+===================
+Parser for IC Markets MT5 Position History XLSX exports.
+
+The file contains one sheet ("MT5 Position history List") with:
+  - Row 0: "Report"
+  - Row 1: Name / Produced At metadata
+  - Row 2: Column headers
+  - Row 3+: Deal rows (one row per leg — In or Out)
+
+Each closed trade has two legs sharing the same Position ID:
+  - "Trade Buy In" / "Trade Sell In"  → entry leg  (Profit = 0)
+  - "Trade Buy Out" / "Trade Sell Out" → exit leg   (Profit = actual P/L)
+
+Open positions have only an In leg (no Out yet).
+
+Usage
+-----
+    from icmarkets_parser import parse_icmarkets_xlsx, get_icmarkets_accounts
+
+    # Get list of accounts in the file
+    accounts = get_icmarkets_accounts(file_bytes)
+    # → ['11586098', '11586099']
+
+    # Parse all accounts (returns combined DataFrame)
+    df = parse_icmarkets_xlsx(file_bytes)
+
+    # Parse a specific account
+    df = parse_icmarkets_xlsx(file_bytes, account="11586098")
+
+Output columns (normalised to match mt5_parser schema)
+-------------------------------------------------------
+    symbol, type, open_time, close_time, open_price, close_price,
+    volume, net_profit, win, commission, swap, comment,
+    _account, _strategy, position_id, position_status,
+    open_date, close_date, day_of_week, hour, duration_min,
+    symbol_base
+"""
+
+import io
+import pandas as pd
+import numpy as np
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# Public helpers
+# ─────────────────────────────────────────────────────────────────────────────
+
+def get_icmarkets_accounts(file_bytes: bytes) -> list[str]:
+    """Return sorted list of account numbers found in the file."""
+    raw = _read_raw(file_bytes)
+    if raw is None:
+        return []
+    accounts = raw["Account Number"].dropna().unique().tolist()
+    return sorted([str(a) for a in accounts if str(a).strip()])
+
+
+def parse_icmarkets_xlsx(file_bytes: bytes, account: str = None) -> pd.DataFrame:
+    """
+    Parse IC Markets position history XLSX into a normalised trade DataFrame.
+
+    Parameters
+    ----------
+    file_bytes : bytes
+        Raw bytes of the .xlsx file.
+    account : str, optional
+        If provided, only trades for this account number are returned.
+        If None, all accounts are combined.
+
+    Returns
+    -------
+    pd.DataFrame with normalised columns ready for use in mt5_parser-compatible
+    analysis pages.
+    """
+    raw = _read_raw(file_bytes)
+    if raw is None or raw.empty:
+        return pd.DataFrame()
+
+    # Filter by account if requested
+    if account:
+        raw = raw[raw["Account Number"].astype(str) == str(account)].copy()
+    if raw.empty:
+        return pd.DataFrame()
+
+    # ── Separate In (entry) and Out (exit) legs ────────────────────────────
+    ins  = raw[raw["Transaction Type"].str.contains("In",  na=False)].copy()
+    outs = raw[raw["Transaction Type"].str.contains("Out", na=False)].copy()
+
+    for df in (ins, outs):
+        df["Position"] = pd.to_numeric(df["Position"], errors="coerce")
+
+    # ── Pair by Position ID ────────────────────────────────────────────────
+    paired = ins.merge(
+        outs[["Position", "Date Time", "Open Price", "Profit",
+              "Transaction Type"]].rename(columns={
+            "Date Time":        "Date Time_close",
+            "Open Price":       "Close Price",
+            "Profit":           "Profit_close",
+            "Transaction Type": "TT_close",
+        }),
+        on="Position",
+        how="left",   # keep open positions too (no Out leg yet)
+    )
+
+    # ── Build normalised columns ───────────────────────────────────────────
+    out = pd.DataFrame()
+    out["position_id"]     = paired["Position"]
+    out["symbol"]          = paired["Symbol"].astype(str)
+    out["symbol_base"]     = out["symbol"].str.split(".").str[0]
+    out["_account"]        = paired["Account Number"].astype(str)
+    out["position_status"] = paired["Position Status"].astype(str)
+
+    # Direction from the In leg transaction type
+    out["type"] = paired["Transaction Type"].apply(
+        lambda x: "buy" if "Buy" in str(x) else "sell"
+    )
+
+    out["open_time"]   = pd.to_datetime(paired["Date Time"],       errors="coerce")
+    out["close_time"]  = pd.to_datetime(paired["Date Time_close"], errors="coerce")
+    out["open_price"]  = pd.to_numeric(paired["Open Price"],       errors="coerce")
+    out["close_price"] = pd.to_numeric(paired["Close Price"],      errors="coerce")
+    out["volume"]      = pd.to_numeric(paired["Trade Volume Lots"],errors="coerce")
+    out["net_profit"]  = pd.to_numeric(paired["Profit_close"],     errors="coerce").fillna(0)
+    out["commission"]  = 0.0   # IC Markets file doesn't separate commission
+    out["swap"]        = 0.0
+    out["comment"]     = ""
+    out["_strategy"]   = out["symbol_base"]  # use symbol as strategy label
+
+    # ── Derived columns ────────────────────────────────────────────────────
+    out["win"]          = out["net_profit"] > 0
+    out["open_date"]    = out["open_time"].dt.date
+    out["close_date"]   = out["close_time"].dt.date
+    out["day_of_week"]  = out["open_time"].dt.day_name()
+    out["hour"]         = out["open_time"].dt.hour
+    out["duration_min"] = ((out["close_time"] - out["open_time"])
+                           .dt.total_seconds() / 60).round(1)
+
+    return out.reset_index(drop=True)
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# Internal helpers
+# ─────────────────────────────────────────────────────────────────────────────
+
+def _read_raw(file_bytes: bytes) -> pd.DataFrame | None:
+    """Read the raw sheet and return a DataFrame with named columns."""
+    try:
+        buf = io.BytesIO(file_bytes)
+        df  = pd.read_excel(buf, sheet_name=0, header=None, dtype=str)
+    except Exception:
+        return None
+
+    # Find the header row — it contains "Symbol" in column 0
+    header_row = None
+    for i, row in df.iterrows():
+        if str(row.iloc[0]).strip() == "Symbol":
+            header_row = i
+            break
+
+    if header_row is None:
+        return None
+
+    df.columns = df.iloc[header_row].tolist()
+    df = df.iloc[header_row + 1:].copy()
+    df.columns.name = None
+
+    # Keep only real data rows (Position Status = Open or Closed)
+    if "Position Status" in df.columns:
+        df = df[df["Position Status"].isin(["Open", "Closed"])].copy()
+
+    return df.reset_index(drop=True)
\ No newline at end of file
diff --git a/view_trade_analysis.py b/view_trade_analysis.py
index 19eb112..a9b2f7a 100644
--- a/view_trade_analysis.py
+++ b/view_trade_analysis.py
@@ -11,37 +11,132 @@ sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 from mt5_parser import detect_and_parse, calc_stats
 
 
+
+def _normalise_ic(df):
+    """Map IC Markets DataFrame columns to the schema expected by calc_stats."""
+    import pandas as pd
+    out = df.copy()
+    # calc_stats / render helpers need: open_time, close_time, symbol, type,
+    # strategy, net_profit, win, volume, open_price, close_price,
+    # commission, swap, profit, duration_min, day_of_week, hour
+    if "symbol_base" in out.columns and "strategy" not in out.columns:
+        out["strategy"] = out["symbol_base"]
+    if "net_profit" in out.columns and "profit" not in out.columns:
+        out["profit"] = out["net_profit"]
+    if "commission" not in out.columns:
+        out["commission"] = 0.0
+    if "swap" not in out.columns:
+        out["swap"] = 0.0
+    if "sl" not in out.columns:
+        out["sl"] = None
+    if "tp" not in out.columns:
+        out["tp"] = None
+    # Ensure win column
+    if "win" not in out.columns and "net_profit" in out.columns:
+        out["win"] = out["net_profit"] > 0
+    # Ensure day_of_week and hour
+    if "open_time" in out.columns:
+        out["open_time"] = pd.to_datetime(out["open_time"], errors="coerce")
+        if "day_of_week" not in out.columns:
+            out["day_of_week"] = out["open_time"].dt.day_name()
+        if "hour" not in out.columns:
+            out["hour"] = out["open_time"].dt.hour
+    if "close_time" in out.columns:
+        out["close_time"] = pd.to_datetime(out["close_time"], errors="coerce")
+    if "duration_min" not in out.columns and "open_time" in out.columns and "close_time" in out.columns:
+        out["duration_min"] = ((out["close_time"] - out["open_time"])
+                               .dt.total_seconds() / 60).round(1)
+    return out
+
+
 def render():
     st.title("📊 Trade Analysis")
 
     # ── Session state ─────────────────────────────────────────────────────────
-    if 'ta_df' not in st.session_state:
-        st.session_state['ta_df']     = None
-        st.session_state['ta_format'] = None
+    for _k, _v in {
+        'ta_df': None, 'ta_format': None,
+        'ta_accounts': [], 'ta_ic_bytes': None,
+    }.items():
+        if _k not in st.session_state:
+            st.session_state[_k] = _v
 
-    # ── File upload ───────────────────────────────────────────────────────────
-    col1, col2 = st.columns([4, 1])
-    with col1:
-        uploaded = st.file_uploader(
-            "Upload MT5 Report (HTM/HTML) or Quant Analyzer CSV",
-            type=['html', 'htm', 'csv'],
-            key='ta_upload'
+    # ── Source selector ──────────────────────────────────────────────────────
+    src_col1, src_col2 = st.columns([4, 1])
+    with src_col1:
+        source = st.radio(
+            "File source",
+            ["MT5 / Quant Analyzer", "IC Markets XLSX"],
+            horizontal=True, key='ta_source',
         )
-    with col2:
+    with src_col2:
         st.markdown("<br>", unsafe_allow_html=True)
         if st.button("🗑 Clear", key='ta_clear'):
-            st.session_state['ta_df']     = None
-            st.session_state['ta_format'] = None
+            st.session_state['ta_df']      = None
+            st.session_state['ta_format']  = None
+            st.session_state['ta_accounts'] = []
             st.rerun()
 
-    if uploaded:
-        df, fmt = detect_and_parse(uploaded.read(), uploaded.name)
-        if df is not None:
-            st.session_state['ta_df']     = df
-            st.session_state['ta_format'] = fmt
-            st.success(f"✓ Loaded {len(df)} trades — {fmt}")
-        else:
-            st.error("Could not parse report — check file format")
+    # ── File upload ───────────────────────────────────────────────────────────
+    if source == "MT5 / Quant Analyzer":
+        uploaded = st.file_uploader(
+            "Upload MT5 Report (HTM/HTML) or Quant Analyzer CSV",
+            type=None, key='ta_upload',
+        )
+        if uploaded and uploaded.name.lower().endswith(('.htm','.html','.csv')):
+            df, fmt = detect_and_parse(uploaded.read(), uploaded.name)
+            if df is not None:
+                st.session_state['ta_df']       = df
+                st.session_state['ta_format']   = fmt
+                st.session_state['ta_accounts'] = []
+                st.success(f"✓ Loaded {len(df)} trades — {fmt}")
+            else:
+                st.error("Could not parse report — check file format")
+        elif uploaded:
+            st.warning("Please upload a .htm, .html, or .csv file.")
+
+    else:  # IC Markets XLSX
+        uploaded = st.file_uploader(
+            "Upload IC Markets Position History (.xlsx)",
+            type=None, key='ta_upload',
+        )
+        if uploaded and uploaded.name.lower().endswith(('.xlsx','.xls')):
+            try:
+                from icmarkets_parser import get_icmarkets_accounts, parse_icmarkets_xlsx
+            except ImportError as e:
+                st.error(f"icmarkets_parser.py not found — ensure it is in the MT5Tools folder. ({e})")
+                uploaded = None
+            if uploaded:
+                try:
+                    file_bytes = uploaded.read()
+                    accounts   = get_icmarkets_accounts(file_bytes)
+                    if not accounts:
+                        st.error("No accounts found — check this is an IC Markets Position History export.")
+                    else:
+                        st.session_state['ta_ic_bytes']  = file_bytes
+                        st.session_state['ta_accounts']  = accounts
+                        st.session_state['ta_format']    = "IC Markets XLSX"
+                        df_ic = parse_icmarkets_xlsx(file_bytes, account=accounts[0])
+                        df_ic = _normalise_ic(df_ic)
+                        st.session_state['ta_df'] = df_ic
+                        st.success(f"✓ Loaded {len(df_ic)} trades — {len(accounts)} account(s) found")
+                except Exception as e:
+                    st.error(f"Error parsing file: {e}")
+                    import traceback; st.code(traceback.format_exc())
+        elif uploaded:
+            st.warning("Please upload an .xlsx file.")
+
+    # IC Markets account selector (shown after upload)
+    if (st.session_state.get('ta_accounts') and
+            st.session_state.get('ta_source', source) == "IC Markets XLSX"):
+        accounts = st.session_state['ta_accounts']
+        ac_opts  = ["All accounts"] + accounts
+        sel_ac   = st.selectbox("Account", ac_opts, key='ta_ic_account')
+        acct     = None if sel_ac == "All accounts" else sel_ac
+        if st.session_state.get('ta_ic_bytes'):
+            from icmarkets_parser import parse_icmarkets_xlsx
+            df_ic = parse_icmarkets_xlsx(st.session_state['ta_ic_bytes'], account=acct)
+            df_ic = _normalise_ic(df_ic)
+            st.session_state['ta_df'] = df_ic
 
     df_all = st.session_state['ta_df']
     fmt    = st.session_state['ta_format']
@@ -330,4 +425,4 @@ def render():
             data      = df[show_cols].to_csv(index=False),
             file_name = f"mt5_trades_{date_from}_{date_to}.csv",
             mime      = 'text/csv'
-        )
+        )
\ No newline at end of file